Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures
Abstract Background The incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patien...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-11-01
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| Series: | European Journal of Medical Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40001-023-01515-7 |
| _version_ | 1797453489017716736 |
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| author | Zhibin Xing Yiwen Xu Yuxuan Wu Xiaochen Fu Pengfei Shen Wenqiang Che Jing Wang |
| author_facet | Zhibin Xing Yiwen Xu Yuxuan Wu Xiaochen Fu Pengfei Shen Wenqiang Che Jing Wang |
| author_sort | Zhibin Xing |
| collection | DOAJ |
| description | Abstract Background The incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patient group, hoping to help clinicians improve the prognosis of patients. Methods This is a retrospective study based on the data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to screen risk factors. The receiver operating characteristic (ROC) curve was drawn, and the areas under the curve (AUC), net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. The consistency between the actual probability and the predicted probability was assessed by the calibration curve and Hosmer–Lemeshow goodness of fit test (HL test). Decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit. Results The LASSO regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, Glasgow Coma Scale (GCS), Simplified Acute Physiology Score II (SAPSII), Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The AUC, IDI and NRI of our model in the training set and validation set were better than those of the GCS and SAPSII scoring systems. The calibration curve and HL test results showed that our model prediction results were in good agreement with the actual results (P = 0.833 for the HL test of the training set and P = 0.767 for the HL test of the validation set). DCA showed that our model had a better clinical net benefit than the GCS and SAPSII scoring systems. Conclusion In this study, the independent risk factors for in-hospital death in patients with nonhip femoral fractures were determined, and a prediction model was constructed. The results of this study may help to improve the clinical prognosis of patients with nonhip femoral fractures. |
| first_indexed | 2024-03-09T15:23:34Z |
| format | Article |
| id | doaj.art-9507491dc04b431cbe1b85a19ebdbf15 |
| institution | Directory Open Access Journal |
| issn | 2047-783X |
| language | English |
| last_indexed | 2024-03-09T15:23:34Z |
| publishDate | 2023-11-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj.art-9507491dc04b431cbe1b85a19ebdbf152023-11-26T12:42:03ZengBMCEuropean Journal of Medical Research2047-783X2023-11-0128111010.1186/s40001-023-01515-7Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fracturesZhibin Xing0Yiwen Xu1Yuxuan Wu2Xiaochen Fu3Pengfei Shen4Wenqiang Che5Jing Wang6The First Affiliated Hospital of Jinan UniversityThe First Affiliated Hospital of Jinan UniversityThe First Affiliated Hospital of Jinan UniversityThe First Affiliated Hospital of Jinan UniversityThe First Affiliated Hospital of Jinan UniversityDepartment of Clinical Research, The First Affiliated Hospital of Jinan UniversityThe First Affiliated Hospital of Jinan UniversityAbstract Background The incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patient group, hoping to help clinicians improve the prognosis of patients. Methods This is a retrospective study based on the data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to screen risk factors. The receiver operating characteristic (ROC) curve was drawn, and the areas under the curve (AUC), net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. The consistency between the actual probability and the predicted probability was assessed by the calibration curve and Hosmer–Lemeshow goodness of fit test (HL test). Decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit. Results The LASSO regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, Glasgow Coma Scale (GCS), Simplified Acute Physiology Score II (SAPSII), Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The AUC, IDI and NRI of our model in the training set and validation set were better than those of the GCS and SAPSII scoring systems. The calibration curve and HL test results showed that our model prediction results were in good agreement with the actual results (P = 0.833 for the HL test of the training set and P = 0.767 for the HL test of the validation set). DCA showed that our model had a better clinical net benefit than the GCS and SAPSII scoring systems. Conclusion In this study, the independent risk factors for in-hospital death in patients with nonhip femoral fractures were determined, and a prediction model was constructed. The results of this study may help to improve the clinical prognosis of patients with nonhip femoral fractures.https://doi.org/10.1186/s40001-023-01515-7Nonhip femoral fractureIntensive care unitIn-hospital mortalityNomogram |
| spellingShingle | Zhibin Xing Yiwen Xu Yuxuan Wu Xiaochen Fu Pengfei Shen Wenqiang Che Jing Wang Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures European Journal of Medical Research Nonhip femoral fracture Intensive care unit In-hospital mortality Nomogram |
| title | Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures |
| title_full | Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures |
| title_fullStr | Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures |
| title_full_unstemmed | Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures |
| title_short | Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures |
| title_sort | development and validation of a nomogram for predicting in hospital mortality in patients with nonhip femoral fractures |
| topic | Nonhip femoral fracture Intensive care unit In-hospital mortality Nomogram |
| url | https://doi.org/10.1186/s40001-023-01515-7 |
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