Centre for Health Policy and Management, Trinity College Dublin, 3-4 Foster PlaceDublin 2, Dublin, Ireland.
The Irish Longitudinal Study On Ageing, Trinity College Dublin, Dublin, Ireland.
BMC Geriatr. 2022 Jun 21;22(1):510. doi: 10.1186/s12877-022-03196-z.
We aimed to replicate existing international (US and UK) mortality indices using Irish data. We developed and validated a four-year mortality index for adults aged 50 + in Ireland and compared performance with these international indices. We then extended this model by including additional predictors (self-report and healthcare utilization) and compared its performance to our replication model.
Eight thousand one hundred seventy-four participants in The Irish Longitudinal Study on Ageing were split for development (n = 4,121) and validation (n = 4,053). Six baseline predictor categories were examined (67 variables total): demographics; cardiovascular-related illness; non-cardiovascular illness; health and lifestyle variables; functional variables; self-report (wellbeing and social connectedness) and healthcare utilization. We identified variables independently associated with four-year mortality in the development cohort and attached these variables a weight according to strength of association. We summed the weights to calculate a single index score for each participant and evaluated predicted accuracy in the validation cohort.
Our final 14-predictor (extended) model assigned risk points for: male (1pt); age (65-69: 2pts; 70-74: 4 pts; 75-79: 4pts; 80-84: 6pts; 85 + : 7pts); heart attack (1pt); cancer (3pts); smoked past age 30 (2pts); difficulty walking 100 m (2pts); difficulty using the toilet (3pts); difficulty lifting 10lbs (1pts); poor self-reported health (1pt); and hospital admission in previous year (1pt). Index discrimination was strong (ROC area = 0.78).
Our index is predictive of four-year mortality in community-dwelling older Irish adults. Comparisons with the international indices show that our 12-predictor (replication) model performed well and suggests that generalisability is high. Our 14-predictor (extended) model showed modest improvements compared to the 12-predictor model.
我们旨在使用爱尔兰数据复制现有的国际（美国和英国）死亡率指数。我们为爱尔兰 50 岁及以上的成年人开发并验证了一个四年死亡率指数，并将其与这些国际指数进行了比较。然后，我们通过纳入其他预测因素（自我报告和医疗保健利用情况）扩展了该模型，并将其性能与我们的复制模型进行了比较。
8174 名参与爱尔兰老龄化纵向研究的参与者被分为开发组（n=4121）和验证组（n=4053）。共检查了六个基线预测因素类别（总计 67 个变量）：人口统计学；心血管相关疾病；非心血管疾病；健康和生活方式变量；功能变量；自我报告（幸福感和社交联系）和医疗保健利用情况。我们确定了与开发队列中四年死亡率独立相关的变量，并根据关联强度为这些变量分配权重。我们为每个参与者计算了一个单一的指数得分，并在验证队列中评估了预测准确性。
我们的最终 14 个预测因素（扩展）模型为以下情况分配风险点：男性（1 分）；年龄（65-69 岁：2 分；70-74 岁：4 分；75-79 岁：4 分；80-84 岁：6 分；85 岁及以上：7 分）；心脏病发作（1 分）；癌症（3 分）；30 岁后吸烟（2 分）；100 米行走困难（2 分）；使用厕所困难（3 分）；提举 10 磅重物困难（1 分）；自我报告健康状况差（1 分）；以及前一年住院（1 分）。指数的区分度很强（ROC 面积=0.78）。
我们的指数可以预测爱尔兰社区居住的老年成年人的四年死亡率。与国际指数的比较表明，我们的 12 个预测因素（复制）模型表现良好，表明可推广性较高。与 12 个预测因素模型相比，我们的 14 个预测因素（扩展）模型略有改进。
