Accuracy of quality of life questionnaire as a diagnostic tool for SARS-CoV-2 pulmonary sequelae.

Background: Follow-up after hospital discharge of SARS-CoV-2 survivors represents a huge burden on the healthcare system. We attempt to assess the utility of symptoms and health-related quality of life questionnaire (SF-12) to identify SARS CoV2 pulmonary sequelae. Methods: Prospective, non-interventional follow-up study. A cardiopulmonary exercise test, functional respiratory test (PFT), SF12 questionnaire were performed after hospitalization at six months after the first positive PCR smear. Results: 41 patients were included, female (39%), mean age 57.3 ± 13.7 years. 70% persisted with symptoms. 46% presented a maximum oxygen consumption below 80% of predicted. SF-12 physical domain score was significantly reduced in patients with altered PFT (32.7 vs. 45.9; p < 0.001) and obtained the best sensitivity and specificity to identify PFT alterations (AUC 0.862, Sensitivity 85.7%, Specificity 81.5%). Conclusions: SF-12 questionnaire shows high sensitivity and specificity to detect SARS CoV2 survivors with pulmonary function alterations.

Antecedentes y objetivos: El seguimiento tras el alta hospitalaria de los supervivientes de SARS-CoV-2 representa una enorme carga para el sistema sanitario. Intentamos evaluar la utilidad de los síntomas y el cuestionario de calidad de vida (SF-12) para identificar los pacientes con secuelas pulmonares por SARS-CoV-2. Materiales y métodos: Estudio de seguimiento prospectivo observacional. Después de la hospitalización, a los 6 meses del primer frotis con PCR positiva se realizaron: una prueba de esfuerzo cardiopulmonar, pruebas funcionales respiratorias (PFR) y se aplicó el cuestionario SF-12. Resultados: Se incluyó a 41 pacientes, el 39% eran mujeres, con una edad media de 57,3 ± 13,7 años. El 70% persistía con síntomas. El 46% presentó un consumo máximo de oxígeno por debajo del 80% del predicho. La puntuación del dominio físico del SF-12 fue significativamente más baja en pacientes con PFR alteradas (32,7 vs. 45,9; p < 0,001) y obtuvo la mejor sensibilidad y especificidad para identificar las alteraciones de las PFR (AUC 0,862; sensibilidad 85,7% y especificidad 81,5%). Conclusiones: El cuestionario de calidad de vida SF-12 presenta una alta sensibilidad y especificidad para detectar a los sobrevivientes de SARS-CoV-2 con alteraciones de la función pulmonar.

Accuracy of quality of life questionnaire as a diagnostic tool for SARS-CoV-2 pulmonary sequelae

Background: Follow-up after hospital discharge of SARS-CoV-2 survivors represents a huge burden on the healthcare system. We attempt to assess the utility of symptoms and health-related quality of life questionnaire (SF-12) to identify SARS CoV2 pulmonary sequelae.MethodsProspective, non-interventional follow-up study. A cardiopulmonary exercise test, functional respiratory test (PFT), SF12 questionnaire were performed after hospitalization at six months after the first positive PCR smear.Results41 patients were included, female (39%), mean age 57.3±13.7 years. 70% persisted with symptoms. 46% presented a maximum oxygen consumption below 80% of predicted. SF-12 physical domain score was significantly reduced in patients with altered PFT (32.7 vs. 45.9; p<0.001) and obtained the best sensitivity and specificity to identify PFT alterations (AUC 0.862, Sensitivity 85.7%, Specificity 81.5%).ConclusionsSF-12 questionnaire shows high sensitivity and specificity to detect SARS CoV2 survivors with pulmonary function alterations. (AU)

Antecedentes y objetivos: El seguimiento tras el alta hospitalaria de los supervivientes de SARS-CoV-2 representa una enorme carga para el sistema sanitario. Intentamos evaluar la utilidad de los síntomas y el cuestionario de calidad de vida (SF-12) para identificar los pacientes con secuelas pulmonares por SARS-CoV-2.Materiales y métodosEstudio de seguimiento prospectivo observacional. Después de la hospitalización, a los 6 meses del primer frotis con PCR positiva se realizaron: una prueba de esfuerzo cardiopulmonar, pruebas funcionales respiratorias (PFR) y se aplicó el cuestionario SF-12.ResultadosSe incluyó a 41 pacientes, el 39% eran mujeres, con una edad media de 57,3±13,7 años. El 70% persistía con síntomas. El 46% presentó un consumo máximo de oxígeno por debajo del 80% del predicho. La puntuación del dominio físico del SF-12 fue significativamente más baja en pacientes con PFR alteradas (32,7 vs. 45,9; p<0,001) y obtuvo la mejor sensibilidad y especificidad para identificar las alteraciones de las PFR (AUC 0,862; sensibilidad 85,7% y especificidad 81,5%).ConclusionesEl cuestionario de calidad de vida SF-12 presenta una alta sensibilidad y especificidad para detectar a los sobrevivientes de SARS-CoV-2 con alteraciones de la función pulmonar. (AU)

