The effects of cardiovascular risk factor combined anti-platelet therapy and the risk of cerebrovascular events in patients with T2DM in an urban community over 96-months follow-up: The Beijing communities diabetes study 19

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review

Background

Population segmentation permits the division of a heterogeneous population into relatively homogenous subgroups. This scoping review aims to summarize the clinical applications of data driven and expert driven population segmentation among Type 2 diabetes mellitus (T2DM) patients.

Methods

The literature search was conducted in Medline®, Embase®, Scopus® and PsycInfo®. Articles which utilized expert-based or data-driven population segmentation methodologies for evaluation of outcomes among T2DM patients were included. Population segmentation variables were grouped into five domains (socio-demographic, diabetes related, non-diabetes medical related, psychiatric / psychological and health system related variables). A framework for PopulAtion Segmentation Study design for T2DM patients (PASS-T2DM) was proposed.

Results

Of 155,124 articles screened, 148 articles were included. Expert driven population segmentation approach was most commonly used, of which judgemental splitting was the main strategy employed (n = 111, 75.0%). Cluster based analyses (n = 37, 25.0%) was the main data driven population segmentation strategies utilized. Socio-demographic (n = 66, 44.6%), diabetes related (n = 54, 36.5%) and non-diabetes medical related (n = 18, 12.2%) were the most used domains. Specifically, patients’ race, age, Hba1c related parameters and depression / anxiety related variables were most frequently used. Health grouping/profiling (n = 71, 48%), assessment of diabetes related complications (n = 57, 38.5%) and non-diabetes metabolic derangements (n = 42, 28.4%) were the most frequent population segmentation objectives of the studies.

Conclusions

Population segmentation has a wide range of clinical applications for evaluating clinical outcomes among T2DM patients. More studies are required to identify the optimal set of population segmentation framework for T2DM patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01209-w.

Homocysteine, interleukin-1β, and fasting blood glucose levels as prognostic markers for diabetes mellitus complicated with cerebral infarction and correlated with carotid intima-media thickness

Diabetes mellitus complicated with cerebral infarction (DMCI) has a high incidence and disability rate. Therefore, identification of biomarkers for the early prediction of the development and progression of cerebral infarction (CI) is of great significance for the prevention and treatment of this disease. The roles of serum homocysteine (Hey), interleukin-1β (IL-1β), and fasting blood glucose (FBG) in DMCI and their correlations with carotid intima-media thickness (CIMT) were explored. A total of 124 patients with DMCI (DMCI group) and 103 patients with diabetes mellitus (DM) (DM group) admitted to the People's Hospital of Liuhe District of Nanjing were enrolled in this study. A further 100 healthy controls undergoing physical examinations during the same period (HC group) were also enrolled. CIMT value was detected by carotid artery ultrasound. Hey and FBG levels were determined by a fully automatic biochemical analyzer. The IL-1β level was detected by enzyme-linked immunosorbent assay (ELISA). The levels of Hey, IL-1β, and FBG and the CIMT value in the DMCI and DM groups were significantly higher than those in the HC group (P<0.001). The levels and the value in the DMCI group were significantly higher than those in the DM group (P<0.001). Hey, IL-1β, and FBG levels were positively correlated with CIMT value (r=0.542, P<0.001; r=0.522, P<0.001; r=0.402, P<0.001). Receiver operating characteristic (ROC) curves showed that the sensitivity and specificity of Hey for diagnosing DMCI were 86.29 and 80.58%; those of IL-1β were 68.55 and 86.41%; those of FBG were 69.35 and 88.35%. Multivariate logistic regression analysis revealed that systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), Hey, IL-1β, FBG, and CIMT were independent risk factors for DMCI (P<0.05). In conclusion, patients with DMCI have severe atherosclerosis. Hey, IL-1β, and FBG are involved in the development and progression of DMCI, so they can be used as predictive markers for the disease. Hey, IL-1β, FBG, and CIMT are independent risk factors for patients with DMCI.

Neurovascular decoupling in type 2 diabetes mellitus without mild cognitive impairment: Potential biomarker for early cognitive impairment

Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI) and the acceleration of MCI to dementia. The high glucose level induce disturbance of neurovascular (NV) coupling is suggested to be one potential mechanism, however, the neuroimaging evidence is still lacking. To assess the NV decoupling pattern in early diabetic status, 33 T2DM without MCI patients and 33 healthy control subjects were prospectively enrolled. Then, they underwent resting state functional MRI and arterial spin labeling imaging to explore the hub-based networks and to estimate the coupling of voxel-wise cerebral blood flow (CBF)-degree centrality (DC), CBF-mean amplitude of low-frequency fluctuation (mALFF) and CBF- mean regional homogeneity (mReHo). We further evaluated the relationship between NV coupling pattern and cognitive performance (false discovery rate corrected). T2DM without MCI patients displayed significant decrease in the absolute CBF-mALFF, CBF-mReHo coupling of CBFnetwork and in the CBF-DC coupling of DCnetwork. Besides, networks which involved CBF and DC hubs mainly located in the default mode network (DMN). Furthermore, less severe disease and better cognitive performance in T2DM patients were significantly correlated with higher coupling of CBF-DC, CBF-mALFF or CBF-mReHo, especially for the cognitive dimensions of general function and executive function. Thus, coupling of CBF-DC, CBF-mALFF and CBF-mReHo may serve as promising indicators to reflect NV coupling state and to explain the T2DM related early cognitive impairment.