Clinical trial NCT05524792: Incidence of Diabetes After a COVID-19 Infection
Official title: Incidence of Diabetes After a COVID-19 Infection - Comparison of COVID-19 Patients, Non-infected Individuals, Historic Controls and Patients With Influenza
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: COVID-19
Diabetes Mellitus
Keywords: Long-COVID
Diabetes Mellitus
Health claims data
Administative claims
Healthcare
Lead sponsor: InGef - Institute for Applied Health Research Berlin GmbH
Sponsor class: INDUSTRY
Collaborators: name: Robert Koch Institut
name: Center for Evidence-Based Healthcare, Technische Universität Dresden
name: Techniker Krankenkasse
name: BARMER
name: DAK Gesundheit
name: AOK PLUS
name: Vandage GmbH
name: IKK Classic
First posted: 2022-09-01
Enrollment: 157134
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who are insured in one of the data-contributing health insurance companies and meet the inclusion/exclusion criteria.

Brief summary: Prospective observational study of the POINTED consortium to evaluate whether new diagnoses of diabetes mellitus, occur significantly more frequently in the post-acute phase of a laboratory-confirmed SARS-CoV-2 infection than in carefully matched control groups.

Detailed description: Long-term health sequelae of the coronavirus disease 2019 (COVID-19) are a major public health concern. There is evidence on new-onset hyperglycaemia and insulin resistance in patients without history of diabetes in the post-acute phase of COVID-19 (Long-Covid).

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.

Eligibility criteria: Inclusion Criteria (cohorts: COVID-19 and No COVID-19)

* Persons who were insured for at least one day between 01.01.2020 and 31.03.2021
* 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

Additional inclusion criteria (cohort: COVID-19):

- 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

Exclusion criteria

* Insured with an outpatient confirmed E10-E14 diagnosis or an inpatient main or secondary E10-E14 diagnosis in the four quarters prior to the COVID-19 index quarter or without a corresponding diagnosis between birth to cohort entry
* Insured who are not alive on the first day of the second quarter after the index quarter

Additional Exclusion criteria (cohort: no COVID-19):

-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)

Inclusion Criteria (cohorts: Influenza 2018 and Historical 2018)

* 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

Additional inclusion Criteria (cohort: Influenza 2018):

-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 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.

Primary outcomes:
measure: Type 1 Diabetes mellitus
timeFrame: Starting with the second quarter following inclusion quarter until end of follow-up or death, whatever comes first. Time frame must be at least two quarters following inclusion quarter.
measure: Type 2 Diabetes mellitus
timeFrame: Starting with the second quarter following inclusion quarter until end of follow-up or death, whatever comes first. Time frame must be at least two quarters following inclusion quarter.
measure: Other Diabetes mellitus
timeFrame: Starting with the second quarter following inclusion quarter until end of follow-up or death, whatever comes first. Time frame must be at least two quarters following inclusion quarter.
Secondary outcomes:
measure: Fatigue
timeFrame: Starting with the second quarter following inclusion quarter until end of follow-up or death, whatever comes first. Time frame must be at least two quarters following inclusion quarter.
measure: Taste disorders
timeFrame: Starting with the second quarter following inclusion quarter until end of follow-up or death, whatever comes first. Time frame must be at least two quarters following inclusion quarter.
Other outcomes:
Locations:
city: Dresden
country: Germany
facility: Center for Evidence-Based Healthcare, Technische Universität Dresden
Study officials:
affiliation: Center for Evidence-Based Healthcare, Technische Universität Dresden
name: Jochen Schmitt, Prof. Dr. med.
role: STUDY_DIRECTOR
affiliation: InGef - Institute for Applied Health Research Berlin GmbH
name: Josephine Jacob, MSc
role: PRINCIPAL_INVESTIGATOR
affiliation: Robert Koch-Institut; Fachgebiet 25 - Körperliche Gesundheit
name: Christa Scheidt-Nave, Dr.
role: PRINCIPAL_INVESTIGATOR
affiliation: Robert Koch-Institut; Fachgebiet 24: Gesundheits-bericht-erstattung
name: Lukas Reitzle, Dr.
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.