Development of a Clinical-Based Prediction Model for Pediatric Intussusception: A Prospective Observational Study.

BACKGROUND

Intussusception, where 1 intestinal segment invaginates into another, causes bowel obstruction and ischemia in children, diagnosed via ultrasound. Early identification of patients requiring ultrasound for intussusception diagnosis is essential.

OBJECTIVES

This study aims to develop a clinical prediction model for intussusception based on solely history, symptoms, and physical examination to identify patients needing ultrasound evaluation.

METHODS

This prospective observational study (September 2019-February 2024) in a pediatric emergency department, included children under 6 with suspected intussusception. Logistic regression identified predictors, and a clinical prediction model was developed. Diagnostic performance was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the receiver operating characteristic curve (AUROC).

RESULTS

Out of 83 patients, 29 (34.9%) were diagnosed with intussusception. Key predictors were absence of fever (adjusted odds ratio [aOR] 4.4), intermittent abdominal pain or irritability (aOR 3.4), absence of diarrhea (aOR 8.0), and right upper quadrant (RUQ) tenderness (aOR 8.2). The model, which includes absence of fever (1 point), intermittent abdominal pain or irritability (1 point), absence of diarrhea (2 points), and RUQ tenderness (2 points), demonstrated 66% sensitivity, 83% specificity, 68% PPV, 81.5% NPV, and an AUROC of 0.78, achieving 100% sensitivity and NPV at a threshold score of ≥1 point.

CONCLUSIONS

The prediction model, based on absence of fever, intermittent abdominal pain/irritability, absence of diarrhea, and RUQ tenderness, effectively identifies children at risk for intussusception. It supports timely ultrasound decisions in children with ambiguous abdominal symptoms, improving patient outcomes.