Associations of the metabolic syndrome and its components with cognitive impairment in older adults

BACKGROUND: The metabolic syndrome (MetS) is an established cardiovascular risk factor. Here, we investigated its role in cognitive impairment. METHODS: 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:  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). CONCLUSION: 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. TRIAL REGISTRATION: The study was registered on 15th October 2014 at clinicaltrials.gov (NCT02265263)

Methodology of measuring postoperative cognitive dysfunction: a systematic review

BACKGROUND: Postoperative cognitive dysfunction (POCD) is an adverse outcome that impacts patients' quality of life. Its diagnosis relies on formal cognitive testing performed before and after surgery. The substantial heterogeneity in methodology limits comparability and meta-analysis of studies. This systematic review critically appraises the methodology of studies on POCD published since the 1995 Consensus Statement and aims to provide guidance to future authors by providing recommendations that may improve comparability between future studies. METHODS: This systematic review of literature published between 1995 and 2019 included studies that used baseline cognitive testing and a structured cognitive test battery, and had a minimal follow-up of 1 month. For cohorts with multiple publications, data from the primary publication were supplemented with available data from later follow-up studies. RESULTS: A total of 274 unique studies were included in the analysis. In the included studies, 259 different cognitive tests were used. Studies varied considerably in timing of assessment, follow-up duration, definition of POCD, and use of control groups. Of the 274 included studies, 70 reported POCD as a dichotomous outcome at 1 to <3 months, with a pooled incidence of 2998/10 335 patients (29.0%). CONCLUSIONS: We found an overwhelming heterogeneity in methodology used to study POCD since the publication of the 1995 Consensus Statement. Future authors could improve study quality and comparability through optimal timing of assessment, the use of commonly used cognitive tests including the Consensus Statement ‘core battery’, application of appropriate cut-offs and diagnostic rules, and detailed reporting of the methods used. PROSPERO REGISTRY NUMBER: CRD42016039293

Personalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation

Personalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project.

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation

Personalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation. (C) 2017 Published by Elsevier Masson SAS