Publikationen im NUM
Hier finden Sie eine Liste der Publikationen, die im Zusammenhang mit dem Netzwerk Universitätsmedizin in der ersten und zweiten Förderphase entstanden sind.
[en]
S. Winkelmann,
A. Korth,
B. Voss,
M. A. Nasr,
N. Behrend,
A. Pudszuhn,
V. M. Hofmann,
P. Schendzielorz,
C. Maetzler,
A. Hermes,
C. Borzikowsky,
T. Bahmer,
W. Lieb,
S. Schreiber,
S. Störk,
F. A. Montellano,
M. Witzenrath,
T. Keil,
M. Krawczak,
M. Laudien and
On Behalf Of The Napkon Study Group,
"Persisting chemosensory dysfunction in COVID-19 - a cross-sectional population-based survey",
Rhinology,
vol. 61,
no. 1,
pp. 12—23,
Feb.
2023.
Stichting Nase.
Abstract:
BACKGROUND: Chemosensory dysfunction (CD) has been reported as a common symptom of SARS-CoV-2 infection, but it is not well understood whether and for how long changes of smell, taste and chemesthesis persist in infected individuals. METHODOLOGY: Unselected adult residents of the German federal state of Schleswig-Holstein with Polymerase Chain Reaction (PCR)-test-confirmed SARS-CoV-2 infection were invited to participate in this large cross-sectional study. Data on the medical history and subjective chemosensory function of participants were obtained through questionnaires and visual analogue scales (VAS). Olfactory function (OF) was objectified with the Sniffin Sticks test (SST), including threshold (T), discrimination (D) and identification (I) test as well as summarized TDI score, and compared to that in healthy controls. Gustatory function (GF) was evaluated with the suprathreshold taste strips (TS) test, and trigeminal function was tested with an ampoule containing ammonia. RESULTS: Between November 2020 and June 2021, 667 infected individuals (mean age: 48.2 years) were examined 9.1 months, on average, after positive PCR testing. Of these, 45.6% had persisting subjective olfactory dysfunction (OD), 36.2% had subjective gustatory dysfunction (GD). Tested OD, tested GD and impaired trigeminal function were observed in 34.6%, 7.3% and 1.8% of participants, respectively. The mean TDI score of participants was significantly lower compared to healthy subjects. Significant associations were observed between subjective OD and GD, and between tested OD and GD. CONCLUSION: Nine months after SARS-CoV-2 infection, OD prevalence is significantly increased among infected members of the general population. Therefore, OD should be included in the list of symptoms collectively defining Long-COVID.
| DOI: | 10.4193/Rhin22.176 |
Abstract:
BACKGROUND: Chemosensory dysfunction (CD) has been reported as a common symptom of SARS-CoV-2 infection, but it is not well understood whether and for how long changes of smell, taste and chemesthesis persist in infected individuals. METHODOLOGY: Unselected adult residents of the German federal state of Schleswig-Holstein with Polymerase Chain Reaction (PCR)-test-confirmed SARS-CoV-2 infection were invited to participate in this large cross-sectional study. Data on the medical history and subjective chemosensory function of participants were obtained through questionnaires and visual analogue scales (VAS). Olfactory function (OF) was objectified with the Sniffin Sticks test (SST), including threshold (T), discrimination (D) and identification (I) test as well as summarized TDI score, and compared to that in healthy controls. Gustatory function (GF) was evaluated with the suprathreshold taste strips (TS) test, and trigeminal function was tested with an ampoule containing ammonia. RESULTS: Between November 2020 and June 2021, 667 infected individuals (mean age: 48.2 years) were examined 9.1 months, on average, after positive PCR testing. Of these, 45.6% had persisting subjective olfactory dysfunction (OD), 36.2% had subjective gustatory dysfunction (GD). Tested OD, tested GD and impaired trigeminal function were observed in 34.6%, 7.3% and 1.8% of participants, respectively. The mean TDI score of participants was significantly lower compared to healthy subjects. Significant associations were observed between subjective OD and GD, and between tested OD and GD. CONCLUSION: Nine months after SARS-CoV-2 infection, OD prevalence is significantly increased among infected members of the general population. Therefore, OD should be included in the list of symptoms collectively defining Long-COVID.
T. Aschman,
E. Wyler,
O. Baum,
A. Hentschel,
F. Legler,
C. Preusse,
L. Meyer-Arndt,
I. Büttnerova,
A. Förster,
D. Cengiz,
L. G. T. Alves,
J. Schneider,
C. Kedor,
R. Rust,
J. Bellmann-Strobl,
S. Aminaa,
P. Vajkoczy,
H. Goebel,
M. Landthaler,
V. Corman,
A. Roos,
F. L. Heppner,
H. Radbruch,
F. Paul,
C. Scheibenbogen,
W. Stenzel and
N. F. Dengler,
Post-COVID syndrome is associated with capillary alterations, macrophage infiltration and distinct transcriptomic signatures in skeletal muscles,
Feb.
2023.
A. Silber,
S. Platte,
A. Kumar,
S. Arora,
D. Kadioglu,
M. Schmidt,
H. Storf,
A. G. Chiocchetti and
C. M. Freitag,
"Admission rates and clinical profiles of children and youth with eating disorders treated as inpatients before and during the COVID-19 pandemic in a German university hospital.",
Frontiers in public health,
2023.
Abstract:
Kinder und Jugendliche, die für psychische Gesundheitsstörungen, wie Essstörungen (ED) gefährdet sind, wurden besonders von der COVID-19 Pandemie betroffen, doch sind die Beweise für die am stärksten betroffenen und damit in Deutschland kranken Kinder knapp. Diese Querschnittsstudie untersuchte anonymisierte Routinekrankenhausdaten (demographische Informationen, Diagnosen, Behandlungsmodalitäten) von Patienten, die (<i>n</i> = 2,849) an die Abteilung für Kinder- und Jugendpsychiatrie, Psychosomatik und Psychotherapie (DCAPPP) eines Deutschen Universitätsklinikums zwischen 01/2016 und 02/2022 zugelassen wurden. Absolute und relative Zahl von Patienten mit oder ohne ED vor (01/2016-02/2020) und während der COVID-19 Pandemie (03/2020-02/2022) wurden verglichen. Die Auswirkungen von Schulabschlüssen im Rahmen von Sozialabsperrmaßnahmen für die COVID-19-Abschwächung auf die stationäre Aufnahmequote wurde untersucht, wie sie als potenzieller Risikofaktor für psychische Gesundheitsprobleme in der Jugend diskutiert wurde. Während der COVID-19 Pandemie stieg die ED-Inpatient-Eintrittsrate von 10,5 auf 16,7%, vor allem von Anorexia Nervosa (AN). Im Gegensatz zu früheren Berichten fanden wir keine Veränderung der somatischen und psychischen Störung Komorbidität, Alter oder Sexratio für krankhafte Jugendliche mit ED. Allerdings beobachteten wir eine verkürzte Länge des Krankenhausaufenthalts (LOS) für krankhafte Jugendliche mit und ohne ED. Darüber hinaus präsentierten nicht-ED-Zulassungen eine erhöhte Anzahl von psychischen Störungen Komorbiditäten. Im Gegensatz zu unserer Hypothese waren die Schulabschlüsse nicht mit dem beobachteten Anstieg der ED verbunden. Zusammenfassend wurde die COVID-19 Pandemie mit einer erhöhten Ambulanz für Jugendliche, die an AN leiden, und von Jugendlichen, die von mehreren psychischen Störungen betroffen sind, verbunden. Daher gehen wir davon aus, dass die stationäre Zulassung für Personen mit einer höheren Krankheitslast während der COVID-19 Pandemie priorisiert wurde. Unsere Ergebnisse weisen darauf hin, dass bei Umweltkrisen eine angemessene stationäre psychische Gesundheitsbehandlungsfähigkeit und eine weitere Stärkung der Psychiatrie von Kindern und Jugendlichen in Deutschland erforderlich ist.
| DOI: | 10.3389/fpubh.2023.1281363 |
Abstract:
Kinder und Jugendliche, die für psychische Gesundheitsstörungen, wie Essstörungen (ED) gefährdet sind, wurden besonders von der COVID-19 Pandemie betroffen, doch sind die Beweise für die am stärksten betroffenen und damit in Deutschland kranken Kinder knapp. Diese Querschnittsstudie untersuchte anonymisierte Routinekrankenhausdaten (demographische Informationen, Diagnosen, Behandlungsmodalitäten) von Patienten, die (<i>n</i> = 2,849) an die Abteilung für Kinder- und Jugendpsychiatrie, Psychosomatik und Psychotherapie (DCAPPP) eines Deutschen Universitätsklinikums zwischen 01/2016 und 02/2022 zugelassen wurden. Absolute und relative Zahl von Patienten mit oder ohne ED vor (01/2016-02/2020) und während der COVID-19 Pandemie (03/2020-02/2022) wurden verglichen. Die Auswirkungen von Schulabschlüssen im Rahmen von Sozialabsperrmaßnahmen für die COVID-19-Abschwächung auf die stationäre Aufnahmequote wurde untersucht, wie sie als potenzieller Risikofaktor für psychische Gesundheitsprobleme in der Jugend diskutiert wurde. Während der COVID-19 Pandemie stieg die ED-Inpatient-Eintrittsrate von 10,5 auf 16,7%, vor allem von Anorexia Nervosa (AN). Im Gegensatz zu früheren Berichten fanden wir keine Veränderung der somatischen und psychischen Störung Komorbidität, Alter oder Sexratio für krankhafte Jugendliche mit ED. Allerdings beobachteten wir eine verkürzte Länge des Krankenhausaufenthalts (LOS) für krankhafte Jugendliche mit und ohne ED. Darüber hinaus präsentierten nicht-ED-Zulassungen eine erhöhte Anzahl von psychischen Störungen Komorbiditäten. Im Gegensatz zu unserer Hypothese waren die Schulabschlüsse nicht mit dem beobachteten Anstieg der ED verbunden. Zusammenfassend wurde die COVID-19 Pandemie mit einer erhöhten Ambulanz für Jugendliche, die an AN leiden, und von Jugendlichen, die von mehreren psychischen Störungen betroffen sind, verbunden. Daher gehen wir davon aus, dass die stationäre Zulassung für Personen mit einer höheren Krankheitslast während der COVID-19 Pandemie priorisiert wurde. Unsere Ergebnisse weisen darauf hin, dass bei Umweltkrisen eine angemessene stationäre psychische Gesundheitsbehandlungsfähigkeit und eine weitere Stärkung der Psychiatrie von Kindern und Jugendlichen in Deutschland erforderlich ist.
B. Salzberger,
A. Mellmann,
A. Bludau,
S. Ciesek,
V. Corman,
A. Dilthey,
T. Donker,
T. Eckmanns,
R. Egelkamp,
S. G. Gaterman,
H. Grundmann,
G. Haecker,
M. Kaase,
B. Lange,
M. Mielke,
M. W. Pletz,
T. Semmler,
A. Thuermer,
L. H. Wieler,
T. Wolff,
A. F. Widmer and
S. Scheithauer,
"An appeal for strengthening genomic pathogen surveillance to improve pandemic preparedness and infection prevention: the German perspective",
Infection,
2023.
| DOI: | 10.1007/s15010-023-02040-9 |
| Datei: | https://doi.org/10.1007/s15010-023-02040-9 |
[en]
D. Hellwig,
N. C. Hellwig,
S. Boehner,
T. Fuchs,
R. Fischer and
D. Schmidt,
"Artificial intelligence and deep learning for advancing PET image reconstruction: State-of-the-art and future directions",
Nuklearmedizin,
vol. 62,
no. 6,
pp. 334—342,
2023.
Georg Thieme Verlag KG,
http://dx.doi.org/10.1055/a-2198-0358.
