Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

Topic: Risk, prevention and care in population studies

Introduction Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and variability of HbA1c and lipids for adverse outcomes. Methods This retrospective cohort study consists of type 1 and type 2 diabetic patients who were prescribed insulin at outpatient clinics of Hong Kong public hospitals, from 1st January to 31st December 2009. Standard deviation (SD) and coefficient of variation were used to measure the variability of HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride. The primary outcome is all-cause mortality. Secondary outcomes were diabetes-related complications. Result The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). HbA1c and lipid value and variability were significant predictors of all-cause mortality. Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p Conclusion Raised variability in HbA1c and lipid parameters are associated with an elevated risk in both diabetic complications and all-cause mortality. The association between hypoglycemic frequency, baseline NLR, and both HbA1c and lipid variability implicate a role for inflammation in mediating adverse outcomes in diabetes, but this should be explored further in future studies.

Key findings

• Result The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%).
• HbA1c and lipid value and variability were significant predictors of all-cause mortality.
• Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p < 0.05).

Why it matters

In diabetic patients, higher variability in HbA1c and lipid measures was associated with increased risks of complications including incident dementia. This identifies a possible risk marker, not a treatment, cure, or prevention for Alzheimer's disease.

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Study details

• Study designcohort study
• Participants25,186
• Evidence strengthModerate

Read the original

• DOI: 10.1186/s12902-021-00751-4
• PubMed: 33947391
• Original source →
• Free full text: BMC Endocrine Disorders →

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

@article{lee2021-33947391,
  author  = {Lee, S. and Zhou, J. and Wong, W. T. and Liu, T. and Wu, W. K. K. and Wong, I. C. K. and Zhang, Q. and Tse, G.},
  title   = {{Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning}},
  journal = {BMC endocrine disorders},
  year    = {2021},
  doi     = {10.1186/s12902-021-00751-4},
  pmid    = {33947391},
  url     = {https://doi.org/10.1186/s12902-021-00751-4}
}

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