How to choose the most appropriate cognitive test to evaluate cognitive complaints in primary care.

BACKGROUND: Despite the wealth of research devoted to the performance of individual cognitive tests for diagnosing cognitive impairment (including mild cognitive impairment and dementia), it can be difficult for general practitioners to choose the most appropriate test for a patient with cognitive complaints in daily practice. In this paper we present a diagnostic algorithm for the evaluation of cognitive complaints in primary care. The rationale behind this algorithm is that the likelihood of cognitive impairment -which can be determined after history taking and an informant interview- should determine which cognitive test is most suitable. METHODS: We distinguished three likelihoods of cognitive impairment: not likely, possible or likely. We selected cognitive tests based on pre-defined required test features for each of these three situations and a review of the literature. We incorporated the cognitive tests in a practical diagnostic algorithm. RESULTS: Based on the available literature, in patients with complaints but where cognitive impairment is considered to be unlikely the clock-drawing test can be used to rule out cognitive impairment. When cognitive impairment is possible the Montreal cognitive assessment can be used to rule out cognitive impairment or to make cognitive impairment more likely. When cognitive impairment is likely the Mini-Mental State Examination can be used to confirm the presence of cognitive impairment. CONCLUSIONS: We propose a diagnostic algorithm to increase the efficiency of ruling out or diagnosing cognitive impairment in primary care. Further study is needed to validate and evaluate this stepwise diagnostic algorithm.

High-sensitivity C-reactive protein to detect metabolic syndrome in a centrally obese population: a cross-sectional analysis.

BACKGROUND: People with central obesity have an increased risk for developing the metabolic syndrome, type 2 diabetes and cardiovascular disease. However, a substantial part of obese individuals have no other cardiovascular risk factors, besides their obesity. High sensitivity C-reactive protein (hs-CRP), a marker of systemic inflammation and a predictor of type 2 diabetes and cardiovascular disease, is associated with the metabolic syndrome and its separate components. We evaluated the use of hs-CRP to discriminate between centrally obese people with and without the metabolic syndrome. METHODS: 1165 people with central obesity but without any previous diagnosis of hypertension, dyslipidemia, diabetes or cardiovascular disease, aged 20-70 years, underwent a physical examination and laboratory assays to determine the presence of the metabolic syndrome (NCEP ATP III criteria). Multivariable linear regression analyses were performed to assess which metabolic syndrome components were independently associated with hs-CRP. A ROC curve was drawn and the area under the curve was calculated to evaluate whether hs-CRP was capable to predict the presence of the metabolic syndrome. RESULTS: Median hs-CRP levels were significantly higher in individuals with central obesity with the metabolic syndrome (n = 417; 35.8%) compared to individuals with central obesity without the metabolic syndrome (2.2 mg/L (IQR 1.2-4.0) versus 1.7 mg/L (IQR 1.0-3.4); p < 0.001). Median hs-CRP levels increased with an increasing number of metabolic syndrome components present. In multivariable linear regression analyses, waist circumference and triglycerides were the only components that were independently associated with hs-CRP after adjusting for smoking, gender, alcohol consumption and the other metabolic syndrome components. The area under the ROC curve was 0.57 (95%-CI 0.53-0.60). CONCLUSIONS: Hs-CRP has limited capacity to predict the presence of the metabolic syndrome in a population with central obesity.

People with type 2 diabetes and screen-detected cognitive impairment use acute health care services more often: observations from the COG-ID study.

