Key result
A nomogram incorporating heart rate, temperature, RDW, BUN, GCS, SAPSII, CCI, and cerebrovascular disease accurately predicted in-hospital mortality in ICU patients with nonhip femoral fractures (training set AUC 0.891).
Why the study?
Does a novel nomogram better predict in-hospital mortality compared to GCS and SAPSII in ICU patients with nonhip femoral fractures?
Observational (n=1,334)
No
Does a novel nomogram better predict in-hospital mortality compared to GCS and SAPSII 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.
Prediction model for ICU nonhip femoral fracture mortality is hypothesis-generating; external validation required before any clinical consideration.
Background The incidence of nonhip femoral fractures is gradually increasing, but no 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 The ROC curve was drawn, and the AUC, NRI and 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 HL test. 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 least absolute shrinkage and selection operator (LASSO) regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, GCS, SA PSII, Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The areas under the curve (AUC), integrated discrimination improvement (IDI) and net reclassification index (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). Decision curve analysis (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). Clinical and laboratory risk factors (HR, temperature, RDW, BUN, GCS, SAPSII, CCI, cerebrovascular disease) was evaluated on In-hospital mortality prediction model discrimination (AUC in training set) (AUC 0.891, 95% CI 0.861-0.922). A nomogram incorporating heart rate, temperature, RDW, BUN, GCS, SAPSII, CCI, and cerebrovascular disease accurately predicted in-hospital mortality in ICU patients with nonhip femoral fractures (training set AUC 0.891).
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