COVID-19 Vaccination Prior to SARS-CoV-2 Infection Reduced Risk of Subsequent Diabetes Mellitus: A Real-World Investigation Using U.S. Electronic Health Records
Main finding · New-onset DMResult — go to the resultHazard ratio 0.79 95% CI 0.73–0.86Authors' conclusion
In conclusion, this study validates a 65% higher risk of new-onset diabetes in SARS-CoV-2-infected individuals compared to noninfected counterparts. Furthermore, COVID-19 survivors who received COVID-19 vaccinations experienced a reduced risk of new-onset diabetes, with a dose-dependent effect. Notably, the protective impact of COVID-19 vaccination is more pronounced among the Black/African American population than other ethnic groups. These findings emphasize the imperative of widespread vaccination to mitigate diabetes risk and the need for tailored strategies for diverse demographic groups to ensure equitable protection.
Study context
- Population
- COVID-19 survivors in the TriNetX database (US electronic health records); first cohort: SARS-CoV-2-infected vs noninfected individuals
- Participants
- 83,829 vs 83,829
- Exposure
- COVID-19 vaccination vs no vaccination in COVID-19 survivors
- Vaccinatedn = 83,829
- Unvaccinatedn = 83,829reference
- Outcome
- New-onset DM
Methodological detailsTriNetX electronic health records, 2 cohorts, Cox proportional hazard regression, subgroup, sensitivity and dose-response analyses
- TriNetX electronic health records
- 2 cohorts
- Cox proportional hazard regression
- Subgroup, sensitivity and dose-response analyses
Main finding
As reported in the abstract
Hazard ratio
0.79
95% CI 0.73–0.86
Observational data: associations, not effects.
Further findings
| Outcome | HR (95% CI) | |
|---|---|---|
| New-onset DM, first cohort: SARS-CoV-2-infectedvs noninfected (N = 1,562,606)65% increased risk | 1.65 (1.62–1.68) | |
| 0.512Hazard ratio (log scale) |
Subgroups by sex, age, race and BMI; sensitivity analyses
- Subgroup analyses by sex, age, race, and BMI yielded similar results; consistent in sensitivity analyses and cross-validation with an independent TriNetX data set
Original publication
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