Risk Factors for Epilepsy in a Rural Area in Tanzania
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 AND METHODS: The high prevalence of epilepsy detected in rural Tanzania by Dr. Jilek-Aall since 1960, was verified by the World Health Organization (WHO) survey on neurological and seizure disorders. Neurologists and psychiatrists further interviewed both patients and controls using standard methods. The presence of possible risk factors was complemented by corroborative evidence through interviewing close relatives and scrutinizing medical records. Seizures were classified based on clinical symptoms and the use of EEG. RESULTS: A family history of epilepsy in first-degree relatives was found in 46.6% of patients, but in only 19.6% of controls. The odds ratio for family history with epilepsy was 3.52 (95% confidence interval, CI 2.4-5.74, p < 0.001). A past history of febrile convulsion was found in 44% of patients in comparison to 23% of the control group which was significant (odds ratio 2.4, 95% CI 1.5-3.8; p < 0.001). A history of intrapartum complications was found in 12.1% of patients and 1.8% of controls (odds ratio 7.3, 95% CI 2.5-25.2; p < 0.002). Head injury was not a significant risk factor for epilepsy in this rural community. CONCLUSION: The results indicated a strongly independent association between four factors and the risk of developing epilepsy. It would seem more likely that previous brain insults/diseases play a significant major role in the cause of epilepsy in the Mahenge area. However, a genetic predisposition to low threshold for convulsions cannot be excluded.
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 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 | 0.001 | 0.005 |
| 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 it