Abstract:
Positron emission tomography (PET) is vital for diagnosing diseases and monitoring treatments. Conventional image reconstruction (IR) techniques like filtered backprojection and iterative algorithms are powerful but face limitations. PET IR can be seen as an image-to-image translation. Artificial intelligence (AI) and deep learning (DL) using multilayer neural networks enable a new approach to this computer vision task. This review aims to provide mutual understanding for nuclear medicine professionals and AI researchers. We outline fundamentals of PET imaging as well as state-of-the-art in AI-based PET IR with its typical algorithms and DL architectures. Advances improve resolution and contrast recovery, reduce noise, and remove artifacts via inferred attenuation and scatter correction, sinogram inpainting, denoising, and super-resolution refinement. Kernel-priors support list-mode reconstruction, motion correction, and parametric imaging. Hybrid approaches combine AI with conventional IR. Challenges of AI-assisted PET IR include availability of training data, cross-scanner compatibility, and the risk of hallucinated lesions. The need for rigorous evaluations, including quantitative phantom validation and visual comparison of diagnostic accuracy against conventional IR, is highlighted along with regulatory issues. First approved AI-based applications are clinically available, and its impact is foreseeable. Emerging trends, such as the integration of multimodal imaging and the use of data from previous imaging visits, highlight future potentials. Continued collaborative research promises significant improvements in image quality, quantitative accuracy, and diagnostic performance, ultimately leading to the integration of AI-based IR into routine PET imaging protocols.
| DOI: | 10.1055/a-2198-0358 |
Abstract:
Positron emission tomography (PET) is vital for diagnosing diseases and monitoring treatments. Conventional image reconstruction (IR) techniques like filtered backprojection and iterative algorithms are powerful but face limitations. PET IR can be seen as an image-to-image translation. Artificial intelligence (AI) and deep learning (DL) using multilayer neural networks enable a new approach to this computer vision task. This review aims to provide mutual understanding for nuclear medicine professionals and AI researchers. We outline fundamentals of PET imaging as well as state-of-the-art in AI-based PET IR with its typical algorithms and DL architectures. Advances improve resolution and contrast recovery, reduce noise, and remove artifacts via inferred attenuation and scatter correction, sinogram inpainting, denoising, and super-resolution refinement. Kernel-priors support list-mode reconstruction, motion correction, and parametric imaging. Hybrid approaches combine AI with conventional IR. Challenges of AI-assisted PET IR include availability of training data, cross-scanner compatibility, and the risk of hallucinated lesions. The need for rigorous evaluations, including quantitative phantom validation and visual comparison of diagnostic accuracy against conventional IR, is highlighted along with regulatory issues. First approved AI-based applications are clinically available, and its impact is foreseeable. Emerging trends, such as the integration of multimodal imaging and the use of data from previous imaging visits, highlight future potentials. Continued collaborative research promises significant improvements in image quality, quantitative accuracy, and diagnostic performance, ultimately leading to the integration of AI-based IR into routine PET imaging protocols.
S. Tayebi Arasteh,
J. Romanowicz,
D. F. Pace,
P. Golland,
A. J. Powell,
A. K. Maier,
D. Truhn,
T. Brosch,
J. Weese,
M. Lotfinia,
R. J. Geest and
M. H. Moghari,
"Automated segmentation of 3D cine cardiovascular magnetic resonance imaging",
Frontiers in cardiovascular medicine,
vol. 10,
pp. 1167500,
2023.
Abstract:
As the life expectancy of children with congenital heart disease (CHD) is rapidly increasing and the adult population with CHD is growing, there is an unmet need to improve clinical workflow and efficiency of analysis. Cardiovascular magnetic resonance (CMR) is a noninvasive imaging modality for monitoring patients with CHD. CMR exam is based on multiple breath-hold 2-dimensional (2D) cine acquisitions that should be precisely prescribed and is expert and institution dependent. Moreover, 2D cine images have relatively thick slices, which does not allow for isotropic delineation of ventricular structures. Thus, development of an isotropic 3D cine acquisition and automatic segmentation method is worthwhile to make CMR workflow straightforward and efficient, as the present work aims to establish. Ninety-nine patients with many types of CHD were imaged using a non-angulated 3D cine CMR sequence covering the whole-heart and great vessels. Automatic supervised and semi-supervised deep-learning-based methods were developed for whole-heart segmentation of 3D cine images to separately delineate the cardiac structures, including both atria, both ventricles, aorta, pulmonary arteries, and superior and inferior vena cavae. The segmentation results derived from the two methods were compared with the manual segmentation in terms of Dice score, a degree of overlap agreement, and atrial and ventricular volume measurements. The semi-supervised method resulted in a better overlap agreement with the manual segmentation than the supervised method for all 8 structures (Dice score 83.23 ± 16.76% vs. 77.98 ± 19.64%; P-value ≤0.001). The mean difference error in atrial and ventricular volumetric measurements between manual segmentation and semi-supervised method was lower (bias ≤ 5.2 ml) than the supervised method (bias ≤ 10.1 ml). The proposed semi-supervised method is capable of cardiac segmentation and chamber volume quantification in a CHD population with wide anatomical variability. It accurately delineates the heart chambers and great vessels and can be used to accurately calculate ventricular and atrial volumes throughout the cardiac cycle. Such a segmentation method can reduce inter- and intra- observer variability and make CMR exams more standardized and efficient.
| DOI: | 10.3389/fcvm.2023.1167500 |
| Datei: | https://pubmed.ncbi.nlm.nih.gov/37904806/ |
Abstract:
As the life expectancy of children with congenital heart disease (CHD) is rapidly increasing and the adult population with CHD is growing, there is an unmet need to improve clinical workflow and efficiency of analysis. Cardiovascular magnetic resonance (CMR) is a noninvasive imaging modality for monitoring patients with CHD. CMR exam is based on multiple breath-hold 2-dimensional (2D) cine acquisitions that should be precisely prescribed and is expert and institution dependent. Moreover, 2D cine images have relatively thick slices, which does not allow for isotropic delineation of ventricular structures. Thus, development of an isotropic 3D cine acquisition and automatic segmentation method is worthwhile to make CMR workflow straightforward and efficient, as the present work aims to establish. Ninety-nine patients with many types of CHD were imaged using a non-angulated 3D cine CMR sequence covering the whole-heart and great vessels. Automatic supervised and semi-supervised deep-learning-based methods were developed for whole-heart segmentation of 3D cine images to separately delineate the cardiac structures, including both atria, both ventricles, aorta, pulmonary arteries, and superior and inferior vena cavae. The segmentation results derived from the two methods were compared with the manual segmentation in terms of Dice score, a degree of overlap agreement, and atrial and ventricular volume measurements. The semi-supervised method resulted in a better overlap agreement with the manual segmentation than the supervised method for all 8 structures (Dice score 83.23 ± 16.76% vs. 77.98 ± 19.64%; P-value ≤0.001). The mean difference error in atrial and ventricular volumetric measurements between manual segmentation and semi-supervised method was lower (bias ≤ 5.2 ml) than the supervised method (bias ≤ 10.1 ml). The proposed semi-supervised method is capable of cardiac segmentation and chamber volume quantification in a CHD population with wide anatomical variability. It accurately delineates the heart chambers and great vessels and can be used to accurately calculate ventricular and atrial volumes throughout the cardiac cycle. Such a segmentation method can reduce inter- and intra- observer variability and make CMR exams more standardized and efficient.
V. Kopfnagel,
I. Bernemann,
G. Anton,
T. Illig,
S. Mücke,
C. Dolch,
N. Klopp,
D. Drobek and
M. Kersting,
"Centralized DNA Isolation in the National Pandemic Cohort Network (NAPKON).",
no. ISBN 978-3-8382-1841-0,
pp. 51-52,
2023.
I. Bernemann,
S. Haag,
B. Fösel,
C. Dolch,
N. Klopp,
V. Kopfnagel,
A. Kühn-Steven,
S. Kunze,
S. Mücke,
I. Ruhl,
M. Schieck,
T. Illig and
G. Anton,
"Compliance with study standards in multicentre studies using the example of NAPKON.",
no. ISBN 978-3-8382-1841-0,
pp. 61-62,
2023.
K. O. Yusuf,
A. Schoneberg,
S. Hanß,
M. Wiesenfeldt,
M. Stecher,
L. Mitrov,
S. M. Hopff,
S. Steinbrecher,
F. Kurth,
T. Bahmer,
S. Schreiber,
D. Pape,
A. Hofmann,
M. Kohls,
S. Störk,
H. C. Stubbe,
J. J. Tebbe,
J. C. Hellmuth,
J. Erber,
L. Krist,
S. Rieg,
L. Pilgram,
J. J. Vehreschild,
J. Reese and
D. Krefting,
"Consistency as a Data Quality Measure for German Corona
Consensus Items Mapped from National Pandemic Cohort Network
Data Collections",
Methods Inf Med,
vol. 62,
no. S 01,
pp. e47—e56,
Jan.
2023.
Georg Thieme Verlag KG.
Abstract:
Background As a national effort to better understand the current pandemic, three cohorts collect sociodemographic and clinical data from coronavirus disease 2019 (COVID-19) patients from different target populations within the German National Pandemic Cohort Network (NAPKON). Furthermore, the German Corona Consensus Dataset (GECCO) was introduced as a harmonized basic information model for COVID-19 patients in clinical routine. To compare the cohort data with other GECCO-based studies, data items are mapped to GECCO. As mapping from one information model to another is complex, an additional consistency evaluation of the mapped items is recommended to detect possible mapping issues or source data inconsistencies.Objectives The goal of this work is to assure high consistency of research data mapped to the GECCO data model. In particular, it aims at identifying contradictions within interdependent GECCO data items of the German national COVID-19 cohorts to allow investigation of possible reasons for identified contradictions. We furthermore aim at enabling other researchers to easily perform data quality evaluation on GECCO-based datasets and adapt to similar data models.Methods All suitable data items from each of the three NAPKON cohorts are mapped to the GECCO items. A consistency assessment tool (dqGecco) is implemented, following the design of an existing quality assessment framework, retaining their-defined consistency taxonomies, including logical and empirical contradictions. Results of the assessment are verified independently on the primary data source.Results Our consistency assessment tool helped in correcting the mapping procedure and reveals remaining contradictory value combinations within COVID-19 symptoms, vital signs, and COVID-19 severity. Consistency rates differ between the different indicators and cohorts ranging from 95.84% up to 100%.Conclusion An efficient and portable tool capable of discovering inconsistencies in the COVID-19 domain has been developed and applied to three different cohorts. As the GECCO dataset is employed in different platforms and studies, the tool can be directly applied there or adapted to similar information models.
| DOI: | 10.1055/a-2006-1086 |
Abstract:
Background As a national effort to better understand the current pandemic, three cohorts collect sociodemographic and clinical data from coronavirus disease 2019 (COVID-19) patients from different target populations within the German National Pandemic Cohort Network (NAPKON). Furthermore, the German Corona Consensus Dataset (GECCO) was introduced as a harmonized basic information model for COVID-19 patients in clinical routine. To compare the cohort data with other GECCO-based studies, data items are mapped to GECCO. As mapping from one information model to another is complex, an additional consistency evaluation of the mapped items is recommended to detect possible mapping issues or source data inconsistencies.Objectives The goal of this work is to assure high consistency of research data mapped to the GECCO data model. In particular, it aims at identifying contradictions within interdependent GECCO data items of the German national COVID-19 cohorts to allow investigation of possible reasons for identified contradictions. We furthermore aim at enabling other researchers to easily perform data quality evaluation on GECCO-based datasets and adapt to similar data models.Methods All suitable data items from each of the three NAPKON cohorts are mapped to the GECCO items. A consistency assessment tool (dqGecco) is implemented, following the design of an existing quality assessment framework, retaining their-defined consistency taxonomies, including logical and empirical contradictions. Results of the assessment are verified independently on the primary data source.Results Our consistency assessment tool helped in correcting the mapping procedure and reveals remaining contradictory value combinations within COVID-19 symptoms, vital signs, and COVID-19 severity. Consistency rates differ between the different indicators and cohorts ranging from 95.84% up to 100%.Conclusion An efficient and portable tool capable of discovering inconsistencies in the COVID-19 domain has been developed and applied to three different cohorts. As the GECCO dataset is employed in different platforms and studies, the tool can be directly applied there or adapted to similar information models.
K. O. Yusuf,
O. Miljukov,
A. Schoneberg,
S. Hanß,
M. Wiesenfeldt,
M. Stecher,
L. Mitrov,
S. Hopff,
S. Steinbrecher,
F. Kurth,
T. Bahmer,
S. Schreiber,
D. Pape,
A. Hofmann,
M. Kohls,
S. Störk,
H. C. Stubbe,
J. J. Tebbe,
J. Hellmuth,
J. Erber,
L. Krist,
S. Rieg,
L. Pilgram,
J. J. Vehreschild,
J. Reese and
D. Krefting,
"Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections.",
Jan.
