Development and validation of a predictive model for death in acquired severe ADAMTS13 deficiency-associated idiopathic thrombotic thrombocytopenic purpura: the French TMA Reference Center experience
Bibliographic record
Abstract
BACKGROUND: Acquired thrombotic thrombocytopenic purpura is still associated with a 10-20% death rate. It has still not been possible to clearly identify early prognostic factors of death. This study involved thrombotic thrombocytopenic purpura patients with acquired severe (<10% of normal activity) ADAMTS13 deficiency and aimed to identify prognostic factors associated with 30-day death. DESIGN AND METHODS: The study involved a prospective cohort of patients and was carried out between October 2000 and August 2010. A validation cohort of patients was set up from September 2010 to August 2011. Altogether, 281 (analysis cohort) and 66 (validation cohort) consecutive adult thrombotic thrombocytopenic purpura patients with acquired severe ADAMTS13 deficiency were enrolled. The study evaluated 30-day mortality after treatment initiation according to characteristics at inclusion. RESULTS: Non-survivors (11%) were older (P=10(-6)) and more frequently presented arterial hypertension (P=5.10(-4)) and ischemic heart disease (P=0.013). Prognosis was increasingly poor with age (P=0.004). On presentation, cerebral manifestations were more frequent in non-survivors (P=0.018) and serum creatinine level was higher (P=0.008). The most significant independent variables determining death were age, severe cerebral involvement and LDH level 10 N or over. A 3-level risk score for early death was defined and confirmed in the validation cohort using these variables, with higher values corresponding to increased risk of early death. CONCLUSIONS: A risk score for early death was defined in patients with thrombotic thrombocytopenic purpura and validated on an independent cohort. This score should help to stratify early treatment and identify patients with a worse prognosis.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".