Longitudinal Neuropsychiatric Predictors of  Death in XXXX .

@entity2204 @entity146 @entity195 @entity204 @entity25
UNASSIGNED: Characteristics associated with life expectancy in @entity195 ( @entity195 ) are still far from known. Here we aimed at examining the ability of baseline/longitudinal clinical variables to predict time to @entity204 . One-hundred fifty @entity195 outpatients underwent diagnostic, @entity146 , and functional assessment at baseline (when @entity2204 was also investigated) and at each subsequent annual visit. A random effects joint modeling approach was used to simultaneously model the baseline and longitudinal trajectory of each factor and predict the time to @entity204 , adjusting for demographic covariates. An ancillary analysis of @entity2204 status as a predictor was also conducted. Kaplan-Meier survival curves were constructed to elucidate the relationship between each factor and the estimated probability of @entity204 over time. Shorter survival was associated with male gender, higher education, older age, lower cognition, and worse functioning in daily life, but not @entity2204 status. Longitudinal trajectories increased predictive power over using just baseline levels highlighting apathy, and secondarily aberrant motor behaviors and @entity25 , as a highly reliable predictor for mortality. Apathy was the strongest @entity146 predictor of time to @entity204 , which supports its role in the pathogenesis of the disorder. An increased knowledge of factors modulating survival in @entity195 is a strategic prerequisite to plan therapeutic interventions.
