Demographics and diagnoses at rural health camps in Nepal: cross-sectional study
Bibliographic record
Abstract
BACKGROUND: The charity 'Health Partnership Nepal' is committed to both improving global health care and providing medical training links between Nepal and the UK. This paper analyses data gathered at rural health camps. AIM: To describe the demographics, diagnoses and treatments offered to people attending three rural health camps in Nepal during 2009. Design Cross-sectional study. Setting Three free health care camps established within the Nuwakot district of Nepal during April-May 2009. Camps were staffed by doctors including GPs, nurses and medical students from London and Kathmandu. METHODS: Attendees had treatment sheets completed which recorded their demographics, diagnoses and dispensed medications. RESULTS: The mean age of the 1903 consecutive patients attending was 42.8 years (range one month to 98 years) of whom 68.6% were female and 13.7% were children. The majority, 82.3%, were agricultural workers. For adults (n = 1574), the most frequent complaints were stomach pain 20.1%, musculoskeletal pain 19.3% and visual acuity problems 6.1%. Stomach pain was significantly more common in women than men [21.2% (236/1064) versus 14.5% (65/449) P < 0.01]. For children (n = 249), the most common diagnoses were helminthiasis 10.4%, conjunctivitis 7.6% and upper respiratory tract infection 7.2%. Overall, opthalmological, gastroenterological and rheumatological diagnoses were significantly more common in Nepalese than UK general practice patients. Of 1109 recorded prescriptions, the most common were multivitamins 23%, oral analgesics 15% and oral antibiotics 14%. CONCLUSIONS: There is a considerable unmet disease burden within rural districts of Nepal particularly for stomach pain, musculoskeletal pain and visual acuity problems. When planning similar rurally based health camps, we recommend recruiting GPs and ophthalmologists.
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 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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".