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  1. Ngew KY, Tay HZ, Yusof AKM
    BMC Cardiovasc Disord, 2023 Nov 08;23(1):545.
    PMID: 37940867 DOI: 10.1186/s12872-023-03536-w
    PURPOSE: Percutaneous coronary intervention (PCI) is a common treatment modality for coronary artery disease. Accurate prediction of patients at risk for complications and hospital readmission after PCI could improve the overall clinical management. We aimed to develop and validate predictive models to predict any cardiac event within a year post PCI procedure.

    METHODS: This is a retrospective cohort study utilizing data from the National Cardiovascular Disease (NCVD)-PCI registry. The data collected (N = 28,007) were split into training set (n = 24,409) and testing set (n = 3598). Four predictive models (logistic regression [LR], random forest method, support vector machine [SVM], and artificial neural network) were developed and validated. The outcome on risk prediction were compared.

    RESULTS: The demographic and clinical features of patients in the training and testing cohorts were similar. Patients had mean age ± standard deviation of 58.15 ± 10.13 years at admission with a male majority (82.66%). In over half of the procedures (50.61%), patients had chronic stable angina. Within 1 year of follow up mortality, target vessel revascularization (TVR), and composite event of mortality and TVR were 3.92%, 9.48%, and 12.98% respectively. LR was the best model in predicting mortality event within 1-year post-PCI (AUC: 0.820). SVM had the highest discrimination power for both TVR event (AUC: 0.720) and composite event of mortality and TVR (AUC: 0.720).

    CONCLUSIONS: This study successfully identified optimal prediction models with the good discriminatory ability for mortality outcome and good discrimination ability for TVR and composite event of mortality and TVR with a simple machine learning framework.

  2. Nizar MHA, Chan CK, Khalil A, Yusof AKM, Lai KW
    Curr Med Imaging, 2020;16(5):584-591.
    PMID: 32484093 DOI: 10.2174/1573405615666190114151255
    BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular heart disease. However, the images from echocardiogram are poor in comparison to Computerized Tomography and Magnetic Resonance Imaging scan. This study proposes the development of Convolutional Neural Networks (CNN) that can function optimally during a live echocardiographic examination for detection of the aortic valve. An automated detection system in an echocardiogram will improve the accuracy of medical diagnosis and can provide further medical analysis from the resulting detection.

    METHODS: Two detection architectures, Single Shot Multibox Detector (SSD) and Faster Regional based Convolutional Neural Network (R-CNN) with various feature extractors were trained on echocardiography images from 33 patients. Thereafter, the models were tested on 10 echocardiography videos.

    RESULTS: Faster R-CNN Inception v2 had shown the highest accuracy (98.6%) followed closely by SSD Mobilenet v2. In terms of speed, SSD Mobilenet v2 resulted in a loss of 46.81% in framesper- second (fps) during real-time detection but managed to perform better than the other neural network models. Additionally, SSD Mobilenet v2 used the least amount of Graphic Processing Unit (GPU) but the Central Processing Unit (CPU) usage was relatively similar throughout all models.

    CONCLUSION: Our findings provide a foundation for implementing a convolutional detection system to echocardiography for medical purposes.

  3. Yusof AKM, Halil NM, Jaffar N, Sabian IS, Looi ZL
    Malays J Med Sci, 2023 Oct;30(5):116-128.
    PMID: 37928782 DOI: 10.21315/mjms2023.30.5.10
    BACKGROUND: Uncontrolled hypertension can cause cardiovascular disease and is an important public health issue. Single-pill combination (SPC) therapies possess combined blood pressure (BP)-lowering effect and may improve compliance to treatment. This study assessed the effectiveness of valsartan (Val)-based SPC therapies in achieving BP control in hypertensive patients.

