Related Experiment Video
Updated: Jan 21, 2026
12:18
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
7.9K
Unveiling the relationship between stress-hyperglycemia ratio and cardiometabolic multimorbidity risk using
Shouxin Wei1, Sijia Yu2, Chuan Qian3
1Department of Gastrointestinal Surgery, Suining Central Hospital, Suining, China. weishouxin@sns120.cn.
European Journal of Medical Research
|January 20, 2026
Summary
The stress-hyperglycemia ratio (SHR) shows a U-shaped link with cardiometabolic multimorbidity (CMM) risk. Higher SHR levels may indicate increased CMM risk, suggesting SHR
Area of Science:
- Cardiovascular Research
- Metabolic Disease Epidemiology
- Biomarker Analysis
Background:
- Cardiometabolic multimorbidity (CMM) presents a significant global health challenge.
- The stress-hyperglycemia ratio (SHR) is a novel biomarker with prognostic implications, but its role in CMM is unclear.
Purpose of the Study:
- To investigate the association between SHR and CMM risk.
- To evaluate the clinical utility of SHR in CMM risk assessment.
Main Methods:
- Cross-sectional analysis of NHANES data (12,279 participants).
- Weighted logistic regression and machine learning (gradient boosting machine) for CMM prediction.
- External validation using CHARLS data; mediation analysis for BMI and WC roles.
Main Results:
- A U-shaped relationship exists between SHR and CMM risk.
- Elevated SHR levels are associated with significantly increased CMM risk (OR=116.890 above 0.841).
- Machine learning model (AUC=0.880) identified age, SHR, and WC as key predictors; BMI and WC mediate the SHR-CMM link.
Conclusions:
- SHR exhibits a non-linear, U-shaped association with CMM risk, highlighting its potential for early diagnosis.
- Machine learning-based predictive models can enhance personalized CMM risk assessment.
Keywords:
CHARLSCardiometabolic multimorbidityMachine learning modelsNHANESStress–hyperglycemia ratioMore Related Videos
06:19Constructing and Visualizing Models using Mime-based Machine-learning Framework
Published on: July 22, 2025
2.3K
13:35Acute and Chronic Models of Hyperglycemia in Zebrafish: A Method to Assess the Impact of Hyperglycemia on Neurogenesis and the Biodistribution of Radiolabeled Molecules
Published on: June 26, 2017
13.9K
Related Concept Videos
02:12Relationship Formation
45.2K
What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
45.2K
01:28Ending Relationships
172
The dissolution of intimate relationships presents complex emotional and psychological challenges, particularly when emotional bonds are strong, the relationship is long-standing, and perceived alternatives are limited. This distress often intensifies in romantic breakups, where the initiator may experience greater turmoil than the rejected partner. Contributing factors include residual attachment, guilt over causing pain, and uncertainty about how to manage the situation. The stress is further...
172
01:22Interpreting R Charts
341
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
341
01:19Machines
559
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
A free-body diagram of the...
559
01:25Interpreting Run Charts
3.0K
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
3.0K
01:12Relative Risk
2.0K
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
2.0K