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All Journal International Journal of Integrated Health Sciences Althea Medical Journal Indonesian Journal on Computing (Indo-JC) JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Cardiology Indonesian Journal of Obstetrics & Gynecology Science Building of Informatics, Technology and Science The International Journal of Medical Science and Health Research
Miftah Pramudyo
Department Of Cardiology And Vascular Medicine Faculty Of Medicine Universitas Padjadjaran/Dr. Hasan Sadikin General Hospital Bandung
Computer Science & IT Control & Systems Engineering Dentistry Electrical & Electronics Engineering Health Professions Medicine & Pharmacology Nursing Public Health Veterinary

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Correlation between MMP-9 Level and Diastolic Dysfunction in Concentric Left Ventricular Hypertrophy Patients Pramudyo, Miftah; Jungjunan, Ridho; Martanto, Erwan; Achmad, Chaerul
International Journal of Integrated Health Sciences Vol 9, No 1 (2021)
Publisher : Faculty of Medicine Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15850/ijihs.v9n1.2175

Abstract

Objective: To establish the relationship between plasma matrix metalloproteinase (MMP)-9 levels and diastolic functional abnormalities using the E/e’ measurement in concentric type Hypertensive Heart Disease (HHD) patients.Methods: A cross-sectional study was conducted from November 2014 to January 2015 in population with hypertension and concentric Left Ventricular Hypertrophy (LVH). Diastolic function was assessed with E/e’ measurement using echocardiography. The relationship between the two variables was analyzed using Spearman correlation.Results: Thirty-nine subjects (14 males, 35.9%) with the average relative wall thickness of 0.7(±0.15), average body weight of 63.45 (±12.97) kg, average height of 155.51 (±7.12) cm, average body mass index of 26.23 (±5.08) kg/m2, and mean age of 55 (±10) years were fit to be included in the analysis. The median systolic blood pressure was 140 (110-220) mmHg while the median diastolic blood pressure and median left ventricular mass index were 80 (70-110) mmHg and 119.24 (103.05-205.69) g/m2, respectively. The median MMP-9 was measured at 108 (4-460) ng/mL and the median E/e' was 10.99 (6.2-20.42). There was a significant positive correlation between MMP-9 and E/e' (r = 0.416, p = 0.004).Conclusion: There is a significant moderate positive correlation between the MMP-9 level and diastolic dysfunction in concentric LVH patients. 
Study of Denoising Method to Detect Valvular Heart Disease Using Phonocardiogram (PCG) Muhammad Yaumil Ihza Ihza; Satria Mandala; Miftah Pramudyo
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 1 (2022): April, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.1.610

Abstract

Heart sound is a very weak acoustic signal, very susceptible to external acoustic signals and electrical disturbances, especially friction caused by the subject's breathing or body movements. The heart sound signal will be recorded in a phonocardiogram (PCG) and produce heart sounds, noise, and extra sounds. The purpose of this work is to denoise the signal from the heart sounds recorded on the PCG and determine valvular heart disease (VHD). Several methods have been proposed for denoising heart sound signals, both in the time domain and in the frequency domain. Most of these methods still have problems for denoising results. In this paper, the techniques used to denoise the heart sound signal are Discrete Wavelet Transform (DWT), Short Term Fourier Transform (STFT), and Low-Pass filter.
Characteristics of In-Hospital Mortality among Patients with Acute Coronary Syndrome: A Single-Center Study in West Java, Indonesia Dennis Bonang Tessy; Miftah Pramudyo; Charlotte Johanna Cool
Althea Medical Journal Vol 8, No 2 (2021)
Publisher : Faculty of Medicine Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15850/amj.v8n2.2281

Abstract

Background: Acute Coronary Syndrome (ACS) is a severe manifestation of coronary artery disease, classified into unstable angina (UA), non-ST-segment elevation myocardial infarction (NSTEMI), and ST-segment elevation myocardial infarction (STEMI). In-hospital mortality in patients with ACS remains high despite the advancement of therapy. This study aimed to evaluate the characteristics of in-hospital mortality among ACS patients in West Java, Indonesia.Methods: This descriptive cross-sectional study analyzed retrospective secondary data of ACS patients who died during hospitalization in the period of July 2018 to June 2019 that were recorded in the ACS registry.Results: A total of 17 patients died during hospitalization in the study period. The mean age was 64.1 years, predominantly female (n=10). The prevalent diagnoses were STEMI (n=11) and NSTEMI (n=6). Interestingly, no patients had died from UA. Hypertension was the most frequent risk factor (11 of 17). Mortality among Killip Class I, II, III, and IV were 7, 5, 1, and 4 patients, respectively. The number of patients who died after underwent Percutaneous Coronary Intervention (PCI) was lower (n=6) than those who did not undergo PCI or those without revascularization (n=11).Conclusions: The incidence of in-hospital mortality with acute coronary syndrome is high in females, STEMI diagnosis, Killip Class I, and no revascularization.
Study of Machine Learning Algorithm on Phonocardiogram Signals for Detecting of Coronary Artery Disease Satria Mandala; Miftah Pramudyo; Ardian Rizal; Maurice Fikry
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 3 (2020): December, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.3.536