    METHODS: This was a retrospective study. Data were extracted from the hybrid medical records of patients from the Institut Jantung Negara (IJN), Malaysia. Adults with established diagnosis of hypertension and on prescription of Val-based SPC therapies as part of routine medical care from 1 January 2013 to 31 December 2018, with ≥ 1 year of follow-up were included. Primary endpoint was proportion of patients achieving therapeutic BP control (BP < 140/90 mmHg). Secondary outcomes included change from baseline (CFB) in systolic BP (SBP) and diastolic BP (DBP), and subgroup analysis was based on baseline SBP categories and presence of diabetes.

    RESULTS: Study included 409 hypertensive patients. The mean (standard deviation [SD]) age of the population was 65.1 (10.6) years old, with male predominance (61.6%). Proportion of patients achieving target BP between baseline and follow-up were 57.0% (P < 0.001). Mean CFB in SBP and DBP were recorded as 19.52 mmHg and 7.47 mmHg, respectively. Over half of the patients achieved the target BP in all subgroups categorised by SBP at baseline, except the subgroup of SBP 160 mmHg-179 mmHg. SPC therapies were continued in 97.3% of patients at 1-year follow-up.

    CONCLUSION: Patients using Val-based SPC therapies had significant reduction in BP with good tolerability, with 57% of patients achieving target BP over a prolonged 1-year follow-up period. Uptake of SPC therapy is warranted to improve patient care and outcomes in hypertension.

  4. Nuruddin AAB, Ahmad WAW, Waliszewski M, Heang TM, Bang LH, Yusof AKM, et al.
    Cardiol Ther, 2021 Jun;10(1):175-187.
    PMID: 33275200 DOI: 10.1007/s40119-020-00204-4
    INTRODUCTION: The objective of this study was to compare the accumulated clinical outcomes of two Malaysian all-comers populations, each treated with different polymer-free sirolimus-eluting stents (PF-SES) of similar stent design.

    METHODS: The Malaysian subpopulation of two all-comers observational studies based on the same protocol (ClinicalTrials.gov Identifiers: NCT02629575 and NCT02905214) were combined and compared to a Malaysian-only cohort which was treated with a later-generation PF-SES. The PF-SES's used differed only in their bare-metal backbone architecture, with otherwise identical sirolimus coating. The primary endpoint was the accumulated target lesion revascularization (TLR) rate at 12 months. The rates of major adverse cardiac events (MACE), stent thrombosis (ST) and myocardial infarction (MI) were part of the secondary endpoints.

    RESULTS: A total of 643 patients were treated with either the first-generation PF-SES (413 patients) or second-generation PF-SES (230 patients). Patient demographics were similar in terms of age (p = 0.744), male gender (0.987), diabetes mellitus (p = 0.293), hypertension (p = 0.905) and acute coronary syndrome (ACS, 44.8% vs. 46.1%, p = 0.752) between groups. There were no differences between treatment groups in terms of lesion length (20.8 ± 7.3 mm vs. 22.9 ± 7.9, p = 0.111) or vessel diameter (2.87 ± 0.39 vs. 2.93 ± 0.40, p = 0.052) despite numerically smaller diameters in the first-generation PF-SES group. The second-generation PF-SES tended to have more complex lesions as characterized by calcification (10.3% vs. 16.2%, p = 0.022), severe tortuosity (3.5% vs. 6.9%, p = 0.041) and B2/C lesions (49.2% vs. 62.8%, p 

