Venous Thromboembolism After COVID-19 Infection Among People With and Without Immune-Mediated Inflammatory Diseases
Bibliographic record
Abstract
Importance: Immune-mediated inflammatory diseases (IMIDs) and COVID-19 are independently associated with venous thromboembolisms (VTEs). Objective: To determine if individuals with IMIDs are at higher risk of VTE following COVID-19 infection compared with individuals without IMIDs. Design, Setting, and Participants: Population-based matched cohort study using multiple deterministically linked health administrative databases from Ontario, Canada, and including patients testing positive for COVID-19 between January 1, 2020, and December 30, 2021, and followed up until March 31, 2022. Individuals with IMIDs (n = 28 440) who tested positive for COVID-19 were matched with up to 5 individuals without an IMID (n = 126 437) who tested positive for COVID-19. Matching was based on year of birth, sex, neighborhood income, and rural/urban residence. Data analysis was performed from August 6, 2022, to August 21, 2023. Exposure: Diagnosis of an IMID, identified using algorithms based on diagnostic codes, procedures, and specialist visits. Main Outcome and Measure: The main outcome was estimated age- and sex-standardized incidence of VTE. Proportional cause-specific hazard models compared the risk of VTE in people with and without IMIDs. Death was a competing risk. Models adjusted for history of VTE, 2 or more doses of a COVID-19 vaccine 14 or more days prior to COVID-19 diagnosis, and the Charlson Comorbidity Index. Routinely collected health data were used, so the hypothesis tested was formulated after data collection but prior to being granted access to data. Results: The study included 28 440 individuals (16 741 [58.9%] female; 11 699 [41.1%] male) with an IMID diagnosed prior to first COVID-19 diagnosis, with a mean (SD) age of 52.1 (18.8) years at COVID-19 diagnosis. These individuals were matched to 126 437 controls without IMIDs. The incidence of VTE within 6 months of COVID-19 diagnosis among 28 440 individuals with an IMID was 2.64 (95% CI, 2.23-3.10) per 100 000 person-days compared with 2.18 (95% CI, 1.99-2.38) per 100 000 person-days among 126 437 matched individuals without IMIDs. The VTE risk was not statistically significantly different among those with vs without IMIDs (adjusted hazard ratio, 1.12; 95% CI, 0.95-1.32). Conclusions and Relevance: In this retrospective population-based cohort study of individuals with IMIDs following COVID-19, individuals with IMIDs did not have a higher risk of VTE compared with individuals without an IMID. These data provide reassurance to clinicians caring for individuals with IMIDs and COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".