Estimation of disability weight for paragonimiasis: a systematic analysis
Notice bibliographique
Résumé
BACKGROUND: Paragonimiasis, caused by helminths of the genus Paragonimus spp., is a neglected tropical disease. Human suffering from paragonimiasis is often misunderstood and its quantification by the disability weight of the disability-adjusted life years largely varies in different global burden of disease (GBD) estimates. This paper is to systematically review clinical paragonimiasis cases and requantify the disability weight of human paragonimiasis. METHODS: A systematic analysis was conducted using articles from the following databases: PubMed, Institute for Scientific Information Web of Science, China National Knowledge Infrastructure, the Chinese scientific journal databases Wanfang Data and CQVIP, Africa Journal Online, and the System for Information on Grey Literature in Europe. Search terms were the combination of "paragonim*" with "clinical" or "infection". Only articles fulfilling the following conditions were recruited for this study: the occurrence of clinical signs and symptoms of paragonimiasis in human beings were reported; diagnosis was confirmed; no comorbidities were reported; the reviewed clinical cases or epidemiological findings were not already included in any other articles. The information and frequencies of paragonimiasis outcomes from included articles using predefined data fields were extracted two times by two separate individuals. Outcome disability weights were selected mainly from the GBD 2004 and GBD 2013 datasets. Frequencies and disability weights of paragonimiasis outcomes were modelled into a decision tree using the additive approach and multiplicative approach, respectively. Monte Carlo simulations were run 5000 times for an uncertainty analysis. RESULTS: The disability weight estimates of paragonimiasis were simulated with 5302 clinical cases from 80 general articles. The overall disability weight was estimated at 0.1927 (median 0.1956) with a 95% uncertainty interval (UI) of 0.1632-0.2378 using the additive approach, and 0.1791 (median 0.1816) with a 95% UI of 0.1530-0.2182 using the multiplicative approach. The simulated disability weights of Paragonimus westermani cases were higher than that of P. skrjabini cases. Lung outcomes and headache were the top two contributors to disability weight for both species. CONCLUSIONS: The use of paragonimiasis disability weight needs to be reconsidered with regard to availability of morbidity data and species variation. Calculating the disease burden of paragonimiasis requires further modification and thus has considerable implications for public health prioritization in research, monitoring, and control.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| 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 | 0,000 |
| 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 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 ».