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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\u2010related 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\u2010based scoring approach. The discrimination and calibration were assessed via Harrell's\n                      <jats:italic>C<\/jats:italic>\n                      \u2010statistic and a calibration plot, respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 2610 patients aged \u226565\u00a0years (men, 38.3%) were analyzed. Over a mean follow\u2010up of 4.1\u00a0years, 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\u2010reported comorbidities (pulmonary disease and diabetes). The model showed good discrimination and calibration for 1\u20135\u2010year mortality (Harrell's\n                      <jats:italic>C<\/jats:italic>\n                      \u2010statistic, 0.739\u20130.779). Some predictors were specifically associated with cause\u2010specific mortality.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This predictive model has good discriminative ability for 1\u2010 to 5\u2010year mortality and can be easily implemented for people with mild cognitive impairment and all stages of dementia referred to a memory clinic.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/gps.6020","type":"journal-article","created":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T04:29:56Z","timestamp":1698812996000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Developing a predictive model for mortality in patients with cognitive 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