Assessment of Post-Dengue Rheumatic Symptoms Using the WOMAC and DAS-28 Questionnaires in a Honduran Population after a Four-Month Follow-Up
Bibliographic record
Abstract
Introduction: Alphaviruses may cause arthritis, but there is a lack of studies assessing it in flaviviruses such as dengue. Through the 28 Joint Disease Activity Score (DAS-28), incorporating swollen joint counts, and through the Arthritis Index from Western Ontario and McMaster Universities (WOMAC), we assessed pain, stiffness, and dimensions of arthritic function in post-DENV patients. Methods: Prospective study of a cohort of participants who were diagnosed with dengue in centres in Honduras from December 2019 to February 2020, with a follow-up period of 4 months to evaluate post-dengue rheumatological disease through the WOMAC and DAS-28 questionnaires. Results: After a four-month follow-up phase with 281 participants, the final cohort comprised 58.8% women and 41.20% men. After the follow-up, 63.02% persisted with the clinical findings. According to WOMAC, joint involvement was higher in women with (58.76%) (p < 0.0001) these symptoms or functional limitations when performing daily activities were limited to pain when walking (34.81% vs. 5.51%), climbing or descending stairs (36.46% vs. 8.66%), and at night at bedtime (28.73% vs. 7.08%). With the DAS-28, we found at least one alteration with inflammation or pain in 14.91% of the participants, primarily women (p < 0.01). Discussion: Joint involvement was high during the dengue epidemic in 2019. We observed a significant proportion of women with inflammation and joint pain, showing that dengue may lead to the development of chronic rheumatological findings, although lower than in CHIKV, still affecting everyday life and, consequently, their quality of life. Additional long-term evaluation studies after dengue are required.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".