BACKGROUND: Patients with type 2 diabetes have an increased risk of cognitive impairment which can lead to impaired diabetes self-management and an increased risk of diabetes-related complications. Routine screening for cognitive impairment in elderly patients with type 2 diabetes is therefore increasingly advocated. The aim of this study is to investigate whether people with type 2 diabetes and screen-detected cognitive impairment use acute health care services more often than patients not suspected of cognitive impairment. METHODS: People with type 2 diabetes ≥ 70 years were screened for cognitive impairment in primary care. Diagnoses in screen positives were established at a memory clinic. Information about acute health care use was collected for 2 years prior to and 2 years after screening and compared to screen negatives. RESULTS: 154 participants (38% female, mean age 76.7 ± 5.2 years, diabetes duration 8.7 ± 8.2 years) were included, 37 patients with cognitive impairment, 117 screen negatives. A higher percentage of participants with cognitive impairment compared to screen negative patients used acute health care services; this difference was significant for general practitioner's out of hours services (56% versus 34% used this service over 4 years, p = 0.02). The mean number of acute health care visits was also higher in those with cognitive impairment than in screen negatives (2.2 ± 2.8 versus 1.4 ± 2.2 visits in 4 years, p < 0.05; 1.4 ± 2.2 versus 0.7 ± 1.5 visits in 2 years after screening, p = 0.03). Factors that could have played a role in this increased risk of acute health care services use were a low educational level, the presence of depressive symptoms (CES-D score ≥ 16), self-reported problems in self-care and self-reported problems in usual activities. CONCLUSIONS: People with type 2 diabetes and screen-detected cognitive impairment use acute health care services more often.

Depressive symptoms and quality of life after screening for cognitive impairment in patients with type 2 diabetes: observations from the Cog-ID cohort study.

OBJECTIVES: To assess changes in depressive symptoms and health-related quality of life (HRQOL) after screening for cognitive impairment in people with type 2 diabetes. DESIGN: A prospective cohort study, part of the Cognitive Impairment in Diabetes (Cog-ID) study. SETTING: Participants were screened for cognitive impairment in primary care. People suspected of cognitive impairment (screen positives) received a standardised evaluation at a memory clinic. PARTICIPANTS: Participants ≥70 years with type 2 diabetes were included in Cog-ID between August 2012 and September 2014, the current study includes 179 patients; 39 screen positives with cognitive impairment, 56 screen positives without cognitive impairment and 84 participants not suspected of cognitive impairment during screening (screen negatives). OUTCOME MEASURES: Depressive symptoms and HRQOL assessed with the Center for Epidemiologic Studies Depression Scale (CES-D), 36-Item Short-Form Health Survey, European Quality of Life-5 Dimensions questionnaire and the EuroQol Visual Analogue Scale. Outcomes were assessed before the screening, and 6 and 24 months after screening. An analysis of covariance model was fitted to assess differences in score changes among people diagnosed with cognitive impairment, screen negatives and screen positives without cognitive impairment using a factor group and baseline score as a covariate. RESULTS: Of all participants, 60.3% was male, mean age was 76.3±5.0 years, mean diabetes duration 13.0±8.5 years. At screening, participants diagnosed with cognitive impairment had significantly more depressive symptoms and a worse HRQOL than screen negatives. Scores of both groups remained stable over time. Screen positives without cognitive impairment scored between the other two groups at screening, but their depressive symptoms decreased significantly during follow-up (mean CES-D: -3.1 after 6 and -2.1 after 24 months); their HRQOL also tended to improve. CONCLUSIONS: Depressive symptoms are common in older people with type 2 diabetes. Screening for and a subsequent diagnosis of cognitive impairment will not increase depressive symptoms.

Applicability of diagnostic constructs for cognitive impairment in patients with type 2 diabetes mellitus.

AIMS: Type 2 diabetes mellitus (T2DM) is associated with subtle cognitive changes, but also with more severe stages of cognitive dysfunction, including mild cognitive impairment (MCI) and dementia. For these severe stages, it is uncertain which domains are primarily affected and if all patients with impairment are captured by formal criteria for MCI or dementia. METHODS: Ninety-five patients with T2DM suspected of cognitive impairment, identified through screening in primary care, underwent neuropsychological examination assessing five different domains. MCI or dementia were diagnosed using formal criteria. RESULTS: Forty-seven participants (49%) had impairment on at least one domain, most often involving memory (30%), information processing speed (22%) and visuoperception and construction (22%). Of these 47 people, 29 (62%) had multi-domain impairment. Of the 47 participants with objective impairment, 36 (77%) met criteria for MCI, three (6%) for dementia and eight (17%) met neither diagnosis, mostly because these patients did not complain about acquired dysfunction. CONCLUSIONS: This study shows that the clinical diagnostic evaluation of cognitive impairment in patients with T2DM should take into account that multiple domains can be affected and that not all patients with objective cognitive impairment fulfill criteria for MCI or dementia.