2023.
| DOI: | 10.1055/a-2006-1086 |
S. Mücke,
S. Kunze,
V. Kopfnagel,
B. Fösel,
I. Bernemann,
C. Dolch,
N. Klopp,
D. Lindemann,
B. Lorenz-Depiereux,
T. Illig,
G. Anton and
P. Christ,
"Decentralized biobanking in NAPKON - 500 sample requests later.",
no. ISBN 978-3-8382-1841-0,
pp. 53-54,
2023.
C. Nürnberger,
K. S. Appel,
M. C. Polidori,
N. Hettich,
T. Bahmer,
C. Förster,
C. Lemhöfer and
On Behalf Of The Napkon Study Group,
"Der Post-COVID-Score ist zur Identifizierung von Betroffenen in der SÜP anwendbar. Die Einbeziehung von Assessmentinstrumenten kann zu einer detaillierteren Darstellung beitragen",
Poster NAPKON Vention 2023, Frankfurt,
2023.
M. Lebedin,
C. V. García,
L. Spatt,
C. Ratswohl,
C. Thibeault,
L. Ostendorf,
F. Paul,
L. E. Sander,
F. Kurth and
K. Rosa,
"Discriminating promiscuous from target-specific autoantibodies in COVID-19",
European Journal of Immunology,
vol. 53,
no. 5,
pp. 2250210,
2023.
Abstract:
Abstract Diverse autoantibodies were suggested to contribute to severe outcomes of COVID-19, but their functional implications are largely unclear. ACE2, the SARS-CoV-2 receptor and a key regulator of blood pressure, was described to be one of many targets of autoantibodies in COVID-19. ACE2 in its soluble form (sACE2) is highly elevated in the blood of critically ill patients, raising the question of whether sACE2:spike complexes induce ACE2 reactivity. Screening 247 COVID-19 patients, we observed elevated sACE2 and anti-ACE2 IgG that were poorly correlated. Interestingly, levels of IgGs recognizing ACE2, IFNα2, and CD26 strongly correlated in severe COVID-19, with 15% of sera showing polyreactivity versus 4.1% exhibiting target-directed autoimmunity. Promiscuous autoantibodies failed to impair the activity of ACE2 and IFNα2, while only specific anti-IFNα2 IgG compromised cytokine function. Our study suggests that the detection of autoantibodies in COVID-19 is often attributed to a promiscuous reactivity, potentially misinterpreted as target-specific autoimmunity with functional impact.
| DOI: | 10.1002/eji.202250210 |
| Pubmed: | 36856018 |
| Datei: | https://onlinelibrary.wiley.com/doi/abs/10.1002/eji.202250210 |
Abstract:
Abstract Diverse autoantibodies were suggested to contribute to severe outcomes of COVID-19, but their functional implications are largely unclear. ACE2, the SARS-CoV-2 receptor and a key regulator of blood pressure, was described to be one of many targets of autoantibodies in COVID-19. ACE2 in its soluble form (sACE2) is highly elevated in the blood of critically ill patients, raising the question of whether sACE2:spike complexes induce ACE2 reactivity. Screening 247 COVID-19 patients, we observed elevated sACE2 and anti-ACE2 IgG that were poorly correlated. Interestingly, levels of IgGs recognizing ACE2, IFNα2, and CD26 strongly correlated in severe COVID-19, with 15% of sera showing polyreactivity versus 4.1% exhibiting target-directed autoimmunity. Promiscuous autoantibodies failed to impair the activity of ACE2 and IFNα2, while only specific anti-IFNα2 IgG compromised cytokine function. Our study suggests that the detection of autoantibodies in COVID-19 is often attributed to a promiscuous reactivity, potentially misinterpreted as target-specific autoimmunity with functional impact.
[en]
T. Fuchs,
L. Kaiser,
D. Müller,
L. Papp,
R. Fischer and
J. Tran-Gia,
"Enhancing interoperability and harmonisation of nuclear medicine image data and associated clinical data",
Nuklearmedizin,
vol. 62,
no. 6,
pp. 389-398,
2023.
Georg Thieme Verlag KG,
http://dx.doi.org/10.1055/a-2187-5701.
Abstract:
Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions.
| DOI: | 10.1055/a-2187-5701 |
Abstract:
Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions.
K. Tilch and
S. M. Hopff,
"Entscheidungsverhalten zur Einwilligung in Studienmodule bei Patient:innen des Nationalen Pandemie Kohorten Netzes.",
Poster KIT Kongress 2023, Leipzig,
2023.
S. Scheithauer,
A. Dilthey,
A. Bludau,
S. Ciesek,
V. Corman,
T. Donker,
T. Eckmanns,
R. Egelkamp,
H. Grundmann,
G. Häcker,
M. Kaase,
B. Lange,
A. Mellmann,
M. Mielke,
M. Pletz,
B. Salzberger,
A. Thürmer,
A. Widmer,
L. Wieler,
T. Wolff,
S. Gatermann and
T. Semmler,
"Etablierung der Genomischen Erreger-Surveillance zur Stärkung des Pandemie- und Infektionsschutzes in Deutschland",
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz,
vol. 66,
no. 4,
pp. 443—449,
2023.
| DOI: | 10.1007/s00103-023-03680-w |
S. Scheithauer,
A. Dilthey,
A. Bludau,
S. Ciesek,
V. Corman,
T. Donker,
T. Eckmanns,
R. Egelkamp,
H. Grundmann,
G. Haecker,
M. Kaase,
B. Lange,
A. Mellmann,
M. Mielke,
M. Pletz,
B. Salzberger,
A. Thuermer,
A. Widmer,
L. H. Wieler,
T. Wolff,
S. Gatermann and
T. Semmler,
"Etablierung der Genomischen Erreger-Surveillance zur Stärkung des Pandemie- und Infektionsschutzes in Deutschland. [Establishment of genomic pathogen surveillance to strengthen pandemic preparedness and infection prevention in Germany].",
Bundesgesundheitsblatt -Gesundheitsforschung - Gesundheitsschutz,
2023.
| DOI: | 10.1007/s00103-023-03680-w |
| Datei: | https://doi.org/10.1007/s00103-023-03680-w |
S. Sikdar,
"Krankheitskostenanalyse der stationären Behandlung von COVID-19 Patient:innen.",
Poster KIT Kongress 2023, Leipzig,
2023.
L. Schmidbauer,
C. Nürnberger,
C. Fiessler,
K. Franzpötter,
J. Haug,
F. Haug,
A. Hermes,
S. Jiru-Hillmann,
O. Miljukov,
A. Ruß,
J. J. Vehreschild,
M. Krawczak,
M. Witzenrath,
W. Lieb,
S. Schmidt,
J. Reese,
P. Heuschmann and
C. Bauer,
"NUKLEUS – NUM Klinische Epidemiologie- und Studienplattform",
Poster NAPKON Vention 2023, Frankfurt,
2023.
L. Schmidbauer,
C. Nürnberger,
C. Fiessler,
K. Franzpötter,
F. Haug,
J. Haug,
A. Hermes,
S. Jiru-Hillmann,
K. Günther,
O. Miljukov,
A. Ruß,
J. J. Vehreschild,
M. Krawczak,
M. Witzenrath,
W. Lieb,
M. Rose,
S. Schmidt,
W. Hoffmann,
J. Schmitt,
P. Ihle,
J. Reese and
P. U. Heuschmann,
"NUKLEUS – NUM Klinische Epidemiologie- und Studienplattform Epidemiology Core Unit (ECU)",
Poster DGEpi 2023, Würzburg,
2023.
M. Hoffmann,
L. Wong,
P. Arora,
L. Zhang,
C. Rocha,
A. Odle,
I. Nehlmeier,
A. Kempf,
A. Richter,
N. Halwe,
J. Schön,
L. Ulrich,
D. Hoffmann,
M. Beer,
C. Drosten,
S. Perlman and
S. Pöhlmann,
"Omicron subvariant BA.5 efficiently infects lung cells",
Nature communications,
vol. 14,
no. 1,
pp. 3500,
2023.
| DOI: | 10.1038/s41467-023-39147-4 |
M. Hoffmann,
L. R. Wong,
P. Arora,
L. Zhang,
C. Rocha,
A. Odle,
I. Nehlmeier,
A. Kempf,
A. Richter,
N. J. Halwe,
J. Schoen,
L. Ulrich,
D. Hoffmann,
M. Beer,
C. Drosten,
S. Perlman and
S. Poehlmann,
"Omicron subvariant BA.5 efficiently infects lung cells",
Nature Communications,
2023.
| DOI: | 10.1038/s41467-023-39147-4 |
| Datei: | https://doi.org/10.1038/s41467-023-39147-4 |
P. Fervers,
F. Fervers,
M. Rinneburger,
M. Weisthoff,
J. Kottlors,
R. Reimer,
D. Zopfs,
E. Celik,
D. Maintz,
N. Große-Hokamp and
T. Persigehl,
"Physiological iodine uptake of the spine's bone marrow in dual-energy computed tomography - using artificial intelligence to define reference values based on 678 CT examinations of 189 individuals.",
Frontiers in endocrinology,
2023.
Abstract:
Die Jodaufnahme des Knochenmarks im dualen energetischen CT (DECT) ist bei maligner Krankheit erhöht. Wir wollten nach intravenöser Kontrastanwendung den physiologischen Bereich der Knochenmark-Iodaufnahme untersuchen und die Abhängigkeit von vBMD, Jod-Blutpool, Patientenalter und Sex untersuchen. Retrospektive Analyse von onkologischen Patienten ohne Nachweis der metastasierenden Erkrankung. DECT-Untersuchungen wurden an einem Spektraldetektor CT-Scanner in Portal venöser Kontrastphase durchgeführt. Die Thorax- und Lendenwirbelsäule wurden durch ein vortrainiertes neuronales Netz segmentiert, wobei volumetrische Jodkonzentrationsdaten erhalten wurden [mg/ml]. vBMD wurde mit einer phantomlosen, CE-zertifizierten Software [mg/cm3] bewertet. Der Jod-Blutpool wurde durch ROI-basierte Messungen in den großen Bauchgefäßen geschätzt. Ein multivariates Regressionsmodell passte zur abhängigen Variablen "medianen Knochenmark-Iodaufnahme". Zur Beurteilung der Auswirkungen jedes Kovariats wurden standardisierte Regressionskoeffizienten (β) berechnet. 678 aufeinanderfolgende DECT-Prüfungen von 189 Personen (93 weiblich, Alter 61.4 ± 16.0 Jahre) wurden bewertet. KI-basierte Segmentierung lieferte Volumendaten von 97,9 % der eingeschlossenen Wirbel (n=11,286). Die 95<sup>th</sup>-prozentile Knochenmark-Iodaufnahme, als Surrogat für den oberen Rand der physiologischen Verteilung, lag zwischen 4,7-6,4 mg/ml vBMD (p <0.001, mittlere β=0,50) und Portalven-Iod-Blutpool (p <0.001, mittlere β=0,43) vermittelte den stärksten Einfluss. Darauf aufbauend wurden angepasste Referenzwerte berechnet. Die Knochenmark-Iodaufnahme zeigt ein deutliches Profil je nach vBMD, Jod-Blutpool, Patientenalter und Sex. Diese Studie ist die erste, die die angepassten Referenzwerte liefert.
| DOI: | 10.3389/fendo.2023.1098898 |
Abstract:
Die Jodaufnahme des Knochenmarks im dualen energetischen CT (DECT) ist bei maligner Krankheit erhöht. Wir wollten nach intravenöser Kontrastanwendung den physiologischen Bereich der Knochenmark-Iodaufnahme untersuchen und die Abhängigkeit von vBMD, Jod-Blutpool, Patientenalter und Sex untersuchen. Retrospektive Analyse von onkologischen Patienten ohne Nachweis der metastasierenden Erkrankung. DECT-Untersuchungen wurden an einem Spektraldetektor CT-Scanner in Portal venöser Kontrastphase durchgeführt. Die Thorax- und Lendenwirbelsäule wurden durch ein vortrainiertes neuronales Netz segmentiert, wobei volumetrische Jodkonzentrationsdaten erhalten wurden [mg/ml]. vBMD wurde mit einer phantomlosen, CE-zertifizierten Software [mg/cm3] bewertet. Der Jod-Blutpool wurde durch ROI-basierte Messungen in den großen Bauchgefäßen geschätzt. Ein multivariates Regressionsmodell passte zur abhängigen Variablen "medianen Knochenmark-Iodaufnahme". Zur Beurteilung der Auswirkungen jedes Kovariats wurden standardisierte Regressionskoeffizienten (β) berechnet. 678 aufeinanderfolgende DECT-Prüfungen von 189 Personen (93 weiblich, Alter 61.4 ± 16.0 Jahre) wurden bewertet. KI-basierte Segmentierung lieferte Volumendaten von 97,9 % der eingeschlossenen Wirbel (n=11,286). Die 95<sup>th</sup>-prozentile Knochenmark-Iodaufnahme, als Surrogat für den oberen Rand der physiologischen Verteilung, lag zwischen 4,7-6,4 mg/ml vBMD (p <0.001, mittlere β=0,50) und Portalven-Iod-Blutpool (p <0.001, mittlere β=0,43) vermittelte den stärksten Einfluss. Darauf aufbauend wurden angepasste Referenzwerte berechnet. Die Knochenmark-Iodaufnahme zeigt ein deutliches Profil je nach vBMD, Jod-Blutpool, Patientenalter und Sex. Diese Studie ist die erste, die die angepassten Referenzwerte liefert.