Accuracy of quality of life questionnaire as a diagnostic tool for SARS-CoV-2 pulmonary sequelae.

BACKGROUND: Follow-up after hospital discharge of SARS-CoV-2 survivors represents a huge burden on the healthcare system. We attempt to assess the utility of symptoms and health-related quality of life questionnaire (SF-12) to identify SARS CoV2 pulmonary sequelae. METHODS: Prospective, non-interventional follow-up study. A cardiopulmonary exercise test, functional respiratory test (PFT), SF12 questionnaire were performed after hospitalization at six months after the first positive PCR smear. RESULTS: 41 patients were included, female (39%), mean age 57.3±13.7 years. 70% persisted with symptoms. 46% presented a maximum oxygen consumption below 80% of predicted. SF-12 physical domain score was significantly reduced in patients with altered PFT (32.7 vs. 45.9; p<0.001) and obtained the best sensitivity and specificity to identify PFT alterations (AUC 0.862, Sensitivity 85.7%, Specificity 81.5%). CONCLUSIONS: SF-12 questionnaire shows high sensitivity and specificity to detect SARS CoV2 survivors with pulmonary function alterations.

ADataViewer: exploring semantically harmonized Alzheimer's disease cohort datasets.

BACKGROUND: Currently, Alzheimer's disease (AD) cohort datasets are difficult to find and lack across-cohort interoperability, and the actual content of publicly available datasets often only becomes clear to third-party researchers once data access has been granted. These aspects severely hinder the advancement of AD research through emerging data-driven approaches such as machine learning and artificial intelligence and bias current data-driven findings towards the few commonly used, well-explored AD cohorts. To achieve robust and generalizable results, validation across multiple datasets is crucial. METHODS: We accessed and systematically investigated the content of 20 major AD cohort datasets at the data level. Both, a medical professional and a data specialist, manually curated and semantically harmonized the acquired datasets. Finally, we developed a platform that displays vital information about the available datasets. RESULTS: Here, we present ADataViewer, an interactive platform that facilitates the exploration of 20 cohort datasets with respect to longitudinal follow-up, demographics, ethnoracial diversity, measured modalities, and statistical properties of individual variables. It allows researchers to quickly identify AD cohorts that meet user-specified requirements for discovery and validation studies regarding available variables, sample sizes, and longitudinal follow-up. Additionally, we publish the underlying variable mapping catalog that harmonizes 1196 unique variables across the 20 cohorts and paves the way for interoperable AD datasets. CONCLUSIONS: In conclusion, ADataViewer facilitates fast, robust data-driven research by transparently displaying cohort dataset content and supporting researchers in selecting datasets that are suited for their envisioned study. The platform is available at https://adata.scai.fraunhofer.de/ .

Erratum: Publisher Correction: ComPath: an ecosystem for exploring, analyzing, and curating mappings across pathway databases.

[This corrects the article DOI: 10.1038/s41540-018-0078-8.].

ComPath: an ecosystem for exploring, analyzing, and curating mappings across pathway databases.

Although pathways are widely used for the analysis and representation of biological systems, their lack of clear boundaries, their dispersion across numerous databases, and the lack of interoperability impedes the evaluation of the coverage, agreements, and discrepancies between them. Here, we present ComPath, an ecosystem that supports curation of pathway mappings between databases and fosters the exploration of pathway knowledge through several novel visualizations. We have curated mappings between three of the major pathway databases and present a case study focusing on Parkinson's disease that illustrates how ComPath can generate new biological insights by identifying pathway modules, clusters, and cross-talks with these mappings. The ComPath source code and resources are available at https://github.com/ComPath and the web application can be accessed at https://compath.scai.fraunhofer.de/.