Annali italiani di chirurgia · 2026
Analysis of Influencing Factors and Construction of Prediction Model for Delirium After Intraspinal Anesthesia in Elderly Patients Undergoing Femoral Neck Fracture Surgery.
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Liu Juan, Liu XiuFeng, Zhang Chen
Аннотация
AIM: To analyze the influencing factors of postoperative delirium (POD) after intraspinal anesthesia in elderly patients undergoing femoral neck fracture (FNF) surgery and to construct a prediction model for early identification of high-risk patients.
METHODS: This retrospective study included 407 elderly patients who underwent FNF surgery under spinal anesthesia from January 2020 to January 2024 as the modeling cohort; and another 82 patients who underwent similar surgery under spinal anesthesia between February 2024 and February 2025, according to the same inclusion and exclusion criteria, as an independent time-limited external validation cohort. Data were collected from the hospital's electronic medical records. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for POD. A nomogram prediction model was constructed and validated internally and externally.
RESULTS: The incidence of POD was 16.95% (69/407). Independent risk factors identified were age >80 years (odds ratio (OR) = 2.25, 95% CI: 1.25-4.05, p = 0.007), diabetes (OR = 1.91, 95% CI: 1.03-3.56, p = 0.041), preoperative hemoglobin <90 g/L (OR = 2.11, 95% CI: 1.14-3.90, p = 0.017), preoperative albumin <30 g/L (OR = 3.76, 95% CI: 1.95-7.25, p < 0.001), preoperative waiting time ≥3 days (OR = 2.62, 95% CI: 1.40-4.90, p = 0.003), American Society of Anesthesiologists (ASA) grade ≥III (OR = 2.12, 95% CI: 1.08-4.17, p = 0.029), postoperative hypoxemia (OR = 2.22, 95% CI: 1.22-4.05, p = 0.009), and postoperative visual analog scale (VAS) score ≥4 (OR = 2.55, 95% CI: 1.39-4.68, p = 0.002). The nomogram exhibited strong discriminative ability (area under the curve (AUC) = 0.79 for internal, 0.85 for external validation) and satisfactory calibration (Hosmer-Lemeshow p > 0.05).
CONCLUSIONS: This study identified independent risk factors for POD after intraspinal anesthesia in elderly FNF patients and established a nomogram with excellent predictive ability, offering a reliable tool for early detection of high-risk cases and facilitating implementation of targeted preventive measures.
METHODS: This retrospective study included 407 elderly patients who underwent FNF surgery under spinal anesthesia from January 2020 to January 2024 as the modeling cohort; and another 82 patients who underwent similar surgery under spinal anesthesia between February 2024 and February 2025, according to the same inclusion and exclusion criteria, as an independent time-limited external validation cohort. Data were collected from the hospital's electronic medical records. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for POD. A nomogram prediction model was constructed and validated internally and externally.
RESULTS: The incidence of POD was 16.95% (69/407). Independent risk factors identified were age >80 years (odds ratio (OR) = 2.25, 95% CI: 1.25-4.05, p = 0.007), diabetes (OR = 1.91, 95% CI: 1.03-3.56, p = 0.041), preoperative hemoglobin <90 g/L (OR = 2.11, 95% CI: 1.14-3.90, p = 0.017), preoperative albumin <30 g/L (OR = 3.76, 95% CI: 1.95-7.25, p < 0.001), preoperative waiting time ≥3 days (OR = 2.62, 95% CI: 1.40-4.90, p = 0.003), American Society of Anesthesiologists (ASA) grade ≥III (OR = 2.12, 95% CI: 1.08-4.17, p = 0.029), postoperative hypoxemia (OR = 2.22, 95% CI: 1.22-4.05, p = 0.009), and postoperative visual analog scale (VAS) score ≥4 (OR = 2.55, 95% CI: 1.39-4.68, p = 0.002). The nomogram exhibited strong discriminative ability (area under the curve (AUC) = 0.79 for internal, 0.85 for external validation) and satisfactory calibration (Hosmer-Lemeshow p > 0.05).
CONCLUSIONS: This study identified independent risk factors for POD after intraspinal anesthesia in elderly FNF patients and established a nomogram with excellent predictive ability, offering a reliable tool for early detection of high-risk cases and facilitating implementation of targeted preventive measures.