Javier Olazarán

Nonpharmacological Therapies in Alzheimer’s Disease: A Systematic Review of Efficacy

Introduction: Nonpharmacological therapies (NPTs) can improve the quality of life (QoL) of people with Alzheimer’s disease (AD) and their carers. The objective of this study was to evaluate the best evidence on the effects of NPTs in AD and related disorders (ADRD) by performing a systematic review and meta-analysis of the entire field. Methods: Existing reviews and major electronic databases were searched for randomized controlled trials (RCTs). The deadline for study inclusion was September 15, 2008. Intervention categories and outcome domains were predefined by consensus. Two researchers working together detected 1,313 candidate studies of which 179 RCTs belonging to 26 intervention categories were selected. Cognitive deterioration had to be documented in all participants, and degenerative etiology (indicating dementia) had to be present or presumed in at least 80% of the subjects. Evidence tables, meta-analysis and summaries of results were elaborated by the first author and reviewed by author subgroups. Methods for rating level of evidence and grading practice recommendations were adapted from the Oxford Center for Evidence-Based Medicine. Results: Grade A treatment recommendation was achieved for institutionalization delay (multicomponent interventions for the caregiver, CG). Grade B recommendation was reached for the person with dementia (PWD) for: improvement in cognition (cognitive training, cognitive stimulation, multicomponent interventions for the PWD); activities of daily living (ADL) (ADL training, multicomponent interventions for the PWD); behavior (cognitive stimulation, multicomponent interventions for the PWD, behavioral interventions, professional CG training); mood (multicomponent interventions for the PWD); QoL (multicomponent interventions for PWD and CG) and restraint prevention (professional CG training); for the CG, grade B was also reached for: CG mood (CG education, CG support, multicomponent interventions for the CG); CG psychological well-being (cognitive stimulation, multicomponent interventions for the CG); CG QoL (multicomponent interventions for PWD and CG). Conclusion: NPTs emerge as a useful, versatile and potentially cost-effective approach to improve outcomes and QoL in ADRD for both the PWD and CG.

Amyloid precursor protein metabolism and inflammation markers in preclinical Alzheimer disease

Objective: To investigate CSF markers involved in amyloid precursor protein processing, neuronal damage, and neuroinflammation in the preclinical stages of Alzheimer disease (AD) and participants with suspected non-Alzheimer pathology (SNAP). Methods: We collected CSF from 266 cognitively normal volunteers participating in a cross-sectional multicenter study (the SIGNAL study) to investigate markers involved in amyloid precursor protein processing (Aβ42, sAPPβ, β-secretase activity), neuronal damage (total-tau [t-tau], phospho-tau [p-tau]), and neuroinflammation (YKL-40). We analyzed the relationship among biomarkers, clinical variables, and the APOE genotype, and compared biomarker levels across the preclinical stages of the National Institute on Aging–Alzheimers Association classification: stage 0, 1, 2, 3, and SNAP. Results: The median age in the whole cohort was 58.8 years (range 39.8–81.6). Participants in stages 2–3 and SNAP had higher levels of YKL-40 than those in stages 0 and 1. Participants with SNAP had higher levels of sAPPβ than participants in stage 0 and 1. No differences were found between stages 0, 1, and 2–3 in sAPPβ and β-secretase activity in CSF. Age correlated with t-tau, p-tau, and YKL-40. It also correlated with Aβ42, but only in APOE ε4 carriers. Aβ42 correlated positively with t-tau, sAPPβ, and YKL-40 in participants with normal Aβ42. Conclusions: Our findings suggest that inflammation in the CNS increases in normal aging and is intimately related to markers of neurodegeneration in the preclinical stages of AD and SNAP. sAPPβ and β-secretase activity are not useful diagnostic or staging markers in preclinical AD.