Undiagnosed cognitive impairment, health status and depressive symptoms in patients with type 2 diabetes.

AIMS: Type 2 diabetes (T2DM) is associated with cognitive impairment. We examined whether undiagnosed cognitive impairment in T2DM-patients is associated with a reduced health status and depressive symptoms. METHODS: In an observational study, 225 T2DM-patients aged ≥70years were examined at their homes and (some of them) at a memory clinic for undiagnosed cognitive impairment (dementia or mild cognitive impairment [MCI], defined according to internationally accepted criteria). Questionnaires assessing health status (SF-36, EQ-5D, EQ-VAS) and depressive symptoms (CES-D) were filled out. Health status and depressive symptoms were compared between patients with and without cognitive impairment. RESULTS: Patients with cognitive impairment (n=57) showed significantly lower scores on the physical and mental summary scores of the SF-36 than patients with normal cognition (difference: 3.5 (95%-CI 0.7-6.3, p=0.02, effect size 0.41) and 2.9 (95%-CI 0.3-5.6; p=0.03, effect size 0.37). EQ-5D index and EQ-VAS scores were significantly lower in patients with cognitive impairment. Depression (CES-D≥16) occurred almost twice as often in patients with cognitive impairment (RR 1.8; 95%-CI: 1.1-3.0). CONCLUSIONS: Undiagnosed cognitive impairment in T2DM-patients is associated with a reduced health status and more depressive symptoms. Detection of cognitive impairment in T2DM-patients identifies a vulnerable patient group that could benefit from tailored treatment and care.

Cognitive function in patients with diabetes mellitus: guidance for daily care.

Diabetes mellitus is associated with an increase in the risk of dementia and the proportion of patients who convert from mild cognitive impairment (MCI) to dementia. In addition to MCI and dementia, the stages of diabetes-associated cognitive dysfunction include subtle cognitive changes that are unlikely to affect activities of daily life or diabetes self-management. These diabetes-associated cognitive decrements have structural brain correlates detectable with brain MRI, but usually show little progression over time. Although cognitive decrements do not generally represent a pre-dementia stage in patients below the age of 60-65 years, in older individuals these subtle cognitive changes might represent the earliest stages of a dementia process. Acknowledgment of diabetes-associated cognitive decrements can help to improve understanding of patients' symptoms and guide management. Future challenges are to establish the importance of screening for cognitive impairment in people with diabetes, to identify those at increased risk of accelerated cognitive decline at an early stage, and to develop effective treatments.

Cognitive Impairment in Diabetes: Rationale and Design Protocol of the Cog-ID Study.

BACKGROUND: Cognitive impairment frequently co-occurs with type 2 diabetes but is often undiagnosed. Cognitive impairment affects self-management leading to treatment-related complications. OBJECTIVE: The aim of this study is to develop a stepped diagnostic procedure, consisting of a screening test complemented by an evaluation by a general practitioner (GP), to detect undiagnosed cognitive impairment in older people with type 2 diabetes. METHODS: The accuracy of two self-administered cognitive tests, the "Test Your Memory" (TYM) and "Self-Administered Gerocognitive Examination" (SAGE) alone, and in combination with an evaluation by a GP will be assessed. A diagnosis of mild cognitive impairment (MCI) or dementia at a memory clinic will serve as reference standard. This cognitive impairment in diabetes (Cog-ID) study will include 513 people from primary care facilities aged ≥70 with type 2 diabetes. The participants will first fill out the TYM and SAGE tests, followed by a standardized GP evaluation for cognitive impairment, including a mini mental state examination (MMSE). Subsequently, participants suspected of cognitive impairment (on either test or the GP assessment) and a random sample of 15% (65/435) of participants without suspected cognitive impairment will be referred to the memory clinic. At the memory clinic, a medical examination, neuropsychological examination, and magnetic resonance imaging (MRI) of the brain will be performed. Participants will also fill out questionnaires assessing health status and depressive symptoms at baseline and after 6 and 24 months. RESULTS: This research obtained funding and ethical approval. Enrolment started in August, 2012, and all study-related activities will be completed in September, 2016. CONCLUSIONS: With the results from this study, physicians will be able to detect cognitive impairment affecting type 2 diabetes patients through case-finding, and can use tailored care to reduce associated complications. Additionally, the results may stimulate discussions about cognitive impairment and whether early recognition is desirable.

