The COVID-19 Pandemic as an Opportunity and Challenge for Registries in Health Services Research: Lessons Learned from the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)

Zusammenfassung Ziel der Studie Aus der durch das Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) bedingten Coronavirus-Krankheit-2019 (COVID-19) haben sich Chancen und Herausforderungen fur den Aufbau von Registern in der Versorgungsforschung ergeben. Diese sollen exemplarisch am aktuell gro ss ten sektorenubergreifenden Register mit einem detaillierten klinischen Datensatz zu mit SARS-CoV-2 infizierten Patient:innen in Deutschland, der Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS), aufgezeigt werden. Methodik Ziele von LEOSS waren es, ein kollaboratives und integratives Register zur Erfassung von anonymen Daten aus der Versorgung zu schaffen und die Daten der Wissenschaft im Sinne eines Open Science Ansatzes rasch bereitzustellen. Alleiniges Einschlusskriterium war der virologische Nachweis von SARS-CoV-2. Schlusselstrategien waren die Reallokation der vorhandenen personellen und technischen Ressourcen, die fruhe und direkte Einbeziehung von Vertreter:innen des Datenschutzes und der Ethikkommissionen sowie die Entscheidung zu einem iterativen und agilen Entwicklungs- und Anpassungsprozess. Ergebnisse Getragen von den zahlreichen kollaborierenden Institutionen konnte ein transsektorales und internationales Netzwerk mit aktuell 133 aktiv rekrutierenden Standorten und 7227 dokumentierten Fallen aufgebaut werden (Stand 18.03.2021, ein Jahr seit Rekrutierungsstart von LEOSS). Die Nutzung der Daten wurde uber auf der Projektwebseite verfugbare Werkzeuge zur Datenexploration, wie auch uber die teilautomatisierte Bereitstellung von Datensatzen verschiedenen Umfangs, innerhalb kurzer Zeit ermoglicht. Es wurden 97 Antrage zur Datennutzung aus 27 Themengebieten begutachtet. Im Peer-Review-Verfahren wurden 9 Arbeiten in internationalen Fachzeitschriften veroffentlicht. Schlussfolgerung Mit LEOSS konnte in kurzester Zeit ein System zur Erfassung klinischer Verlaufsdaten zu COVID-19 in Deutschland etabliert werden. Auch wenn in anderen Projekten fur spezifische Fragestellungen weitaus gro ss ere Datenbestande durch direkten Zugriff auf Quellsysteme analysiert werden konnten, wurde durch den einheitlich gepflegten und technisch gepruften Dokumentationsstandard mit vielen fachspezifischen Details ein sehr gro ss er Datensatz mit wertvollen Alleinstellungsmerkmalen geschaffen. Aus den Erfahrungen von LEOSS konnen Implikationen fur die zukunftige Gestaltung von Registern und eine rasche Reaktion auf Pandemien abgeleitet werden. Abstract Objective The Coronavirus Disease-2019 (COVID-19) pandemic has brought opportunities and challenges, especially for health services research based on routine data. In this article we will demonstrate this by presenting lessons learned from establishing the currently largest registry in Germany providing a detailed clinical dataset on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients: the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS). Methods LEOSS is based on a collaborative and integrative research approach with anonymous recruitment and collection of routine data and the early provision of data in an open science context. The only requirement for inclusion was a SARS-CoV-2 infection confirmed by virological diagnosis. Crucial strategies to successfully realize the project included the dynamic reallocation of available staff and technical resources, an early and direct involvement of data protection experts and the ethics committee as well as the decision for an iterative and dynamic process of improvement and further development. Results Thanks to the commitment of numerous institutions, a transsectoral and transnational network of currently 133 actively recruiting sites with 7,227 documented cases could be established (status: 18.03.2021). Tools for data exploration on the project website, as well as the partially automated provision of datasets according to use cases with varying requirements, enabled us to utilize the data collected within a short period of time. Data use and access processes were carried out for 97 proposals assigned to 27 different research areas. So far, nine articles have been published in peer-reviewed international journals. Conclusion As a collaborative effort of the whole network, LEOSS developed into a large collection of clinical data on COVID-19 in Germany. Even though in other international projects, much larger data sets could be analysed to investigate specific research questions through direct access to source systems, the uniformly maintained and technically verified documentation standard with many discipline-specific details resulted in a large valuable data set with unique characteristics. The lessons learned while establishing LEOSS during the current pandemic have already created important implications for the design of future registries and for pandemic preparedness and response

