Post-operative cognitive dysfunction (POCD) occurs relatively frequently, in 10 to 54% of patients during the first few weeks after surgery (1). It is usually transient (2), but unlike for post-operative delirium (POD), clear diagnostic criteria are...

The metabolic syndrome (MetS) is an established cardiovascular risk factor. Here, we investigated its role in cognitive impairment. Baseline data from 202 participants (aged 65 to 87 years) of the BioCog study were used. All were free of clinical dementia (MMSE≥24/30). Cognitive impairment was defined as the lowest tertile of a cognitive summary score. Multiple logistic regression analyses examined associations of body mass index (BMI), triglycerides (TG), high-density lipoprotein (HDL-C), glucose and glycated hemoglobin A1c (HbA1c) levels with the odds of cognitive impairment. MetS was defined as ≥3 of its 5 components obesity (BMI ≥ 30 kg/m2), elevated TG (TG ≥1.7 mmol/L), reduced HDL-C (males: < 1.0 mmol/L; females: < 1.3 mmol/L), elevated glucose (glucose ≥5.5 mmol/L and/or diagnosed diabetes) and elevated blood pressure (history of hypertension). Analyses controlled for age, sex and smoking history. Lower HDL-C was significantly associated with a higher odds of cognitive impairment (OR 2.70 per 1 mmol/L reduction; 95% CI 1.25, 5.56; p = 0.011), whereas BMI, TG, glucose and HbA1c were not (all p > 0.05). Results for HDL-C were similar when HDL-C, glucose, BMI and TG were entered into a single model (OR 2.56 per 1 mmol/L reduction, 95% CI 1.09, 5.88, p = 0.031) and when cerebrovascular disease and coronary heart disease were additionally controlled for (OR 2.56 per 1 mmol/L reduction, 95% CI 1.06, 6.25, p = 0.036). Among the 5 MetS components, participants with elevated TG were at 2-fold increased odds of impairment (OR 2.09, 95% CI 1.08, 4.05, p = 0.028) including when the remaining 4 MetS components were entered (OR 2.23, 95% CI 1.07, 4.65, p = 0.033), but the finding was no longer statistically significant when cerebrovascular disease and coronary heart disease were additionally controlled for (p = 0.11). Presence of MetS and of obesity, reduced HDL-C, elevated glucose or elevated blood pressure were not significantly associated with impairment (all p > 0.05). Our findings support low HDL-C as an independent risk marker of cognitive impairment in older age. The need for research into mediatory and confounding factors, and re-evaluation of traditional cut-off points is highlighted. The study was registered on 15th October 2014 at clinicaltrials.gov ( NCT02265263 ).

The present study introduces the assessment of depression and depressive symptoms in the German National Cohort (NAKO), a population-based mega cohort. Distribution of core measures, and associatio...

Background: Age-related cognitive impairment is rising in prevalence but is not yet fully characterized in terms of its epidemiology. Here, we aimed to elucidate the role of obesity, diabetes and hypertension as candidate risk factors. Methods: Original baseline data from 3 studies (OCTOPUS, DECS, SuDoCo) were obtained for secondary analysis of cross-sectional associations of diabetes, hypertension, blood pressure, obesity (body mass index [BMI] ≥30 kg/m²) and BMI with presence of cognitive impairment in log-binomial regression analyses. Cognitive impairment was defined as scoring more than 2 standard deviations below controls on at least one of 5–11 cognitive tests. Underweight participants (BMI<18.5 kg/m²) were excluded. Results were pooled across studies in fixed-effects inverse variance models. Results: Analyses totaled 1545 participants with a mean age of 61 years (OCTOPUS) to 70 years (SuDoCo). Cognitive impairment was found in 29.0% of participants in DECS, 8.2% in SuDoCo and 45.6% in OCTOPUS. In pooled analyses, after adjustment for age, sex, diabetes and hypertension, obesity was associated with a 1.29-fold increased prevalence of cognitive impairment (risk ratio [RR] 1.29; 95% CI 0.98, 1.72). Each 1 kg/m² increment in BMI was associated with 3% increased prevalence (RR 1.03; 95% CI 1.00, 1.06). None of the remaining risk factors were associated with impairment. Conclusion: Our results show that older people who are obese have higher prevalence of cognitive impairment compared with normal weight and overweight individuals, and independently of co-morbid hypertension or diabetes. Prospective studies are needed to investigate the temporal relationship of the association.

Metabolic syndrome and its components are risk factors for cognitive impairment, but their contribution to perioperative neurocognitive disorders is unknown. We examined their associations with the risk of postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) in older patients. In 765 male and female participants aged ≥65 years, we measured preoperative metabolic parameters and screened for POD for 7 days or until discharge. POCD was defined through comparison of cognitive change on six neuropsychological tests with non-surgical controls. Multiple logistic regression analyses examined the association of metabolic parameters with risk of POD and POCD with adjustment for age, sex, and surgery type. A total of 149 patients (19.5% of 765) developed POD and 53 (10.1% of 520 attendees) had POCD at 3 months. Patients with metabolic syndrome were at 1.85-fold higher risk of POD (95% confidence interval [CI] 1.26-2.70). Each 1 mmol L^-1 higher high-density lipoprotein cholesterol (HDL-C) was associated with a 0.47-fold lower POD risk (95% CI 0.30-0.74). Each 1 kg m^-2 higher body mass index (BMI) was associated with a 1.09-fold higher POCD risk (95% CI 1.02- 1.16). Older surgical patients with metabolic syndrome were at increased risk of POD. Only reduced HDL-C was significantly associated with POD. For POCD, a higher preoperative BMI was identified as a risk factor. These findings add to mounting evidence of a distinct epidemiology of POD and POCD. Screening programmes taking advantage of HDL-C and BMI measurements and of metabolic interventions in reducing perioperative neurocognitive disorders should be evaluated. NCT02265263.