Psychotropic Medications and Falls in Nursing Homes: A Cross-Sectional Study

BACKGROUND Psychotropic medications are very frequently used in nursing homes and have been associated with falls. Little is known on the potential differences between types and subtypes of these medications, and also regarding different prescription patterns. METHODS Data from 4502 residents living in 41 nursing homes belonging to a Spanish private chain were collected during a study period of 1 month and analyzed. Frequency of injurious and noninjurious falls were investigated for the following groups of psychotropic medications: typical neuroleptics; atypical neuroleptics; antidepressants; short and middle half-life benzodiazepines (BZD); long half-life BZD; BZD (of any type) administered only if needed; other hypnotic, sedative or anxiolytic drugs; cholinesterase inhibitors, and memantine. OR (95% CI) were calculated using regression analysis adjusted for age, sex, number of medications, physical restraint, and cognitive performance. RESULTS Mean age (SD) was 84.3 (8.6) and 73.4% of the subjects were female. Psychotropic medication was prescribed to 2987 residents (66.3%), and there were 490 falls. Total falls were associated with use of atypical neuroleptics (OR 1.50, CI 1.17‒1.94), antidepressants (OR 1.36, CI 1.03‒1.78), short and middle half-life BZD (OR 1.27, CI 1.00‒1.60), long half-life BZD (OR 1.65, CI 1.14‒2.38), cholinesterase inhibitors (OR 1.42, CI 1.05‒1.92), and memantine (OR 1.90, CI 1.32‒2.74). Injurious falls were associated with typical neuroleptics (OR 1.77, CI 0.99‒3.17), atypical neuroleptics (OR 1.64, CI 1.11‒2.44), and long half-life BZD (OR 2.57, CI 1.56‒4.25). The use of 2 or more psychotropics in combination was also associated with a significant increase of total falls and injurious falls. CONCLUSIONS Psychotropic medications were highly prescribed in the studied sample and were associated with falls. The most unsafe profile was detected for long half-life BZD, neuroleptics, and psychotropics in combination.

Cerebral Blood Flow is an Earlier Indicator of Perfusion Abnormalities than Cerebral Blood Volume in Alzheimer's Disease

The purpose of this study was to elucidate whether cerebral blood flow (CBF) can better characterize perfusion abnormalities in predementia stages of Alzheimers disease (AD) than cerebral blood volume (CBV) and whether cortical atrophy is more associated with decreased CBV or with decreased CBF. We compared measurements of CBV, CBF, and mean cortical thickness obtained from magnetic resonance images in a group of healthy controls, patients with mild cognitive impairment (MCI) who converted to AD after 2 years of clinical follow-up (MCI-c), and patients with mild AD. A significant decrease in perfusion was detected in the parietal lobes of the MCI-c patients with CBF parametric maps but not with CBV maps. In the MCI-c group, a negative correlation between CBF values and cortical thickness in the right parahippocampal gyrus suggests an increase in CBF that depends on cortical atrophy in predementia stages of AD. Our study also suggests that CBF deficits appear before CBV deficits in the progression of AD, as CBV abnormalities were only detected at the AD stage, whereas CBF changes were already detected in the MCI stage. These results confirm the hypothesis that CBF is a more sensitive parameter than CBV for perfusion abnormalities in MCI-c patients.

Mild cognitive impairment and dementia in primary care: the value of medical history.

BACKGROUND Primary care should be the place for the early detection of mild cognitive impairment (MCI) and dementia; however, a considerable proportion of these processes remain undetected at this setting. Family doctors may not have enough time or expertise for cognitive testing. The utility of clinical variables, other than cognitive tests, has hardly been investigated. OBJECTIVES To explore the diagnostic and prognostic value of the variables that are usually collected in the medical history of patients with suspected cognitive impairment. METHODS In this cohort study, people aged ≥ 50 years were prospectively searched for cognitive decline of unknown aetiology by seven primary care physicians (PCP) during their practice. The baseline assessment included demographic variables, symptom-related variables, medical and psychiatric co-morbidity, family history of dementia and neurological exam. The diagnosis was made by a neurologist at baseline and after 1 year. RESULTS One hundred and seventy-six patients were analysed of whom 81 (46.0%) had MCI and 18 (10.2%) had dementia at baseline. After 1 year, 8 (9.9%) MCI patients had progressed to dementia, but 48 (59.3%) had reverted to normal cognition. Old age, source of symptoms (informant or PCP), short duration and low education were associated with MCI or dementia at baseline; low education predicted progression to dementia in MCI patients and less chronic medical conditions and younger age predicted reversion from MCI to normal cognition (P < 0.05, adjusted regression models). CONCLUSION Clinical data usually collected on medical history by PCP are useful to detect patients with MCI and dementia and also to predict MCI outcome.

