Construction and validation of a predictive model for supportive care needs within 24 hours after surgical anesthesia recovery in breast cancer patients
- VernacularTitle:乳腺癌患者手术麻醉苏醒后24 h内支持性照护需求预测模型的构建与验证
- Author:
Wuhui ZHANG
1
;
Yaya XU
;
Xiumei LYU
;
Qian ZHANG
Author Information
- Keywords: breast cancer; perioperative management; supportive care; predictive model; anesthesia recovery; medical economics; symptom burden; quality of recovery
- From: Journal of Clinical Medicine in Practice 2025;29(15):52-57
- CountryChina
- Language:Chinese
- Abstract: Objective To construct and validate a precise predictive model for supportive care needs within 24 hours after surgical anesthesia recovery in breast cancer patients.Methods A retro-spective analysis was conducted on data of 156 breast cancer patients who underwent surgical treat-ment in the hospital from June 2022 to June 2024.Based on their supportive care needs within 24 hours after surgical anesthesia recovery,the patients were divided into no and low demand group(n=41)and moderate and high demand group(n=115).Clinical data of the two groups were compared using one-way analysis of variance.Binary Logistic regression analysis was employed to identify fac-tors influencing supportive care needs within 24 hours after surgical anesthesia recovery in breast cancer patients,and a predictive model was constructed accordingly.Results Binary Logistic re-gression analysis revealed that sources of medical expenses(non-urban medical insurance),occupa-tion(worker),primary caregiver(spouse),the M.D.Anderson Symptom Inventory(MDASI)score,and Quality of Recovery(QoR)score were all influencing factors for supportive care needs within 24 hours after surgical anesthesia recovery in breast cancer patients(P＜0.05).Receiver op-erating characteristic(ROC)curve analysis showed that the area under the curve(AUC)for predic-ting supportive care needs within 24 hours after surgical anesthesia recovery in breast cancer patients was 0.635 for sources of medical expenses,0.723 for occupation,0.618 for primary caregiver,0.742 for MDASI score,and 0.749 for QoR score,respectively.The AUC of the predictive model for sup-portive care needs within 24 hours after surgical anesthesia recovery in breast cancer patients was 0.965,with a sensitivity of 93.0％and a specificity of 90.2％.Internal validation of the model using the Bootstrap method with B=1,000 self-sampling times demonstrated an overall predictive accuracy of 88.5％,indicating good predictive performance.Conclusion Sources of medical ex-penses(non-urban medical insurance),occupation(worker),primary caregiver(spouse),MDASI score,and QoR score are all influencing factors for supportive care needs within 24 hours after surgi-cal anesthesia recovery in breast cancer patients.The predictive model constructed based on these factors exhibits good predictive value and can serve as a quantitative decision-making tool for optimi-zing postoperative nursing pathways.