A. Surov,
H. Kardas,
G. Besutti,
M. Pellegrini,
M. Ottone,
M. R. Onur,
F. Atak,
A. G. Erdemir,
E. Hocaoglu,
Ö. Yıldız,
E. Inci,
E. Cingöz,
M. Cingöz,
M. Dursun,
İ. Korkmaz,
Ç. Orhan,
A. Strobel,
A. Wienke and
M. Pech,
"Prognostic Role of the Pectoralis Musculature in Patients with COVID-19. A Multicenter Study.",
Academic radiology,
Jan.
2023.
Abstract:
Um die Auswirkungen der niedrigen Skelettmuskelmasse bei Patienten mit COVID-19 auf relevante Ergebnisse wie 30-Tage-Sterblichkeit zu bewerten, müssen Intubation und intensiver Pflegeeinheit Zulassung erforderlich sein. Für diese Studie wurden Daten aus sechs Zentren erworben. Die gewonnene Probe umfasst 1138 Patienten. Es gab 547 Frauen (48,1%) und 591 Männer (51.9%) mit einem mittleren Alter von 54.5 ± 18,8 Jahre; mittleres Alter, 55 Jahre; Reichweite, 18-84 Jahre). In jedem Fall wurde thoracic CT ohne intravenöse Applikation von Kontrastmittel durchgeführt. Die folgenden Parameter der Pectoralis-Muskeln wurden geschätzt: Muskelfläche als Summe der bilateralen Bereiche der pectoralis großen und kleineren Muskeln, Muskeldichte, Muskelindex (PMI) (Pectoralis-Muskelbereich geteilt durch den Körperhöhenwinkel des Patienten) als Verhältnis pectoralis großen und kleinen Muskeln geteilt durch die Körperhöhe des Patienten ≥2</sup>, und Muskelmaß als PMI x Muskeldichte. Insgesamt wurden 220 Patienten (19,33%) in die Intensivstation zugelassen. Bei 171 Patienten (15,03%) wurde eine mechanische Lungenentlüftung durchgeführt. Schließlich starben 154 Patienten (13,53%) innerhalb der Beobachtungszeit von 30-Tag. Alle untersuchten Parameter des Pectoralis-Muskels waren bei den Patienten mit ungünstigen Kursen von Covid-19 niedriger. Alle pectoralis Muskelparameter wurden mit 30-Tage-Sterblichkeit in multivariate Analysen eingestellt für Alter und Geschlecht: pectoralis Muskelfläche, HR = 0.93 CI 95% (0.91-0.95) p < 0.001; pectoralis Muskeldichte, HR = 0.94 CI 95% (0.93-0.96) p < 0.001; pectoralis Muskelindex, HR = 0.79 CI 95% (0.75-0.85) p < 0.001, pectoralis Die analysierten Muskelparameter können jedoch nicht zur Vorhersage von Krankheitskursen verwendet werden.
| DOI: | 10.1016/j.acra.2022.05.003 |
Abstract:
Um die Auswirkungen der niedrigen Skelettmuskelmasse bei Patienten mit COVID-19 auf relevante Ergebnisse wie 30-Tage-Sterblichkeit zu bewerten, müssen Intubation und intensiver Pflegeeinheit Zulassung erforderlich sein. Für diese Studie wurden Daten aus sechs Zentren erworben. Die gewonnene Probe umfasst 1138 Patienten. Es gab 547 Frauen (48,1%) und 591 Männer (51.9%) mit einem mittleren Alter von 54.5 ± 18,8 Jahre; mittleres Alter, 55 Jahre; Reichweite, 18-84 Jahre). In jedem Fall wurde thoracic CT ohne intravenöse Applikation von Kontrastmittel durchgeführt. Die folgenden Parameter der Pectoralis-Muskeln wurden geschätzt: Muskelfläche als Summe der bilateralen Bereiche der pectoralis großen und kleineren Muskeln, Muskeldichte, Muskelindex (PMI) (Pectoralis-Muskelbereich geteilt durch den Körperhöhenwinkel des Patienten) als Verhältnis pectoralis großen und kleinen Muskeln geteilt durch die Körperhöhe des Patienten ≥2</sup>, und Muskelmaß als PMI x Muskeldichte. Insgesamt wurden 220 Patienten (19,33%) in die Intensivstation zugelassen. Bei 171 Patienten (15,03%) wurde eine mechanische Lungenentlüftung durchgeführt. Schließlich starben 154 Patienten (13,53%) innerhalb der Beobachtungszeit von 30-Tag. Alle untersuchten Parameter des Pectoralis-Muskels waren bei den Patienten mit ungünstigen Kursen von Covid-19 niedriger. Alle pectoralis Muskelparameter wurden mit 30-Tage-Sterblichkeit in multivariate Analysen eingestellt für Alter und Geschlecht: pectoralis Muskelfläche, HR = 0.93 CI 95% (0.91-0.95) p < 0.001; pectoralis Muskeldichte, HR = 0.94 CI 95% (0.93-0.96) p < 0.001; pectoralis Muskelindex, HR = 0.79 CI 95% (0.75-0.85) p < 0.001, pectoralis Die analysierten Muskelparameter können jedoch nicht zur Vorhersage von Krankheitskursen verwendet werden.
R. Heyder,
N. C. Office,
N. S. Group,
N. Coordination,
R. Coordination,
A. Coordination and
G. S. Group,
"The German Network of University Medicine: technical and organizational approaches for research data platforms",
Jan.
2023.
| DOI: | 10.1007/s00103-022-03649-1 |
[en]
I. Miederer,
J. M. M. Rogasch,
R. Fischer,
T. Fuchs,
C. Lapa,
P. Lohmann,
K. Shi,
J. Tran-Gia,
T. Wendler and
D. Hellwig,
"The Medical Informatics Initiative and the Network University Medicine - Perspectives for Nuclear Medicine",
Nuklearmedizin,
vol. 62,
no. 5,
pp. 276—283,
2023.
Georg Thieme Verlag KG,
http://dx.doi.org/10.1055/a-2067-7642.
Abstract:
Digitization in the healthcare sector and the support of clinical workflows with artificial intelligence (AI), including AI-supported image analysis, represent a great challenge and equally a promising perspective for preclinical and clinical nuclear medicine. In Germany, the Medical Informatics Initiative (MII) and the Network University Medicine (NUM) are of central importance for this transformation. This review article outlines these structures and highlights their future role in enabling privacy-preserving federated multi-center analyses with interoperable data structures harmonized between site-specific IT infrastructures. The newly founded working group "Digitization and AI" in the German Society of Nuclear Medicine (DGN) as well as the Fach- und Organspezifische Arbeitsgruppe (FOSA, specialty- and organ-specific working group) founded for the field of nuclear medicine (FOSA Nuklearmedizin) within the NUM aim to initiate and coordinate measures in the context of digital medicine and (image-)data-driven analyses for the DGN.
| DOI: | 10.1055/a-2067-7642 |
Abstract:
Digitization in the healthcare sector and the support of clinical workflows with artificial intelligence (AI), including AI-supported image analysis, represent a great challenge and equally a promising perspective for preclinical and clinical nuclear medicine. In Germany, the Medical Informatics Initiative (MII) and the Network University Medicine (NUM) are of central importance for this transformation. This review article outlines these structures and highlights their future role in enabling privacy-preserving federated multi-center analyses with interoperable data structures harmonized between site-specific IT infrastructures. The newly founded working group "Digitization and AI" in the German Society of Nuclear Medicine (DGN) as well as the Fach- und Organspezifische Arbeitsgruppe (FOSA, specialty- and organ-specific working group) founded for the field of nuclear medicine (FOSA Nuklearmedizin) within the NUM aim to initiate and coordinate measures in the context of digital medicine and (image-)data-driven analyses for the DGN.
P. Thiam,
L. Lausser,
C. Kloth,
D. Blaich,
A. Liebold,
M. Beer and
H. A. Kestler,
"Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images.",
Frontiers in artificial intelligence,
2023.
Abstract:
In den letzten Jahren wurden mehrere tiefgreifende Lernansätze im Bereich der medizinischen Bildanalyse erfolgreich angewandt. Speziell wurden verschiedene tiefe neuronale Netzwerkarchitekturen für die Detektion verschiedener Pathologien auf der Grundlage von Brust-Röntgenbildern vorgeschlagen und bewertet. Während die durchgeführten Bewertungen sehr vielversprechende Ergebnisse gezeigt haben, bestehen die meisten von ihnen in der Ausbildung und Bewertung der Leistung der vorgeschlagenen Ansätze auf einem einzigen Datensatz. Die Verallgemeinerung solcher Modelle ist jedoch in einer Kreuzdomaineinstellung recht begrenzt, da bei der Auswertung dieser Modelle auf Datensätzen, die aus verschiedenen medizinischen Zentren stammen oder unter verschiedenen Protokollen aufgezeichnet werden, ein signifikanter Leistungsabbau beobachtet werden kann. Der Leistungsabbau wird meist durch die Domänenverschiebung zwischen dem Trainingssatz und dem Bewertungssatz verursacht. Um dieses Problem zu lindern, werden in der aktuellen Arbeit unterschiedliche ununterbrochene Domänenanpassungsansätze vorgeschlagen und ausgewertet, um Kardiomegalie basierend auf Brust-Röntgenbildern in einer Kreuzdomäneneinstellung zu erkennen. Die vorgeschlagenen Ansätze erzeugen Domäneninvariante Merkmalsdarstellungen durch Anpassung der Parameter eines auf einer großen Menge markierter Proben optimierten Modells an eine Reihe von unmarkierten Bildern, die aus einem anderen Datensatz stammen. Die durchgeführte Auswertung weist auf die Wirksamkeit der vorgeschlagenen Ansätze hin, da die angepassten Modelle optimierte Modelle ausprägen, die ohne jede Form der Domänenanpassung direkt auf die Auswertesätze angewendet werden.
| DOI: | 10.3389/frai.2023.1056422 |
Abstract:
In den letzten Jahren wurden mehrere tiefgreifende Lernansätze im Bereich der medizinischen Bildanalyse erfolgreich angewandt. Speziell wurden verschiedene tiefe neuronale Netzwerkarchitekturen für die Detektion verschiedener Pathologien auf der Grundlage von Brust-Röntgenbildern vorgeschlagen und bewertet. Während die durchgeführten Bewertungen sehr vielversprechende Ergebnisse gezeigt haben, bestehen die meisten von ihnen in der Ausbildung und Bewertung der Leistung der vorgeschlagenen Ansätze auf einem einzigen Datensatz. Die Verallgemeinerung solcher Modelle ist jedoch in einer Kreuzdomaineinstellung recht begrenzt, da bei der Auswertung dieser Modelle auf Datensätzen, die aus verschiedenen medizinischen Zentren stammen oder unter verschiedenen Protokollen aufgezeichnet werden, ein signifikanter Leistungsabbau beobachtet werden kann. Der Leistungsabbau wird meist durch die Domänenverschiebung zwischen dem Trainingssatz und dem Bewertungssatz verursacht. Um dieses Problem zu lindern, werden in der aktuellen Arbeit unterschiedliche ununterbrochene Domänenanpassungsansätze vorgeschlagen und ausgewertet, um Kardiomegalie basierend auf Brust-Röntgenbildern in einer Kreuzdomäneneinstellung zu erkennen. Die vorgeschlagenen Ansätze erzeugen Domäneninvariante Merkmalsdarstellungen durch Anpassung der Parameter eines auf einer großen Menge markierter Proben optimierten Modells an eine Reihe von unmarkierten Bildern, die aus einem anderen Datensatz stammen. Die durchgeführte Auswertung weist auf die Wirksamkeit der vorgeschlagenen Ansätze hin, da die angepassten Modelle optimierte Modelle ausprägen, die ohne jede Form der Domänenanpassung direkt auf die Auswertesätze angewendet werden.
