Prognostic importance of preoperative anti-PF4/heparin antibodies in patients undergoing cardiac surgery
Bibliographic record
Abstract
It was the objective of this study to obtain best estimates of the prevalence of anti-PF4/heparin antibodies in patients not suspected to have clinical heparin-induced thrombocytopenia (HIT) prior to undergoing cardiac surgery and to determine whether preoperative antibody status and antibody class is predictive of postoperative thromboembolic outcomes, non-thromboembolic outcomes, length of stay, and mortality. PubMed and EMBASE online databases were searched up to July 2011, and we included studies involving adults undergoing cardiac surgery examining the relationship between preoperative anti-PF4/heparin antibodies (ELISA) and postoperative clinical outcomes. Five studies involving a combined total of 2,332 patients met our inclusion criteria. Preoperative anti-PF4/heparin antibodies were detected in 5-22% of patients. No study demonstrated an association between preoperative anti-PF4/heparin antibodies and postoperative thromboembolic outcomes or mortality. Three studies demonstrated a statistically significant association between preoperative anti-PF4/heparin antibodies and length of stay while two showed an association with non-thromboembolic complications. In the one study that examined outcomes by anti-PF4/heparin antibody class, IgM antibodies predicted non-thromboembolic complications and length-of-stay. None of the studies reported prior heparin exposure, and most studies did not examine the relationship of the absolute value of antibody titres (ELISA OD) and risk, nor the incidence of true/clinical HIT in preoperative positive or negative patients. In conclusion, pre-formed anti-PF4/heparin antibodies are common in patients undergoing cardiac surgery, but the available literature does not support that they predict postoperative thromboembolic complications or death. There does appear to be an association between anti-PF4/heparin antibodies and non-thromboembolic adverse events, but a causal relationship is unlikely.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".