Systematic Review of Individual Patient Data COVID-19 Infection and Vaccination–Associated Thrombotic Microangiopathy
Bibliographic record
Abstract
Introduction Sporadic cases of atypical hemolytic uremic syndrome (aHUS) have been described in the literature in association with COVID-19 infection and vaccination in adults and pediatric patients. The exact mechanisms underlying COVID-19–associated thrombotic microangiopathies (TMAs) remain incompletely understood. Herein, we present a detailed meta-analysis of the clinical characteristics, outcomes, and management strategies of COVID-19–associated aHUS and thrombotic thrombocytopenic purpura (TTP). Methods This study was performed following the Preferred Reporting Items for Systematic Reviews and Meta-analyses updated guidelines. PubMed was utilized for searching for case reports and series. Adverse outcome at last follow-up was defined as estimated glomerular filtration rate < 30 ml/min per 1.73 m 2 (patients with aHUS), no remission with therapy, or patient death. Data were analyzed using Wilcoxon rank and Chi-square tests. Results Our analysis cohort included 118 studies reporting on 170 patients. These included 84 cases of aHUS and 86 cases of TTP resulting from COVID-19 infection ( n = 92) or vaccination ( n = 78). Significantly more cases of aHUS were reported after infection ( n = 65) than immunization ( n = 19), compared to TTP, where the reverse was true ( n = 27 and n = 59, respectively; P < 0.001). In patients with aHUS with stage 3 acute kidney injury (AKI), requirement of kidney replacement therapy (KRT) was seen in three-fourths of the cohort for a median of 15. In patients with TTP, severe COVID-19 infection ( P = 0.04) predicted nonremission or death at last follow-up. Administration of i.v., rituximab and caplacizumab were protective ( P = 0.03 and P = 0.06, respectively). Immune TTP (iTTP) was reported more often than HUS following mRNA vaccines (81% vs. 58%; P = 0.06). Conclusion COVID-19 infection and vaccination are a potential trigger for onset or relapse of aHUS and TTP, especially in patients who are not on maintenance complement inhibitors or immunosuppression.
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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 | 0.011 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.012 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".