The association between platelet dysfunction and adverse outcomes in cardiac surgical patients
Bibliographic record
Abstract
Haemostatic activation during cardiopulmonary bypass is associated with prothrombotic complications. Although it is not possible to detect and quantify haemostatic activation directly, platelet dysfunction, as measured with point-of-care-assays, may be a useful surrogate. In this study, we assessed the association between cardiopulmonary bypass-associated platelet dysfunction and adverse outcomes in 3010 cardiac surgical patients. Platelet dysfunction, as measured near the end of the rewarming phase of cardiopulmonary bypass, was calculated as the proportion of non-functional platelets after activation with collagen. Logistic regression and multivariable analyses were applied to assess the relationship between platelet dysfunction and a composite of in-hospital death; myocardial infarction; stroke; deep vein thrombosis or pulmonary embolism; and acute kidney injury (greater than a two-fold increase in creatinine). The outcome occurred in 251 (8%) of 3010 patients. The median (IQR [range]) percentage platelet dysfunction was less for those without the outcome as compared with those with the outcome; 14% (8-28% [1-99%]) vs. 19% (11-45% [2-98%]), p < 0.001. After risk adjustment, platelet dysfunction was independently associated with the composite outcome (p < 0.001), such that for each 1% increase in platelet dysfunction there was an approximately 1% increase in the composite outcome (OR 1.012; 95%CI 1.006-1.018). This exploratory study suggests that cardiopulmonary bypass-associated platelet dysfunction has prognostic value and may be a useful clinical measure of haemostatic activation in cardiac surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".