Prevalence of Pulmonary Disorders in Patients with End Stage Renal Disease on Hemodialysis

Kabil, Ahmed; Basiony, Fareed Shawky; Nour, Mohamed O.; Makboul, Khaled S.

doi:10.21608/ejhm.2019.36033

Cited by 2 publications

(1 citation statement)

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“…Similar methods have been shown to be accurate and effective [ 12 , 13 , 14 , 15 , 16 ] in previous works. However, hemodialysis patients are predisposed to a considerable prevalence of pulmonary complications (e.g., pulmonary edema 8.20–20.50%, pleural effusions 22.95–33.80%) [ 17 , 18 ]. The incidence of permanent pacemaker implantation was 5.93- and 3.50-fold greater in hemodialysis and peritoneal dialysis patients than in controls (1.44 and 0.85 versus 0.24 per 1000 person-years, respectively) [ 19 ].…”

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confidence: 99%

Validation of an Automated Cardiothoracic Ratio Calculation for Hemodialysis Patients

et al. 2023

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Cardiomegaly is associated with poor clinical outcomes and is assessed by routine monitoring of the cardiothoracic ratio (CTR) from chest X-rays (CXRs). Judgment of the margins of the heart and lungs is subjective and may vary between different operators. Methods: Patients aged > 19 years in our hemodialysis unit from March 2021 to October 2021 were enrolled. The borders of the lungs and heart on CXRs were labeled by two nephrologists as the ground truth (nephrologist-defined mask). We implemented AlbuNet-34, a U-Net variant, to predict the heart and lung margins from CXR images and to automatically calculate the CTRs. Results: The coefficient of determination (R2) obtained using the neural network model was 0.96, compared with an R2 of 0.90 obtained by nurse practitioners. The mean difference between the CTRs calculated by the nurse practitioners and senior nephrologists was 1.52 ± 1.46%, and that between the neural network model and the nephrologists was 0.83 ± 0.87% (p < 0.001). The mean CTR calculation duration was 85 s using the manual method and less than 2 s using the automated method (p < 0.001). Conclusions: Our study confirmed the validity of automated CTR calculations. By achieving high accuracy and saving time, our model can be implemented in clinical practice.

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