ArticlePediatric research2026
Pyloric index: a novel nomogram predictor of metabolic alkalosis in congenital hypertrophic pyloric stenosis.
Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMetabolic alkalosis (MA) is a common complication of congenital hypertrophic pyloric stenosis (CHPS). This study develops and validates a nomogram to predict MA probability in CHPS infants.
methodsA retrospective study was conducted on CHPS patients at the First Affiliated Hospital of Zhengzhou University. Patients were divided into CHPS and MA-CHPS groups. Lasso and logistic regression selected predictive factors, and a nomogram was developed. Discriminative ability was assessed using the C-index with bootstrap validation. Calibration curves evaluated predictive accuracy, while decision curve analysis (DCA) assessed clinical applicability.
resultsA total of 107 cases were included in the final analysis, with 81 in the CHPS group and 26 in the MA-CHPS group. The predictive nomogram included the following factors: weight at diagnosis, symptom duration, and pyloric index (PI). The C-index of the predictive nomogram was determined to be 0.818, with a bootstrap validation (1000 resamples) yielding a corrected C-index of 0.798, indicating good discriminative ability. Calibration curves demonstrated a high degree of consistency between predicted and actual results. DCA confirmed good clinical utility.
conclusionWe developed a nomogram to predict the probability of MA in CHPS patients, enabling early identification of poor prognosis and improving outcomes. IMPACT STATEMENT: This study presents a novel predictive model for assessing the probability of metabolic alkalosis (MA) in congenital hypertrophic pyloric stenosis (CHPS) infants. It is the first model integrating the pyloric index (PI) as a predictive factor, alongside weight at diagnosis and symptom duration. The nomogram demonstrated strong discriminative ability and clinical utility, aiding early MA identification and improving perioperative management. By providing a practical risk stratification tool, this model enhances clinical decision-making, facilitates timely interventions, and ultimately improves outcomes for CHPS infants.
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