Hebrew SeniorLife, The Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA.
Hebrew SeniorLife, The Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA; Connell School of Nursing, Boston College, Chestnut Hill, MA, USA.
J Am Med Dir Assoc. 2023 Sep;24(9):1405-1411. doi: 10.1016/j.jamda.2023.06.011. Epub 2023 Jul 28.
Examine cognitive changes over time among nursing home residents and develop a risk model for identifying predictors of cognitive decline.
Using secondary analysis design with Minimum Data Set data, cognitive status was based on the Cognitive Performance Scale (CPS).
Baseline and 7 quarterly follow-up analyses of US and Canadian interRAI data (N = 1,257,832) were completed.
Logistic regression analyses identified predictors of decline to form the CogRisk-NH scale.
At baseline, about 15% of residents were cognitively intact (CPS = 0), and 11.2% borderline intact (CPS = 1). The remaining more intact, with mild impairment (CPS = 2), included 15.0%. Approximately 59% residents fell into CPS categories 3 to 6 (moderate to severe impairment). Over time, increasing proportions of residents declined: 17.1% at 6 months, 21.6% at 9 months, and 34.0% at 21 months. Baseline CPS score was a strong predictor of decline. Categories 0 to 2 had 3-month decline rates in midteens, and categories 3 to 5 had an average decline rate about 9%. Consequently, a 2-submodel construction was employed-one for CPS categories 0 to 2 and the other for categories 3 to 5. Both models were integrated into a 6-category risk scale (CogRisk-NH). CogRisk-NH scale score distribution had 15.9% in category 1, 26.84% in category 2, and 36.7% in category 3. Three higher-risk categories (ie, 4-6) represented 20.6% of residents. Mean decline rates at the 3-month assessment ranged from 4.4% to 28.3%. Over time, differentiation among risk categories continued: 6.9% to 38.4.% at 6 months, 11.0% to 51.0% at 1 year, and 16.2% to 61.4% at 21 months, providing internal validation of the prediction model.
Cognitive decline rates were higher among residents in less-impaired CPS categories. CogRisk-NH scale differentiates those with low likelihood of decline from those with moderate likelihood and, finally, much higher likelihood of decline. Knowledge of resident risk for cognitive decline enables allocation of resources targeting amenable factors and potential interventions to mitigate continuing decline.
观察养老院居民随时间推移的认知变化，并制定一个识别认知能力下降预测因素的风险模型。
使用最小数据集中的二次分析设计，基于认知表现量表（CPS）来评估认知状态。
完成了美国和加拿大 interRAI 数据的基线和 7 个季度随访分析（N=1,257,832）。
逻辑回归分析确定了下降的预测因素，以形成 CogRisk-NH 量表。
在基线时，约 15%的居民认知功能完整（CPS=0），11.2%为边缘完整（CPS=1）。其余认知功能更完整，轻度受损（CPS=2）的比例为 15.0%。大约 59%的居民属于 CPS 类别 3 至 6（中度至重度受损）。随着时间的推移，越来越多的居民出现衰退：6 个月时为 17.1%，9 个月时为 21.6%，21 个月时为 34.0%。基线 CPS 评分是下降的有力预测因素。类别 0 至 2 的 3 个月下降率在十几岁左右，类别 3 至 5 的平均下降率约为 9%。因此，采用了 2 个子模型构建方法，一个用于 CPS 类别 0 至 2，另一个用于类别 3 至 5。两个模型都被整合到一个 6 类风险量表（CogRisk-NH）中。CogRisk-NH 量表的分布为 15.9%在类别 1，26.84%在类别 2，36.7%在类别 3。三个高风险类别（即 4-6）占居民的 20.6%。3 个月评估时的平均下降率从 4.4%到 28.3%不等。随着时间的推移，风险类别之间的差异仍在继续：6 个月时为 6.9%至 38.4%，1 年时为 11.0%至 51.0%，21 个月时为 16.2%至 61.4%，为预测模型提供了内部验证。
认知功能下降率在 CPS 类别中受损程度较低的居民中更高。CogRisk-NH 量表区分了那些下降可能性较低的人群和那些下降可能性中等的人群，最终区分了那些下降可能性较高的人群。了解居民认知能力下降的风险，能够为有针对性地分配资源提供依据，针对可改变的因素和潜在的干预措施，以减轻持续下降的影响。
