Surgical Needs of Nepal: Pilot Study of Population Based Survey in Pokhara, Nepal
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.
Bibliographic record
Abstract
BACKGROUND: The Surgeons OverSeas assessment of surgical need (SOSAS) tool, a population-based survey on surgical conditions in low- and middle-income countries (LMICs), was performed in Sierra Leone and Rwanda. This pilot study in Nepal is the initial implementation of the SOSAS survey in South Asia. METHODS: A pilot study of SOSAS, modified for Nepal's needs and reprogrammed using mobile data collection software, was undertaken in Pokhara in January 2014. Cluster randomized sampling was utilized to interview 100 individuals in 50 households within two wards of Pokhara, one rural and one urban. The first portion of the survey retrieved demographic data, including household members and time to nearest health facilities. The second portion interviewed two randomly selected individuals from each household, inquiring about surgical conditions covering six anatomical regions. RESULTS: The pilot SOSAS in Nepal was easily completed over 3 days, including training of 18 Nepali interns over 2 days. The response rate was 100 %. A total of 13 respondents had a current surgical need (face 4, chest 1, back 1, abdomen 1, groin 3, extremity 3), although eight reported there was no need for surgical care. Five respondents (5 %) had a current unmet surgical need. CONCLUSION: The SOSAS pilot study in Nepal was successfully conducted, demonstrating the feasibility of performing SOSAS in South Asia. The estimated 5 % current unmet surgical need will be used for sample size calculation for the full country survey. Utilizing and improving on the SOSAS tool to measure the prevalence of surgical conditions in Nepal will help enumerate the global surgical burden of disease.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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 it