Disability with Persistent Pain Following an Epidemic of Chikungunya in Rural South India
Bibliographic record
Abstract
OBJECTIVE: We investigated the effects of chronic rheumatic and musculoskeletal symptoms on the functional status of people affected by the chikungunya (CKG) epidemic in the Calicut District, Kerala, South India in 2009. METHODS: A cross-sectional house-to-house survey was conducted 18 months after the CKG epidemic to assess functional status of individuals with post-epidemic persistent pain. All respondents over age 15 years with persistent pain fitting the epidemiological case definition were included. Participants' functional status was assessed using the Health Assessment Questionnaire-Disability Index (HAQ-DI). Factors affecting severity of HAQ-DI were analyzed by ordinal regression. RESULTS: Of 3869 subjects interviewed, 1195 (34.3%) had a positive history of CHIKV virus infection (epidemiological or confirmed); 36.28% (624/1720) of CKG-affected individuals had persistent pain 18 months post epidemic. Mean age of those affected was 48.22 ± 15.6 years; 23.2% had no disability, while 16.2% had moderate to severe disability on the HAQ-DI. Significant factors affecting severity of disability on HAQ-DI included previous rheumatic musculoskeletal disease (OR 2.27), joint and soft-tissue involvement (OR 3.74), only joint involvement (OR 2.14), female sex (OR 1.44), diet (OR 4.73), and history of joint swelling (OR 1.72). CONCLUSION: Persistence of pain noted in post-CKG disease resulted in significantly deteriorated functional status of those affected.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".