Results from a roving, active case finding initiative to improve tuberculosis detection among older people in rural cambodia using the Xpert MTB/RIF assay and chest X-ray
Notice bibliographique
Résumé
Cambodia has one of the highest tuberculosis (TB) prevalence rates in the world. People aged 55 years and over account for an estimated 50% of the country's TB burden, yet this group has a low notification rate owing to specific barriers in accessing health services. One-off active case finding (ACF) days with mobile GeneXpert and X-ray systems were organized at 75 government health facilities in four operational districts. Symptomatic community members with an abnormal chest X-ray were tested using the Xpert MTB/RIF assay. People with TB were then treated at health facilities after screening services moved onto the next site. De-identified project data were analysed to produce descriptive statistics about the people tested on Xpert and those diagnosed with TB. A linear regression was fit through the 12 quarters of National TB Program (NTP) TB case notification data immediately prior to ACF. The regression was used to calculate trend-expected notifications during and after the ACF quarters. Notifications from the ACF quarters were then compared to actual notifications from the previous year and to the trend-expected notifications during the ACF quarter by age group and type of TB. Finally, NTP TB treatment outcomes for the patients started on treatment during the ACF quarter were compared to those from a year prior. 2068 individuals submitted sputum for Xpert MTB/RIF testing, resulting in the identification of 319 (15.4%) bacteriologically-positive TB patients and an additional 574 people who were clinically diagnosed with TB. In the ACF quarters, new bacteriologically-positive notifications increased +119.2% for all ages and +262.7% for people aged 55 and over compared with trend-expected notifications. Treatment initiation figures remained above trend-expected notifications for three full quarters after ACF. The treatment success rate across all operational districts was significantly higher for patients detected in the ACF quarters (88.8% vs 94.5%, p = 0.012). A series of roving, one-off ACF days at government health facilities were able to increase TB diagnosis, treatment initiation and treatment outcomes in a key population with high TB prevalence. Targeted ACF interventions such as this could be used to reduce a backlog of untreated, prevalent TB.
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Comment cette classification a été obtenuedéplier
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 | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».