Enrollment of dengue patients in a prospective cohort study in Umphang District, Thailand, during the COVID‐19 pandemic: Implications for research and policy
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Background and Aims: Dengue is endemic in Thailand and imposes a high burden on the health system and society. We conducted a prospective cohort study in Umphang District, Tak Province, Thailand, to investigate the share of dengue cases with long symptoms and their duration. Here we present the results of the enrollment process during the COVID-19 pandemic with implications and challenges for research and policy. Methods: In a prospective cohort study conducted in Umphang District, Thailand, we examined the prevalence of persistent symptoms in dengue cases. Clinically diagnosed cases were offered free laboratory testing, We enrolled ambulatory dengue patients regardless of age who were confirmed through a highly sensitive laboratory strategy (positive NS1 and/or IgM), agreed to follow-up visits, and gave informed consent. We used multivariate logistic regressions to assess the probability of clinical dengue being laboratory confirmed. To determine the factors associated with study enrollment, we analyzed the relationship of patient characteristics and month of screening to the likelihood of participation. To identify underrepresented groups, we compared the enrolled cohort to external data sources. Results: The 150 clinical cases ranged from 1 to 85 years old. Most clinical cases (78%) were confirmed by a positive laboratory test, but only 19% of those confirmed enrolled in the cohort study. Women, who were half as likely to enroll as men, were underrepresented in the cohort. Conclusions: The Thai physicians' clinical diagnoses at this rural district hospital had good agreement with laboratory diagnoses. By identifying underrepresented groups and disparities, future studies can ensure the creation of statistically representative cohorts to maximize their scientific value. This involves recruiting and retaining underrepresented groups in health research, such as women in this study. Promising strategies for meaningful inclusion include multi-site enrollment, offering in-home or virtual services, and providing in-kind benefits like childcare for underrepresented groups.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle