Bruyère Research Institute (Hsu, Manuel, Tanuseputro); Clinical Epidemiology Program (Hsu, Manuel, Bennett, Taljaard, Beach, Sequeira, Kobewka, Tanuseputro), Ottawa Hospital Research Institute; ICES uOttawa (Chalifoux, Manuel, Spruin, Talarico, Tanuseputro); School of Epidemiology and Public Health (Taljaard, Manuel), Division of Palliative Care (Tanuseputro) and Department of Medicine (Kobewka), University of Ottawa, Ottawa, Ont.; Department of Clinical Epidemiology and Biostatistics (Costa), McMaster University, Hamilton, Ont.; ICES Central (Bronskill); Women's College Research Institute (Bronskill), Women's College Hospital, Toronto, Ont.
CMAJ. 2021 Jul 5;193(26):E997-E1005. doi: 10.1503/cmaj.200022.
Prognostication tools that report personalized mortality risk and survival could improve discussions about end-of-life and advance care planning. We sought to develop and validate a mortality risk model for older adults with diverse care needs in home care using self-reportable information - the Risk Evaluation for Support: Predictions for Elder-Life in the Community Tool (RESPECT).
Using a derivation cohort that comprised adults living in Ontario, Canada, aged 50 years and older with at least 1 Resident Assessment Instrument for Home Care (RAI-HC) record between Jan. 1, 2007, and Dec. 31, 2012, we developed a mortality risk model. The primary outcome was mortality 6 months after a RAI-HC assessment. We used proportional hazards regression with robust standard errors to account for clustering by the individual. We validated this algorithm for a second cohort of users of home care who were assessed between Jan. 1 and Dec. 31, 2013. We used Kaplan-Meier survival curves to estimate the observed risk of death at 6 months for assessment of calibration and median survival. We constructed 61 risk groups based on incremental increases in the estimated median survival of about 3 weeks among adults at high risk and 3 months among adults at lower risk.
The derivation and validation cohorts included 435 009 and 139 388 adults, respectively. We identified a total of 122 823 deaths within 6 months of a RAI-HC assessment in the derivation cohort. The mean predicted 6-month mortality risk was 10.8% (95% confidence interval [CI] 10.7%-10.8%) and ranged from 1.54% (95% CI 1.53%-1.54%) in the lowest to 98.1% (95% CI 98.1%-98.2%) in the highest risk group. Estimated median survival spanned from 28 days (11 to 84 d at the 25th and 75th percentiles) in the highest risk group to over 8 years (1925 to 3420 d) in the lowest risk group. The algorithm had a c-statistic of 0.753 (95% CI 0.750-0.756) in our validation cohort.
The RESPECT mortality risk prediction tool that makes use of readily available information can improve the identification of palliative and end-of-life care needs in a diverse older adult population receiving home care.
能够报告个性化死亡率和生存概率的预后工具可以改善有关临终和预先护理计划的讨论。我们试图使用可自我报告的信息（即 RESPECT 工具，即支持评估：社区老年人预后预测工具）为接受家庭护理的具有不同护理需求的老年人开发和验证一种死亡率风险模型。
使用包含 2007 年 1 月 1 日至 2012 年 12 月 31 日期间至少有 1 份居家护理居民评估工具（RAI-HC）记录的、居住在加拿大安大略省的 50 岁及以上成年人的推导队列，我们开发了一种死亡率风险模型。主要结局是在 RAI-HC 评估后 6 个月的死亡率。我们使用比例风险回归和稳健标准误差来考虑个体的聚类。我们使用 2013 年 1 月 1 日至 12 月 31 日接受家庭护理评估的第二组用户验证了该算法。我们使用 Kaplan-Meier 生存曲线来估计评估的 6 个月时的死亡观察风险和中位生存。我们基于高风险人群中约 3 周和低风险人群中约 3 个月的估计中位生存递增，构建了 61 个风险组。
推导队列和验证队列分别包括 435009 名和 139388 名成年人。在推导队列中，在 RAI-HC 评估后 6 个月内，我们共确定了 122823 例死亡。6 个月的预测死亡率风险平均为 10.8%（95%置信区间[CI] 10.7%-10.8%），范围从最低风险组的 1.54%（95%CI 1.53%-1.54%）到最高风险组的 98.1%（95%CI 98.1%-98.2%）。估计的中位生存时间从最高风险组的 28 天（第 25 和第 75 百分位为 11 至 84 天）到最低风险组的 8 年以上（1925 至 3420 天）。该算法在验证队列中的 C 统计量为 0.753（95%CI 0.750-0.756）。
使用现成信息的 RESPECT 死亡率预测工具可以改善对接受家庭护理的不同老年人群体的姑息治疗和临终关怀需求的识别。
