Ze Zhang, Haotian Zhao, Zhiyang Zhang, Lijing Jia, Ling Long, You Fu, Quansheng Du
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Nomograms were developed to show predictive models, and the discrimination, calibration, and clinical usefulness of the models were assessed using the C-index, calibration plots, and decision curve analysis (DCA).</p><p><strong>Results: </strong>Two hundred patients were ultimately included for analysis. In the development cohort, 38 (27.1%) of 140 patients developed ARDS, and in the internal validation cohort, 13 (21.7%) of 60 patients developed ARDS. The multivariate logistic regression analysis revealed the site of perforation (OR = 0.164, P = 0.006), the duration of surgery (OR = 0.986, P = 0.008), BMI (OR = 1.197, P = 0.015), SOFA (OR = 1.443, P = 0.001), lactate (OR = 1.500, P = 0.017), and albumin (OR = 0.889, P = 0.007) as the independent risk factors for ARDS development. The area under the curve (AUC) was 0.921 (95% CI: 0.869, 0.973) for the development cohort and 0.894 (95% CI: 0.809, 0.978) for the validation cohort. The calibration curve and decision curve analysis (DCA) demonstrate that the nomogram possesses good predictive value and clinical practicability.</p><p><strong>Conclusion: </strong>Our research introduced a nomogram that integrates six independent risk factors, facilitating the precise prediction of ARDS risk in postoperative patients following gastrointestinal perforation.</p>","PeriodicalId":16107,"journal":{"name":"Journal of Inflammation Research","volume":"18 ","pages":"221-236"},"PeriodicalIF":4.2000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724661/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Simple Nomogram for Predicting the Development of ARDS in Postoperative Patients with Gastrointestinal Perforation: A Single-Center Retrospective Study.\",\"authors\":\"Ze Zhang, Haotian Zhao, Zhiyang Zhang, Lijing Jia, Ling Long, You Fu, Quansheng Du\",\"doi\":\"10.2147/JIR.S496559\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Acute respiratory distress syndrome (ARDS) is a severe form of organ dysfunction and a common postoperative complication. This study aims to develop a predictive model for ARDS in postoperative patients with gastrointestinal perforation to facilitate early detection and effective prevention.</p><p><strong>Methods: </strong>In this single-center retrospective study, clinical data were collected from postoperative patients with gastrointestinal perforation admitted to the ICU in Hebei Provincial People's Hospital from October 2017 to May 2024. Univariate analysis and multifactorial logistic regression analysis were used to determine the independent risk factors for developing ARDS. Nomograms were developed to show predictive models, and the discrimination, calibration, and clinical usefulness of the models were assessed using the C-index, calibration plots, and decision curve analysis (DCA).</p><p><strong>Results: </strong>Two hundred patients were ultimately included for analysis. 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引用次数: 0
摘要
背景:急性呼吸窘迫综合征(ARDS)是一种严重的器官功能障碍,也是常见的术后并发症。本研究旨在建立消化道穿孔术后ARDS的预测模型,以便早期发现和有效预防。方法:本研究为单中心回顾性研究,收集2017年10月至2024年5月河北省人民医院ICU收治的胃肠道穿孔术后患者的临床资料。采用单因素分析和多因素logistic回归分析确定发生ARDS的独立危险因素。利用c指数、校准图和决策曲线分析(DCA)评估模型的鉴别性、校准性和临床实用性。结果:200例患者最终纳入分析。在发展队列中,140例患者中有38例(27.1%)发生ARDS,在内部验证队列中,60例患者中有13例(21.7%)发生ARDS。多因素logistic回归分析显示,穿孔部位(OR = 0.164, P = 0.006)、手术时间(OR = 0.986, P = 0.008)、BMI (OR = 1.197, P = 0.015)、SOFA (OR = 1.443, P = 0.001)、乳酸(OR = 1.500, P = 0.017)、白蛋白(OR = 0.889, P = 0.007)是ARDS发生的独立危险因素。发展组曲线下面积(AUC)为0.921 (95% CI: 0.869, 0.973),验证组为0.894 (95% CI: 0.809, 0.978)。标定曲线和决策曲线分析(DCA)表明,该图具有良好的预测价值和临床实用性。结论:我们的研究引入了一种整合6个独立危险因素的nomogram方法,有助于准确预测胃肠道穿孔术后患者发生ARDS的风险。
A Simple Nomogram for Predicting the Development of ARDS in Postoperative Patients with Gastrointestinal Perforation: A Single-Center Retrospective Study.
Background: Acute respiratory distress syndrome (ARDS) is a severe form of organ dysfunction and a common postoperative complication. This study aims to develop a predictive model for ARDS in postoperative patients with gastrointestinal perforation to facilitate early detection and effective prevention.
Methods: In this single-center retrospective study, clinical data were collected from postoperative patients with gastrointestinal perforation admitted to the ICU in Hebei Provincial People's Hospital from October 2017 to May 2024. Univariate analysis and multifactorial logistic regression analysis were used to determine the independent risk factors for developing ARDS. Nomograms were developed to show predictive models, and the discrimination, calibration, and clinical usefulness of the models were assessed using the C-index, calibration plots, and decision curve analysis (DCA).
Results: Two hundred patients were ultimately included for analysis. In the development cohort, 38 (27.1%) of 140 patients developed ARDS, and in the internal validation cohort, 13 (21.7%) of 60 patients developed ARDS. The multivariate logistic regression analysis revealed the site of perforation (OR = 0.164, P = 0.006), the duration of surgery (OR = 0.986, P = 0.008), BMI (OR = 1.197, P = 0.015), SOFA (OR = 1.443, P = 0.001), lactate (OR = 1.500, P = 0.017), and albumin (OR = 0.889, P = 0.007) as the independent risk factors for ARDS development. The area under the curve (AUC) was 0.921 (95% CI: 0.869, 0.973) for the development cohort and 0.894 (95% CI: 0.809, 0.978) for the validation cohort. The calibration curve and decision curve analysis (DCA) demonstrate that the nomogram possesses good predictive value and clinical practicability.
Conclusion: Our research introduced a nomogram that integrates six independent risk factors, facilitating the precise prediction of ARDS risk in postoperative patients following gastrointestinal perforation.
期刊介绍:
An international, peer-reviewed, open access, online journal that welcomes laboratory and clinical findings on the molecular basis, cell biology and pharmacology of inflammation.