The Prevalence of Small Intestinal Bacterial Overgrowth in Patients with Non-Alcoholic Liver Diseases: NAFLD, NASH, Fibrosis, Cirrhosis—A Systematic Review, Meta-Analysis and Meta-Regression
Notice bibliographique
Résumé
Bacterial overgrowth in the small intestine (SIBO) is a pathological growth of the intestinal microbiota in the small intestine that causes clinical symptoms and can lead to digestive and absorption disorders. There is increasing evidence that people with NAFLD have a distinct gut microflora profile as well metabolome changes compared to people without NAFLD. Thorough analysis of observational and RCT studies in the current databases (EMBASE, Web of Science, PubMed, Cinahl, Clinical Trials) was conducted from 3 November 2021 to 21 June 2022. The following inclusion criteria were applied: confirmed NAFLD, NASH, LIVER FIBROSIS, CIRRHOSIS due to steatosis; diagnostic methods of liver diseases—biopsy, elastography, transabdominal ultrasound; nonalcoholic fatty liver disease activity score; confirmed SIBO; diagnostic methods of SIBO−breath tests (hydrogen test; methane test and mix test; duodenal and jejunal aspiration before any type of intervention; adults above 18yo; number of participants ≥20; full articles. We excluded review articles, populations with HBV/HCV infection and alcohol etiology and interventions that may affect NAFLD or SIBO treatment. The quality of each study methodology was classified by means of the Cochrane Collaboration’s tool (RCT) and Newcastle—Ottawa Quality Assessment Scale adapted for cross-sectional, cohort and case-control studies. The random effects meta-analysis of outcomes for which ≥2 studies contributed data was conducted. The I2 index to measure heterogeneity and the χ2 test of homogeneity (statistically significant heterogeneity p < 0.05) were applied. For categorical outcome, the pooled event rate (effect size) was calculated. This systematic review was reported according to PRISMA reporting guidelines. We initially identified 6643 studies, from which 18 studies were included in final meta-analysis. The total number of patients was 1263. Accepted SIBO diagnostic methods were both available breath tests (n-total = 15) and aspirate culture (n-total = 3). We found that among patients with non-alcoholic liver diseases, the random overall event rate of SIBO was 0.350 (95% CI, 0.244−0.472), p = 0.017. The subgroup analysis regarding a type of diagnosis revealed that the lowest ER was among patients who developed simultaneously NAFLD, NASH and fibrosis: 0.197 (95% CI, 0.054−0.510) as compared to other annotated subgroups. The highest prevalence of SIBO was observed in the NASH subgroup: 0.411 (95% CI, 0.219−0.634). There were no statistically significant differences in the prevalence of SIBO in different subgroups (p = 0.854). Statistically significant heterogeneity between studies was estimated (I2 = 86.17%, p = 0.00). Egger’s test did not indicate a publication bias (df = 16, p = 0.885). A meta-regression using a random-effects model revealed that higher percentage of males in the population with liver diseases is a predisposing factor toward SIBO (Q = 4.11, df = 1, p = 0.0426 with coefficient = 0.0195, SE = 0.0096, Z = 2.03). We showed that the prevalence of SIBO in patients with chronic non-alcoholic liver diseases can be as high as 35%, and it increases with the percentage of men in the population. The prevalence of SIBO does not differ significantly depending on the type of chronic liver disease. Despite the high heterogeneity and moderate and low quality of included studies, our meta-analysis suggests the existence of a problem of SIBO in the population of patients with non-alcoholic liver diseases, and the presence of SIBO, in turn, determines the therapeutic treatment of such type of patients, which indicates the need for further research in this area. The study protocol was registered with the international Prospective Register of Systematic Reviews (PROSPERO ID: CRD42022341473).
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 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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,003 |
| Bibliométrie | 0,000 | 0,001 |
| 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) | 0,001 | 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 ».