Neurocysticercosis and Epilepsy in Bhutan: A Cross-sectional study (I7-4A)
Bibliographic record
Abstract
OBJECTIVE: We sought to assess the burden of neurocysticercosis (NCC) in a cross-sectional analysis of patients with epilepsy in Bhutan. Given the high burden of NCC reported in neighboring countries, we postulated that a significant proportion of people with epilepsy in Bhutan would carry the disease. BACKGROUND: Neurocysticercosis is endemic to Southeast Asia, but the burden in Bhutan is unknown. Epilepsy is common in Bhutan, with the National Referral Center reporting over 1,200 cases per year. As a preventable cause of epilepsy, understanding the burden of neurocysticercosis is an important component of epilepsy treatment and prevention. DESIGN/METHODS: Between April and November 2014, we enrolled 107 participants with a diagnosis of epilepsy at Jigme Dorji Wangchuk National Referral Hospital in Thimphu, Bhutan. All participants completed a standardized survey detailing their experience with epilepsy. Serum was tested for Taenia solium IgG using an enzyme-linked immunoassay from DRG International, and all positive results at 1:64 dilution were re-tested for confirmation. Positive tests will be correlated with magnetic resonance imaging (MRI) data for each patient when available. RESULTS: Of the 107 patients with epilepsy tested in this study, 4 had serum that was positive for Taenia solium IgG. On repeat testing of the same sample, only 50[percnt] of these samples were positive for NCC and two were positive for Echinococcus. None of the infected patients reported a known history of brain infection. Only 62/107 (58[percnt]) patients indicated awareness of brain infections leading to seizures. CONCLUSIONS: The prevalence of neurocysticercosis on serological testing in this cohort was lower than what has been reported in neighboring countries. Awareness of brain infections was limited. Echinococcocus may lead to false positive results in cysticercosis serum testing in regions of overlapping endemicity. Study Supported by: Grand Challenges Canada, Thrasher Research Foundation, & Partners Center for Expertise in Global Health
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".