A Systematic Review of Heparin to Treat Burn Injury
Bibliographic record
Abstract
This systematic review was conducted to assess the evidence for using heparin to treat burn injury. The following databases were searched for relevant studies: MEDLINE, EMBASE, CINAHL, The Cochrane Central Database of Controlled Trials, Web of Science, and BIOSIS. Additional searches involved the reference lists of included studies, the "grey " literature (eg, government reports), and consultations with experts to obtain unpublished manuscripts. Included studies were summarized descriptively and in tabular form, and assessed for methodological quality. A metaanalysis was conducted to obtain a summary estimate for the association between heparin use and postburn mortality. Nine studies were abstracted and included in the review. Five studies contained adult and pediatric patients, one contained adults only, and three contained pediatric patients only. Burn etiologies included flame, scald, thermal, or smoke inhalation. Heparin administration was done topically, subcutaneously, intravenously, or via aerosol. Heparin was reported to have a beneficial impact on mortality, graft and wound healing, and pain control. For mortality, the overall estimate (relative risk) of heparin's effect was 0.32 (95% confidence interval = 0.18-0.57). Heparin's reported benefits may be severely biased because the abstracted studies were beset by poor methodological quality (eg, inadequate definitions of treatment and outcome, no control of confounding). Given poor study quality, there is no strong evidence to indicate that heparin can improve clinical outcomes in the treatment of burn injury. Further research is needed to assess the clinical utility of using heparin in the treatment of burn injury.
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 | 0.014 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".