Mild @entity73 in XXXX : Diagnosis and progression to @entity303 .

@entity1 @entity3602 @entity303 @entity73 @entity16 @entity191 @entity1726 @entity717 @entity2414
INTRODUCTION: Mild @entity73 is common in nondemented @entity191 @entity1 ( @entity1726 ) and is considered as a risk factor for @entity303 ( @entity3602 ). Recently, the @entity717 ( @entity717 ) published guidelines for @entity1726 , although the studies available are still limited. The aim of this work was to characterize @entity1726 and its progression to @entity303 . Moreover, the study variables could be considered as predictors for the progression of @entity73 . METHOD: The study included 43 @entity1 with idiopathic @entity1726 (mean age = 59.19 years, SD = 9.64) and 20 healthy and neurologically normal controls (mean age = 60.85 years, SD = 12.26). The criteria proposed by the @entity717 Task Force were applied for the @entity1726 diagnosis. Follow-up assessments were conducted within six to eight years after the diagnosis of @entity1726 . RESULTS: The results showed that 60.5% of the @entity1 were diagnosed with @entity1726 when a comprehensive assessment was performed ( @entity717 criteria Level 2), while 23.3% of the @entity1 met MCI criteria when a brief assessment was used ( @entity717 criteria Level 1). Multiple domain impairment was the most frequent impairment (96.2%). A total of 42.3% of @entity1726 @entity1 had @entity303 in the follow-up study. Logistic regression showed that the Hoehn and Yahr stage and education significantly contributed to the prediction of @entity1726 . Moreover, the Hoehn and Yahr stage and memory domain significantly contributed to the prediction of @entity303 . CONCLUSIONS: The results of the study: (a) provide relevant data about the process of validation of the @entity717 , (b) reinforce the hypothesis that @entity1726 is more frequent than previous studies showed without applying @entity717 criteria, and (c) confirm that @entity1726 is a risk factor for the onset of @entity303 . Finally, the study shows that @entity16 , educational level and @entity2414 were predictors for the progression of @entity73 .
