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Record W2328837958 · doi:10.1097/bcr.0000000000000305

Surgical Burn Care by Médecins Sans Frontières-Operations Center Brussels

2015· article· en· W2328837958 on OpenAlexaff
Barclay T. Stewart, Miguel Trelles, Lynette Dominguez, Evan G. Wong, Hervé Tribunal Fiozounam, Ghulam Hiadar Hassani, Clemence Akemani, Aemer Naseer, Innocent Bagura Ntawukiruwabo, Adam L. Kushner

Bibliographic record

VenueJournal of Burn Care & Research · 2015
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcGill University Health Centre
FundersFogarty International Center
KeywordsMedicineBurn centerHealth careOdds ratioMedical emergencyConfidence intervalEmergency medicinePoison controlEconomic growth

Abstract

fetched live from OpenAlex

Humanitarian organizations care for burns during crisis and while supporting healthcare facilities in low-income and middle-income countries. This study aimed to define the epidemiology of burn-related procedures to aid humanitarian response. In addition, operational data collected from humanitarian organizations are useful for describing surgical need otherwise unmet by national health systems. Procedures performed in operating theatres run by Médecins Sans Frontières-Operations Centre Brussels (MSF-OCB) from July 2008 through June 2014 were reviewed. Surgical specialist missions were excluded. Burn procedures were quantified, related to demographics and reason for humanitarian response, and described. A total of 96,239 operations were performed at 27 MSF-OCB projects in 15 countries between 2008 and 2014. Of the 33,947 general surgical operations, 4,280 (11%) were for burns. This proportion steadily increased from 3% in 2008 to 24% in 2014. People receiving surgical care from conflict relief missions had nearly twice the odds of having a burn operation compared with people requiring surgery in communities affected by natural disaster (adjusted odds ratio, 1.94; 95% confidence interval, 1.46-2.58). Nearly 70% of burn procedures were planned serial visits to the theatre. A diverse skill set was required. Unmet humanitarian assistance needs increased US$400 million dollars in 2013 in the face of an increasing number of individuals affected by crisis and a growing surgical burden. Given the high volume of burn procedures performed at MSF-OCB projects and the resource intensive nature of burn management, requisite planning and reliable funding are necessary to ensure quality for burn care in humanitarian settings.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.421
Teacher spread0.351 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations45
Published2015
Admission routes1
Has abstractyes

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