Risk for heparin-induced thrombocytopenia with unfractionated and low-molecular-weight heparin thromboprophylaxis: a meta-analysis
Bibliographic record
Abstract
Heparin-induced thrombocytopenia (HIT) is an uncommon but potentially devastating complication of anticoagulation with unfractionated heparin (UFH) or low-molecular-weight heparin (LMWH). Our objective was to determine and compare the incidences of HIT in surgical and medical patients receiving thromboprophylaxis with either UFH or LMWH. All relevant studies identified in the MEDLINE database (1984-2004), not limited by language, and from reference lists of key articles were evaluated. Randomized and nonrandomized controlled trials comparing prophylaxis with UFH and LMWH and measuring HIT or thrombocytopenia as outcomes were included. Two reviewers independently extracted data on thromboprophylaxis (type, dose, frequency, and duration), definition of thrombocytopenia, HIT assay, and rates of the following outcomes: HIT, thrombocytopenia, and thromboembolic events. HIT was defined as a decrease in platelets to less than 50% or to less than 100 x 10(9)/L and positive laboratory HIT assay. Fifteen studies (7287 patients) were eligible: 2 randomized controlled trials (RCTs) measuring HIT (1014 patients), 3 prospective studies (1464 patients) with nonrandomized comparison groups in which HIT was appropriately measured in both groups, and 10 RCTs (4809 patients) measuring thrombocytopenia but not HIT. Three analyses were performed using a random effects model and favored the use of LMWH: (1) RCTs measuring HIT showed an odds ratio (OR) of 0.10 (95% confidence interval [CI], 0.01-0.2; P = .03); (2) prospective studies measuring HIT showed an OR of 0.10 (95% CI, 0.03-0.33; P < .001); (3) all 15 studies measured thrombocytopenia. The OR was 0.47 (95% CI, 0.22-1.02; P = .06). The inverse variance-weighted average that determined the absolute risk for HIT with LMWH was 0.2%, and with UFH the risk was 2.6%. Most studies were of patients after orthopedic surgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.069 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".