Cognitive disorders in diabetic patients.

This chapter gives an overview of the literature on cognitive dysfunction in adults with type 1 or type 2 diabetes. First, methods to evaluate cognitive functioning and the pattern and severity of cognitive dysfunction in relation to diabetes will be discussed. The reader will note that diabetes is associated with worse cognitive functioning and an increased dementia risk. Next, diabetes-associated abnormalities on brain MRI, including reductions in brain volume - i.e., cerebral atrophy - and vascular lesions, will be addressed. At the group level there are clear relations between these imaging abnormalities and cognitive dysfunction, but at the level of the individual patient these relations are often less clear. Subsequently, risk factors for cognitive performance will be discussed. Evidently, these risk factors are related to diabetes type and the age of the patients involved. For type 1 diabetes, an early age at diabetes onset is the most consistent risk factor, whereas in type 2 diabetes, vascular risk factors and vascular comorbidities are consistent indicators of increased risk. The final section of the chapter addresses possible preventive and treatment measures and implications for daily care.

Screening for increased cardiometabolic risk in primary care: a systematic review.

BACKGROUND: Many programmes to detect and prevent cardiovascular disease (CVD) have been performed, but the optimal strategy is not yet clear. AIM: To present a systematic review of cardiometabolic screening programmes performed among apparently healthy people (not yet known to have CVD, diabetes, or cardiometabolic risk factors) and mixed populations (apparently healthy people and people diagnosed with risk factor or disease) to define the optimal screening strategy. DESIGN AND SETTING: Systematic review of studies performed in primary care in Western countries. METHOD: MEDLINE, Embase, and CINAHL databases were searched for studies screening for increased cardiometabolic risk. Exclusion criteria were studies designed to assess prevalence of risk factors without follow-up or treatment; without involving a GP; when fewer than two risk factors were considered as the primary outcome; and studies constrained to ethnic minorities. RESULTS: The search strategy yielded 11 445 hits; 26 met the inclusion criteria. Five studies (1995-2012) were conducted in apparently healthy populations: three used a stepwise method. Response rates varied from 24% to 79%. Twenty-one studies (1967-2012) were performed in mixed populations; one used a stepwise method. Response rates varied from 50% to 75%. Prevalence rates could not be compared because of heterogeneity of used thresholds and eligible populations. Observed time trends were a shift from mixed to apparently healthy populations, increasing use of risk scores, and increasing use of stepwise screening methods. CONCLUSION: The optimal screening strategy in primary care is likely stepwise, in apparently healthy people, with the use of risk scores. Increasing public awareness and actively involving GPs might facilitate screening efficiency and uptake.

The "Test Your Memory" test performs better than the MMSE in a population without known cognitive dysfunction.

