The factors associated with mild cognitive impairment in outpatient practice

  • Marija Lazarević Health Center “Dr. Milenko Marin”, Loznica, Serbia
  • Dragan Milovanović University of Kragujevac, Faculty of Medical Sciences, Department for Pharmacology, Kragujevac, Serbia
  • Dejana Ružić Zečević University of Kragujevac, Faculty of Medical Sciences, Department for Pharmacology, Kragujevac, Serbia
Keywords: cognitive dysfunction, comorbidity, diabetes mellitus, type 2, risk assessment, risk factors, vitamin b 12

Abstract


Background/Aim. Previous studies showed that mild cognitive impairment (MCI) was more common in patients with comorbidities and those using medications that disrupt the homeostasis of vitamin B12. The aim of our study was to determine which of these factors are significantly associated with MCI, as well as which are the most significant risk factors for predicting its occurrence. Methods. The data have been prospectively collected for 200 adults (35–65 years old) in primary care settings enrolled in the clinical study with the case-control approach. Results. By applying the χ2 test for independence, we have determined that the MCIs and the use of proton-pump inhibitors (PPIs) (p < 0.0005), as well as metformin (p < 0.0005), are independent factors. In addition, a significantly higher percentage of subjects who had MCI also had a peptic ulcer and diabetes mellitus type 2 (T2DM). Direct logistic regression has been implemented in order to estimate the influence of many probability factors on whether the study patients would have the MCI. Two variables made statistically significant contributions to the model, and these are the serum concentrations of vitamin B12 [odds ratio (OR) = 0.953; 95% confidence interval (CI) 0.936–0.971; < 0.001] and T2DM (OR = 6.681; 95% CI 1.305–34.198; = 0.023). Conclusion. The absolute and relative risk associations of exposure to medicines and MCI is lower than those of comorbidities and MCI. Serum concentrations of vitamin B12, as well as the presence of T2DM, have the greatest statistically significant influence on predicting MCI.

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Published
2023/08/01
Section
Original Paper