S. M. Hopff,
"Vergleich von Akut- und Langzeit-Symptomen bei mit den SARS-CoV-2-Varianten Delta und Omikron infizierten Patient:innen - Ergebnisse des Nationalen Pandemie Kohorten Netzes (NAPKON)",
Vortrag KIT Kongress 2023, Leipzig,
2023.
M. Berens,
A. Bludau,
D. Fenz,
J. Hoffmann,
C. Lang,
J. Schmitt,
W. Hoffmann and
S. Scheithauer,
"Leadership is replaced by participation in Pandemic Preparedness: A rapid review of the existing evidence on recommended approaches in crises."
in 7th International Conference on Prevention & Infection Control (ICPIC), Geneva, Switzerland.,
2023.
| DOI: | 10.1186/s13756-023-01276-2 |
| Datei: | https://doi.org/10.1186/s13756-023-01276-2 |
S. Scheithauer,
A. Bludau,
S. Heinemann,
M. Anton and
P. Knolle,
"COVID-19-Impfstrategien für Beschäftigte deutscher Kliniken: Ergebnisse einer Befragung von Leitungen der (Krankenhaus‑)Hygiene im Rahmen des B-FAST-Projektes [COVID-19 vaccination strategy for employees of German hospitals: results of a survey of infection control practitioners within the B-FAST project]",
Bundesgesundheitsbl,
vol. 65,
pp. 1299–1306,
Dez.
2022.
| DOI: | 10.1007/s00103-022-03607-x |
| Datei: |  https://www.dghm-kongress.de/fileadmin/congress/media/dghm2021/pdf/DGHM_2021_digital_Programme_booklet.pdf |
S. Scheithauer,
A. Bludau,
S. Heinemann,
M. Anton and
P. Knolle,
"COVID-19-Impfstrategien für Beschäftigte deutscher Kliniken: Ergebnisse einer Befragung von Leitungen der (Krankenhaus‑)Hygiene im Rahmen des B-FAST-Projektes [COVID-19 vaccination strategy for employees of German hospitals: results of a survey of infection control practitioners within the B-FAST project]",
Bundesgesundheitsbl,
vol. 65,
pp. 1299–1306,
Dez.
2022.
| DOI: | 10.1007/s00103-022-03607-x |
H. Almubarak,
S. Elsayed,
F. Mazzacane,
F. Schlunk,
H. Cao,
L. H. Vu,
E. Vogt,
A. Dell Orco,
D. Desser,
M. F. H. Böhmer,
B. H. Akkurt,
P. B. Sporns,
T. Penzkofer,
U. Hanning,
A. Morotti and
J. Nawabi,
"Diagnostic Accuracy and Reliability of Noncontrast Computed Tomography Markers for Acute Hematoma Expansion among Radiologists.",
Tomography (Ann Arbor, Mich.),
Dez.
2022.
Abstract:
Noncontrast Computed Tomography (NCCT) Funktionen sind vielversprechende Marker für akute Hämatomenausweitung (HE) bei Patienten mit intracerebraler Blutung (ICH). Es bleibt unklar, ob die genaue Identifizierung dieser Marker auch bei Rattern mit unterschiedlichen Erfahrungsstufen zuverlässig ist. Patienten mit akuter spontaner ICH in vier Tertiärzentren in Deutschland und Italien wurden von Januar 2017 bis Juni 2020 rückwirkend aufgenommen. Insgesamt wurden neun NCCT-Marker von einer Radiologie, einem Radiologie-Stipendiaten und einem Neuroradiologie-Stipendiaten mit verschiedenen Ebenen Erfahrung in der ICH-Bildgebung bewertet. Interrater-Relationen des Anwohner- und Radiologiekollegen wurden durch berechnete Cohen's kappa (κ)-Statistiken in Bezug auf den Neuroradiologie-Stipendiaten, der als Goldstandard bezeichnet wurde, ausgewertet. Gold-Standard-Ratings wurden nach berechneten Interrater κ-Statistiken bewertet. Globale Interrater-Relationen wurden durch berechnete Fleiss kappa-Statistiken in allen drei Lesern bewertet. Ein Vergleich der Empfänger-Betriebseigenschaften (ROCs) wurde verwendet, um Unterschiede in der Diagnosegenauigkeit für die Vorhersage der akuten Hämatomen-Expansion (HE) unter den Rattern zu bewerten. Für den Bewohner mit Interrater Cohen's kappa von 0,70 (95% CI 0.65-0.81) bis 0,96 (95% CI 0.94-0.98) wurde eine substantiell-zu-fast-perfect interrater concordance gefunden. Der Interrater Cohens Kappa für den Radiologie-Stipendiat war moderat bis fast perfekt und reichte von 0,58 (95% CI 0.52-0.65) bis 94 (95% CI 92-0.97). Der Intrarater Gold-Standard Cohen's kappa war fast perfekt und reichte von 0,79 (95% CI 0.78-0.90) bis 0,98 (95% CI 0.78-0.90). Der globale Interrater Fleiss kappa reichte von 0,62 (95%CI 0.57-0.66) auf 0,93 (95%CI 0.89-0.97). Die Diagnosegenauigkeit für die Vorhersage der akuten Hämatomenausdehnung (HE) war für das Inselzeichen und das Flüssigkeitszeichen unterschiedlich, mit <i>p</i>-Werten < 0,05. Die NCCT-Marker hatten eine weitgehend durchgängige Interrater-Vereinbarung unter den Raten mit unterschiedlichen Erfahrungsstufen. Unterschiede in der Diagnosegenauigkeit für die Vorhersage von akutem HE wurden in zwei von neun NCCT-Markern gefunden. Die Studie unterstreicht das vielversprechende Nutzen von NCCT-Markern für eine akute HE-Prädiktion.
| DOI: | 10.3390/tomography8060242 |
Abstract:
Noncontrast Computed Tomography (NCCT) Funktionen sind vielversprechende Marker für akute Hämatomenausweitung (HE) bei Patienten mit intracerebraler Blutung (ICH). Es bleibt unklar, ob die genaue Identifizierung dieser Marker auch bei Rattern mit unterschiedlichen Erfahrungsstufen zuverlässig ist. Patienten mit akuter spontaner ICH in vier Tertiärzentren in Deutschland und Italien wurden von Januar 2017 bis Juni 2020 rückwirkend aufgenommen. Insgesamt wurden neun NCCT-Marker von einer Radiologie, einem Radiologie-Stipendiaten und einem Neuroradiologie-Stipendiaten mit verschiedenen Ebenen Erfahrung in der ICH-Bildgebung bewertet. Interrater-Relationen des Anwohner- und Radiologiekollegen wurden durch berechnete Cohen's kappa (κ)-Statistiken in Bezug auf den Neuroradiologie-Stipendiaten, der als Goldstandard bezeichnet wurde, ausgewertet. Gold-Standard-Ratings wurden nach berechneten Interrater κ-Statistiken bewertet. Globale Interrater-Relationen wurden durch berechnete Fleiss kappa-Statistiken in allen drei Lesern bewertet. Ein Vergleich der Empfänger-Betriebseigenschaften (ROCs) wurde verwendet, um Unterschiede in der Diagnosegenauigkeit für die Vorhersage der akuten Hämatomen-Expansion (HE) unter den Rattern zu bewerten. Für den Bewohner mit Interrater Cohen's kappa von 0,70 (95% CI 0.65-0.81) bis 0,96 (95% CI 0.94-0.98) wurde eine substantiell-zu-fast-perfect interrater concordance gefunden. Der Interrater Cohens Kappa für den Radiologie-Stipendiat war moderat bis fast perfekt und reichte von 0,58 (95% CI 0.52-0.65) bis 94 (95% CI 92-0.97). Der Intrarater Gold-Standard Cohen's kappa war fast perfekt und reichte von 0,79 (95% CI 0.78-0.90) bis 0,98 (95% CI 0.78-0.90). Der globale Interrater Fleiss kappa reichte von 0,62 (95%CI 0.57-0.66) auf 0,93 (95%CI 0.89-0.97). Die Diagnosegenauigkeit für die Vorhersage der akuten Hämatomenausdehnung (HE) war für das Inselzeichen und das Flüssigkeitszeichen unterschiedlich, mit <i>p</i>-Werten < 0,05. Die NCCT-Marker hatten eine weitgehend durchgängige Interrater-Vereinbarung unter den Raten mit unterschiedlichen Erfahrungsstufen. Unterschiede in der Diagnosegenauigkeit für die Vorhersage von akutem HE wurden in zwei von neun NCCT-Markern gefunden. Die Studie unterstreicht das vielversprechende Nutzen von NCCT-Markern für eine akute HE-Prädiktion.
P. Fervers,
F. Fervers,
A. Jaiswal,
M. Rinneburger,
M. Weisthoff,
P. Pollmann-Schweckhorst,
J. Kottlors,
H. Carolus,
S. Lennartz,
D. Maintz,
R. Shahzad and
T. Persigehl,
"Assessment of COVID-19 lung involvement on computed tomography by deep-learning-, threshold-, and human reader-based approaches-an international, multi-center comparative study.",
Quantitative imaging in medicine and surgery,
Nov.
2022.
Abstract:
Das Ausmaß der Lungenbeteiligung an der Coronavirus-Krankheit 2019 (COVID-19)-Pneumonie, quantifiziert auf berechnete Tomographie (CT), ist ein etablierter Biomarker für Prognosen und führt klinische Entscheidungsfindungen. Der klinische Standard ist semi-quantitatives Scoring von Lungeneinbindung durch einen erfahrenen Leser. Wir wollen die Leistung automatisierter Tief- und Schwellenverfahren mit dem manuellen semiquantitativen Lungenscoring vergleichen. Darüber hinaus wollen wir eine optimale Schwelle zur Quantifizierung der beteiligten Lunge in der COVID-Pneumonie-Brust-CT unter Verwendung eines multizentrischen Datensatzes untersuchen. Insgesamt wurden 250 Patienten aufgenommen, 50 aufeinanderfolgende Patienten mit RT-PCR bestätigten COVID-19 aus unserer lokalen institutionellen Datenbank und weitere 200 Patienten aus vier internationalen Datensätzen (n=50 pro). Das Engagement der Lung wurde semi-quantitative von drei erfahrenen Radiologen nach der etablierten Brust CT Punktzahl (CCS) von 0-25 bewertet. Die Interrater-Verlässlichkeit wurde durch den Intra-Klasse-Korrelationskoeffizienten (ICC) gemeldet. Die Deep-learning-basierte Segmentierung von Grundglas und Konsolidierung wurde von CT Pulmo Auto Results Prototyp Plugin auf IntelliSpace Discovery (Philips Healthcare, Niederlande) erhalten. Die Threshold-basierte Segmentierung der betroffenen Lunge wurde mit Hilfe eines Open-Source-Tools für die Ganzlungssegmentierung unter Anwesenheit schwerer Pathologien (R231CovidWeb, Hofmanninger <i>et al.</i>, 2020) und fortlaufender quantitativer Bewertung der Lungendämpfung durchgeführt. Die beste Schwelle wurde durch Training und Testen einer linearen Regression von tiefgreifenden und schwellenbasierten Ergebnissen in einer fünffachen Cross-Validationsstrategie untersucht. Median CCS unter 250 bewerteten Patienten betrug 10 [6-15]. Inter-Rater Zuverlässigkeit des CCS war ausgezeichnet [ICC 0.97 (0.97-0.98)]. Die beste Dämpfungsschwelle für die Identifizierung der betroffenen Lunge betrug -522 HU. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Das manuelle semiquantitative CCS unterschätzt das Ausmaß der COVID-Pneumonie in höheren Score-Bereichen, was seine klinische Nützlichkeit bei schweren Erkrankungen begrenzt. Die klinische Umsetzung vollautomatischer Methoden, wie tiefgreifende oder schwellenbasierte Ansätze (beste Schwelle in unserem Multicenter-Datensatz: -522 HU), könnte Zeit des geschulten Personals sparen, Interreader-Variabilität abschaffen und eine wirklich quantitative, lineare Bewertung der COVID-Lungenbeteiligung ermöglichen.
