Longitudinal Evaluation of Metabolic Benefits of Inactivated COVID-19 Vaccination in Diabetic Patients in Tianjin, China

Abstract

BACKGROUND Diabetes significantly heightens risks of COVID-19 infection, and vaccine hesitancy remains high due to safety concerns. MATERIAL AND METHODS This study assessed the effects of inactivated COVID-19 vaccine in 548 diabetic patients from Tianjin, China, categorized by vaccination status: unvaccinated (n=94), primary immunization (n=117), and booster immunization (n=337). A total of 22 clinical values were assessed prior to vaccination, 3 months after vaccination, and 12 months after vaccination. Variables with a normal distribution were compared across groups using one-way ANOVA, while non-normally distributed variables were compared using the Kruskal-Wallis test and chi-square tests for categorical data. Linear mixed-effects models were used to evaluate the effects of time and vaccine type on these clinical values, with random intercepts to account for within-subject variability and interaction terms for detailed group comparisons over time. RESULTS Baseline results showed no major differences across groups, including fasting glucose, HbA1c, granulocytes, hemoglobin, platelets, renal function markers such as uric acid, creatinine, and eGFR. Booster vaccination significantly reduced FPG (Estimate=-0.123, p<0.001) and HbA1c (Estimate=-0.049, p<0.01), with primary vaccination also reducing FPG (Estimate=-0.118, p<0.001) and HbA1c (Estimate=-0.040, p<0.05). However, creatinine decreased and bilirubin levels rose in vaccinated groups but remained within the normal physiological range. Other indicators showed no significant changes. CONCLUSIONS In conclusion, COVID-19 inactivated vaccine can provide metabolic benefits for diabetic patients.

Figure 1

Baseline laboratory values by vaccination group. Baseline levels of key clinical biomarkers in diabetic patients are presented, stratified by COVID-19 vaccination status: Group A (unvaccinated), Group B (primary immunization), and Group C (booster immunization). Significance levels annotated as *** p<0.001, ** p<0.01, * p<0.05, and “ns” indicating non-significant differences.

Figure 2

Longitudinal biomarker trends across VACTYPE groups. Longitudinal trends of 22 biomarkers over a 12-month period are depicted for VACTYPE groups A, B, and C. Each panel shows the progression of a specific biomarker with the Y-axis indicating measurement values and the X-axis representing time from baseline.

Figure 3

Effect differences in laboratory values relative to VACTYPEA. The forest plot illustrates estimated effect differences of 22 biomarkers relative to the reference group VACTYPEA. The X-axis displays effect differences with 95% confidence intervals.