  5. Yunus MM, Sabarudin A, Karim MKA, Nohuddin PNE, Zainal IA, Shamsul MSM, et al.
    Diagnostics (Basel), 2022 Aug 19;12(8).
    PMID: 36010355 DOI: 10.3390/diagnostics12082007
    Atherosclerosis is known as the leading factor in heart disease with the highest mortality rate among the Malaysian population. Usually, the gold standard for diagnosing atherosclerosis is by using the coronary computed tomography angiography (CCTA) technique to look for plaque within the coronary artery. However, qualitative diagnosis for noncalcified atherosclerosis is vulnerable to false-positive diagnoses, as well as inconsistent reporting between observers. In this study, we assess the reproducibility and repeatability of segmenting atherosclerotic lesions manually and semiautomatically in CCTA images to identify the most appropriate CCTA image segmentation method for radiomics analysis to quantitatively extract the atherosclerotic lesion. Thirty (30) CCTA images were taken retrospectively from the radiology image database of Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, Malaysia. We extract 11,700 radiomics features which include the first-order, second-order and shape features from 180 times of image segmentation. The interest vessels were segmentized manually and semiautomatically using LIFEx (Version 7.0.15, Institut Curie, Orsay, France) software by two independent radiology experts, focusing on three main coronary blood vessels. As a result, manual segmentation with a soft-tissuewindowing setting yielded higher repeatability as compared to semiautomatic segmentation with a significant intraclass correlation coefficient (intra-CC) 0.961 for thefirst-order and shape features; intra-CC of 0.924 for thesecond-order features with p < 0.001. Meanwhile, the semiautomatic segmentation has higher reproducibility as compared to manual segmentation with significant interclass correlation coefficient (inter-CC) of 0.920 (first-order features) and a good interclass correlation coefficient of 0.839 for the second-order features with p < 0.001. The first-order, shape order and second-order features for both manual and semiautomatic segmentation have an excellent percentage of reproducibility and repeatability (intra-CC > 0.9). In conclusion, semi-automated segmentation is recommended for inter-observer study while manual segmentation with soft tissue-windowing can be used for single observer study.
  6. Bonaventura K, Schwefer M, Yusof AKM, Waliszewski M, Krackhardt F, Steen P, et al.
    Adv Ther, 2020 05;37(5):2210-2223.
    PMID: 32274746 DOI: 10.1007/s12325-020-01320-2
    INTRODUCTION: Scoring balloon angioplasty (SBA) for lumen gain prior to stent implantations or drug-coated balloon angioplasty (DCB) is considered an essential interventional tool for lesion preparation. Recent evidence indicates that SBA may play a pivotal role in enhancing the angiographic and clinical outcomes of DCB angioplasty.

    METHODS: We studied the systematic use of SBA with a low profile, non-slip element device prior to DCB angioplasty in an unselected, non-randomized patient population. This prospective, all-comers study enrolled patients with de novo lesions as well as in-stent restenotic lesions in bare metal stents (BMS-ISR) and drug-eluting stents (DES-ISR). The primary endpoint was the target lesion failure (TLF) rate at 9 months (ClinicalTrials.gov Identifier NCT02554292).

    RESULTS: A total of 481 patients (496 lesions) were recruited to treat de novo lesions (78.4%, 377), BMS-ISR (4.0%, 19), and DES-ISR (17.6%, 85). Overall risk factors were acute coronary syndrome (ACS, 20.6%, 99), diabetes mellitus (46.8%, 225), and atrial fibrillation (8.5%, 41). Average lesion lengths were 16.7 ± 10.4 mm in the de novo group, and 20.1 ± 8.9 mm (BMS-ISR) and 16.2 ± 9.8 mm (DES-ISR) in the ISR groups. Scoring balloon diameters were 2.43 ± 0.41 mm (de novo), 2.71 ± 0.31 mm (BMS-ISR), and 2.92 ± 0.42 mm (DES-ISR) whereas DCB diameters were 2.60 ± 0.39 mm (de novo), 3.00 ± 0.35 mm (BMS-ISR), and 3.10 ± 0.43 mm (DES-ISR), respectively. The overall accumulated TLF rate of 3.0% (14/463) was driven by significantly higher target lesion revascularization rates in the BMS-ISR (5.3%, 1/19) and the DES-ISR group (6.0%, 5/84). In de novo lesions, the TLF rate was 1.1% (4/360) without differences between calcified and non-calcified lesions (p = 0.158) and small vs. large reference vessel diameters with a cutoff value of 3.0 mm (p = 0.901).

    CONCLUSIONS: The routine use of a non-slip element scoring balloon catheter to prepare lesions suitable for drug-coated balloon angioplasty is associated with high procedural success rates and low TLF rates in de novo lesions.

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