Thrombotic thrombocytopenic purpura associated with clopidogrel: further evaluation.
Bibliographic record
Abstract
BACKGROUND: Eleven cases of thrombotic thrombocytopenic purpura (TTP) associated with clopidogrel therapy have been published. OBJECTIVES: To perform a comprehensive causality assessment of the 11 published cases of TTP to assess quantitatively the extent to which clopidogrel was the causative factor. METHODS: The 11 reports of TTP were analyzed using the Bayesian Adverse Reaction Diagnostic Instrument to calculate the posterior probability (PsP) that clopidogrel caused the TTP based on epidemiological and clinical trials data (expressed as prior odds) and the clinical characteristics of each case (expressed as likelihood ratios). RESULTS: Clopidogrel was implicated as the causative factor of the TTP (PsP>0.75) in only five of the 11 cases. The PsP for clopidogrel was lowered by concomitant use of a statin, a history of cancer and the occurrence of relapsing TTP (in the absence of clopidogrel) in the remaining six cases. CONCLUSIONS: This systematic analysis provides strong evidence, based on the case information reported, that clopidogrel was the causative factor in at least some cases of TTP.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".