Predictive modeling of bronchopulmonary dysplasia in premature infants: the impact of new diagnostic standards.

IF 2.1 3区医学 Q2 PEDIATRICS

Frontiers in Pediatrics Pub Date : 2024-10-29 eCollection Date: 2024-01-01 DOI:10.3389/fped.2024.1434823

Lijun Tang, Weibin Wu, Weimin Huang, Guangliang Bi

{"title":"Predictive modeling of bronchopulmonary dysplasia in premature infants: the impact of new diagnostic standards.","authors":"Lijun Tang, Weibin Wu, Weimin Huang, Guangliang Bi","doi":"10.3389/fped.2024.1434823","DOIUrl":null,"url":null,"abstract":"Aim: To provide a risk prediction for bronchopulmonary dysplasia (BPD) in premature infants under the new diagnostic criteria and establish a prediction model.Methods: In this study, we retrospectively collected case data on preterm infants admitted to the NICU from August 2015 to August 2018. A lasso analysis was performed to identify the risk factors associated with the development of BPD. A nomogram predictive model was constructed in accordance with the new diagnostic criteria for BPD.Result: A total of 276 preterm infants were included in the study.The incidence of BPD under the 2018 diagnostic criteria was 11.2%. Mortality was significantly higher in the BPD group than the non-BPD group under the 2018 diagnostic criteria (P < 0.05). Fourteen possible variables were selected by the Lasso method, with a penalty coefficient λ=0.0154. The factors that eventually entered the logistic regression model included birth weight [BW, OR = 0.9945, 95% CI: 0.9904-0.9979], resuscitation way (OR = 4.8249, 95% CI: 1.3990-19.4752), intrauterine distress (OR = 8.0586, 95% CI: 1.7810-39.5696), score for SNAPPE-II (OR = 1.0880, 95% CI: 1.0210-1.1639), hematocrit (OR = 1.1554, 95% CI: 1.0469-1.2751) and apnea (OR = 7.6916, 95% CI: 1.4180-52.1236). The C-index after adjusting for fitting deviation was 0.894.Conclusion: This study made a preliminary exploration of the risk model for early prediction of BPD and indicated good discrimination and calibration in premature infants.","PeriodicalId":12637,"journal":{"name":"Frontiers in Pediatrics","volume":"12 ","pages":"1434823"},"PeriodicalIF":2.1000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11558522/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Pediatrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fped.2024.1434823","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"PEDIATRICS","Score":null,"Total":0}

引用次数: 0

Abstract

Aim: To provide a risk prediction for bronchopulmonary dysplasia (BPD) in premature infants under the new diagnostic criteria and establish a prediction model.

Methods: In this study, we retrospectively collected case data on preterm infants admitted to the NICU from August 2015 to August 2018. A lasso analysis was performed to identify the risk factors associated with the development of BPD. A nomogram predictive model was constructed in accordance with the new diagnostic criteria for BPD.

Result: A total of 276 preterm infants were included in the study.The incidence of BPD under the 2018 diagnostic criteria was 11.2%. Mortality was significantly higher in the BPD group than the non-BPD group under the 2018 diagnostic criteria (P < 0.05). Fourteen possible variables were selected by the Lasso method, with a penalty coefficient λ=0.0154. The factors that eventually entered the logistic regression model included birth weight [BW, OR = 0.9945, 95% CI: 0.9904-0.9979], resuscitation way (OR = 4.8249, 95% CI: 1.3990-19.4752), intrauterine distress (OR = 8.0586, 95% CI: 1.7810-39.5696), score for SNAPPE-II (OR = 1.0880, 95% CI: 1.0210-1.1639), hematocrit (OR = 1.1554, 95% CI: 1.0469-1.2751) and apnea (OR = 7.6916, 95% CI: 1.4180-52.1236). The C-index after adjusting for fitting deviation was 0.894.

Conclusion: This study made a preliminary exploration of the risk model for early prediction of BPD and indicated good discrimination and calibration in premature infants.

查看原文本刊更多论文

早产儿支气管肺发育不良的预测模型：新诊断标准的影响。

目的：根据新的诊断标准对早产儿支气管肺发育不良（BPD）进行风险预测，并建立预测模型：在这项研究中，我们回顾性地收集了2015年8月至2018年8月期间NICU收治的早产儿病例数据。我们进行了拉索分析，以确定与 BPD 发生相关的风险因素。根据BPD的新诊断标准，构建了一个提名图预测模型：根据2018年的诊断标准，BPD的发生率为11.2%。根据2018年诊断标准，BPD组死亡率明显高于非BPD组（Pλ=0.0154。最终进入逻辑回归模型的因素包括出生体重[BW，OR = 0.9945，95% CI：0.9904-0.9979]、复苏方式（OR = 4.8249，95% CI：1.3990-19.4752）、宫内窘迫（OR = 8.0586，95% CI：1.7810-39.5696）、SNAPPE-II 评分（OR = 1.0880，95% CI：1.0210-1.1639）、血细胞比容（OR = 1.1554，95% CI：1.0469-1.2751）和呼吸暂停（OR = 7.6916，95% CI：1.4180-52.1236）。调整拟合偏差后的 C 指数为 0.894：本研究对早期预测 BPD 的风险模型进行了初步探索，结果表明该模型在早产儿中具有良好的区分度和校准性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Frontiers in Pediatrics Medicine-Pediatrics, Perinatology and Child Health

CiteScore

3.60

自引率

7.70%

发文量

2132

审稿时长

14 weeks

期刊介绍： Frontiers in Pediatrics (Impact Factor 2.33) publishes rigorously peer-reviewed research broadly across the field, from basic to clinical research that meets ongoing challenges in pediatric patient care and child health. Field Chief Editors Arjan Te Pas at Leiden University and Michael L. Moritz at the Children''s Hospital of Pittsburgh are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. Frontiers in Pediatrics also features Research Topics, Frontiers special theme-focused issues managed by Guest Associate Editors, addressing important areas in pediatrics. In this fashion, Frontiers serves as an outlet to publish the broadest aspects of pediatrics in both basic and clinical research, including high-quality reviews, case reports, editorials and commentaries related to all aspects of pediatrics.