Bibliographic record
Abstract
Background: Chemical burns represent a small part of burn injuries, but the incidence seems to increase. Traditionally a chemical burn is rinsed with water or water and soap. Diphoterine is an amphoteric, chelating, polyvalent, slightly hypertonic solution made for decontamination of chemical splashes proposing one treatment suitable for most kinds of chemical burns. Objective: In this systematic review we aimed to assess the effect of Diphoterine on chemical burns compared with water or no treatment. The primary endpoint was depth of burn and secondary outcomes included pain, duration of hospitalization, time to return to work, need for surgery, pH, and complications associated with using Diphoterine. Methods: PubMed, Embase, Cochrane Library, Web of Science, and Google Scholar were systematically searched on March 22, 2021 using the term “Diphoterine”. Interventional, observational, and cohort studies were included. No language restrictions were applied. Risk of bias was assessed using the Cochrane Risk of Bias assessment tool for randomized trials and the Newcastle-Ottawa Scale (NOS 0-9) for non-randomized studies.Results: A total of 8 studies were included. Only 1 retrospective study evaluated the depth of a chemical burn and found no difference between the Diphoterine group and the control group. Three studies reported on pain and found a more pronounced decrease in pain when using Diphoterine compared to the control groups. Two studies found significant improvement of pH when using Diphoterine. No studies found a difference in time to return to work or duration of hospitalization. No studies addressed the need for surgery. No studies found any complications associated to the use of Diphoterine. Risk of bias was judged high in the included RCT and the rest of the studies was awarded between 3 and 7 stars on NOS. Conclusion: This systematic review found no difference between Diphoterine compared with water or no treatment on depth of a chemical burn. Diphoterine seems to be associated with less pain compared to water or no treatment, and Diphoterine seems to have a neutralizing effect of chemical burns.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".