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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Indonesian Journal of Cardiology
Oktavia Lilyasari
Faculty of Medicine, University of Indonesia/ Harapan Kita National Cardiovascular Center
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Health Professions Mathematics Mechanical Engineering Medicine & Pharmacology Physics Transportation

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Pengaruh Tricuspid Annular Plane Systolic Excursion (TAPSE) Pasca Pembedahan Katup Mitral Terhadap Mortalitas Jangka Panjang Erriyanti, Sabrina; Soesanto, Amiliana M; Sakidjan, Indriwanto; Atmosudigdo, A.; Lilyasari, Oktavia; Ariani, Rina; Siagian, Sisca Natalia
Jurnal Kardiologi Indonesia Vol 43 No 1 (2022): Indonesian Journal of Cardiology: January - March 2022
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1196

Abstract

Background: Heart valve disease is still a significant health burden in the world, including Indonesia. The postoperative outcome of mitral valve surgery is influenced by many things, including decreased right ventricular (RV) function, which is the most common complication. Several studies have shown that decreased RV function after mitral valve surgery is associated with long-term outcomes. TAPSE is a routine and easy measurement of RV systolic function. A decrease in TAPSE after cardiac surgery is common because of the effects of pericardiotomy, and does not necessarily reflect a decrease in RV ejection fraction (RVEF). Regardless of whether postoperative TAPSE values ​​indicate right ventricular systolic function or only due to the effects of pericardiotomy, it is still not clear whether postoperative TAPSE values ​​have a prognostic value to long-term mortality after mitral valve surgery. Therefore, the objective of this study is to obtain information regarding the relationship of TAPSE echocardiographic parameters after mitral valve surgery with long-term mortality. Methods: This is a retrospective cohort study, looking at the effect of TAPSE on outcome after mitral valve surgery. The analysis starts from the starting point of the study when the patient was discharged alive from the hospital after mitral valve surgery (operation period January 2016 – February 2017) to the end point of the study, which was June 30th, 2021 and the observed outcome was mortality from any cause. Results: Of the 266 study subjects, 11 subjects died within 4-5 years after mitral valve surgery, the mortality is 4%. Bivariate analysis was performed on several factors and no relationship was found between the analyzed variables and mortality. Conclusion: There is no relationship between mortality and TAPSE after mitral valve surgery. This article has a related Erratum.
FUZZY LOGISTIC REGRESSION APPLICATION ON PREDICTIONS CORONARY HEART DISEASE Febriani, Vera; Lestari, Dian; Mardiyati, Sri; Lilyasari, Oktavia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.119 KB) | DOI: 10.30598/barekengvol17iss1pp0571-0580

Abstract

According to the World Health Organization (WHO) in 2015, 70% of cardiac deaths were caused by coronary heart disease (CHD). Based on WHO data in 2017, 17.5 million deaths were recorded, equivalent to 30% of the total deaths in the world caused by coronary heart disease. Coronary heart disease is a disorder of heart function caused by plaque that accumulates in arterial blood vessels so that it interferes with the supply of oxygen to the heart tissue. This causes reduced blood flow to the heart muscle and oxygen deficiency occurs. In more serious circumstances, it can result in a heart attack. Risk factors for coronary heart disease include age, gender, hypertension, cholesterol, heredity, diabetes mellitus, obesity, dyslipidemia, smoking and lack of physical activity. If a person's chances of suffering from coronary heart disease can be predicted early based on the existing risk factors, then the mortality rate of coronary heart disease can be suppressed. The objective of this study is to build a model that can predict the possibility of a patient suffering from coronary heart disease. The study used the Fuzzy Logistic Regression model. This model was used to maximize prediction results in which data size was limited. The least square method was used to estimate the value of the parameter. We obtained from National Cardiovascular Center Harapan Kita, Jakarta. Evaluation with the Mean Degree of Membership method showed that the model built was feasible and good enough to predict coronary heart disease. By using the confusion matrix, the accuracy of the prediction model is 80.00%, with a specificity of 42.85% and a sensitivity of 100%.
Simple Scoring System for Predicting In-Hospital Mortality after Heart Valve Surgery in A Developing Country Soesanto, Amiliana M; Asmuni, Melyana; Lilyasari, Oktavia; Husink, Aron; Ariyanti, Novi; Hardjosworo, Arinto Bono Adji
Jurnal Kardiologi Indonesia Vol 42 No 4 (2021): Indonesian Journal of Cardiology: October - December 2021
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1174

Abstract

Background: Various scoring systems predict mortality after cardiac surgery, but not many were designed for specific valvular surgery. Developing countries have different characteristics of patients and conditions in cardiac centers compare to developed countries. We aimed to develop a simple scoring system for predicting in-hospital mortality after valve surgery and further validate the scoring system. Methods: For developing the scoring system, the data was taken from the medical record of patient underwent valve surgery in 2012 - 2014, and for the validation study, it was from 2015 to 2016. The scoring system was developed using logistic regression models, then validated using calibration and discrimination analysis. Result: For developing a scoring system, we recruited 1040 patients in the study. The in-hospital mortality rate was 68 (6.5%). Eight variables were incorporated, including; functional class, hypertension, previous open-heart surgery, impaired renal function, right ventricular dysfunction, emergent operation, coronary artery bypass surgery, and tricuspid valve surgery. The mortality risk score has Hosmer Lemeshow (H-L) test p-value = 0.212; AUC = 0.813 (CI 95% = 0.758–0.867); and cut-off point of 5, predicting 14% risk of death (sensitivity 72.1%, specificity 75.3%). In the validation study, 789 subjects were recruited. The observed and predicted mortality were 8.6% and 11.9% respectively, with H-L test p-value = 0.169 and AUC 0.761 (95% CI; 0.702-0.821) Conclusion: We have developed a simple scoring system for predicting in-hospital mortality after valve surgery. The mortality risk score was well-calibrated with a moderate discrimination value in the validation study.
The Impact of Tricuspid Annular Plane Systolic Excursion (TAPSE) After Mitral Valve Surgery on Long Term Mortality Erriyanti, Sabrina; Soesanto, Amiliana M; Sakidjan, Indriwanto; Atmosudigdo, A.; Lilyasari, Oktavia; Ariani, Rina; Siagian, Sisca Natalia
Jurnal Kardiologi Indonesia Vol 46 No 4 (2025): October - December, 2025
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.2003

Abstract

In “The Impact of Tricuspid Annular Plane Systolic Excursion (TAPSE) After Mitral Valve Surgery on Long Term Mortality” (Indonesian Journal of Cardiology, 43(1), 1-8. https://doi.org/10.30701/ijc.1196), there is an error noted. An error has been found in the PDF version of this article. The DOI printed in the PDF is incorrect. The correct DOI is https://doi.org/10.30701/ijc.1196. The error occurs only in the PDF; the DOI listed in the article metadata is already correct. The publisher apologizes for any inconvenience caused by this error. DOI of original article: https://doi.org/10.30701/ijc.1196
Co-Authors Amiliana M Soesanto Ariani, Rina Ariyanti, Novi Asmuni, Melyana Atmosudigdo, A. DIAN LESTARI Erriyanti, Sabrina Febriani, Vera Hardjosworo, Arinto Bono Adji Husink, Aron Indriwanto Sakidjan Sisca Natalia Siagian Sri Mardiyati