Background: Hypoglycemia is one of the most common complications in patients with DN during hemodialysis. The purpose of the study is to construct a clinical automatic calculation to predict risk of hypoglycemia during hemodialysis for patients with diabetic nephropathy.
Methods: In this cross-sectional study, patients provided information for the questionnaire and received blood glucose tests during hemodialysis. The data were analyzed with logistic regression and then an automated calculator for risk prediction was constructed based on the results. From May to November 2022, 207 hemodialysis patients with diabetes nephropathy were recruited. Patients were recruited at blood purifying facilities at two hospitals in Beijing and Inner Mongolia province, China. Hypoglycemia is defined according to the standards of medical care in diabetes issued by ADA (2021). The blood glucose meter was used uniformly for blood glucose tests 15 minutes before the end of hemodialysis or when the patient did not feel well during hemodialysis.
Results: The incidence of hypoglycemia during hemodialysis was 50.2% (104/207). The risk prediction model included 6 predictors, and was constructed as follows: Logit (P) = 1.505×hemodialysis duration 8~15 years (OR = 4.506, 3 points) + 1.616×hemodialysis duration 16~21 years (OR = 5.032, 3 points) + 1.504×having hypotension during last hemodialysis (OR = 4.501, 3 points) + 0.788×having hyperglycemia during the latest hemodialysis night (OR = 2.199, 2 points) + 0.91×disturbance of potassium metabolism (OR = 2.484, 2 points) + 2.636×serum albumin<35 g/L (OR = 13.963, 5 points)-4.314. The AUC of the prediction model was 0.866, with Matthews correlation coefficient (MCC) of 0.633, and Hosmer-Lemeshow χ of 4.447(P = 0.815). The automatic calculation has a total of 18 points and four risk levels.
Conclusions: The incidence of hypoglycemia during hemodialysis is high in patients with DN. The risk prediction model in this study had a good prediction outcome. The hypoglycemia prediction automatic calculation that was developed using this model can be used to predict the risk of hypoglycemia in DN patients during hemodialysis and also help identify those with a high risk of hypoglycemia during hemodialysis.
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| http://dx.doi.org/10.1186/s13098-023-01177-9 | DOI Listing |
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