Mortality Risk and Its Association with Geriatric Domain Deficits in Older Outpatients: The Amsterdam Ageing Cohort.

INTRODUCTION: In older patients, life expectancy is determined by a complex interaction of multiple geriatric domains. A comprehensive geriatric assessment (CGA) captures different geriatric domains. Yet, if and how components of the CGA are related to mortality in an outpatient geriatric setting is unknown. In the Amsterdam Ageing Cohort, we therefore studied distribution and accumulation of geriatric domain deficits in relation to mortality. METHODS: All patients received a CGA as part of standard care, independent of referral reason. We summarized deficits on the CGA, using predefined cutoffs, in 5 geriatric domains: somatic, mental, nutritional, physical, and social domain. Information on mortality was obtained from the Dutch municipal register. We used age- and sex-adjusted Cox proportional hazards analyses to relate the separate domains and accumulation of impaired domains to overall mortality. RESULTS: From the 1,055 geriatric outpatients (53% female; age 79 ± 7 years), 172 patients (16%) had died after 1.7 ± 1.1 years. In 626 patients (59%), 3 or more domains were impaired. All domains were independently associated with mortality, with the highest hazard for the somatic domain (HR 3.7 [1.7-8.0]) and the lowest hazard for the mental domain (HR 1.5 [1.1-12.0]). In addition, accumulation of impaired domains showed a gradually increased mortality risk, ranging from HR 2.2 (0.8-6.1) for 2 domains to HR 9.6 (3.7-24.7) for all 5 domains impaired. CONCLUSIONS: This study provides evidence that impairment in multiple geriatric domains is highly prevalent and independently and cumulatively associated with mortality in an outpatient geriatric setting.

Slowing: A Vascular Geriatric Syndrome?

OBJECTIVES: This study aimed to investigate the interrelation between slowing in walking, thinking and mood, and their relationship with cerebral small vessel disease (CSVD) in a geriatric population. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: 566 geriatric outpatients from the Amsterdam Aging Cohort (49% female; age 79 ±6 years), who visited the Amsterdam UMC geriatric outpatient memory clinic. METHODS: Patients underwent a comprehensive geriatric assessment, brain imaging, and a neuropsychological assessment as part of medical care. Three slowing aspects were investigated: gait speed, processing speed, and apathy symptoms (higher scores indicating more advanced slowing). We visually rated CSVD [white matter hyperintensities (WMHs), strategic lacunes, and microbleeds] on brain imaging. RESULTS: Regression analyses showed that slowing in walking (gait speed) was associated with slowing in thinking [processing speed; ß = 0.35, 95% confidence interval (CI) 0.22, 0.48] and slowing in mood (apathy symptoms; ß = 0.21, 95% CI 0.13, 0.30), independent of important confounders. Large confluent areas of WMH (Fazekas 3) were associated with all slowing aspects: gait speed (ß = 0.49, 95% CI 0.28, 0.71), processing speed (ß = 0.36, 95% CI 0.19, 0.52) and apathy symptoms (ß = 0.30, 95% CI 0.09, 0.51). In addition, in patients with more slowing aspects below predefined cutoffs, severe WMH was more common. Presence of ≥3 microbleeds was associated with apathy symptoms (ß = 0.39, 95% CI 0.12, 0.66), whereas lacunes were not associated with slowing. CONCLUSIONS AND IMPLICATIONS: This study provides evidence that slowing in walking, thinking, and mood are closely related and associated with CSVD. This phenotype or geriatric syndrome could be helpful to identify and characterize patients with CSVD.

The Mini Mental State Examination does not accurately screen for objective cognitive impairment in Fabry Disease.

Fabry disease (FD) patients may suffer from objective cognitive impairment (OCI). This study assessed the accuracy of the Mini Mental State Examination (MMSE) to screen for OCI in FD patients. Presence or absence of OCI was established using a neuropsychological test battery. For different MMSE cutoffs sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and clinical utility index (CUI) to identify OCI were calculated. Eighty-one patients were included (mean age 44.5 ± 14.3, 35% men, 74% classical phenotype) of which 13 patients (16%) had OCI. The median MMSE score was 29 (range: 25-30). MMSE cutoffs ≤28 and ≤29 had the highest sensitivity and specificity, with higher specificity reached at cutoff ≤28 (sensitivity: .46, specificity: .73) and higher sensitivity at cutoff ≤29 (sensitivity: .92, specificity: .40). PPV was low for both cutoffs (PPV ≤28: .25, PPV ≤29: .23) resulting in a low positive CUI (case finding ability). The results of our study indicate that the MMSE does not accurately screen for OCI in FD, with poor sensitivity-specificity trade-off at all cutoffs. The low PPV shows that the majority of FD patients that score below the cutoffs do not suffer from OCI. Administering the MMSE as a screening test will lead to unnecessary referrals for neuropsychological testing, which is time consuming and burdensome. Screening tools designed to accurately detect mild (executive) impairment might prove more appropriate to screen for OCI in FD.