Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland.
Graduate School for Health Sciences, University of Bern, Bern, Switzerland.
PLoS One. 2022 Aug 5;17(8):e0271923. doi: 10.1371/journal.pone.0271923. eCollection 2022.
Multimorbidity is highly prevalent among older adults and associated with a high mortality. Prediction of mortality in multimorbid people would be clinically useful but there is no mortality risk index designed for this population. Our objective was therefore to develop and internally validate a 1-year mortality prognostic index for older multimorbid adults.
We analysed data of the OPERAM cohort study in Bern, Switzerland, including 822 adults aged 70 years or more with multimorbidity (3 or more chronic medical conditions) and polypharmacy (use of 5 drugs or more for >30 days). Time to all-cause mortality was assessed up to 1 year of follow-up. We performed a parametric Weibull regression model with backward stepwise selection to identify mortality risk predictors. The model was internally validated and optimism corrected using bootstrapping techniques. We derived a point-based risk score from the regression coefficients. Calibration and discrimination were assessed by the calibration slope and C statistic.
805 participants were included in the analysis. During 1-year of follow-up, 158 participants (20%) had died. Age, Charlson-Comorbidity-Index, number of drugs, body mass index, number of hospitalizations, Barthel-Index (functional impairment), and nursing home residency were predictors of 1-year mortality in a multivariable model. Using these variables, the 1-year probability of dying could be predicted with an optimism-corrected C statistic of 0.70. The optimism-corrected calibration slope was 0.93. Based on the derived point-based risk score to predict mortality risk, 7% of the patients classified at low-risk of mortality, 19% at moderate-risk, and 37% at high-risk died after one year of follow-up. A simpler mortality score, without the Charlson-Comorbidity-Index and Barthel-Index, showed reduced discriminative power (optimism-corrected C statistic: 0.59) compared to the full score.
We developed and internally validated a mortality risk index including for the first-time specific predictors for multimorbid adults. This new 1-year mortality prediction point-based score allowed to classify multimorbid older patients into three categories of increasing risk of mortality. Further validation of the score among various populations of multimorbid patients is needed before its implementation into practice.
多种疾病在老年人中非常普遍，与高死亡率相关。预测多种疾病患者的死亡率在临床上可能很有用，但目前尚无为此人群设计的死亡率风险指数。因此，我们的目标是开发并内部验证一种针对老年多种疾病患者的 1 年死亡率预测指数。
我们分析了瑞士伯尔尼 OPERAM 队列研究的数据，该研究纳入了 822 名 70 岁或以上患有多种疾病（3 种或以上慢性疾病）和多种药物治疗（使用 5 种或更多药物超过 30 天）的成年人。通过 1 年的随访评估全因死亡率。我们使用向后逐步选择的参数 Weibull 回归模型来确定死亡率风险预测因子。使用 bootstrap 技术对模型进行内部验证和校正。我们从回归系数中得出一个基于点的风险评分。通过校准斜率和 C 统计量评估校准和区分能力。
在 1 年的随访期间，有 158 名（20%）参与者死亡。年龄、Charlson 合并症指数、药物种类、体重指数、住院次数、Barthel 指数（功能障碍）和疗养院居住情况是多变量模型中 1 年死亡率的预测因素。使用这些变量，可以预测 1 年死亡率的概率，校正后 C 统计量为 0.70。校正后校准斜率为 0.93。基于预测死亡率风险的基于点的风险评分，7%的患者被归类为低死亡率风险，19%为中死亡率风险，37%为高死亡率风险，在 1 年随访后死亡。一个不包括 Charlson 合并症指数和 Barthel 指数的更简单的死亡率评分显示出降低的区分能力（校正后 C 统计量：0.59），与全评分相比。
我们开发并内部验证了一种死亡率风险指数，其中首次包括了针对多种疾病成年人的特定预测因子。这种新的 1 年死亡率预测基于点的评分允许将多种疾病的老年患者分为死亡率风险递增的三个类别。在将该评分应用于各种多种疾病患者人群之前，需要进一步验证。