| DOI: | 10.21037/qims-22-175 |
Abstract:
Das Ausmaß der Lungenbeteiligung an der Coronavirus-Krankheit 2019 (COVID-19)-Pneumonie, quantifiziert auf berechnete Tomographie (CT), ist ein etablierter Biomarker für Prognosen und führt klinische Entscheidungsfindungen. Der klinische Standard ist semi-quantitatives Scoring von Lungeneinbindung durch einen erfahrenen Leser. Wir wollen die Leistung automatisierter Tief- und Schwellenverfahren mit dem manuellen semiquantitativen Lungenscoring vergleichen. Darüber hinaus wollen wir eine optimale Schwelle zur Quantifizierung der beteiligten Lunge in der COVID-Pneumonie-Brust-CT unter Verwendung eines multizentrischen Datensatzes untersuchen. Insgesamt wurden 250 Patienten aufgenommen, 50 aufeinanderfolgende Patienten mit RT-PCR bestätigten COVID-19 aus unserer lokalen institutionellen Datenbank und weitere 200 Patienten aus vier internationalen Datensätzen (n=50 pro). Das Engagement der Lung wurde semi-quantitative von drei erfahrenen Radiologen nach der etablierten Brust CT Punktzahl (CCS) von 0-25 bewertet. Die Interrater-Verlässlichkeit wurde durch den Intra-Klasse-Korrelationskoeffizienten (ICC) gemeldet. Die Deep-learning-basierte Segmentierung von Grundglas und Konsolidierung wurde von CT Pulmo Auto Results Prototyp Plugin auf IntelliSpace Discovery (Philips Healthcare, Niederlande) erhalten. Die Threshold-basierte Segmentierung der betroffenen Lunge wurde mit Hilfe eines Open-Source-Tools für die Ganzlungssegmentierung unter Anwesenheit schwerer Pathologien (R231CovidWeb, Hofmanninger <i>et al.</i>, 2020) und fortlaufender quantitativer Bewertung der Lungendämpfung durchgeführt. Die beste Schwelle wurde durch Training und Testen einer linearen Regression von tiefgreifenden und schwellenbasierten Ergebnissen in einer fünffachen Cross-Validationsstrategie untersucht. Median CCS unter 250 bewerteten Patienten betrug 10 [6-15]. Inter-Rater Zuverlässigkeit des CCS war ausgezeichnet [ICC 0.97 (0.97-0.98)]. Die beste Dämpfungsschwelle für die Identifizierung der betroffenen Lunge betrug -522 HU. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Das manuelle semiquantitative CCS unterschätzt das Ausmaß der COVID-Pneumonie in höheren Score-Bereichen, was seine klinische Nützlichkeit bei schweren Erkrankungen begrenzt. Die klinische Umsetzung vollautomatischer Methoden, wie tiefgreifende oder schwellenbasierte Ansätze (beste Schwelle in unserem Multicenter-Datensatz: -522 HU), könnte Zeit des geschulten Personals sparen, Interreader-Variabilität abschaffen und eine wirklich quantitative, lineare Bewertung der COVID-Lungenbeteiligung ermöglichen.
C. González,
K. Gotkowski,
M. Fuchs,
A. Bucher,
A. Dadras,
R. Fischbach,
I. J. Kaltenborn and
A. Mukhopadhyay,
"Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation",
Medical image analysis,
vol. 82,
pp. 102596,
Nov.
2022.
Abstract:
Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation. However, deep learning models are not trusted in the clinical routine due to failing silently on out-of-distribution (OOD) data. We propose a lightweight OOD detection method that leverages the Mahalanobis distance in the feature space and seamlessly integrates into state-of-the-art segmentation pipelines. The simple approach can even augment pre-trained models with clinically relevant uncertainty quantification. We validate our method across four chest CT distribution shifts and two magnetic resonance imaging applications, namely segmentation of the hippocampus and the prostate. Our results show that the proposed method effectively detects far- and near-OOD samples across all explored scenarios.
| DOI: | 10.1016/j.media.2022.102596 |
| Datei: | https://pubmed.ncbi.nlm.nih.gov/36084564/ |
Abstract:
Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation. However, deep learning models are not trusted in the clinical routine due to failing silently on out-of-distribution (OOD) data. We propose a lightweight OOD detection method that leverages the Mahalanobis distance in the feature space and seamlessly integrates into state-of-the-art segmentation pipelines. The simple approach can even augment pre-trained models with clinically relevant uncertainty quantification. We validate our method across four chest CT distribution shifts and two magnetic resonance imaging applications, namely segmentation of the hippocampus and the prostate. Our results show that the proposed method effectively detects far- and near-OOD samples across all explored scenarios.
[en]
T. J. Hartung,
C. Neumann,
T. Bahmer,
I. Chaplinskaya-Sobol,
M. Endres,
J. Geritz,
K. G. Haeusler,
P. U. Heuschmann,
H. Hildesheim,
A. Hinz,
S. Hopff,
A. Horn,
M. Krawczak,
L. Krist,
J. Kudelka,
W. Lieb,
C. Maetzler,
A. Mehnert-Theuerkauf,
F. A. Montellano,
C. Morbach,
S. Schmidt,
S. Schreiber,
F. Steigerwald,
S. Störk,
W. Maetzler and
C. Finke,
"Fatigue and cognitive impairment after COVID-19: A prospective multicentre study",
EClinicalMedicine,
vol. 53,
no. 101651,
pp. 101651,
Nov.
2022.
Elsevier BV.
Abstract:
Background: Reliable estimates of frequency, severity and associated factors of both fatigue and cognitive impairment after COVID-19 are needed. Also, it is not clear whether the two are distinct sequelae of COVID-19 or part of the same syndrome." Methods: In this prospective multicentre study, frequency of post-COVID fatigue and cognitive impairment were assessed in n = 969 patients (535 [55%] female) $\geq$6 months after SARS-CoV-2 infection with the FACIT-Fatigue scale (cut-off $łeq$30) and Montreal Cognitive Assessment ($łeq$25 mild, $łeq$17 moderate impairment) between November 15, 2020 and September 29, 2021 at University Medical Center Schleswig-Holstein, Campus Kiel and University Hospital W"urzburg in Germany. 969 matched non-COVID controls were drawn from a pre-pandemic, randomised, Germany-wide population survey which also included the FACIT-Fatigue scale. Associated sociodemographic, comorbid, clinical, psychosocial factors and laboratory markers were identified with univariate and multivariable linear regression models. Findings: On average 9 months after infection, 19% of patients had clinically relevant fatigue, compared to 8% of matched non-COVID controls (p < 0.001). Factors associated with fatigue were female gender, younger age, history of depression and the number of acute COVID symptoms. Among acute COVID symptoms, altered consciousness, dizziness and myalgia were most strongly associated with long-term fatigue. Moreover, 26% of patients had mild and 1% had moderate cognitive impairment. Factors associated with cognitive impairment were older age, male gender, shorter education and a history of neuropsychiatric disease. There was no significant correlation between fatigue and cognitive impairment and only 5% of patients suffered from both conditions. Interpretation: Fatigue and cognitive impairment are two common, but distinct sequelae of COVID-19 with potentially separate pathophysiological pathways. Funding: German Federal Ministry of Education and Research (BMBF).
| DOI: | 10.1016/j.eclinm.2022.101651 |
| Pubmed: | 36133318 |
Abstract:
Background: Reliable estimates of frequency, severity and associated factors of both fatigue and cognitive impairment after COVID-19 are needed. Also, it is not clear whether the two are distinct sequelae of COVID-19 or part of the same syndrome." Methods: In this prospective multicentre study, frequency of post-COVID fatigue and cognitive impairment were assessed in n = 969 patients (535 [55%] female) $\geq$6 months after SARS-CoV-2 infection with the FACIT-Fatigue scale (cut-off $łeq$30) and Montreal Cognitive Assessment ($łeq$25 mild, $łeq$17 moderate impairment) between November 15, 2020 and September 29, 2021 at University Medical Center Schleswig-Holstein, Campus Kiel and University Hospital W"urzburg in Germany. 969 matched non-COVID controls were drawn from a pre-pandemic, randomised, Germany-wide population survey which also included the FACIT-Fatigue scale. Associated sociodemographic, comorbid, clinical, psychosocial factors and laboratory markers were identified with univariate and multivariable linear regression models. Findings: On average 9 months after infection, 19% of patients had clinically relevant fatigue, compared to 8% of matched non-COVID controls (p < 0.001). Factors associated with fatigue were female gender, younger age, history of depression and the number of acute COVID symptoms. Among acute COVID symptoms, altered consciousness, dizziness and myalgia were most strongly associated with long-term fatigue. Moreover, 26% of patients had mild and 1% had moderate cognitive impairment. Factors associated with cognitive impairment were older age, male gender, shorter education and a history of neuropsychiatric disease. There was no significant correlation between fatigue and cognitive impairment and only 5% of patients suffered from both conditions. Interpretation: Fatigue and cognitive impairment are two common, but distinct sequelae of COVID-19 with potentially separate pathophysiological pathways. Funding: German Federal Ministry of Education and Research (BMBF).
C. Werlein,
M. Ackermann,
H. Stark,
H. R. Shah,
A. Tzankov,
J. D. Haslbauer,
S. Stillfried,
R. D. Bülow,
A. El-Armouche,
S. Kuenzel,
J. L. Robertus,
M. Reichardt,
A. Haverich,
A. Höfer,
L. Neubert,
E. Plucinski,
P. Braubach,
S. Verleden,
T. Salditt,
N. Marx,
T. Welte,
J. Bauersachs,
H. Kreipe,
S. J. Mentzer,
P. Boor,
S. M. Black,
F. Länger,
M. Kuehnel and
D. Jonigk,
"Inflammation and vascular remodeling in COVID-19 hearts",
Angiogenesis,
vol. 26,
no. 2,
pp. 233—248,
Nov.
2022.
| DOI: | 10.1007/s10456-022-09860-7 |
| Datei: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9660162/ |
[de]
K. Gaede,
J. Heidemann,
H. Goebels,
A. Heinemann,
K. Püschel and
B. Ondruschka,
"Pandemic Preparedness bei der Obduktion? Potentiale und Grenzen des IfSG",
Medizinrecht,
vol. 40,
no. 11,
pp. 892—901,
Nov.
2022.
| DOI: | 10.1007/s00350-022-6331-6 |
| Datei: | https://doi.org/10.1007/s00350-022-6331-6 |
C. Yüksel,
M. Sähn,
M. Kleines,
J. C. Brokmann,
C. K. Kuhl,
D. Truhn,
A. Ritter,
P. Isfort and
M. F. Schulze-Hagen,
"Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2",
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin,
vol. 194,
no. 11,
pp. 1229-1241,
Nov.
2022.
