Risk factors analysis and prediction nomogram establishment of acute kidney injury in hip fracture patients with severe underlying diseases
10.3760/cma.j.cn121113-20230326-00163
- VernacularTitle:合并严重基础疾病的髋部骨折患者急性肾损伤风险因素分析及预测模型建立
- Author:
Chen LI
1
;
Lan JIA
;
Jiacheng ZANG
;
Shujun YU
;
Xueqing BI
;
Jia MENG
;
Jie LIU
;
Jingbo WANG
;
Yinguang ZHANG
Author Information
1. 天津市天津医院创伤髋关节科，天津 300211
- Keywords:
Hip fractures;
Acute kidney injury;
Risk factors;
Intensive care units;
Predictive nomogram
- From:
Chinese Journal of Orthopaedics
2023;43(16):1094-1103
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the risk factors of acute kidney injury (AKI) in hip fracture patients with serious underlying diseases and establish a prediction nomogram.Methods:Clinical information of hip fracture patients admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center (BIDMC) was analyzed using the Medical Information Mart for Intensive Care (MIMIC)-IV. Patient comorbidities, disease scores, vital signs and laboratory tests, surgical modalities, invasive procedures, and drug use were recorded. According to the diagnostic criteria of AKI in the Kidney Disease Improving Global Outcome (KDIGO) guideline, the enrolled patients were randomly divided into training set and validation set. Based on logistic regression analysis, least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was used to analyze the risk factors of AKI after admission, and the corresponding prediction model was calculated.Results:A total of 474 patients were enrolled, including 331 in the training set and 143 in the validation set. According to the diagnostic criteria of AKI of KDIGO guidelines, the patients were divided into AKI group (159 cases) and non-AKI group (172 cases). Univariate analysis showed that age ( t=2.61, P=0.009), coronary heart disease (χ 2=2.08, P=0.038), heart failure (χ 2=2.60, P=0.009), hemoglobin ( t=1.89, P=0.059), platelets ( t=1.81, P=0.070), urea nitrogen ( t=2.83, P=0.005), blood creatinine ( t=3.65, P<0.001), blood sodium ( t=2.55, P=0.011), blood glucose ( t=2.52, P=0.012), anion gap ( t=3.44, P=0.001), diastolic blood pressure ( t=2.72, P=0.007), mean arterial pressure ( t=2.16, P=0.031), SOFA score ( t=3.69, P<0.001), simplified acute physiological function score II (SAPSII) score ( t=2.95, P=0.003), as well as furosemide (χ 2=2.03, P=0.042), vancomycin (χ 2=1.70, P=0.089), vasoactive medications (χ 2=3.74, P<0.001) and use of invasive mechanical ventilation (χ 2=4.81, P<0.001) were risk factors associated with the development of AKI in hip fracture patients. Multivariate logistic regression analysis showed that age ( OR=1.03, P<0.001), coronary heart disease ( OR=2.05, P=0.069), hemoglobin ( OR=0.88, P=0.050), blood creatinine ( OR=1.37, P=0.009), blood sodium ( OR=1.07, P=0.026), anion gap ( OR=1.09, P=0.028) and vasoactive medications ( OR=3.83, P=0.018) and the use of invasive mechanical ventilation ( OR=6.56, P<0.001) were independent predictors of the development of AKI in hip fracture patients with serious underlying diseases. The area under the curve of the nomogram prediction model constructed by the above 8 predictors was 0.789, and the calibration curve of the nomogram was close to the ideal diagonal. Decision curve analysis showed that the net benefit of the model was significant. Conclusion:The incidence of AKI is high in hip fracture patients with serious underlying diseases. Age, coronary heart disease, hemoglobin, serum creatinine, serum sodium, anion gap, vasoactive drugs, and invasive mechanical ventilation can predict the occurrence of AKI to a certain extent. Combined with the risk factors, the construction of the corresponding prediction model can predict and manage the diagnosis and treatment of AKI in patients with hip fracture complicated with severe underlying diseases.
