Emergency Surgery Data and Documentation Reporting Forms for Sudden-Onset Humanitarian Crises, Natural Disasters and the Existing Burden of Surgical Disease
Bibliographic record
Abstract
Following large-scale disasters and major complex emergencies, especially in resource-poor settings, emergency surgery is practiced by Foreign Medical Teams (FMTs) sent by governmental and non-governmental organizations (NGOs). These surgical experiences have not yielded an appropriate standardized collection of data and reporting to meet standards required by national authorities, the World Health Organization, and the Inter-Agency Standing Committee's Global Health Cluster. Utilizing the 2011 International Data Collection guidelines for surgery initiated by Médecins Sans Frontières, the authors of this paper developed an individual patient-centric form and an International Standard Reporting Template for Surgical Care to record data for victims of a disaster as well as the co-existing burden of surgical disease within the affected community. The data includes surgical patient outcomes and perioperative mortality, along with referrals for rehabilitation, mental health and psychosocial care. The purpose of the standard data format is fourfold: (1) to ensure that all surgical providers, especially from indigenous first responder teams and others performing emergency surgery, from national and international (Foreign) medical teams, contribute relevant and purposeful reporting; (2) to provide universally acceptable forms that meet the minimal needs of both national authorities and the Health Cluster; (3) to increase transparency and accountability, contributing to improved humanitarian coordination; and (4) to facilitate a comprehensive review of services provided to those affected by the crisis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".