Browsing by Author "Yerokhovych, Viktoriia"

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    The impact of war on people with type 2 diabetes in Ukraine: a survey study.
    (eClinicalMedicine, 2024-12-15) Sulaieva, Oksana; Yerokhovych, Viktoriia; Zemskov, Sergii
    Background Although the number of studies reporting war-induced effects on the health of the Ukrainian population has been growing, there are still little data on assessing patients with type 2 diabetes (T2D) during the war. This study aimed to evaluate the impact of war on T2D patients’ health to define key risk factors promoting disease progression. Methods A survey covering various aspects of T2D patients’ experience and glycemic control data was conducted from June 2022 to February 2024. Overall, 1193 patients from all regions of Ukraine were enrolled in the study. According to the difference between the initial and current levels of HbA1c, all the respondents were subdivided into two categories: progressors (with HbA1c levels greater than 5% of the initial value) and stable (patients with stable HbA1c levels). Next, the impact of intrinsic and war-related factors on T2D progression was assessed via logistic regression analysis and machine learning tools. Findings Two years of war experience was associated with significant increase in the median HbA1c from 7.8% (7.0–8.93) to 8.4% (7.4–9.9; p < 0.001), with the highest value occurring in eastern and northern Ukraine. HbA1c levels demonstrated a time-dependent pattern of growth, reflecting the cumulative effect of war-related factors on T2D patients’ health. Witnesses of armed attacks and occupation aggravated the T2D course. Experience with military actions (p = 0.002), occupation (p = 0.001), internal displacement (p = 0.018) and family member injury or death (p = 0.031) increased HbA1c. In addition, lack of regular glucose monitoring (p < 0.001), consultation by endocrinologists (p < 0.001), diet inconsistency (p = 0.017) and scarcity of physical activity (p = 0.047) affected the HbA1c parameters. Interpretation This study demonstrated a dramatic cumulative effect of the war on T2D patients’ health. Uncovered direct and indirect war-related risk factors can guide further adjustment of diabetic care in Ukraine to improve T2D patient support.
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    Unveiling risk factors for post-COVID-19 syndrome development in people with type 2 diabetes.
    (Frontiers in Endocrinology, 2024-12-11) Sulaieva, Oksana; Matviichuk, Anton; Yerokhovych, Viktoriia; Zemskov, Sergii
    Introduction: Post-COVID-19 syndrome (PCS) is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-associated chronic condition characterized by long-term violations of physical and mental health. People with type 2 diabetes (T2D) are at high risk for severe COVID-19 and PCS. Aim: The current study aimed to define the predictors of PCS development in people with T2D for further planning of preventive measures and improving patient outcomes. Materials and methods: The data were collected through the national survey targeting persons with T2D concerning the history of COVID-19 course and signs and symptoms that developed during or after COVID-19 and continued for more than 12 weeks and were not explained by an alternative diagnosis. In total, 469 patients from different regions of Ukraine were enrolled in the study. Among them, 227 patients reported PCS development (main group), while 242 patients did not claim PCS symptoms (comparison group). Stepwise multivariate logistic regression and probabilistic neural network (PNN) models were used to select independent risk factors. Results: Based on the survey data, 8 independent factors associated with the risk of PCS development in T2D patients were selected: newly diagnosed T2D (OR 4.86; 95% CI 2.55–9.28; p<0.001), female sex (OR 1.29; 95% CI 0.86–1.94; p=0.220), COVID-19 severity (OR 1.35 95% CI 1.05–1.70; p=0.018), myocardial infarction (OR 2.42 95% CI 1.26–4.64; p=0.002) and stroke (OR 3.68 95% CI 1.70–7.96; p=0.001) in anamnesis, HbA1c above 9.2% (OR 2.17 95% CI 1.37–3.43; p=0.001), and the use of insulin analogs (OR 2.28 95% CI 1.31–3.94; p=0.003) vs human insulin (OR 0.67 95% CI 0.39–1.15; p=0.146). Although obesity aggravated COVID-19 severity, it did not impact PCS development. In ROC analysis, the 8-factor multilayer perceptron (MLP) model exhibited better performance (AUC 0.808; 95% CІ 0.770–0.843), allowing the prediction of the risk of PCS development with a sensitivity of 71.4%, specificity of 76%, PPV of 73.6% and NPV of 73.9%. Conclusions: Patients who were newly diagnosed with T2D, had HbA1c above 9.2%, had previous cardiovascular or cerebrovascular events, and had severe COVID-19 associated with mechanical lung ventilation were at high risk for PCS.