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All Journal Indonesian Journal of Cardiology
Liastuti, Lies Dina
Bagian Kardiologi Fakultas Kedokteran Universitas Indonesia Rumah Sakit Jantung Harapan Kita, Jakarta
Health Professions Medicine & Pharmacology

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Efek Enhanced External Counterpulsation Terhadap Perbaikan Kontraktilitas Miokard yang masih viabel pada penderita penyakit jantung koroner Utojo Lubiantoro; Fadilah Supari; Lies Dina Liastuti
Jurnal Kardiologi Indonesia Vol. 26, No. 1 Januari - Maret 2002
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.v26i1.271

Abstract

Objective: To obtain data about the effect of EECP on dysfunctional but viable myocardial contractility in patient with coronary heart disease.Methods: This is an experimental study which include twenty male coronary heart disease but viable myocardium. Before EECP treatment, all subjects under 2D echocardiographic examination and myocardial contractility was measured as WMSI. Patients is given EECP 1 hour daily (5-6 times a week) for a total of 36 hours. Immediately after EECP treatment, WMSI is measured again for each subject. The value between before and after EECP treatment is analyzed with Wilcoxon signed rank test. Significant result if p < 0,05.Results: WMSI decreased after EECP treatment from 1,58+0,39 to 1,53+0,40, but the difference was not significant.Conclusion: EECP does not improve dysfunctional but viable myocardial contractility in patients with coronary heart disease
Cryptogenic Stroke: Cardiac Rhythm Monitoring as An Indispensable Screening Modality Sunu Budhi Raharjo; Sarah Humaira; Lies Dina Liastuti
Jurnal Kardiologi Indonesia Vol 42 No 3 (2021): Indonesian Journal of Cardiology: July - September 2021
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1143

Abstract

The prevalence of stroke in Indonesia increased overtime. CS ranges from 15 to 40% from all ischemic strokes. Finding the etiology of ischemic stroke is important to prevent recurrence. AF is predicted as the etiology behind CS. The current recommendation only supports short period of ECG monitoring. However, studies have shown that a higher detection rate can be achieved with longer duration of monitoring. ICM, a diagnostic tool with the highest detection rate, is still considered cost-effective when the calculation takes into account the QALY gained. Digital health tools such as handheld devices and smartwatch ECG have revolutionized the screening of AF however it is still considered as pre-diagnostic and verification is needed to confirm the rhythm generated.
Exploring Clinical and Echocardiographic Factors in EHRA Type 2 Atrial Fibrillation for Predicting Ischaemic Stroke: A Search for Unrevealed Insights Simbolon, Jessica Putri Natalia; Raharjo, Sunu Budhi; Santoso, Anwar; Liastuti, Lies Dina; Hermanto, Dony Yugo; Rossimaria, Vienna; Pritazahra, Armalya; Hanafy, Dicky Armein; Yuniadi, Yoga
Jurnal Kardiologi Indonesia Vol 44 No 3 (2023): Indonesian Journal of Cardiology: July - September 2023
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1562

Abstract

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia in adults. Valvular heart diseases (VHD), regardless of the arrhythmic problems, increase the risk of thromboembolism, which are even higher in those with associated atrial fibrillation. The EHRA (Evaluated Heartvalves, Rheumatic or Artificial) classification categorised AF patients with significant VHD into type 1 and type 2. Unfortunately, there are currently very limited data on risk prediction in stroke-related valvular AF, particularly in the Asian population. Aims: To investigate the clinical and echocardiographic risk factors for ischaemic stroke prediction in patients with EHRA type 2 VHD. Methods: This retrospective study enrolled 695 AF patients with EHRA type 2 VHD. The data were collected from patients' medical records who met the inclusion and exclusion criteria from 2015 until 2020. The primary outcome was ischaemic strokes within observation period. Results: There were 67 ischaemic stroke events (9,6%) of the total sample. Our analysis found that none of the analysed variables proved to be statistically significant risk factors in predicting the occurrence of ischaemic stroke. The median CHA2DS2-VASc risk prediction in the sample was 3, with an accuracy of AUC 0.502 (CI 95%; 0.429 – 0.576), sensitivity 56.7% and specificity 44.7%. Conclusion: Based on the parameters analysed in this study, no factor was statistically well-predictive to predict the ischaemic stroke incidence in EHRA type 2 VHD AF. In addition, the CHA2DS2-VAS accuracy was low in this population. Further exploration is needed to build an accurate ischaemic stroke risk prediction for EHRA type 2 VHD.This article has a related Erratum.
The Use of Artificial Intelligence (AI) to Predict Heart Failure in Type II Diabetes Mellitus Patients: A Systematic Review Liastuti, Lies Dina; Suwana, Averina Geffanie; Muharrom, Muhammad Aji; Irfannadhira, Aruni Cahya; Nursakina, Yosilia
Jurnal Kardiologi Indonesia Vol 44 No 4 (2023): Indonesian Journal of Cardiology: October - December 2023
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1689

