An Assessment of the Relationship between Structural and Functional Imaging of Cerebrovascular Disease and Cognition-Related Fibers

Sarcopenic obesity in nursing home residents: a multi-center study on diagnostic methods and their association with instrumental activities of daily living

BACKGROUND

Sarcopenic obesity (SO) in nursing home residents is rarely studied. We aimed to evaluate and compare the prevalence and consistency of different SO diagnostic methods and to investigate which criterion demonstrated a stronger association with instrumental activities of daily living (IADL) disability.

METHODS

We consecutively recruited older adults aged ≥ 60 years, residing in 15 nursing homes in Zigong City, China. Sarcopenia obesity was defined according to the European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity criteria (SOESPEN), recommending skeletal muscle mass (SMM) adjusted by body weight (SMM/W) to identify low muscle mass. Further, we adapted ESPEN criteria (SOESPEN-M) by employing SMM adjusted by body mass index (SMM/BMI).

RESULTS

We included 832 participants (median age 73.0 years, 296 women). The prevalence of SOESPEN and SOESPEN-M was 43.5% and 45.3%, respectively. SOESPEN showed good consistency with SOESPEN-M (Cohen's kappa = 0.759). More than one-third of participants in the normal weight group were diagnosed with SOESPEN or SOESPEN-M. Even within the underweight group, the prevalence of SOESPEN and SOESPEN-M was 8.9% and 22.2%, respectively. Participants with IADL disability had significantly lower SMM/W and SMM/BMI, but higher fat mass percentage of body weight (FM%) than participants without IADL disability. After full adjustment for potential confounders, SOESPEN-M (OR 1.68, 95% CI 1.21 to 2.32), but not SOESPEN (OR 1.28, 95% CI 0.93 to 1.75), remained significantly associated with IADL disability.

CONCLUSIONS

Both SOESPEN and SOESPEN-M showed a high prevalence among nursing home residents, even among individuals with underweight or normal weight. While SOESPEN had a good consistency with SOESPEN-M, only SOESPEN-M was independently associated with IADL disability. Screening and diagnosis of SO should be conducted in nursing home residents irrespective of BMI.

Relationship between glycemic variability and cognitive function in lacune patients with type 2 diabetes

BACKGROUND

Lacunes are the manifestations of lacunar infarction which can lead many patients to the clinical outcome of disability or dementia. However, the relationship between lacune burden, cognitive function and blood glucose fluctuation in patients with type 2 diabetes mellitus (T2DM) complicated with lacunes is not very clear.

AIM

To explore the correlation between glucose variability, lacune burden and cognitive function in patients with lacunes complicated with T2DM.

METHODS

The clinical and imaging data of 144 patients with lacunes combined with T2DM were reviewed retrospectively. 72 h continuous glucose monitoring was performed. The Montreal Cognitive Assessment was used to assess cognitive function. The burden of lacunes was evaluated using magnetic resonance imaging performance. Multifactorial logistic regression analysis was used to study the affecting the lacune load and cognitive impairment in patients. To predict the value of patients' cognitive impairment with lacunes complicated with T2DM, a receiver operating characteristic (ROC) curve and a nomogram prediction model were constructed.

RESULTS

The standard deviation (SD) of the average blood glucose concentration, percentage coefficient of variation (%CV) and time of range (TIR) were significantly different between the low and the high load groups (P < 0.05). The SD, %CV and TIR of the cognitive impairment group and non-cognitive impairment group were significantly different (P < 0.05). SD (odds ratio (OR): 3.558, 95% confidence interval (CI): 1.268-9.978, P = 0.006), and %CV (OR: 1.192, 95%CI: 1.081-1.315, P < 0.05) were the risk factors for an increased infarct burden in lacunes patients complicated with T2DM. TIR (OR: 0.874, 95%CI: 0.833-0.928, P < 0.05) is a protective factor. In addition, an increased SD (OR: 2.506, 95%CI: 1.008-6.23, P = 0.003), %CV (OR: 1.163, 95%CI: 1.065-1.270, P < 0.05) were the risk factors for cognitive impairment in patients with lacunes complicated with T2DM, TIR (OR: 0.957, 95%CI: 0.922-0.994, P < 0.05) is a protective factor. A nomogram prediction model of the risk of cognitive impairment was established based on SD, %CV and TIR. Decision curve analysis and the internal calibration analysis were used for internal verification and showed that the model was clinical benefit. The area under the ROC curves for predicting cognitive impairment in patients with lacunes complicated with T2DM was drawn were %CV: 0.757 (95%CI :0.669-0.845, P < 0.05), TIR: 0.711 (95%CI: 0.623-0.799, P < 0.05).

CONCLUSION

Blood glucose variability is closely associated with the level of lacune burden and cognitive dysfunction in lacune patients combined with T2DM. %CV, TIR have a certain predictive effect in cognitive impairment in lacune patients.

Total Burden of Cerebral Small Vessel Disease on MRI May Predict Cognitive Impairment in Parkinson’s Disease

(1) Objective: to investigate the association between the total burden of cerebral small vessel disease (CSVD) and cognitive function in Parkinson’s disease (PD). (2) Methods: this retrospective study compared clinical and neuroimaging characteristics of 122 PD patients to determine the association between cognitive decline and total burden of CSVD in PD. All patients underwent brain MRI examinations, and their total CSVD burden scores were evaluated by silent lacunar infarction (SLI), cerebral microbleeds (CMB), white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS). The cognitive function was assessed by administering Mini-Mental State Examination (MMSE). Receiver-operating characteristic (ROC) curve and the area under the ROC curve (AUC) were performed to quantify the accuracy of the total burden of CSVD and PVH in discriminating PD patients with or without cognitive impairment. (3) Results: the PD patients with cognitive impairment had a significantly higher SLI, CMB, periventricular hyperintensities (PVH), deep white matter hyperintensities (DWMH), enlarged perivascular spaces of basal ganglia (BG-EPVS), and the total CSVD score compared with no cognitive impairment. Total CSVD score and MMSE had a significant negative correlation (r = −0. 483). Furthermore, total burden of CSVD and PVH were the independent risk factors of cognitive impairment in PD, and their good accuracy in discriminating PD patients with cognitive impairment from those with no cognitive impairment was confirmed by the results of ROC curves. (4) Conclusions: total burden of CSVD tightly linked to cognitive impairment in PD patients. The total burden of CSVD or PVH may predict the cognitive impairment in PD.