Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction
Abstract To develop and validate a nomogram model for discriminating simple intestinal obstruction and strangulated intestinal obstruction, thus providing objective evidence for clinical decision-making. Following pre-established inclusion and exclusion criteria, a retrospective analysis was conduct...
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-82131-1 |
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| author | Yanjing Zhu Qiangqiang Wang Lvhao Cao Tongyuan Zhang Jiawei Chang Xingyu Wang |
| author_facet | Yanjing Zhu Qiangqiang Wang Lvhao Cao Tongyuan Zhang Jiawei Chang Xingyu Wang |
| author_sort | Yanjing Zhu |
| collection | DOAJ |
| description | Abstract To develop and validate a nomogram model for discriminating simple intestinal obstruction and strangulated intestinal obstruction, thus providing objective evidence for clinical decision-making. Following pre-established inclusion and exclusion criteria, a retrospective analysis was conducted on the clinical data of 560 patients diagnosed with intestinal obstruction who were admitted to the Emergency Surgery Department of the First Affiliated Hospital of Anhui Medical University between January 1, 2020, and December 31, 2022. The data was subsequently split into a training cohort (n = 393) and a validation cohort (n = 167) using a 7:3 ratio. To identify independent risk and protective factors associated with strangulated intestinal obstruction, a multivariate logistic regression analysis was employed. Based on the identified factors, a nomogram prediction model was constructed. The model’s discriminatory ability was assessed using the receiver operating characteristic (ROC) curve, the area under the curve (AUC), and the corrected C-index. The Hosmer-Lemeshow test was utilized to evaluate the model’s goodness of fit in both the training and validation cohorts. Calibration curves were generated to assess the model’s accuracy in predicting the probability of strangulated intestinal obstruction. Finally, decision curve analysis (DCA) was performed to evaluate the model’s potential clinical utility. Multivariate logistic regression analysis identified neutrophil percentage, peritoneal irritation sign, and abdominal fluid as independent risk factors for strangulated intestinal obstruction, while albumin emerged as an independent protective factor. These factors were incorporated into the nomogram, demonstrating high discrimination (AUC of 0.842[95%CI: 0.787–0.897] in the training set and 0.839 [95%CI: 0.742–0.937] in the validation set) and good calibration. The corrected C-index further supported the model’s performance in the training (0.833) and validation (0.813) cohorts. The Hosmer-Lemeshow test results (p = 0.759 and p = 0.505, respectively) indicated a good model fit in both cohorts. Calibration curves confirmed the close agreement between the nomogram predictions and actual observations. Finally, DCA corroborated the model’s net clinical benefit. The comprehensive nomogram developed in this study emerged as a promising and convenient tool for evaluating the risk of strangulated intestinal obstruction, thereby aiding clinicians in screening the high-risk population. |
| format | Article |
| id | doaj-art-2ef8bc54914340fea0a244e231dcb756 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-2ef8bc54914340fea0a244e231dcb7562025-08-20T02:43:32ZengNature PortfolioScientific Reports2045-23222024-12-0114111010.1038/s41598-024-82131-1Development and validation of a nomogram model to predict the risk of strangulated intestinal obstructionYanjing Zhu0Qiangqiang Wang1Lvhao Cao2Tongyuan Zhang3Jiawei Chang4Xingyu Wang5Department of Emergency Surgery, the First Affiliated Hospital of Anhui Medical UniversityDepartment of Emergency Surgery, the First Affiliated Hospital of Anhui Medical UniversityDepartment of Emergency Surgery, the First Affiliated Hospital of Anhui Medical UniversityDepartment of Emergency Surgery, the First Affiliated Hospital of Anhui Medical UniversityDepartment of Emergency Surgery, the First Affiliated Hospital of Anhui Medical UniversityDepartment of Emergency Surgery, the First Affiliated Hospital of Anhui Medical UniversityAbstract To develop and validate a nomogram model for discriminating simple intestinal obstruction and strangulated intestinal obstruction, thus providing objective evidence for clinical decision-making. Following pre-established inclusion and exclusion criteria, a retrospective analysis was conducted on the clinical data of 560 patients diagnosed with intestinal obstruction who were admitted to the Emergency Surgery Department of the First Affiliated Hospital of Anhui Medical University between January 1, 2020, and December 31, 2022. The data was subsequently split into a training cohort (n = 393) and a validation cohort (n = 167) using a 7:3 ratio. To identify independent risk and protective factors associated with strangulated intestinal obstruction, a multivariate logistic regression analysis was employed. Based on the identified factors, a nomogram prediction model was constructed. The model’s discriminatory ability was assessed using the receiver operating characteristic (ROC) curve, the area under the curve (AUC), and the corrected C-index. The Hosmer-Lemeshow test was utilized to evaluate the model’s goodness of fit in both the training and validation cohorts. Calibration curves were generated to assess the model’s accuracy in predicting the probability of strangulated intestinal obstruction. Finally, decision curve analysis (DCA) was performed to evaluate the model’s potential clinical utility. Multivariate logistic regression analysis identified neutrophil percentage, peritoneal irritation sign, and abdominal fluid as independent risk factors for strangulated intestinal obstruction, while albumin emerged as an independent protective factor. These factors were incorporated into the nomogram, demonstrating high discrimination (AUC of 0.842[95%CI: 0.787–0.897] in the training set and 0.839 [95%CI: 0.742–0.937] in the validation set) and good calibration. The corrected C-index further supported the model’s performance in the training (0.833) and validation (0.813) cohorts. The Hosmer-Lemeshow test results (p = 0.759 and p = 0.505, respectively) indicated a good model fit in both cohorts. Calibration curves confirmed the close agreement between the nomogram predictions and actual observations. Finally, DCA corroborated the model’s net clinical benefit. The comprehensive nomogram developed in this study emerged as a promising and convenient tool for evaluating the risk of strangulated intestinal obstruction, thereby aiding clinicians in screening the high-risk population.https://doi.org/10.1038/s41598-024-82131-1Simple intestinal obstructionStrangulated intestinal obstructionPrediction modelNomogram |
| spellingShingle | Yanjing Zhu Qiangqiang Wang Lvhao Cao Tongyuan Zhang Jiawei Chang Xingyu Wang Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction Scientific Reports Simple intestinal obstruction Strangulated intestinal obstruction Prediction model Nomogram |
| title | Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction |
| title_full | Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction |
| title_fullStr | Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction |
| title_full_unstemmed | Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction |
| title_short | Development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction |
| title_sort | development and validation of a nomogram model to predict the risk of strangulated intestinal obstruction |
| topic | Simple intestinal obstruction Strangulated intestinal obstruction Prediction model Nomogram |
| url | https://doi.org/10.1038/s41598-024-82131-1 |
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