The impact of the COVID-19 pandemic on incidence and clinical presentation of thrombotic microangiopathies: data from a laboratory centralizing ADAMTS-13 testing in Quebec
Bibliographic record
Abstract
BACKGROUND: Coronavirus disease 2019 (COVID-19) primarily induces respiratory symptoms. However, some patients develop thrombotic microangiopathies (TMA) during their infection. This study aimed to compare the incidence and clinical presentation of patients referred for TMA suspicion in Quebec (Canada) before and during the COVID-19 pandemic, utilizing data from a laboratory centralizing ADAMTS-13 testing. RESULTS: During the pre-pandemic period (2017–2019), 500 patients were referred for TMA suspicion, of whom 423 had no prior TMA episodes. Among these, 50 patients exhibited ADAMTS-13 activity ≤ 10%, confirming a diagnosis of thrombotic thrombocytopenic purpura (TTP). In the pandemic period (2020–2022), 683 patients were referred for TMA suspicion, with 600 experiencing their first TMA episode. TTP was identified in 53 patients. In our cohort, the mean incidence of TTP cases remained steady between the pre-pandemic and the pandemic period (approximately 2 cases per million persons per year). Females with TTP were younger during the pandemic compared to the pre-pandemic period (median age 41.5 vs. 51.5 years; p = 0.032). Overall, the clinical presentation of TTP and suspected TMA other than TTP patients remained comparable between the two periods. The mean incidence of suspected TMA other than TTP cases increased in males during the pandemic compared to the previous period (20.3 vs. 12.7 per million persons per year; p = 0.023), particularly in men aged 50–59 years (28.7 vs. 11.9 per million persons per year; p = 0.05). A weak cross-correlation between new COVID-19-related hospitalizations and new cases of suspected TMA other than TTP was observed, peaking at a lag of 1 week (r = 0.258). COVID-19-associated TMA was suspected in 17 patients, with 3 cases confirmed as TTP based on ADAMTS-13 activity results. Patients with suspected TMA other than TTP associated with COVID-19 were predominantly male (86%) with a median age of 53 years (IQR: 43.2–69.2). CONCLUSION: The incidence of TTP did not change during COVID-19 pandemic. An increase referral of other suspected TMA was observed in our cohort, especially in males.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".