Thrombotic thrombocytopenic purpura/haemolytic uraemic syndrome: a new index predicting response to plasma exchange
Bibliographic record
Abstract
Despite the favourable response of thrombotic thrombocytopenic purpura/haemolytic uraemic syndrome (TTP/HUS) to plasma exchange, an early level of mortality persists. Non-response has been associated with a low frequency of exchange. The Rose index of TTP/HUS severity, occasionally used to predict the response of TTP/HUS to plasma exchange, remains unsatisfactory. The purpose of this study was to develop a new index predicting response of TTP/HUS to plasma exchange and to compare it with the Rose index. Retrospective analysis of 171 cases of TTP/HUS from 39 apheresis units across Canada between 1980 and 2001 was conducted. Logistic regression analysis was used to derive a model predicting 6-month mortality from presenting characteristics. The reduced model contained age >40 years, haemoglobin <9.0 g/dl and the presence of a fever at presentation. Gender, platelet count, creatinine and neurological signs were not part of the final model. This model predicted 13.4% of outcome variance. Predictive scores of 0, 2, 4 and 6 correlated with 6-month mortality rates of 12.5%, 14.0%, 31.3% and 61.5% respectively in our source population. This simple model may help identify those patients who would benefit from higher treatment intensity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".