Developing a predictive model for mortality in patients with cognitive impairment

Abstract

AbstractObjectivesWe developed a predictive model for all‐cause mortality and examined the risk factors for cause‐specific mortality among people with cognitive impairment in a Japanese memory clinic‐based cohort (2010–2018).MethodsThis retrospective cohort study included people aged ≥65 years with mild cognitive impairment or dementia. The survival status was assessed based on the response of participants or their close relatives via a postal survey. Potential predictors including demographic and lifestyle‐related factors, functional status, and behavioral and psychological status were assessed at the first visit at the memory clinic. A backward stepwise Cox regression model was used to select predictors, and a predictive model was developed using a regression coefficient‐based scoring approach. The discrimination and calibration were assessed via Harrell's C‐statistic and a calibration plot, respectively.ResultsA total of 2610 patients aged ≥65 years (men, 38.3%) were analyzed. Over a mean follow‐up of 4.1 years, 544 patients (20.8%) died. Nine predictors were selected from the sociodemographic and clinical variables: age, sex, body mass index, gait performance, physical activity, and ability for instrumental activities of daily living, cognitive function, and self‐reported comorbidities (pulmonary disease and diabetes). The model showed good discrimination and calibration for 1–5‐year mortality (Harrell's C‐statistic, 0.739–0.779). Some predictors were specifically associated with cause‐specific mortality.ConclusionsThis predictive model has good discriminative ability for 1‐ to 5‐year mortality and can be easily implemented for people with mild cognitive impairment and all stages of dementia referred to a memory clinic.