Background: Glycated hemoglobin (HbA1c) is widely used for the diagnosis and monitoring of diabetes mellitus; however, its interpretation is largely based on fixed diagnostic thresholds. This study moves beyond describing a glycemic continuum by translating the non-linear HbA1c–microvascular relationship into an individualized risk estimation framework. Methods: In this cross-sectional observational study, adult subjects from a real-world clinical cohort were analyzed using HbA1c as a continuous variable. Associations between HbA1c and metabolic parameters were assessed using correlation analysis. Linear regression was applied to evaluate the relationship between HbA1c and cumulative diabetes-related complication burden. Non-linear associations between HbA1c and the risk of presenting at least one complication were explored using restricted cubic spline logistic regression models. Additional risk estimation analyses focused on the HbA1c gray zone (5.5–6.4%). Results: HbA1c showed a strong continuous association with fasting plasma glucose (ρ = 0.73, p < 0.001) and was positively associated with cumulative complication burden (β = 0.016 per 1% increase in HbA1c, p = 0.009). Non-linear modeling revealed a progressive increase in complication risk beginning below the diagnostic threshold for diabetes, with an inflection of the risk curve within the HbA1c gray zone. Individuals within this interval exhibited a higher prevalence and increased odds of presenting at least one complication compared with lower HbA1c values, although some estimates did not reach statistical significance. Conclusions: HbA1c acts as a continuous and non-linear marker of metabolic stress, with potentially biologically meaningful increases in complication risk emerging below traditional diagnostic thresholds. We demonstrate a non-linear acceleration of microvascular risk within the 5.5–6.4% interval, rather than a simple linear gradient. These findings support the concept of a glycemic risk continuum and highlight the clinical relevance of the HbA1c sub-diagnostic interval for early risk stratification and preventive strategies.

Background: Assessing disease severity in hospitalized patients is essential for risk stratification and clinical decision-making. While formal severity scores are not always available in routine practice, organ support requirements may serve as pragmatic markers of critical illness. This study evaluated organ support modalities as indicators of disease severity and their association with in-hospital mortality. Methods: This retrospective observational study included 1332 adult hospitalized patients managed in either the intensive care unit or medical wards. Data on demographics, clinical complications, organ support requirements (mechanical ventilation, inotropic support, and hemodialysis), and outcomes were extracted from medical records. Cumulative organ support burden was categorized as none, single-organ, or multi-organ support. In-hospital mortality was the primary outcome. Results: Mechanical ventilation was required in approximately 71% of patients, inotropic support was required in 31%, and hemodialysis was required in 8%. Mortality was markedly higher among patients requiring organ support compared to those who did not. Mortality reached 70.4% in ventilated patients, 85.1% in those receiving inotropes, and 84.8% in those undergoing hemodialysis. A clear dose–response relationship was observed, with mortality increasing from 3.9% in patients requiring no support to 54.9% in those requiring one modality and 87.6% in those requiring multiple supports. Conclusions: Organ support requirements were strongly associated with in-hospital mortality and may serve as pragmatic prognostic indicators in retrospective datasets where formal severity scores are unavailable. However, given that organ support is initiated in response to clinical deterioration, these variables should be interpreted primarily as markers of prognostic association rather than independent severity measures.

Background: Length of stay (LOS) reflects healthcare utilization but may also capture patient clinical trajectories. We investigated the relationship between LOS categories, organ support requirements, and in-hospital mortality. Methods: This retrospective observational study included 1332 consecutive adult ICU patients in a tertiary-care center. ICU LOS patterns were categorized using median-based and predefined cutoffs. Multivariable logistic regression was used to identify independent predictors of in-hospital mortality. Results: Prolonged ICU LOS was associated with higher crude mortality (61.0% vs. 43.5%, p < 0.001). However, in LOS-adjusted models, mortality was independently associated with mechanical ventilation (aOR 29.89, 95% CI 17.92–49.86), inotropic support (aOR 4.94, 95% CI 3.50–6.97), hemodialysis (aOR 5.43, 95% CI 2.52–11.72), older age, and diabetes mellitus. Prolonged LOS was not independently associated with mortality (aOR 0.93, p = 0.630). Conclusions: LOS reflects underlying disease severity rather than acting as an independent driver of mortality. Integrating LOS pattern assessment with markers of organ dysfunction may improve risk stratification and resource planning in hospitalized populations.