Abstract

Several methods of detecting coronary artery disease (CAD) have been developed, but they are expensive and generally use an invasive catheterization method. This research provides a solution to this problem by developing an inexpensive and non-invasive digital stethoscope for detecting CAD. To prove the effectiveness of this device, twenty-one subjects consisting of 11 CAD patients and 10 healthy people from Hasan Sadikin Hospital Bandung were selected as validation test participants. In addition, auscultation was carried out at four different locations around their chests, such as the aorta, pulmonary, tricuspid, and mitral. Then the phonocardiogram data taken from the stethoscope were analyzed using machine learning. To obtain optimal detection accuracy, several types of kernels such as radial basis function kernel (RBF), polynomial kernel and linear kernel of Support Vector Machine (SVM) have been analyzed. The experimental results show that the linear kernel outperforms compared to others; it provides a detection accuracy around 66%. Followed by RBF is 56% and Polynomial is 46%. In addition, the observation of phonocardiogram signals around the aorta is highly correlated with CAD, giving an average detection accuracy for the kernel of 66%; followed by 44% tricuspid and 43% pulmonary.
Performance Analysis of PPG Signal Denoising Method Using DWT and EMD for Detection of PVC and AF Arrhytmias: Analisis Performansi Metode Denoising Sinyal PPG Menggunakan DWT dan EMD untuk deteksi Aritmia PVC dan AF Muhammad Aniq Wafa; Satria Mandala; Miftah Pramudyo
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.648

Abstract

In the cardiac arrhythmia detection system using a Photoplethysmography (PPG) sensor, noise is often found in the PPG signal due to internal and external factors in the signal retrieval process. So it is necessary to do a denoising process to remove noise before the signal is used. This study aims to test the Discrete wavelet transform (DWT) and Empirical Mode Decomposition (EMD) methods in removing noise from the PPG signal and to test the denoising signal on the Premature Arrhythmia Verticular Contractions (PVC) and Atrial Fibrillation (AF) detection systems. The parameters used to compare the performance of the denoising method are Mean Square Error (MSE), Signal to Noise Ratio (SNR), Accuracy, F1, Precision, and Recall. The method with the highest SNR, Accuracy, F1, Precision, and Recall values ​​and the lowest MSE values ​​is the best denoising method.
Study of Classification Method to Detect Coronary Heart Disease Based On Signal Photoplethysmography (PPG) Azha Alvin Rahmansyah; Satria Mandala; Miftah Pramudyo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4823

Abstract

Coronary heart disease (CHD) is one of the deadliest diseases in the world, especially in Indonesia. This disease is caused by the accumulation of fat in blood vessels and can cause heart attacks that can endanger a person's health and safety. There are several methods for detecting CAD, such as using Electrocardiogram (ECG) signals and Photophlethysmograph (PPG) signals. However, studies that have tested machine learning classification methods to detect CAD using PPG signals are rarely found compared to detection using ECG. This study uses PPG signals taken from smartphone cameras to detect CHD, so that CHD detection is easier and affordable. To be able to diagnose CHD, machine learning assistance is needed to determine whether CHD is positive or negative. This study proposes a classification algorithm study to detect CAD. There are 3 classification methods used in this study. The three methods are KNN, SVM, and decision tree. The final results obtained in this study resulted in the best classification for KNN 81%, SVM 90%, and Decision Tree 90%. Each classification used has been carried out before and after tuning
A Study of Feature Selection Method to Detect Coronary Heart Disease (CHD) on Photoplethysmography (PPG) Signals Faizal Akbari Putra; Satria Mandala; Miftah Pramudyo
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2259

