HALP score and clinical parameters predict time to glycemic stability in hospitalized type 2 diabetes patients
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Key Takeaway
Consider using HALP score and clinical parameters to identify hospitalized type 2 diabetes patients at risk for delayed glycemic stability.
This retrospective cohort study analyzed data from 356 hospitalized patients diagnosed with type 2 diabetes. The primary objective was to evaluate the association between specific clinical parameters and the time required to achieve glycemic stability. The analysis focused on older age, lower hemoglobin levels, higher HbA1c levels, and a lower HALP score as potential predictors.
The results indicated that older age, lower hemoglobin level, higher HbA1c, and a lower HALP score were independent risk factors associated with a longer time to glycemic stability. The predictive model demonstrated a C-index of 0.81, with a 95% confidence interval ranging from 0.78 to 0.84. No specific adverse events, serious adverse events, discontinuations, or tolerability data were reported in the study.
Key limitations include the observational nature of the retrospective design, which precludes definitive causal conclusions regarding the identified risk factors. Funding sources and potential conflicts of interest were not reported. While the findings may assist clinicians in early identification of patients at risk for delayed stabilization, these results should be interpreted with caution regarding their generalizability and the strength of the evidence.
The study suggests that incorporating these parameters could facilitate personalized management strategies and optimize inpatient diabetes care. However, further research is needed to confirm these associations and determine the clinical utility of the HALP score in diverse hospital settings.
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View Original Abstract ↓
BackgroundAchieving rapid glycemic stabilization is a critical goal in the inpatient management of type 2 diabetes mellitus(T2DM). This study aimed to develop and validate a nomogram incorporating the hemoglobin, albumin, lymphocyte, and platelet (HALP) score and key clinical parameters to predict the time to glycemic stability in hospitalized T2DM patients.MethodsWe conducted a retrospective analysis of 356 hospitalized T2DM patients. Baseline demographic, clinical, and laboratory data, including the HALP score, were collected. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent predictors for the time to glycemic stability. The model’s discriminative ability was assessed using the concordance index, and its calibration was evaluated with calibration curves. Decision curve analysis (DCA) was used to estimate clinical utility.ResultsMultivariate Cox regression analysis identified older age, lower hemoglobin level, higher hemoglobin A1c (HbA1c), and a lower HALP score as independent risk factors associated with a longer time to glycemic stability. These four variables were integrated into a prognostic nomogram, which demonstrated good predictive accuracy, with a C-index of 0.81(95% CI:0.78 – 0.84) in the training cohort. The calibration curves showed satisfactory agreement between predicted and observed probabilities. Decision curve analysis (DCA) indicated favorable clinical net benefit across a reasonable range of threshold probabilities.ConclusionsWe developed and validated a practical nomogram that effectively predicts the time to glycemic stability in hospitalized T2DM patients, that may assist clinicians in early identification of patients at risk for delayed stabilization, thereby facilitating personalized management strategies and optimizing inpatient diabetes care.
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