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Record W4285744196 · doi:10.22037/aaem.v10i1.1534

Adherence to Referral Criteria for Burn Patients; a Systematic Review.

2022· review· en· W4285744196 on OpenAlexaff
Ali Bazzi, Mohammad Javad Ghazanfari, Masoumeh Norouzi, Mohammadreza Mobayen, Fateme Jafaraghaee, Amir Emami Zeydi, Joseph Osuji, Samad Karkhah

Bibliographic record

VenuePubMed · 2022
Typereview
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsMount Royal University
Fundersnot available
KeywordsReferralMedicineBurn injuryRehabilitationScopusEmergency medicineMEDLINEPhysical therapyIntensive care medicineFamily medicineSurgery

Abstract

fetched live from OpenAlex

Introduction: Burn injuries are under-appreciated trauma, associated with substantial morbidity and mortality. It is necessary to refer patients in need of specialized care to more specialized centers for treatment and rehabilitation of burn injuries. This systematic review aimed to assess the adherence to referral criteria for burn patients. Methods: An extensive search was conducted on Scopus, PubMed, and Web of Science online databases using the relevant keywords from the earliest to October 7, 2021. The quality of the included studies was assessed using the appraisal tool for cross-sectional studies (AXIS tool). Results: Among a total of 7,455 burn patients included in the nine studies, 60.95% were male. The most frequently burned areas were the hands (n=3) and the face (n=2). The most and least common burn mechanisms were scalds (62.76%) and electrical or chemical (2.88%), respectively. 51.88% of burn patients had met ≥ 1 referral criteria. The overall adherence to the referral criteria for burn patients was 58.28% (17.37 to 93.39%). The highest and lowest adherence rates were related to Western Cape Provincial (WCP) (26.70%) and National Burn Care Review (NBCR) (4.97%) criteria, respectively. Conclusion: The overall adherence to the referral criteria for burn patients was relatively desirable. Therefore, well-designed future studies are suggested in order to uncover approaches to improve adherence to referral criteria for burn patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.186
GPT teacher head0.393
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations44
Published2022
Admission routes1
Has abstractyes

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