Kyoto University Health Service, Yoshida-Honmachi, Sakyo-ku, Kyoto, 606-8501, Japan.
Department of Data Science, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan.
Environ Health Prev Med. 2021 Apr 10;26(1):45. doi: 10.1186/s12199-021-00968-8.
Predicting adverse health events and implementing preventative measures are a necessary challenge. It is important for healthcare planners and policymakers to allocate the limited resource to high-risk persons. Prediction is also important for older individuals, their family members, and clinicians to prepare mentally and financially. The aim of this study is to develop a prediction model for within 11-year dependent status requiring long-term nursing care or death in older adults for each sex.
We carried out age-specified cohort study of community dwellers in Nisshin City, Japan. The older adults aged 64 years who underwent medical check-up between 1996 and 2000 were included in the study. The primary outcome was the incidence of the psychophysically dependent status or death or by the end of the year of age 75 years. Univariable logistic regression analyses were performed to assess the associations between candidate predictors and the outcome. Using the variables with p-values less than 0.1, multivariable logistic regression analyses were then performed with backward stepwise elimination to determine the final predictors for the model.
Of the 1525 female participants at baseline, 105 had an incidence of the study outcome. The final prediction model consisted of 15 variables, and the c-statistics for predicting the outcome was 0.763 (95% confidence interval [CI] 0.714-0.813). Of the 1548 male participants at baseline, 211 had incidence of the study outcome. The final prediction model consisted of 16 variables, and the c-statistics for predicting the outcome was 0.735 (95% CI 0.699-0.771).
We developed a prediction model for older adults to forecast 11-year incidence of dependent status requiring nursing care or death in each sex. The predictability was fair, but we could not evaluate the external validity of this model. It could be of some help for healthcare planners, policy makers, clinicians, older individuals, and their family members to weigh the priority of support.
预测不良健康事件并采取预防措施是一项必要的挑战。对于医疗保健规划者和政策制定者来说，将有限的资源分配给高风险人群非常重要。预测对于老年人、他们的家庭成员和临床医生来说也是重要的，以便在心理和财务上做好准备。本研究的目的是为每一种性别建立一个预测模型，以预测在 11 年内需要长期护理或死亡的依赖状态。
我们进行了一项特定年龄的队列研究，研究对象为日本日进市的社区居民。纳入研究的是在 1996 年至 2000 年期间接受体检的 64 岁以上老年人。主要结果是出现精神依赖状态或死亡或在 75 岁之前的那一年结束。采用单变量逻辑回归分析评估候选预测因子与结果之间的关联。然后，使用 p 值小于 0.1 的变量，采用向后逐步消除法进行多变量逻辑回归分析，以确定模型的最终预测因子。
在基线时，1525 名女性参与者中有 105 人发生了研究结果。最终的预测模型包括 15 个变量，预测结果的 c 统计量为 0.763（95%置信区间 [CI] 0.714-0.813）。在基线时，1548 名男性参与者中有 211 人发生了研究结果。最终的预测模型包括 16 个变量，预测结果的 c 统计量为 0.735（95%置信区间 [CI] 0.699-0.771）。
我们为老年人开发了一个预测模型，以预测每一种性别 11 年内需要护理的依赖状态或死亡的发生率。预测的准确性是中等的，但我们无法评估该模型的外部有效性。这可能对医疗保健规划者、政策制定者、临床医生、老年人及其家庭成员权衡支持的优先级有所帮助。
