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Enregistrement W3190753973 · doi:10.1016/s1473-3099(21)00052-9

Initiation and completion of treatment for latent tuberculosis infection in migrants globally: a systematic review and meta-analysis

2021· article· en· W3190753973 sur OpenAlexaff

Notice bibliographique

RevueThe Lancet Infectious Diseases · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueTuberculosis Research and Epidemiology
Établissements canadiensJewish General Hospital
Organismes subventionnairesMedical Research CouncilNational Institute for Health and Care ResearchEuropean Society of Clinical Microbiology and Infectious DiseasesRosetrees TrustMinistero della SaluteAcademy of Medical Sciences
Mots-clésTuberculosisLatent tuberculosisMEDLINEInfectious disease (medical specialty)EpidemiologyHealth services

Résumé

récupéré en direct d'OpenAlex

Background Latent tuberculosis infection (LTBI) is one of the most prevalent infections globally and can lead to the development of active tuberculosis disease. In many low-burden countries, LTBI is concentrated within migrant populations often because of a higher disease burden in the migrant's country of origin. National programmes consequently focus on screening and treating LTBI in migrants to prevent future tuberculosis cases; however, how effective these programmes are is unclear. We aimed to assess LTBI treatment initiation and outcomes among migrants, and the factors that influence both. Methods For this systematic review and meta-analysis, we searched Embase, MEDLINE, and Global Health, and manually searched grey literature from Jan 1, 2000, to April 21, 2020. We included primary research articles reporting on LTBI treatment initiation or completion, or both, in migrants and excluded articles in which data were not stratified by migrant status, or in which the data were related to outcomes before 2000. There were no geographical or language restrictions. All included studies were quality appraised using recognised tools depending on their design, and we assessed the heterogeneity of analyses using I 2 . We extracted data on the numbers of migrants initiating and completing treatment. Our primary outcomes were LTBI treatment initiation and completion in migrants (defined as foreign-born). We used random-effects meta-regression to examine the influence of factors related to these outcomes. The study is registered with PROSPERO (CRD42019140338). Findings 2199 publications were retrieved screened, after which 39 publications from 13 mostly high-income, low-burden countries were included in our analyses, with treatment initiation and completion data reported for 31 598 migrants positive for LTBI, with not all articles reporting the full pathway from initiation to completion. The pooled estimate for the true proportion of migrants testing positive who initiated treatment was 69% (95% CI 51–84; I 2 = 99·62%; 4409 of 8764). The pooled estimate for the true proportion of migrants on treatment in datasets, who subsequently completed it was 74% (95% CI=66–81; I 2 = 99·19%; 15 516 of 25 629). Where data were provided for the entire treatment pathway, the pooled estimate for the true proportion of migrants who initiated and completed treatment after a positive test was only 52% (95% CI 40–64; I 2 = 98·90%; 3289 of 6652). Meta-regression showed that LTBI programmes are improving, with more recent reported data (2010–20) associated with better rates of treatment initiation and completion, with multiple complex factors affecting treatment outcomes in migrants. Interpretation Although our analysis highlights that LTBI treatment initiation and completion in migrants has improved considerably from 2010–20, there is still room for improvement, with drop out reported along the entire treatment pathway. The delivery of these screening and treatment programmes will require further strengthening if the targets to eradicate tuberculosis in low-incidence countries are to be met, with greater focus needed on engaging migrants more effectively in the clinic and understanding the diverse and unique barriers and facilitators to migrants initiating and completing treatment. Funding European Society of Clinical Microbiology and Infectious Diseases, the Rosetrees Trust, the National Institute for Health Research, and the Academy of Medical Sciences.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,327
Score d'incertitude au seuil0,273

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,103
Tête enseignante GPT0,379
Écart entre enseignants0,275 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations59
Publié2021
Routes d'admission1
Résumé présentoui

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