A blood-based, 7-metabolite signature for the early diagnosis of Alzheimer's disease.

Accurate blood-based biomarkers of Alzheimers disease (AD) could constitute simple, inexpensive, and non-invasive tools for the early diagnosis and treatment of this devastating neurodegenerative disease. We sought to develop a robust AD biomarker panel by identifying alterations in plasma metabolites that persist throughout the continuum of AD pathophysiology. Using a multicenter, cross-sectional study design, we based our analysis on metabolites whose levels were altered both in AD patients and in patients with amnestic mild cognitive impairment (aMCI), the earliest identifiable stage of AD. UPLC coupled to mass spectrometry was used to independently compare the levels of 495 plasma metabolites in aMCI (n = 58) and AD (n = 100) patients with those of normal cognition controls (NC, n = 93). Metabolite alterations common to both aMCI and AD patients were used to generate a logistic regression model that accurately distinguished AD from NC patients. The final panel consisted of seven metabolites: three amino acids (glutamic acid, alanine, and aspartic acid), one non-esterified fatty acid (22:6n-3, DHA), one bile acid (deoxycholic acid), one phosphatidylethanolamine [PE(36:4)], and one sphingomyelin [SM(39:1)]. Detailed analysis ruled out the influence of potential confounding variables, including comorbidities and treatments, on each of the seven biomarkers. The final model accurately distinguished AD from NC patients (AUC, 0.918). Importantly, the model also distinguished aMCI from NC patients (AUC, 0.826), indicating its potential diagnostic utility in early disease stages. These findings describe a sensitive biomarker panel that may facilitate the specific detection of early-stage AD through the analysis of plasma samples.

Detecting MCI and dementia in primary care: efficiency of the MMS, the FAQ and the IQCODE

OBJECTIVES To study the yield of three instruments for detection of patients with cognitive impairment in primary care. To investigate whether combining tests is better for detecting impairment than applying them separately. METHODS Seven primary care physicians (PCP) systematically recruited individuals aged over 49 years with a complaint or suspicion of cognitive impairment. The tests administered were the Mini-Mental State Test (MMS), the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) and the Pfeffer Functional Activities Questionnaire (FAQ). We calculated sensitivity, specificity and the area under the curve (AUC) and applied logistic regression analysis to determine the yield of the tests in combination. The gold standard was the clinical judgement of a neurologist based on a comprehensive assessment, which included a formal neuropsychological workup. RESULTS Of the 160 study patients, 90 (56%) had cognitive impairment (15 of these had dementia). The MMS had a sensitivity of 77% and a specificity of 70% in screening for cognitive impairment, with an AUC of 0.82. Incorporation of the IQCODE increased the AUC to 0.86 (P = 0.01). As for dementia, the FAQ reached a sensitivity of 87% and a specificity of 82%, with an AUC of 0.91. Incorporation of the MMS increased the AUC to 0.95 (P = 0.03). CONCLUSIONS Cognitive impairment is probably underdiagnosed in primary care. The combination of the FAQ and the MMS had excellent performance for dementia detection; however, no satisfactory instrument or instrument combination could be found for cognitive impairment.