Abstract:
So far, typical findings for COVID-19 in computed tomography (CT) have been described as bilateral, multifocal ground glass opacities (GGOs) and consolidations, as well as intralobular and interlobular septal thickening. On the contrary, round consolidations with the halo sign are considered uncommon and are typically found in fungal infections, such as invasive pulmonary aspergillosis. The authors recently observed several patients with COVID-19 pneumonia presenting with round, multifocal consolidations accompanied by a halo sign. As this may indicate alterations of CT morphology based on the virus variant, the aim of this study was to investigate this matter in more detail. 161 CT scans of patients with confirmed SARS-CoV-2 infection (RT-PCR within 2 days of CT) examined between January 2021 and September 15, 2021 were included. Follow-up examinations, patients with invasive ventilation at the time of CT, and patients with insufficient virus typing for variants of concern (VOC) were excluded. CT scans were assessed for vertical and axial distribution of pulmonary patterns, degree of involvement, uni- vs. bilaterality, reticulations, and other common findings. The mean density of representative lesions was assessed in Hounsfield units. Results were compared using Mann-Whitney U-tests, Student's t-rests, descriptive statistics, and Fisher's exact tests. 75 patients did not meet the inclusion criteria. Therefore, 86/161 CT scans of unique patients were analyzed. PCR VOC testing confirmed manifestation of the Delta-VOC SARS-CoV-2 in 22 patients, 39 patients with Alpha-VOC and the remaining 25 patients with Non-VOC SARS-CoV-2 infections. Three patients with the Delta-VOC demonstrated multiple pulmonary masses or nodules with surrounding halo sign, whereas no patients with either Alpha-VOC (p = 0.043) or non-VOC (p = 0.095) demonstrated these findings. All three patients were admitted to normal wards and had no suspicion of a pulmonary co-infection. Patients with Delta-VOC were less likely to have ground glass opacities compared to Alpha-VOC (7/22 or 31.8 % vs. 4/39 or 10.3 %; p < 0.001), whereas a significant difference has not been observed between Delta-VOC and non-VOC (5/25 or 20 %; p = 0.348). The mean representative density of lesions did not show significant differences between the studied cohorts. In this study 3 out of 22 patients (13.6 %) with Delta-VOC presented with bilateral round pulmonary masses or nodules with surrounding halo signs, which has not been established as a notable imaging pattern in COVID-19 pneumonia yet. Compared to the other cohorts, a lesser percentage of patients with Delta-VOC presented with ground glass opacities. Based on these results Delta-VOC might cause a divergence in CT-morphologic phenotype. · Until recently, CT-morphologic signs of COVID-19 pneumonia have been presumed to be uncontroversially understood. Yet, recently the authors observed diverging pulmonary alterations in patients infected with Delta-VOC.. · These imaging alterations included round pulmonary masses or nodules with surrounding halo sign.. · These imaging alterations have not yet been established as typical for COVID-19 pneumonia, yet.. · Based on these results, Delta-VOC could impose a divergence of CT-morphologic phenotype.. · Yüksel C, Sähn M, Kleines M et al. Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2 . Fortschr Röntgenstr 2022; 194: 1229 - 1241.
| DOI: | 10.1055/a-1826-0436 |
| Datei: | https://pubmed.ncbi.nlm.nih.gov/35850138/ |
Abstract:
So far, typical findings for COVID-19 in computed tomography (CT) have been described as bilateral, multifocal ground glass opacities (GGOs) and consolidations, as well as intralobular and interlobular septal thickening. On the contrary, round consolidations with the halo sign are considered uncommon and are typically found in fungal infections, such as invasive pulmonary aspergillosis. The authors recently observed several patients with COVID-19 pneumonia presenting with round, multifocal consolidations accompanied by a halo sign. As this may indicate alterations of CT morphology based on the virus variant, the aim of this study was to investigate this matter in more detail. 161 CT scans of patients with confirmed SARS-CoV-2 infection (RT-PCR within 2 days of CT) examined between January 2021 and September 15, 2021 were included. Follow-up examinations, patients with invasive ventilation at the time of CT, and patients with insufficient virus typing for variants of concern (VOC) were excluded. CT scans were assessed for vertical and axial distribution of pulmonary patterns, degree of involvement, uni- vs. bilaterality, reticulations, and other common findings. The mean density of representative lesions was assessed in Hounsfield units. Results were compared using Mann-Whitney U-tests, Student's t-rests, descriptive statistics, and Fisher's exact tests. 75 patients did not meet the inclusion criteria. Therefore, 86/161 CT scans of unique patients were analyzed. PCR VOC testing confirmed manifestation of the Delta-VOC SARS-CoV-2 in 22 patients, 39 patients with Alpha-VOC and the remaining 25 patients with Non-VOC SARS-CoV-2 infections. Three patients with the Delta-VOC demonstrated multiple pulmonary masses or nodules with surrounding halo sign, whereas no patients with either Alpha-VOC (p = 0.043) or non-VOC (p = 0.095) demonstrated these findings. All three patients were admitted to normal wards and had no suspicion of a pulmonary co-infection. Patients with Delta-VOC were less likely to have ground glass opacities compared to Alpha-VOC (7/22 or 31.8 % vs. 4/39 or 10.3 %; p < 0.001), whereas a significant difference has not been observed between Delta-VOC and non-VOC (5/25 or 20 %; p = 0.348). The mean representative density of lesions did not show significant differences between the studied cohorts. In this study 3 out of 22 patients (13.6 %) with Delta-VOC presented with bilateral round pulmonary masses or nodules with surrounding halo signs, which has not been established as a notable imaging pattern in COVID-19 pneumonia yet. Compared to the other cohorts, a lesser percentage of patients with Delta-VOC presented with ground glass opacities. Based on these results Delta-VOC might cause a divergence in CT-morphologic phenotype. · Until recently, CT-morphologic signs of COVID-19 pneumonia have been presumed to be uncontroversially understood. Yet, recently the authors observed diverging pulmonary alterations in patients infected with Delta-VOC.. · These imaging alterations included round pulmonary masses or nodules with surrounding halo sign.. · These imaging alterations have not yet been established as typical for COVID-19 pneumonia, yet.. · Based on these results, Delta-VOC could impose a divergence of CT-morphologic phenotype.. · Yüksel C, Sähn M, Kleines M et al. Possible Alterations of Imaging Patterns in Computed Tomography for Delta-VOC of SARS-CoV-2 . Fortschr Röntgenstr 2022; 194: 1229 - 1241.
C. Lemhöfer,
K. S. Appel,
W. Häuser,
N. Hettich,
M. Kohls and
M. C. Polidori,
"Post-COVID: Alles eine Frage der Definition?",
Dtsch Med Wochenschr,
vol. 147,
no. 21,
pp. 1391—1397,
Okt.
2022.
Georg Thieme Verlag KG.
Abstract:
Die Pr"avalenz des Post-COVID-Syndroms (PCS) ist noch nicht abschließend gekl"art. Die bisherigen Definitionen bilden vorrangig zeitliche Aspekte ab, lassen jedoch funktionelle Defizite sowie die Objektivierung von Symptomen außer Acht. Dies f"uhrt zu diagnostischen sowie therapeutischen Unklarheiten. In Pubmed wurde daher nach systematischen Reviews gesucht, die sich mit den Folgen einer SARS-CoV-2-Infektion befassten. Die zugrunde liegenden Definitionen sowie zeitlichen Einschlusskriterien wurden extrahiert. 16 systematische Reviews wurden eingeschlossen, davon 11 mit einer Definition des PCS. In 58 % der analysierten Einzelstudien wurden Patienten mit einer Symptomatik > 12 Wochen und damit entsprechend der Definition des PCS inkludiert. Fazit: Eine weitere Pr"azisierung der Definition des PCS ist notwendig, um Diagnostik und eine multimodale Behandlung zu erleichtern und die knappen therapeutischen Ressourcen entsprechend zu nutzen.
Abstract:
Die Pr"avalenz des Post-COVID-Syndroms (PCS) ist noch nicht abschließend gekl"art. Die bisherigen Definitionen bilden vorrangig zeitliche Aspekte ab, lassen jedoch funktionelle Defizite sowie die Objektivierung von Symptomen außer Acht. Dies f"uhrt zu diagnostischen sowie therapeutischen Unklarheiten. In Pubmed wurde daher nach systematischen Reviews gesucht, die sich mit den Folgen einer SARS-CoV-2-Infektion befassten. Die zugrunde liegenden Definitionen sowie zeitlichen Einschlusskriterien wurden extrahiert. 16 systematische Reviews wurden eingeschlossen, davon 11 mit einer Definition des PCS. In 58 % der analysierten Einzelstudien wurden Patienten mit einer Symptomatik > 12 Wochen und damit entsprechend der Definition des PCS inkludiert. Fazit: Eine weitere Pr"azisierung der Definition des PCS ist notwendig, um Diagnostik und eine multimodale Behandlung zu erleichtern und die knappen therapeutischen Ressourcen entsprechend zu nutzen.
M. Voigtlaender,
C. Edler,
M. Gerling,
J. Schädler,
B. Ondruschka,
A. S. Schröder,
J. Sperhake,
S. Ehrhardt,
L. Wang,
M. Haddad,
V. Kiencke,
T. Renné,
K. Roedl,
S. Kluge,
D. Wichmann and
F. Länger,
"Thromboembolic events in deceased patients with proven SARS-CoV-2 infection: Frequency, characteristics and risk factors",
Thrombosis Research,
vol. 218,
pp. 171—176,
Okt.
2022.
Abstract:
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| DOI: | 10.1016/j.thromres.2022.08.021 |
| Datei: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420077/ |
Abstract:
Unlabelled Image
T. J. Hartung,
C. Neumann,
T. Bahmer,
I. Chaplinskaya-Sobol,
M. Endres,
J. Geritz,
K. G. Haeusler,
P. Heuschmann,
H. Hildesheim,
A. Hinz,
S. Hopff,
A. Horn,
M. Krawczak,
L. Krist,
J. Kudelka,
W. Lieb,
C. Maetzler,
A. Mehnert-Theuerkauf,
F. Montellano,
C. Morbach,
S. Schmidt,
S. Schreiber,
F. Steigerwald,
S. Störk,
W. Maetzler and
C. Finke,
"Fatigue and cognitive impairment after COVID-19: A prospective multicentre study.",
EClinicalMedicine,
Sep.
2022.
| DOI: | 10.1016/j.eclinm.2022.101651 |
[eng]
S. Krasemann,
C. Dittmayer,
S. Stillfried,
J. Meinhardt,
F. Heinrich,
K. Hartmann,
S. Pfefferle,
E. Thies,
R. Manitius,
T. A. D. Aschman,
J. Radke,
A. Osterloh,
S. Schmid,
E. Buhl,
J. Ihlow,
F. Dubois,
V. Arnhold,
S. Elezkurtaj,
D. Horst,
A. Hocke,
S. Timm,
S. Bachmann,
V. Corman,
H. Goebel,
J. Matschke,
S. Stanelle-Bertram,
G. Gabriel,
D. Seilhean,
B. Ondruschka,
M. Ochs,
W. Stenzel,
F. L. Heppner,
P. Boor,
H. Radbruch,
M. Laue and
M. Glatzel,
"Assessing and improving the validity of COVID-19 autopsy studies - A multicentre approach to establish essential standards for immunohistochemical and ultrastructural analyses",
EBioMedicine,
vol. 83,
pp. 104193,
Sep.
2022.
Abstract:
BACKGROUND: Autopsy studies have provided valuable insights into the pathophysiology of COVID-19. Controversies remain about whether the clinical presentation is due to direct organ damage by SARS-CoV-2 or secondary effects, such as overshooting immune response. SARS-CoV-2 detection in tissues by RT-qPCR and immunohistochemistry (IHC) or electron microscopy (EM) can help answer these questions, but a comprehensive evaluation of these applications is missing. METHODS: We assessed publications using IHC and EM for SARS-CoV-2 detection in autopsy tissues. We systematically evaluated commercially available antibodies against the SARS-CoV-2 proteins in cultured cell lines and COVID-19 autopsy tissues. In a multicentre study, we evaluated specificity, reproducibility, and inter-observer variability of SARS-CoV-2 IHC. We correlated RT-qPCR viral tissue loads with semiquantitative IHC scoring. We used qualitative and quantitative EM analyses to refine criteria for ultrastructural identification of SARS-CoV-2. FINDINGS: Publications show high variability in detection and interpretation of SARS-CoV-2 abundance in autopsy tissues by IHC or EM. We show that IHC using antibodies against SARS-CoV-2 nucleocapsid yields the highest sensitivity and specificity. We found a positive correlation between presence of viral proteins by IHC and RT-qPCR-determined SARS-CoV-2 viral RNA load (N= 35; r=-0.83, p-value \textless0.0001). For EM, we refined criteria for virus identification and provide recommendations for optimized sampling and analysis. 135 of 144 publications misinterpret cellular structures as virus using EM or show only insufficient data. We provide publicly accessible digitized EM sections as a reference and for training purposes. INTERPRETATION: Since detection of SARS-CoV-2 in human autopsy tissues by IHC and EM is difficult and frequently incorrect, we propose criteria for a re-evaluation of available data and guidance for further investigations of direct organ effects by SARS-CoV-2. FUNDING: German Federal Ministry of Health, German Federal Ministry of Education and Research, Berlin University Alliance, German Research Foundation, German Center for Infectious Research.
| DOI: | 10.1016/j.ebiom.2022.104193 |
Abstract:
BACKGROUND: Autopsy studies have provided valuable insights into the pathophysiology of COVID-19. Controversies remain about whether the clinical presentation is due to direct organ damage by SARS-CoV-2 or secondary effects, such as overshooting immune response. SARS-CoV-2 detection in tissues by RT-qPCR and immunohistochemistry (IHC) or electron microscopy (EM) can help answer these questions, but a comprehensive evaluation of these applications is missing. METHODS: We assessed publications using IHC and EM for SARS-CoV-2 detection in autopsy tissues. We systematically evaluated commercially available antibodies against the SARS-CoV-2 proteins in cultured cell lines and COVID-19 autopsy tissues. In a multicentre study, we evaluated specificity, reproducibility, and inter-observer variability of SARS-CoV-2 IHC. We correlated RT-qPCR viral tissue loads with semiquantitative IHC scoring. We used qualitative and quantitative EM analyses to refine criteria for ultrastructural identification of SARS-CoV-2. FINDINGS: Publications show high variability in detection and interpretation of SARS-CoV-2 abundance in autopsy tissues by IHC or EM. We show that IHC using antibodies against SARS-CoV-2 nucleocapsid yields the highest sensitivity and specificity. We found a positive correlation between presence of viral proteins by IHC and RT-qPCR-determined SARS-CoV-2 viral RNA load (N= 35; r=-0.83, p-value \textless0.0001). For EM, we refined criteria for virus identification and provide recommendations for optimized sampling and analysis. 135 of 144 publications misinterpret cellular structures as virus using EM or show only insufficient data. We provide publicly accessible digitized EM sections as a reference and for training purposes. INTERPRETATION: Since detection of SARS-CoV-2 in human autopsy tissues by IHC and EM is difficult and frequently incorrect, we propose criteria for a re-evaluation of available data and guidance for further investigations of direct organ effects by SARS-CoV-2. FUNDING: German Federal Ministry of Health, German Federal Ministry of Education and Research, Berlin University Alliance, German Research Foundation, German Center for Infectious Research.