Abstract

Heart failure (HF) is a critical concern for individuals with Type II Diabetes Mellitus (T2DM), significantly increasing morbidity and mortality rates. Artificial Intelligence (AI) and machine learning hold promise in enhancing predictive capabilities and guiding personalised interventions. This systematic review evaluates existing AI models' effectiveness in predicting HF complications in T2DM patients. A comprehensive literature search identified 8 relevant studies, predominantly from European, North American, and Southeastern populations. These studies utilised multi-centered registries and electronic medical records to develop AI models predominantly focused on supervised learning algorithms. While the AI models had promising performance, these models lack external validation with diverse populations and reproducibility, hindering their clinical applicability. Moreover, variations in outcome definitions and input features underscore the need for standardised approaches. Despite these limitations, AI models offer valuable insights into HF risk assessment in T2DM, highlighting the importance of further validation and reproducibility for clinical integration.
Longitudinal Strain Assessment Of Myocardial Dysfunction In Covid-19 Patients: Correlating Clinical Symptoms And Laboratory Results At Admission And Four Months Post-Treatment Liastuti, Lies Dina; Tanto, Ines Vidal; Rachman, Aditya; Robot, Marselly Maria; Dwiputra1, Bambang; Ariani, Rina; Danny, Siska Suridanda; Taofan, Taofan; Sukmawan, Renan
Jurnal Kardiologi Indonesia Vol 45 No 1 (2024): January - March, 2024
Publisher : The Indonesian Heart Association

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30701/ijc.1685

Abstract

Background: Myocardial dysfunction is increasingly recognized as a complication of COVID-19 infection, with implications for patient prognosis and long-term cardiovascular health. Longitudinal strain, measured via echocardiography, is a sensitive marker of myocardial function that may provide valuable insights into cardiac involvement in COVID-19 patients. This study aimed to assess myocardial dysfunction using longitudinal strain analysis in COVID-19 patients, correlating clinical symptoms and laboratory results at admission and four months post-treatment. Methods : This study compared clinical and laboratory parameters in COVID-19 patients post-recovery with and without myocardial dysfunction. Adult COVID-19 survivors were included if they were hospitalized and met certain criteria. Independent variables included clinical factors and laboratory factors at admission, while the dependent variable was myocardial dysfunction assessed through longitudinal strain of the left and right ventricles on speckle tracking echocardiography. The study was conducted at the Harapan Kita Heart and Blood Vessel Center (RSJPDHK - FKUI)/Department of Cardiology and Vascular Medicine, Faculty of Medicine, University of Indonesia, Jakarta. Results: This study examined the cardiovascular health of 162 participants three months after getting infected with COVID-19. Those with comorbidities had the lowest LV GLS levels. Admission factors like obesity, SpO2, and PaO2 levels were linked to decreased LV GLS levels. These findings suggest that these admission factors may predict the progression of COVID-19 syndrome and its implications on cardiovascular health. Conclusion: COVID-19 patients with cardiovascular comorbidities have lower LV-GLS values. CAD status during admission affects LV GLS values 3-6 months after COVID-19 infection, indicating myocardial dysfunction. Basal lateral LV-GLS correlates with obesity status, SpO2, and PaO2 during admission. Closely monitor COVID-19 patients with cardiovascular comorbidities and recognize the implications of CAD status on myocardial function post-infection.
Exploring Clinical and Echocardiographic Factors in EHRA Type 2 Atrial Fibrillation for Predicting Ischaemic Stroke: A Search for Unrevealed Insights Simbolon, Jessica Putri Natalia; Raharjo, Sunu Budhi; Santoso, Anwar; Liastuti, Lies Dina; Hermanto, Dony Yugo; Rossimarina, Vienna; Pritazahra, Armalya; Hanafy, Dicky Armein; Yuniadi, Yoga
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.2022

Abstract

In “Exploring Clinical and Echocardiographic Factors in EHRA Type 2 Atrial Fibrillation for Predicting Ischaemic Stroke: A Search for Unrevealed Insights” (Indonesian Journal of Cardiology, 44(3), 87-94. https://doi.org/10.30701/ijc.1562), 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.1562. 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.1562
Co-Authors Aditya Rachman, Aditya Anwar Santoso Ariani, Rina Dicky Armein Hanafy Dwiputra1, Bambang Fadilah Supari Hermanto, Dony Yugo Irfannadhira, Aruni Cahya Muharrom, Muhammad Aji Nursakina, Yosilia Pritazahra, Armalya Renan Sukmawan Robot, Marselly Maria Rossimaria, Vienna Rossimarina, Vienna Sarah Humaira Simbolon, Jessica Putri Natalia Siska Suridanda Danny Sunu Budhi Raharjo Suwana, Averina Geffanie Tanto, Ines Vidal Taofan, Taofan Utojo Lubiantoro Yoga Yuniadi