Key result
A novel eight-variable nomogram accurately predicts in-hospital mortality with an AUC of ~0.89.
Why the study?
Few studies have explored risk factors for in-hospital death or developed mortality prediction models for patients with nonhip femoral fractures in the ICU.
Does a newly developed nomogram improve the prediction of in-hospital mortality compared to GCS and SAPSII scoring systems in ICU patients with nonhip femoral fractures?
Observational (n=1,334)
No
Does a newly developed nomogram improve the prediction of in-hospital mortality compared to GCS and SAPSII scoring systems in ICU patients with nonhip femoral fractures?
Effect estimate: AUC 0.891 (95% CI 0.861-0.922)
A newly developed nomogram provides better prediction of in-hospital mortality than standard GCS and SAPSII scores for ICU patients with nonhip femoral fractures.
May aid ICU risk stratification for nonhip femoral fractures; leaves open prospective validation of any prediction model.
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.
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Xing et al. (2023) conducted an observational in Nonhip femoral fractures (n=1,334). Nomogram incorporating clinical and laboratory risk factors vs. GCS and SAPSII scoring systems was evaluated on In-hospital mortality prediction (Model discrimination/AUC in training set) (AUC 0.891, 95% CI 0.861-0.922). A developed nomogram incorporating heart rate, temperature, RDW, BUN, GCS, SAPSII, CCI, and cerebrovascular disease accurately predicted in-hospital mortality (training AUC 0.891, validation AUC 0.830).
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