Impact of the Population Medicine Multimorbidity Intervention in Xishui County (POPMIX) on People at High Risk for Chronic Obstructive Pulmonary Disease: Protocol for the POPMIX-COPD Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Tobacco-related noncommunicable diseases (NCDs) present a major public health challenge in China, requiring population-level management. Chronic obstructive pulmonary disease (COPD) is the most common and prevalent chronic respiratory disease associated with tobacco use. In addition, COPD shares risk factors with other NCDs that frequently co-occur, leading to multimorbidity. This study focuses on the early detection and integrated management of COPD and related multimorbidity among high-risk populations. Population medicine, an emerging and evolving concept aimed at maximizing population health and well-being, provides a promising framework for shifting interventions against COPD from an individual patient focus to a population-level approach. OBJECTIVE: This study aims to evaluate the effectiveness of a population medicine-based multimorbidity intervention package among individuals at high risk for COPD. METHODS: We are conducting a 2-arm, population-based, stratified cluster randomized controlled trial (cRCT). The intervention integrates community screening, chronic disease management, patient education, digital follow-up, and team-based care. The trial is being implemented in Xishui County, Guizhou Province, a low-resource county in Southwestern China. Each of the 26 townships in Xishui County was considered a cluster and stratified into large and small townships based on population size. An equal number of residents from each township stratum (large and small) were randomized to undergo the COPD Screening Questionnaire. Individuals identified as being at high risk for COPD were considered study participants and were subsequently enrolled in either the intervention or control arm. The target sample size was approximately 2850 individuals. RESULTS: Data collection for the POPMIX-COPD trial began in June 2024. Baseline, 3-month, and 6-month assessments have been completed, and 12-month follow-up assessments are planned to be completed in March 2026. All participants in the intervention arm are being followed for 1 year, with 1 telephone follow-up at month 3 and in-person follow-ups at months 6 and 12. Primary outcomes for each participant include the number of chronic conditions controlled, receipt of lung function testing, and forced expiratory volume in 1 second. In addition, secondary outcomes were health-related quality of life, mental and behavioral health status, health care utilization, knowledge of COPD and asthma, and care cascade indicators for chronic conditions. CONCLUSIONS: This cRCT is the first multimorbidity intervention study designed within the population medicine framework to target populations at high risk for COPD. It was featured as a case study in the report of the Lancet Commission on Investing in Health. The results of the trial are expected to inform the next generation of multimorbidity management and population medicine practices among global health authorities and practitioners. TRIAL REGISTRATION: ClinicalTrials.gov NCT06456996; https://clinicaltrials.gov/ct2/show/NCT06456996. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/85597.
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,002 |
| Méta-épidémiologie (sens large) | 0,009 | 0,006 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,037 | 0,004 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».