Probability of Dying and Survival Analysis of Diabetic and/Hypertensive Patients Who Undergone Hemodialysis with Heart Disease Complication: A Comparison between a Hemodialysis Center Jakarta, Indonesia and Penang, Malaysia

Ramatillah, Diana Laila; Sulaiman, Syed Azhar Syed; Khan, Amer Hayat; Meng, Dato Ong Loke; Markum,

doi:10.5530/jcdr.2018.1.6

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…By using medical profiles of patients such as age, gender, blood pressure and blood sugar, chest pain, and an electrocardiogram (ECG) graph, it can predict the likelihood of patients getting a heart disease or not and make 82% effectually working in necessity. Concurring to [13], design a multilayer perceptron model for analytical detection of heart disease severity based on various factors. The author also organizes a novel principle attribute analysis to understand the direction of the attributes emotional the results.…”

Section: Related Workmentioning

confidence: 99%

Heart disease classification using various heuristic algorithms

Ullah

Khan²,

Alam³

et al. 2022

IJAAS

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<span>In the health sector, the computer-aided diagnosis (CAD) system is a rapidly growing technology because medical diagnostic systems make a huge change as compared to the traditional system. Now a day huge availability of medical data and it needs a proper system to extract them into useful knowledge. Heart disease accounts to be the leading cause of death worldwide. Heuristic algorithms have been exposed to be operative in supporting making decisions and classification from the large quantity of data produced by the healthcare sector. Classification is a prevailing heuristic approach which is commonly used for classification purpose some heuristic algorithm predicts accurate result according to the marks whereas some others exhibit limited accuracy. This paper is used to categorize the attendance of heart disease with a compact number of aspects. Original, 13 attributes are involved in classifying heart disease. A reasonable analysis of these techniques was done to conclude how the cooperative techniques can be applied for improving prediction accuracy in heart disease. Four main classifiers used to construct heart disease prediction based on the experimental results demonstrate that support vector machine, artificial bee colony (ABC), Bat algorithm, and memory-based learner (MBL) provide efficient results. The accuracy differs between 13 features and 8 features in the training dataset is 1.9% and in the validation, dataset is 0.92% of vector machine which is the most accurate heuristic algorithm. </span>

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Section: Related Workmentioning

confidence: 99%

Heart disease classification using various heuristic algorithms

Ullah

Khan²,

Alam³

et al. 2022

IJAAS

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“…Cardiovascular disease is one of the contributing factors to the high mortality among hemodialysis patients [18] . Besides that, some of those patients died from hepatitis infection [19] .…”

Section: Introductionmentioning

confidence: 99%

Mortality of Hemodialysis Patients with Comorbidities at RSUP Prof Dr R.D Kandou, Manado, North Sulawesi

Lukas¹,

Ramatillah²,

Latuharhary³

et al. 2021

Advances in Health Sciences Research

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Background: Hemodialysis is a process in renal replacement function. Comorbid is one of the contributing factors for the high mortality among hemodialysis patients. Objective: To determine the correlation between comorbidities and duration of HD treatment and the effect of HD treatment duration on mortality rates in chronic kidney disease mortality patients undergoing hemodialysis. Methods: A retrospective cohort study was conducted in this study. This study included Hemodialysis patients with comorbid HD patients (DM, Hypertension and Congestive Heart disease) who died in 2018. The HD population was 560 patients (n=84) using convenience sampling method. The analysis was carried out using the Chi Square test and the Kruskall Wallis and Mann-Whitney test. Certificate of Ethical Eligibility from the Health Research Ethics Committee of RSUP DR R.D Kandou Manado no: 064/EC/KEPK-KANDAU/VII/2020. Results: The results of treatment were of 0-24 months (40.5 %), 25-48 months (33.3%) and > 48 months (26.2 %). The analysis showed a significant correlation between the duration of HD treatment and comorbidities in CKD patients undergoing HD, namely comorbid DM after HD (p=0.002), hypertension after HD (p=0.010), congestive heart failure after HD (p=0.003), with 2 comorbidities (p=0.048), and 3 comorbidities (p=0.011). Besides, the effect of the duration of HD treatment on the mortality rate is known that the duration of treatment >48 months gives a lower mortality rate with an average treatment time of 360 days. Conclusion: HD patients with the duration of treatment of 0-12 months died the most than the duration of treatment >25-48 months. There was a significant correlation between Comorbid-3 and the duration of HD treatment in CKD patients (p=0.011).

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Probability of Dying and Survival Analysis of Diabetic and/Hypertensive Patients Who Undergone Hemodialysis with Heart Disease Complication: A Comparison between a Hemodialysis Center Jakarta, Indonesia and Penang, Malaysia

Cited by 2 publications

References 2 publications

Heart disease classification using various heuristic algorithms

Heart disease classification using various heuristic algorithms

Mortality of Hemodialysis Patients with Comorbidities at RSUP Prof Dr R.D Kandou, Manado, North Sulawesi

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