Abstract

Coronary Heart Disease (CHD) is a condition in which the heart's blood supply is blocked or disrupted by fat in the coronary arteries. This disease is the most significant cause of death in Indonesia. CHD can be detected based on the Heart Rate Variability (HRV) index of the Photophletysmograph (PPG) signal taken from a smartphone's camera. However, the use of PPG from smartphone to detect CHD is still rare in real-world applications. Moreover, studies on CHD detection based on PPG signal are also difficult to be found in the scientific literature. Currently, the Electrocardiogram (ECG) signal still dominates as a signal for detecting CHD. This research fills this research gap by proposing a study on the feature selection of PPG signal to detect CHD. There are three feature selection methods studied in this research, i.e., Analysis of Variance (Anova), Pearson Correlation, and Recursive Feature Elimination (RFE). Furthermore, a classification algorithm, called as K-Nearest Neighbors, has also been chosen to create a machine learning model based on the PPG features. The experimental results show that the Pearson Correlation feature selection method produces better CHD detection performance compared to the other two algorithms (Anova and RFE). CHD detection performance using the Pearson Correlation produces an accuracy of 90.9%, sensitivity of 75%, and specificity of 100%.
Study of Feature Extraction Method to Detect Myocardial Infraction Using a Phonocardiogram Ashydiki Malik; Satria Mandala; Miftah Pramudyo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6442

Abstract

Myocardial Infraction is one of the most dangerous and often fatal cardiovascular diseases. To detect this disease early, non-invasive methods based on Phonocardiogram (PCG) signals have become a significant focus of research. However, to present, research on feature extraction from PCG signals is still limited. In this research, we propose a study of feature extraction algorithms using Discrete Wavelet Transform (DWT), Mel Frequency Cepstral Coefficients (MFCC), and Entropy methods to detect heart attacks. In the pre-processing stage, we applied noisereduce to remove noise in the PCG signal. Further, we perform feature extraction using DWT, MFCC, and Entropy methods on the processed PCG signal. Following that, we used a detuned KNN with hyperparameters as the classification algorithm to classify the features into two categories: heart attack and non-heart attack. The test results show that DWT, MFCC, and Entropy-based feature extraction methods can make a significant contribution in detecting Myocardial Infraction. In comparison with other feature extraction algorithms, the test results show that the Entropy-based feature extraction method provides the best accuracy of 99%, with 99% sensitivity and 99% specificity. This research makes an important contribution to the development of heart attack detection methods using PCG signals. With promising results, the Entropy-based feature extraction method can be an effective and efficient approach in detecting coronary heart disease early, which in turn can improve patient prognosis and treatment.
Usefulness of The CHADS2 and CHA2DS2-VASc Scores in Predicting In-Hospital Mortality in Acute Coronary Syndrome Patients: A Single-Center Retrospective Cohort Study Pramudyo, Miftah; Putra, Iwan Cahyo Santosa; Pratama, Fahmi Bagus; Pranata, Raymond
Jurnal Kardiologi Indonesia Vol 44 No 1 (2023): Indonesian Journal of Cardiology: January - March 2023
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1294

Abstract

BackgroundAlthough the GRACE risk score is widely accepted as an established scoring system to predict in-hospital mortality in acute coronary syndrome (ACS) patients, this scoring system still depends on electrocardiography and laboratory findings to determine the results. Therefore, we aim to retrospectively evaluate the association between the CHADS2 and CHA2DS2-VASc score as an anamnesis-only mediated scoring system and in-hospital mortality in hospitalized ACS patients. MethodsThis retrospective cohort study analyzed data of ACS patients from the ACS registry in Dr. Hasan Sadikin Central General Hospital from 2018 to 2021. The outcome of this study was in-hospital mortality. The association between these scoring system and in-hospital mortality were evaluated using binary logistic regression analysis. Receiver operating characteristics (ROC) analysis was also performed to assess the success rate of this scoring system in predicting in-hospital mortality. ResultsA total of 1339 patients were included in this study, and 162 (12.1%) of them died in the hospital. High CHA2DS2-VASc score group (cut-off >2) was significantly associated with higher risk of in-hospital mortality before (OR=2.56 [1.75,3.75]; p<0.001) and after adjustment of several confounding factors (OR=3.39 [1.73,6.64]; p<0.001). Meanwhile, the high CHADS2 score (cutoff >2) was only significantly increased the risk of in-hospital mortality in univariate analysis (OR=2.05[1.47,2.87];p<0.001), but was not significantly associated with in-hospital mortality after multivariate analysis (OR=1.31 [0.92,1.86];p=0.129). ROC analysis revealed that predictive accuracy of CHA2DS2-VASc score was significantly greater compared to CHADS2 score (AUC: 0.653 vs 0.609, p<0.001). However, the predictive value of CHA2DS2-VASc score was significantly lower than the GRACE risk score (AUC: 0.789 vs 0.653, p<0.001). ConclusionOur study showed that the CHA2DS2-VASc score >2 was significantly and independently associated with higher in-hospital mortality in ACS patients compared to the CHA2DS2-VASc score of 1 or lower. Despite its lower predictive accuracy compared to the GRACE risk score, CHA2DS2-VASc score can still be used in practical situations as an alternative scoring system in predicting in-hospital mortality in ACS patients, especially in primary health care settings located in rural areas that lack the diagnostic facilities.This article has a related Erratum.
Management of Decongestion in Acute Heart Failure: Time for a New Approach? Pramudyo, Miftah; Putra, Iwan Cahyo Santosa; Zulkarnain, Edrian; Danny, Siska Suridanda; Bagaswoto, Hendry Purnasidha; Anjarwani, Setyasih; Mazwar, Irmaliyas; Juzar, Dafsah Arifa; Pratama, Vireza; Habib, Faisal; Ispar, Akhtar Fajar Muzakkir Ali; Widyantoro, Bambang
Jurnal Kardiologi Indonesia Vol 43 No 2 (2022): Indonesian Journal of Cardiology: April - June 2022
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1381

