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Record W2257558597 · doi:10.1089/sur.2015.012

Surgery for Conditions of Infectious Etiology in Resource-Limited Countries Affected by Crisis: The Médecins Sans Frontières Operations Centre Brussels Experience

2015· article· en· W2257558597 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSurgical Infections · 2015
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsMcGill University Health Centre
FundersFogarty International Center
KeywordsMedicineSpecialtyOrthopedic surgeryHealth careEpidemiologyHealthcare systemDeveloping countryMedical emergencySurgeryFamily medicineEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Surgery for infection represents a substantial, although undefined, disease burden in low- and middle-income countries (LMICs). Médecins Sans Frontières-Operations Centre Brussels (MSF-OCB) provides surgical care in LMICs and collects data useful for describing operative epidemiology of surgical need otherwise unmet by national health services. This study aimed to describe the experience of MSF-OCB operations for infections in LMICs. By doing so, the results might aid effective resource allocation and preparation of future humanitarian staff. METHODS: Procedures performed in operating rooms at facilities run by MSF-OCB from July 2008 through June 2014 were reviewed. Projects providing specialty care only were excluded. Procedures for infection were described and related to demographics and reason for humanitarian response. RESULTS: A total of 96,239 operations were performed at 27 MSF-OCB sites in 15 countries between 2008 and 2014. Of the 61,177 general operations, 7,762 (13%) were for infections. Operations for skin and soft tissue infections were the most common (64%), followed by intra-abdominal (26%), orthopedic (6%), and tropical infections (3%). The proportion of operations for skin and soft tissue infections was highest during natural disaster missions (p<0.001), intra-abdominal infections during hospital support missions (p<0.001) and orthopedic infections during conflict missions (p<0.001). CONCLUSION: Surgical infections are common causes for operation in LMICs, particularly during crisis. This study found that infections require greater than expected surgical input given frequent need for serial operations to overcome contextual challenges and those associated with limited resources in other areas (e.g., ward care). Furthermore, these results demonstrate that the pattern of operations for infections is related to nature of the crisis. Incorporating training into humanitarian preparation (e.g., surgical sepsis care, ultrasound-guided drainage procedures) and ensuring adequate resources for the care of surgical infections are necessary components for providing essential surgical care during crisis.

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.

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)0.001
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 score0.377
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.321
Teacher spread0.297 · 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