[eng]
M. Casagrande,
A. Fitzek,
M. Spitzer,
K. Püschel,
M. Glatzel,
S. Krasemann,
M. Aepfelbacher,
D. Nörz,
M. Lütgehetmann,
S. Pfefferle and
M. Schultheiss,
"Detection of SARS-CoV-2 genomic and subgenomic RNA in retina and optic nerve of patients with COVID-19",
The British Journal of Ophthalmology,
vol. 106,
no. 9,
pp. 1313—1317,
Sep.
2022.
| DOI: | 10.1136/bjophthalmol-2020-318618 |
N. Hettich,
"Lebensqualität von COVID-19 Erkrankten im Verlauf (Analyse aus dem NAPKON Projekt)",
Vortrag Deutscher Kongress für Physikalische und Rehabilitative Medizin,
Sep.
2022.
M. Weigl and
C. Lemhöfer,
"Leistungen zur Frührehabilitation während und nach dem akutstationären NAPKON Erweiterungsmodul zur Analyse von Pat. in Rehabilitationskliniken nach COVID-19",
Vortrag Deutscher Kongress für Physikalische und Rehabilitative Medizin,
Sep.
2022.
S. Hopff,
"Netzwerk Universitätsmedizin - Aufbau und Projekte inkl. NAPKON",
ortrag Deutscher Kongress für Physikalische und Rehabilitative Medizin,
Sep.
2022.
M. Weigl,
"Post-COVID: Prognostische Faktoren für Einschränkungen der Arbeitsfähigkeit und Bedarf an Rehabilitation (Analyse aus dem NAPKON Projekt",
Vortrag Deutscher Kongress für Physikalische und Rehabilitative Medizin,
Sep.
2022.
[en]
T. Bahmer,
C. Borzikowsky,
W. Lieb,
A. Horn,
L. Krist,
J. Fricke,
C. Scheibenbogen,
K. F. Rabe,
W. Maetzler,
C. Maetzler,
M. Laudien,
D. Frank,
S. Ballhausen,
A. Hermes,
O. Miljukov,
K. G. Haeusler,
N. E. E. Mokhtari,
M. Witzenrath,
J. J. Vehreschild,
D. Krefting,
D. Pape,
F. A. Montellano,
M. Kohls,
C. Morbach,
S. Störk,
J. Reese,
T. Keil,
P. Heuschmann,
M. Krawczak,
S. Schreiber and
N. group,
"Severity, predictors and clinical correlates of Post-COVID syndrome (PCS) in Germany: A prospective, multi-centre, population-based cohort study",
EClinicalMedicine,
vol. 51,
no. 101549,
pp. 101549,
Sep.
2022.
Elsevier BV.
Abstract:
Background: Post-COVID syndrome (PCS) is an important sequela of COVID-19, characterised by symptom persistence for >3 months, post-acute symptom development, and worsening of pre-existing comorbidities. The causes and public health impact of PCS are still unclear, not least for the lack of efficient means to assess the presence and severity of PCS. Methods: COVIDOM is a population-based cohort study of polymerase chain reaction (PCR) confirmed cases of SARS-CoV-2 infection, recruited through public health authorities in three German regions (Kiel, Berlin, W"urzburg) between November 15, 2020 and September 29, 2021. Main inclusion criteria were (i) a PCR confirmed SARS-CoV-2 infection and (ii) a period of at least 6 months between the infection and the visit to the COVIDOM study site. Other inclusion criteria were written informed consent and age $\geq$18 years. Key exclusion criterion was an acute reinfection with SARS-CoV-2. Study site visits included standardised interviews, in-depth examination, and biomaterial procurement. In sub-cohort Kiel-I, a PCS (severity) score was developed based upon 12 long-term symptom complexes. Two validation sub-cohorts (W"urzburg/Berlin, Kiel-II) were used for PCS score replication and identification of clinically meaningful predictors. This study is registered at clinicaltrials.gov (NCT04679584) and at the German Registry for Clinical Studies (DRKS, DRKS00023742). Findings: In Kiel-I (n = 667, 57% women), 90% of participants had received outpatient treatment for acute COVID-19. Neurological ailments (61·5%), fatigue (57·1%), and sleep disturbance (57·0%) were the most frequent persisting symptoms at 6-12 months after infection. Across sub-cohorts (W"urzburg/Berlin, n = 316, 52% women; Kiel-II, n = 459, 56% women), higher PCS scores were associated with lower health-related quality of life (EQ-5D-5L-VAS/-index: r = -0·54/ -0·56, all p < 0·0001). Severe, moderate, and mild/no PCS according to the individual participant's PCS score occurred in 18·8%, 48·2%, and 32·9%, respectively, of the Kiel-I sub-cohort. In both validation sub-cohorts, statistically significant predictors of the PCS score included the intensity of acute phase symptoms and the level of personal resilience. Interpretation: PCS severity can be quantified by an easy-to-use symptom-based score reflecting acute phase disease burden and general psychological predisposition. The PCS score thus holds promise to facilitate the clinical diagnosis of PCS, scientific studies of its natural course, and the development of therapeutic interventions. Funding: The COVIDOM study is funded by the Network University Medicine (NUM) as part of the National Pandemic Cohort Network (NAPKON).
| DOI: | 10.1016/j.eclinm.2022.101549 |
| Pubmed: | 35875815 |
Abstract:
Background: Post-COVID syndrome (PCS) is an important sequela of COVID-19, characterised by symptom persistence for >3 months, post-acute symptom development, and worsening of pre-existing comorbidities. The causes and public health impact of PCS are still unclear, not least for the lack of efficient means to assess the presence and severity of PCS. Methods: COVIDOM is a population-based cohort study of polymerase chain reaction (PCR) confirmed cases of SARS-CoV-2 infection, recruited through public health authorities in three German regions (Kiel, Berlin, W"urzburg) between November 15, 2020 and September 29, 2021. Main inclusion criteria were (i) a PCR confirmed SARS-CoV-2 infection and (ii) a period of at least 6 months between the infection and the visit to the COVIDOM study site. Other inclusion criteria were written informed consent and age $\geq$18 years. Key exclusion criterion was an acute reinfection with SARS-CoV-2. Study site visits included standardised interviews, in-depth examination, and biomaterial procurement. In sub-cohort Kiel-I, a PCS (severity) score was developed based upon 12 long-term symptom complexes. Two validation sub-cohorts (W"urzburg/Berlin, Kiel-II) were used for PCS score replication and identification of clinically meaningful predictors. This study is registered at clinicaltrials.gov (NCT04679584) and at the German Registry for Clinical Studies (DRKS, DRKS00023742). Findings: In Kiel-I (n = 667, 57% women), 90% of participants had received outpatient treatment for acute COVID-19. Neurological ailments (61·5%), fatigue (57·1%), and sleep disturbance (57·0%) were the most frequent persisting symptoms at 6-12 months after infection. Across sub-cohorts (W"urzburg/Berlin, n = 316, 52% women; Kiel-II, n = 459, 56% women), higher PCS scores were associated with lower health-related quality of life (EQ-5D-5L-VAS/-index: r = -0·54/ -0·56, all p < 0·0001). Severe, moderate, and mild/no PCS according to the individual participant's PCS score occurred in 18·8%, 48·2%, and 32·9%, respectively, of the Kiel-I sub-cohort. In both validation sub-cohorts, statistically significant predictors of the PCS score included the intensity of acute phase symptoms and the level of personal resilience. Interpretation: PCS severity can be quantified by an easy-to-use symptom-based score reflecting acute phase disease burden and general psychological predisposition. The PCS score thus holds promise to facilitate the clinical diagnosis of PCS, scientific studies of its natural course, and the development of therapeutic interventions. Funding: The COVIDOM study is funded by the Network University Medicine (NUM) as part of the National Pandemic Cohort Network (NAPKON).
[en]
M. Paparoupa,
A. S. Schröder,
J. Braunsteiner,
M. M. Addo,
M. Lütgehetmann,
K. Roedl,
S. Kluge,
B. Ondruschka and
D. Wichmann,
"The Effects of SARS-CoV-2 Virus Type and of Vaccination Status on Causes of Death Over the Course of the COVID-19 Pandemic.",
Deutsches Ärzteblatt International,
vol. 119,
no. 35-36,
pp. 607—608,
Sep.
2022.
| DOI: | 10.3238/arztebl.m2022.0255 |
| Datei: | https://dx.doi.org/10.3238/arztebl.m2022.0255 |
M. Thormann,
T. Lerach,
S. Gottschling,
J. Omari,
M. Pech and
A. Surov,
"[Radiology residency training during the COVID-19 pandemic : Conception and evaluation of a three-phase online-based teaching concept]",
Radiologie (Heidelberg, Germany),
vol. 62,
no. 8,
pp. 692-700,
Aug.
2022.
Abstract:
The coronavirus pandemic has posed major challenges to clinical training. Innovative and interactive concepts are needed to maintain training for residents even in times of contact restrictions and distance rules. Training concepts for residents are underrepresented in the current literature. We present an innovative online-based training concept for radiology residents in our department, based on a tripartite design; independent case preparation where residents refer to existing knowledge is followed by a case discussion and specific questions and feedback from the participating senior physicians. A questionnaire-based evaluation of the training concept was carried out after 12 months. We found that participants rated the training concept positively when it came to difficulty, representativeness of clinical work and relevance for specialist training. The questionnaire responses also provided insights into the desired duration, the selection of imaging modalities, and frequency of the concept in the future. All respondents stated that they had benefited from the format. Online-based concepts can therefore be a relevant contribution to the clinical training of residents and represent an adequate alternative to or extension of analog concepts.
| DOI: | 10.1007/s00117-022-01005-7 |
| Datei: | https://pubmed.ncbi.nlm.nih.gov/35913573/ |
Abstract:
The coronavirus pandemic has posed major challenges to clinical training. Innovative and interactive concepts are needed to maintain training for residents even in times of contact restrictions and distance rules. Training concepts for residents are underrepresented in the current literature. We present an innovative online-based training concept for radiology residents in our department, based on a tripartite design; independent case preparation where residents refer to existing knowledge is followed by a case discussion and specific questions and feedback from the participating senior physicians. A questionnaire-based evaluation of the training concept was carried out after 12 months. We found that participants rated the training concept positively when it came to difficulty, representativeness of clinical work and relevance for specialist training. The questionnaire responses also provided insights into the desired duration, the selection of imaging modalities, and frequency of the concept in the future. All respondents stated that they had benefited from the format. Online-based concepts can therefore be a relevant contribution to the clinical training of residents and represent an adequate alternative to or extension of analog concepts.