Abstract

As the primary cause of hospitalization in acute heart failure (AHF) patients, congestion was responsible for a higher risk of mortality, rehospitalization, and renal dysfunction in AHF patients. Although loop diuretic was routinely used as the mainstay of AHF therapy, it is still ineffective to obtain the euvolemic state in most hospitalized AHF patients. Therefore, a higher loop diuretic dose was often required to increase the decongestion effect. However, consequently, it can cause several detrimental complications, including renal dysfunction, neurohormonal activation, hyponatremia, hypokalaemia, and reduced blood pressure, which eventually result in poor prognosis. Hence, the new approach may be proposed to optimize decongestion in acute phase, including the use of arginine vasopressin V2 receptor antagonist – Tolvaptan. As an additive therapy to loop diuretic in AHF patients, it can be considered due to its several beneficial effects, including greater decongestion effect, lowered worsening renal function incidence, counteract neurohormonal activation, neutralized hyponatraemic state, no alteration of potassium metabolism, stabilize the blood pressure, and reduced requirement of a higher dose of loop diuretic to achieve an equal or even greater decongestion effect compared to a high dose of loop diuretic alone. Tolvaptan provided favourable outcomes in several specific populations and was considered safe with several mild adverse effects. Several guidelines across countries have approved the use of Tolvaptan in AHF patients with or without hyponatremia. The initial dose of Tolvaptan was 7.5 to 15 mg and can be titrated up to 30 mg. However, further studies were still required to determine the timing dose and optimal dose of Tolvaptan in general and elderly populations with AHF, respectively.This article has a related Erratum.
Co-Authors Adhi Pribadi Akbar, Mohammad Rizki Andria Priyana Anjarwani, Setyasih Aqilah, Nurjihan Syarifah Ardian Rizal Ashydiki Malik Astiawati, Tri ASTRI ASTUTI Augustine Purnomowati Azha Alvin Rahmansyah Aziz, Muhammad Alamsyah Bambang Widyantoro Chaerul Achmad Chaerul Achmad Charlotte Johanna Cool Charlotte Johanna Cool Cool, Charlotte Johanna Danny, Hendry Purnasidha Dennis Bonang Tessy Dhiya Ihsan Ramadhan Endang, Jusup Erwan Martanto Faizal Akbari Putra Fikry, Maurice Frisky Ronald Tua Marbun Habib, Faisal Hakim, Afdhalun Hawani Sasmaya Prameswari Hendry Purnasidha Bagaswoto Ilhami, Yose Ramda Ispar, Akhtar Fajar Muzakkir Ali Jungjunan, Ridho Juzar, Dafsah Arifa Karwiky, Giky Kusumawardhani, Nuraini Yasmin Maurice Fikry Mazwar, Irmaliyas Mohammad Iqbal Mohammad Rizki Akbar Muhammad Aniq Wafa Muhammad Yaumil Ihza Ihza Muzakkir, Akhtar Fajar Nahar Taufiq, Nahar Pranata, Raymond Pratama, Fahmi Bagus Pratama, Vireza Putra, Iwan Cahyo Santosa Putra, Ridwan Abdullah R A, I Made Junior Raharjo, Pradana Pratomo Rheza Felari Simanjuntak Rhinza Seputra Simanjuntak Rizal, Ardian Satria Mandala Siska Suridanda Danny Tatyana Sianipar Zulkarnain, Edrian