Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
157134 participants
OBSERVATIONAL
2018-01-01
2021-09-30
Brief Summary
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Detailed Description
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This study is a longitudinal matched cohort study based on a total data pool of about 35 million SHI insured persons and investigates the incidence of a diabetes mellitus (differentiated into type 1, type 2 and other diabetes mellitus) diagnosis after confirmed SARS-Cov-2 infection compared to different control groups without SARS-Cov-2 infection. Individuals will be followed up from the date of diagnosis of SARS-Cov-2 infection, influenza diagnosis, or a randomly assigned index date for at least two quarters.
To assess effects of Long-Covid on incidence of diabetes mellitus, follow-up begins with the second quarter after the quarter of the index date.
The data analysis is carried out decentrally at the respective data holders of the POINTED consortium. Subsequently, the aggregated individual results are pooled.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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COVID-19
no interventional study
no interventional study
no interventional study
Control I: No COVID-19
no interventional study
no interventional study
no interventional study
Control II: Influenza 2018
no interventional study
no interventional study
no interventional study
Control III: Historical 2018
no interventional study
no interventional study
no interventional study
Interventions
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no interventional study
no interventional study
Eligibility Criteria
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Inclusion Criteria
* Insured who were fully observable in 2019, as well as between 01.01.2020 and the end of the available observation period (maximum 30.09.2021) or until death
* Alternatively to two previous items: or insured who were born between 01.01.2019 and 31.03.2021 and were fully observable until the end of the observation period (30.09.2021) or death
\- Insured with at least one U07.1! confirmed outpatient diagnosis or an inpatient main or secondary diagnosis U07.1! between 01.02.2020 and 31.03.2021
* Insured who were insured for at least one day between 01.01.2018 and 31.03.2019 (COVID-19 inclusion period minus 2 years)
* Insureds who were fully observable in 2017 and between 01.01.2018 and the end of the observation period (30.09.2019) or until death
* Alternative to two previous items: Insured who were fully observable from birth (between 01.01.2017 and 31.03.2019) to 30.09.2019 or until death
-Insured with at least one J10 diagnosis (Influenza) confirmed in an outpatient setting or an inpatient main or secondary J10 diagnosis between 01.02.2018 and 30.06.2018.
Exclusion Criteria
* Insured who are not alive on the first day of the second quarter after the index quarter
-Insured with at least one COVID-19 diagnosis (U07.1 or U07.2) during the observation period (between 01.02.2020 and 30.09.2021)
* Insured with an outpatient confirmed E10-E14 diagnosis or an inpatient main or secondary E10-E14 diagnosis in the four quarters before the index quarter or without a corresponding diagnosis between birth and cohort entry (if period between birth and cohort entry \< four months)
* Insured who are not still alive on the first day of the second quarter after the index quarter.
ALL
No
Sponsors
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Robert Koch Institut
OTHER_GOV
Center for Evidence-Based Healthcare, Technische Universität Dresden
UNKNOWN
Techniker Krankenkasse
OTHER
BARMER
OTHER
DAK Gesundheit
OTHER
AOK PLUS
INDUSTRY
Vandage GmbH
UNKNOWN
IKK Classic
UNKNOWN
InGef - Institute for Applied Health Research Berlin GmbH
INDUSTRY
Responsible Party
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Principal Investigators
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Jochen Schmitt, Prof. Dr. med.
Role: STUDY_DIRECTOR
Center for Evidence-Based Healthcare, Technische Universität Dresden
Josephine Jacob, MSc
Role: PRINCIPAL_INVESTIGATOR
InGef - Institute for Applied Health Research Berlin GmbH
Christa Scheidt-Nave, Dr.
Role: PRINCIPAL_INVESTIGATOR
Robert Koch-Institut; Fachgebiet 25 - Körperliche Gesundheit
Lukas Reitzle, Dr.
Role: PRINCIPAL_INVESTIGATOR
Robert Koch-Institut; Fachgebiet 24: Gesundheits-bericht-erstattung
Locations
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Center for Evidence-Based Healthcare, Technische Universität Dresden
Dresden, , Germany
Countries
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References
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Reitzle L, Ihle P, Heidemann C, Paprott R, Koster I, Schmidt C. [Algorithm for the Classification of Type 1 and Type 2 Diabetes Mellitus for the Analysis of Routine Data]. Gesundheitswesen. 2023 Mar;85(S 02):S119-S126. doi: 10.1055/a-1791-0918. Epub 2022 Jun 2. German.
Other Identifiers
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2022-07 COVID-19 and diabetes
Identifier Type: -
Identifier Source: org_study_id
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