Prediction Models for Sarcopenia in Patients with Maintenance Hemodialysis: A Systematic Review and Meta-Analysis.
J Ren Nutr
; 2024 Jul 10.
Article
in En
| MEDLINE
| ID: mdl-38996829
ABSTRACT
BACKGROUND:
This systematic review and meta-analysis investigated all prediction models for sarcopenia in Maintenance Hemodialysis (MHD) patients.METHODS:
This study used the Systematic Reviews and Meta-Analysis statement (PRISMA) for systematic review. DATA SOURCES PubMed, Web of Science, Embase, Cochrane Library and Medline databases up to September 2023. DATAANALYSIS:
Risk of bias (ROB) was evaluated using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Random effect models were calculated due to high heterogeneity identified.RESULTS:
Fifteen models from twelve studies were analyzed. All studies had high ROB and three of them posed a high risk in terms of applicability. The pooled AUC, sensitivity, and specificity were 0.715, 0.583 and 0.656 respectively. The diagnostic criteria (P=0.0046), country (P=0.0046), and study design (P=0.0087) were significant sources of the heterogeneity. Analysing purely from the data perspective, grouping by diagnostic criterias, the AUC and specificity [(0.773, 95% CI 0.12-0.99, (0.652, 95% CI 0.641-0.664)] of the Asian Working Group for Sarcopenia (AWGS) group was lower than the European Working Group on Sarcopenia in Older People (EWGSOP) group [(0.859, 95% CI 0.12-1.00), (0.874, 95% CI 0.803-0.926)]. Grouping by styles of research, the AUC, sensitivity, and specificity in development group [(0.890, 95% CI 0.16-1.00), (0.751, 95% CI 0.697-0.800), (0.875, 95% CI 0.854-0.895)] were all higher than validation group [(0.715, 95% CI 0.09-0.98), (0.550, 95% CI 0.524-0.576), (0.617, 95% CI 0.604-0.629)].CONCLUSIONS:
Moving forward, there is a critical need to create low-ROB, high-applicability, and more accurate sarcopenia prediction models for MHD patients, customized for diverse global populations.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
J Ren Nutr
Journal subject:
CIENCIAS DA NUTRICAO
/
NEFROLOGIA
Year:
2024
Type:
Article
Affiliation country:
China