First results of the “Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS)"

Purpose Knowledge regarding patients' clinical condition at severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection is sparse. Data in the international, multicenter Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort study may enhance the understanding of COVID-19. Methods Sociodemographic and clinical characteristics of SARS-CoV-2-infected patients, enrolled in the LEOSS cohort study between March 16, 2020, and May 14, 2020, were analyzed. Associations between baseline characteristics and clinical stages at diagnosis (uncomplicated vs. complicated) were assessed using logistic regression models. Results We included 2155 patients, 59.7% (1,287/2,155) were male; the most common age category was 66-85 years (39.6%; 500/2,155). The primary COVID-19 diagnosis was made in 35.0% (755/2,155) during complicated clinical stages. A significant univariate association between age; sex; body mass index; smoking; diabetes; cardiovascular, pulmonary, neurological, and kidney diseases; ACE inhibitor therapy; statin intake and an increased risk for complicated clinical stages of COVID-19 at diagnosis was found. Multivariable analysis revealed that advanced age [46-65 years: adjusted odds ratio (aOR): 1.73, 95% CI 1.25-2.42,p = 0.001; 66-85 years: aOR 1.93, 95% CI 1.36-2.74,p 85 years: aOR 2.38, 95% CI 1.49-3.81,p < 0.001 vs. individuals aged 26-45 years], male sex (aOR 1.23, 95% CI 1.01-1.50,p = 0.040), cardiovascular disease (aOR 1.37, 95% CI 1.09-1.72,p = 0.007), and diabetes (aOR 1.33, 95% CI 1.04-1.69,p = 0.023) were associated with complicated stages of COVID-19 at diagnosis. Conclusion The LEOSS cohort identified age, cardiovascular disease, diabetes and male sex as risk factors for complicated disease stages at SARS-CoV-2 diagnosis, thus confirming previous data. Further data regarding outcomes of the natural course of COVID-19 and the influence of treatment are required

First results of the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS)

Purpose Knowledge regarding patients' clinical condition at severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection is sparse. Data in the international, multicenter Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort study may enhance the understanding of COVID-19. Methods Sociodemographic and clinical characteristics of SARS-CoV-2-infected patients, enrolled in the LEOSS cohort study between March 16, 2020, and May 14, 2020, were analyzed. Associations between baseline characteristics and clinical stages at diagnosis (uncomplicated vs. complicated) were assessed using logistic regression models. Results We included 2155 patients, 59.7% (1,287/2,155) were male; the most common age category was 66-85 years (39.6%; 500/2,155). The primary COVID-19 diagnosis was made in 35.0% (755/2,155) during complicated clinical stages. A significant univariate association between age; sex; body mass index; smoking; diabetes; cardiovascular, pulmonary, neurological, and kidney diseases; ACE inhibitor therapy; statin intake and an increased risk for complicated clinical stages of COVID-19 at diagnosis was found. Multivariable analysis revealed that advanced age [46-65 years: adjusted odds ratio (aOR): 1.73, 95% CI 1.25-2.42,p = 0.001; 66-85 years: aOR 1.93, 95% CI 1.36-2.74,p 85 years: aOR 2.38, 95% CI 1.49-3.81,p < 0.001 vs. individuals aged 26-45 years], male sex (aOR 1.23, 95% CI 1.01-1.50,p = 0.040), cardiovascular disease (aOR 1.37, 95% CI 1.09-1.72,p = 0.007), and diabetes (aOR 1.33, 95% CI 1.04-1.69,p = 0.023) were associated with complicated stages of COVID-19 at diagnosis. Conclusion The LEOSS cohort identified age, cardiovascular disease, diabetes and male sex as risk factors for complicated disease stages at SARS-CoV-2 diagnosis, thus confirming previous data. Further data regarding outcomes of the natural course of COVID-19 and the influence of treatment are required