Background: The relationship between clinical indicators and illness severity in hospitalized patients with both diabetes mellitus (DM) and COVID-19 remains incompletely understood, particularly with respect to endocrine markers. Aim: This study aimed to identify clinical predictors of critical illness in hospitalized adults with DM and COVID-19 and to develop a predictive nomogram for individualized risk assessment. Method: This retrospective cross-sectional study enrolled 393 hospitalized patients with confirmed DM and COVID-19, who were categorized into non-critical (n = 309) and critical (n = 84) groups. We evaluated a comprehensive panel of candidate predictors, including demographic characteristics, vital signs, and laboratory markers such as C-reactive protein (CRP), fasting C-peptide (FCP), and free triiodothyronine (FT3). Multivariable logistic regression was used to develop the prediction model. Results: Multivariate logistic regression identified several independent predictors of critical illness. Elevated levels of blood urea nitrogen (BUN) (OR: 1.100, 95% CI: 1.026–1.183), serum creatinine (SCr) (OR: 1.027, 95% CI: 1.011–1.043), and CRP (OR: 1.011, 95% CI: 1.005–1.019), along with advanced age (OR: 1.073, 95% CI: 1.039–1.112), were significant risk factors. Conversely, lower levels of FCP (OR: 0.483, 95% CI: 0.305–0.737), FT3 (OR: 0.519, 95% CI: 0.313–0.835), and serum sodium (OR: 0.911, 95% CI: 0.860–0.962) were independent protective factors. The resulting nomogram showed excellent discrimination (C-index = 0.964). Conclusion: A combination of clinical and laboratory parameters, including age, renal function, inflammatory markers, and endocrine indicators (FCP and FT3), can effectively predict COVID-19 severity in patients with DM. The developed nomogram provides a practical tool for early risk stratification in this high-risk population.
Yuan et al. (Mon,) studied this question.