Yongcheng Fu, Jian Cheng, Xing Zhou, Xiaohan Qin, Jingyue Wang, Yuanyuan Wang, Shangkun Li, Juan Ding, Da Zhang
{"title":"幽门指数:先天性肥厚性幽门狭窄代谢性碱中毒的一种新的nomogram预测指标。","authors":"Yongcheng Fu, Jian Cheng, Xing Zhou, Xiaohan Qin, Jingyue Wang, Yuanyuan Wang, Shangkun Li, Juan Ding, Da Zhang","doi":"10.1038/s41390-025-04382-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Metabolic 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.</p><p><strong>Methods: </strong>A 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.</p><p><strong>Results: </strong>A 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.</p><p><strong>Conclusion: </strong>We developed a nomogram to predict the probability of MA in CHPS patients, enabling early identification of poor prognosis and improving outcomes.</p><p><strong>Impact statement: </strong>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.</p>","PeriodicalId":19829,"journal":{"name":"Pediatric Research","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pyloric index: a novel nomogram predictor of metabolic alkalosis in congenital hypertrophic pyloric stenosis.\",\"authors\":\"Yongcheng Fu, Jian Cheng, Xing Zhou, Xiaohan Qin, Jingyue Wang, Yuanyuan Wang, Shangkun Li, Juan Ding, Da Zhang\",\"doi\":\"10.1038/s41390-025-04382-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Metabolic 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.</p><p><strong>Methods: </strong>A 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.</p><p><strong>Results: </strong>A 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.</p><p><strong>Conclusion: </strong>We developed a nomogram to predict the probability of MA in CHPS patients, enabling early identification of poor prognosis and improving outcomes.</p><p><strong>Impact statement: </strong>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.</p>\",\"PeriodicalId\":19829,\"journal\":{\"name\":\"Pediatric Research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pediatric Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41390-025-04382-6\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PEDIATRICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pediatric Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41390-025-04382-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
Pyloric index: a novel nomogram predictor of metabolic alkalosis in congenital hypertrophic pyloric stenosis.
Background: Metabolic 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.
Methods: A 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.
Results: A 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.
Conclusion: We 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.
期刊介绍:
Pediatric Research publishes original papers, invited reviews, and commentaries on the etiologies of children''s diseases and
disorders of development, extending from molecular biology to epidemiology. Use of model organisms and in vitro techniques
relevant to developmental biology and medicine are acceptable, as are translational human studies