Accuracy of ultrasound for intussusception in pediatric emergency presentations: a systematic review and diagnostic meta-analysis

INTRODUCTION: Intussusception is a common cause of acute abdominal emergencies in children. This systematic review and diagnostic meta-analysis aimed to determine the diagnostic accuracy of ultrasound for intussusception in pediatric emergency presentations, providing pooled estimates for sensitivity, specificity, predictive values, and diagnostic odds ratios to inform clinical practice. METHODS: Adhering to PRISMA-DTA guidelines, a comprehensive search was conducted in PubMed, Scopus, Cochrane Library, and Web of Science up to July 2025. Bayesian bivariate random-effects meta-analyses were performed to estimate pooled sensitivity, specificity, and other measures, with subgroup and meta-regression analyses to explore heterogeneity. RESULTS: A total of 44 studies comprising 4,142 pediatric patients were included in the quantitative synthesis. The pooled sensitivity of ultrasound for diagnosing intussusception was 96.3% (95% credible interval [CrI] 94.9–97.5%), and the pooled specificity was 95.7% (95% CrI 93.3–97.5%). The area under the hierarchical summary receiver operating characteristic curve (AUC) was 0.81–0.82, indicating good discriminative ability. Positive predictive value (PPV) ranged from 54.1% at 5% prevalence to 99.8% at 95% prevalence, while negative predictive value (NPV) decreased from 99.8% to 57.7% across the same prevalence range. The overall certainty of evidence for sensitivity and specificity was rated as high, with moderate certainty for prevalence due to substantial heterogeneity. CONCLUSION: Ultrasound demonstrates excellent diagnostic performance for pediatric intussusception in emergency settings, with high sensitivity and specificity maintained across patient subgroups and operator backgrounds. These findings support the continued use of ultrasound as the first-line diagnostic modality in both high- and low-resource environments and highlight the importance of structured training to optimize its accuracy. Future research should focus on multicenter prospective studies, standardization of ultrasound protocols, and the integration of artificial intelligence to further enhance diagnostic reliability.