Wang Pan, Xiao Weisheng
Author Affiliations: Departments of Medical Oncology (Ms Wang) and Gastroenterology (Mr Xiao), The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang.
Cancer Nurs. 2025;48(3):e150-e155. doi: 10.1097/NCC.0000000000001290. Epub 2023 Nov 13.
Subsyndromal delirium (SSD) is a clinical manifestation between delirium and nondelirium. There is no established guideline for diagnosing SSD, with a few different tools used for diagnosis.
To construct and verify the risk prediction model for subdelirium syndrome in patients with advanced malignant tumors and explore its application value in risk prediction.
A total of 455 patients admitted to the Oncology Department in a tertiary grade A hospital in Hengyang City were recruited from December 2020 to May 2021. They were selected as the modeling group. The model was constructed by logistic regression. A total of 195 patients with advanced malignant tumors from June 2021 to July 2021 were selected to validate the developed model.
The predictors incorporated into the model were opioids (odds ratio [OR], 1.818), sleep disorders (OR, 1.783), daily living ability score (OR, 0.969), and pain (OR, 1.810). In the modeling group, the Hosmer-Lemeshow goodness-of-fit test was P = .113, the area under the receiver operating characteristic curve was 0.884, the sensitivity was 0.820, and the specificity was 0.893. In the validation group, the Hosmer-Lemeshow goodness-of-fit test P = .108, the area under the receiver operating characteristic curve was 0.843, the Yuden index was 0.670, the sensitivity was 0.804, and the specificity was 0.866.
This model has excellent precision in the risk prediction of subdelirium in patients with advanced malignant tumors.
The model we developed has a guiding significance for specialized tumor nurses to care for patients with advanced malignant tumors and improve their quality of life.
亚综合征谵妄(SSD)是介于谵妄和非谵妄之间的一种临床表现。目前尚无诊断SSD的既定指南,诊断时使用的工具也有所不同。
构建并验证晚期恶性肿瘤患者亚谵妄综合征的风险预测模型,并探讨其在风险预测中的应用价值。
选取2020年12月至2021年5月在衡阳市某三级甲等医院肿瘤科住院的455例患者作为建模组。采用逻辑回归构建模型。选取2021年6月至2021年7月的195例晚期恶性肿瘤患者对所构建的模型进行验证。
纳入模型的预测因素有阿片类药物(比值比[OR],1.818)、睡眠障碍(OR,1.783)、日常生活能力评分(OR,0.969)和疼痛(OR,1.810)。在建模组中,Hosmer-Lemeshow拟合优度检验P = 0.113,受试者工作特征曲线下面积为0.884,灵敏度为0.820,特异度为0.893。在验证组中,Hosmer-Lemeshow拟合优度检验P = 0.108,受试者工作特征曲线下面积为0.843,约登指数为0.670,灵敏度为0.804,特异度为0.866。
该模型在晚期恶性肿瘤患者亚谵妄风险预测中具有良好的精度。
我们开发的模型对肿瘤专科护士护理晚期恶性肿瘤患者及提高其生活质量具有指导意义。