Length of Hospital Stay in Acute Heart Failure With Type 2 Diabetes Mellitus: Forecasting Using WATCH-DM Score مدة الإقامة بالمستشفى في حالات فشل القلب الحاد مع داء السكري من النوع الثاني: التنبؤ باستخدام مقياس WATCH-DM

Faculty Medicine Year: 2024
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Heart Failure Journal of India Heart Failure Journal of India Volume:
Keywords : Length , Hospital Stay , Acute Heart Failure    
Abstract:
Background: The Weight, Age, hyperTension, Creatinine, High-density lipoprotein cholesterol, Diabetes control, Myocardial infarction, and coronary artery bypass grafting (WATCH-DM) score identifies incident heart failure (HF) risk in type 2 diabetes mellitus (T2DM). Extending the ability of this clinical score to stratify the severity of acute HF (AHF) in T2DM patients during the index hospitalization may be of value in enhancing the clinical outcome and resource allocation. Patients and Methods: We recruited 90 AHF patients with T2DM. The length of hospitalization (LOH) could be a proxy for the severity of AHF. According to the median LOH, the studied patients were classified into two groups: group I (LOH <11 days) and group II (LOH ≥11 days). Baseline characteristics, WATCH-DM score, and in-hospital all-cause mortality and adverse events were reported. A multiple logistic regression model was performed to evaluate the association between WATCH-DM and LOS. Results: The results revealed that age, chronic renal failure, WATCH-DM score absolute values and grades, and in-hospital complications were significantly higher in group II (LOH ≥11 days) than in group I (LOH <11 days). LOH showed strong positive correlation with age, WATCH-DM risk score, and in-hospital complications (P < 0.000). AHF diabetic patients with WATCH-DM score ≥13 had prolonged LOH that occurred independently of other potential confounders (B = 2.575, 95% confidence interval = 1.826–3.324, P < 0.000). Conclusion: The WATCH-DM score obtained on hospital admission of AHF diabetic patients demonstrates feasibility in predicting a longer hospital stay, thus providing clinicians with practical bedside tools for risk stratification of AHF diabetic patients.
   
     
 
       

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