Caregivers’ estimation of patients’ quality of life (QoL) in Alzheimer's disease (AD): An approach using the ADRQL

The purpose of this study was to describe the QoL of patients with AD (PAD) as perceived by family caregivers, and to analyze the correlates of such QoL. This study covered 92 PAD enrolled in a cognitive-motor stimulation study. The severity of cognitive impairment ranged from mild cognitive impairment to severe dementia. QoL was measured using the AD-related quality of life (ADRQL) scale. Social and clinical variables (for both PAD and caregiver) as well as other variables relating to cognition, activities of daily living (ADL), behavior, mood and caregiver burden were recorded. Spearman correlation coefficients and multivariate linear regression analysis were used to analyze the correlates of ADRQL (global score and subscores). Behavior and basic ADL were the best predictors of global QoL (coefficient of determination R(2)=0.57, p<0.0005). Cognition contributed marginally to global QoL (R(2)=0.03, p<0.05). The following variables were specifically associated with ADRQL subscores: household income (lower response to surroundings, R(2)=0.11), instrumental ADL (less awareness of self, R(2)=0.09), mood (better feelings and mood, R(2)=0.04), caregiver caring for another dependent person (higher social interaction, R(2)=0.04), and caregiver burden (worse feelings and mood, R(2)=0.03). In conclusion, the main determinants of QoL in PAD are functional capacities and behavior. Other medical, psychological and social variables could also be contributing to specific aspects of QoL on an individual basis.

Quality of life (QoL) in community-dwelling and institutionalized Alzheimer's disease (AD) patients.

The purpose of this study was to describe and compare QoL and its determinants in two groups of patients with AD that differed in place of residence: community or nursing home. This study covered 200 patients with AD (mean age 79.3 ± 8.2 years, 74% female). Fifty-four per cent of the subjects were living in a nursing home and 46% lived at home. QoL was measured using the Alzheimers Disease Related Quality of Life Scale (ADRQL). The ADRQL was answered by the family caregiver (community group) or the professional caregiver (nursing home group). Descriptive statistics, Chi-square test, Mann-Whitney test and multiple regression analysis were used to compare sociodemographic and clinical variables between the two study groups. The institutionalized patients were predominantly women (87.0% vs. 58.7%, p<0.001), were older (84 years vs. 74 years, p<0.001), and had more advanced dementia (Global Deterioration Scale (GDS)>5 79.6% vs. 19.6%, p<0.001). ADRQL total score was higher (i.e., better QoL) for patients living at home than for institutionalized patients (72.6 ± 19.9 vs. 64.8 ± 18.2, p<0.01). Neuropsychiatric symptoms, severity of dementia, depression and functional dependence were significant predictors of worst QoL. Once those variables were controlled a marginal effect of setting on QoL was found, which favored the nursing home (β=0.20, p<0.05).

Utility of the Mini-Cog for Detection of Cognitive Impairment in Primary Care: Data from Two Spanish Studies

Objectives. To study the utility of the Mini-Cog test for detection of patients with cognitive impairment (CI) in primary care (PC). Methods. We pooled data from two phase III studies conducted in Spain. Patients with complaints or suspicion of CI were consecutively recruited by PC physicians. The cognitive diagnosis was performed by an expert neurologist, after formal neuropsychological evaluation. The Mini-Cog score was calculated post hoc, and its diagnostic utility was evaluated and compared with the utility of the Mini-Mental State (MMS), the Clock Drawing Test (CDT), and the sum of the MMS and the CDT (MMS + CDT) using the area under the receiver operating characteristic curve (AUC). The best cut points were obtained on the basis of diagnostic accuracy (DA) and kappa index. Results. A total sample of 307 subjects (176 CI) was analyzed. The Mini-Cog displayed an AUC (±SE) of 0.78 ± 0.02, which was significantly inferior to the AUC of the CDT (0.84 ± 0.02), the MMS (0.84 ± 0.02), and the MMS + CDT (0.86 ± 0.02). The best cut point of the Mini-Cog was 1/2 (sensitivity 0.60, specificity 0.90, DA 0.73, and kappa index 0.48 ± 0.05). Conclusions. The utility of the Mini-Cog for detection of CI in PC was very modest, clearly inferior to the MMS or the CDT. These results do not permit recommendation of the Mini-Cog in PC.