Response to Letter to the Editor Regarding “American Burn Association Clinical Practice Guidelines on Burn Shock Resuscitation” by Cartotto et al.
Bibliographic record
Abstract
To the Editor: We thank the writers for their comments and recognition of the dearth of randomized controlled trials (RCTs) in burn shock resuscitation (BSR). Clinical Practice Guidelines (CPGs) rely on confidence in the scientific evidence, and RCTs provide the strongest evidence. Nearly half of clinicians start albumin before 12 h.1 However, it is difficult to confidently recommend that approach when the only RCT available found increased lung water with the use of albumin before 12 h, compared to crystalloid alone.2 While that finding hasn’t been replicated, more accurately, the question hasn’t been studied. Neither of the 2 investigations we could cite specifically or objectively assessed pulmonary edema following albumin administered between 8 and 12 h.3,4 ABRUPT 2 (NCT04356859) should answer this vital question. Regarding plasma (FFP), our recommendation reflects one small 2005 RCT comparing FFP to crystalloids.5 Modern pathogen-reduced plasma (PRP) and lyophilized plasma,6 though not robustly studied yet, offer enormous potential among civilian and military burn casualties, for greater efficacy and safety from disease transmission and lung injury complications. A specific aim of the ongoing PROpOLIS study (NCT04681638) is to examine PRP and lung injury during BSR. The next iteration of this CPG should therefore contain more direction.
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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 | 0.008 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.034 | 0.037 |
| Insufficient payload (model declined to judge) | 0.015 | 0.016 |
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".