AIM: To examine the relation of performance on the self-administered Test Your Memory test (TYM) and the Mini-Mental State Examination (MMSE) with a comprehensive neuropsychological assessment in a population sample including people with modest cognitive decrements. METHODS: Eighty-six participants (aged 56-77 years), without known cognitive dysfunction, performed a neuropsychological assessment including MMSE, and were asked to fill out the TYM. The relation between both the TYM and the MMSE and a neuropsychological assessment was examined by means of correlation analyses, area under the ROC curves for discriminating between a "normal" and "modest decrements"(≥1SD below the sample mean) group, and Bland-Altman plots. RESULTS: Correlation with the full neuropsychological assessment was significantly stronger for the TYM than the MMSE (r=0.78 versus r=0.55; Steiger's Z=2.66, p<0.01). The TYM showed an area under the ROC-curve of 0.88 (95% CI 0.80 to 0.97) for differentiating between "normal" and "modest decrements" compared with 0.71 (0.53 to 0.90) for the MMSE. Bland-Altman plots showed limits of agreement for the TYM of -1.10 to 1.10 and for the MMSE of -1.39 to 1.38. CONCLUSIONS: The TYM showed good correlation with a neuropsychological assessment, performed better in discriminating between variations of cognition and showed more agreement with a neuropsychological assessment than the MMSE.

Mild depressive symptoms do not influence cognitive functioning in patients with type 2 diabetes.

Type 2 diabetes (T2DM) is associated both with cognitive decrements and depressive symptoms. Since depression in itself has been associated with cognitive decrements we aimed to investigate the influence of depressive symptoms on the relation between T2DM and cognitive functioning. Data were derived from three independent studies on cognitive functioning in patients with T2DM (n=366) and controls without diabetes (n=204), two with longitudinal and one with only cross-sectional assessments. Depressive symptoms were measured with self-report inventories (CES-D or BDI-II). The composite z-score of the domains memory, information-processing speed, and attention and executive function was the primary cognitive outcome measure. Mixed linear regression analyses were used in a stepped approach to compare cognitive functioning between (1) patients with T2DM and controls (cross-sectionally and longitudinally), (2) participants with and without depressive symptoms, separately for patients and controls, and (3) patients and controls after adjustment for depressive symptoms. In addition the mediating effect of depressive symptoms was assessed with a bootstrapping technique. Depressive symptoms were present in 11% of the patients with T2DM and in 7% of controls (p=0.15). Cognitive performance in patients with T2DM was worse than in controls (overall difference composite z-score -0.13). However, T2DM was not associated with accelerated cognitive decline over three years of follow-up relative to controls. Controls with depressive symptoms performed worse than those without depressive symptoms, although not statistically significant. Performance in patients with T2DM with and without depressive symptoms was similar. Adjustment for depressive symptoms and estimation of the mediating effect showed that the difference between patients and controls was not mediated by depressive symptoms. In conclusion, the modest cognitive decrements that are associated with T2DM are not due to the presence of mild depressive symptoms.

Intensive multifactorial treatment and cognitive functioning in screen-detected type 2 diabetes--the ADDITION-Netherlands study: a cluster-randomized trial.

AIM: To assess whether an intensive multifactorial treatment can reduce cognitive decrements and cognitive decline in screen-detected type 2 diabetes. METHODS: The multinational ADDITION-study, a cluster-randomized parallel group trial in patients with screen-detected type 2 diabetes, compared the effectiveness of intensive multifactorial treatment (IT; lifestyle advice and strict regulation of metabolic parameters) with routine care (RC) on cardiovascular outcome. In The Netherlands randomization was stratified according to practice organization. Allocation was concealed from patients. The present study assessed the effect of IT on cognition through two neuropsychological assessments (NPA) on two occasions. The assessments took place three and six years after the start of the intervention. Non-diabetic controls served as reference group. The first NPA was performed in 183 patients (IT: 97; RC: 86) and 69 controls. The second NPA was performed in 135 patients (IT: 71; RC: 64) and 55 controls. Primary outcome was a composite score, including the domains memory, information-processing speed and attention and executive function. Comparisons between the treatment groups were performed with multi-level analyses. RESULTS: The first NPA showed no differences between the treatment groups (mean difference composite z-score: 0.00; 95%-CI -0.16 to 0.16; IT vs RC). Over the next three years cognitive decline in the diabetic groups was within the range of the reference group and did not differ between the treatment arms (difference decline between diabetic groups -0.12; -0.24 to 0.01; IT vs RC). CONCLUSIONS: Six years of IT in screen-detected type 2 diabetes had no benefit on cognitive functioning over RC.