Effects of the COVID-19 pandemic on the management of ST-Segment elevation myocardial infarction in Indonesia: a cohort study [version 1; peer review: 2 approved]

Background: ST-segment elevation myocardial infarction (STEMI) is a form of acute coronary syndrome with high mortality rate. Management of STEMI should be performed as soon as possible to prevent further damage. With the emergence of coronavirus disease 2019 (COVID-19), it may face obstacles. To overcome those problems, some changes in policy focusing on fibrinolytic therapy in STEMI patients have been applied. This study aimed to identify the effects of COVID-19 in management of STEMI patients in Indonesia. Methods: This retrospective study was conducted in Dr. Cipto Mangunkusumo Hospital (CMH), the national referral center in Indonesia. We compared data between 2018 to 2019 and 2020 to 2021 as before and during COVID-19 pandemic period, respectively. We analyzed the effects of COVID-19 on STEMI patients' visits to hospital i.e., monthly hospital admission and symptoms-to-hospital, management of STEMI i.e., the strategies and time of reperfusion, and clinical outcomes of STEMI patients i.e., major adverse coronary event and mortality. Results: There was a significant statistically reduced mean of monthly hospital admissions from 11 to 7 (p = 0.002) and prolonged duration of symptoms-to-hospital during COVID-19 from 8 to 12 hours (p = 0.005). There was also a decrease in primary percutaneous coronary intervention (PPCI) procedures during COVID-19 (65.2% vs. 27.8%, p<0.001), which was accompanied by an increased number of fibrinolytic (1.5% vs. 9.5%, p<0.001) and conservative therapy (28.5% vs. 55.6%, p <0.01). Moreover, there was also a prolonged duration of diagnosis-to-wire-crossing time (160 vs. 186 minutes, p = 0.005), meanwhile, percentage of urgent PCI, door-to-needle time, and clinical outcomes were not statistically significant. Conclusions: During COVID-19 pandemic, the number STEMI patients declined in monthly hospital admission, delays in symptoms-to-hospital time, changes in type of reperfusion strategy, and delays in PPCI procedures in CMH. Meanwhile, fibrinolytic time and clinical outcomes were not affected

Efek Enhanced External Counterpulsation Terhadap Perbaikan Kontraktilitas Miokard yang masih viabel pada penderita penyakit jantung koroner

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 &lt; 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 diseaseTujuan: Untuk mendapatkan data tentang efek dari EECP terhadap perbaikan fungsi kontraktilitas miokard yang disfungsi tapi masih viabel pada penderita penyakit jantung koroner.Metoda: Penelitian ini merupakan penelitian eksperimental yang melibatkan dua puluh pasien penderita penyakit jantung koroner dengan fungsi kontraktilitas miokard yang disfungsi tapi masih viabel. Sebelum terapi EECP 1 jam setiap hari (5-6 kali seminggu) secara totoal merupakan 36 jam. Segera setelah terapi EECP, WMSI diukur kembali untuk setiap subjek. Perbedaan nilai antara sebelum dan sesudah terapi EECP dianalisa dengan test ranking tertanda Wilcoxon. Hasil yang bermakna bila p &lt; 0,05.Hasil: WMSI menurun setelah terapi EECP dari 1,58+0,39 sampai 1,53+0,040, tetapi perbedaannya tidak bermakna (p=0,25). WMSI dari 11 subyek (57,9%) menurun, 3 subyek (15,8%) meningkat dan 5 subyek (26,3%) tidak berubah. Rasio D/S selama terapi EECP berkisar 1,1 sampai 2,6 dengan rerata dari 1,64+0,32. Tidak terlihat adanya efek samping selama terapi EECP.Kesimpulan: EECP tidak meningkatkan perbaikan fungsi kontraktilitas miokard yang disfungsi tapi masih viabel pada penderita penyakit jantung koroner

Cryptogenic Stroke: Cardiac Rhythm Monitoring as An Indispensable Screening Modality

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

Impacts of the COVID-19 Pandemic on the CODE ST-Segment Elevation Myocardial Infarction Program: A Quantitative and Qualitative Analysis

Background: The code ST-segment elevation myocardial infarction (STEMI) program is an operational standard of integrated service for STEMI patients carried out by Dr. Cipto Mangunkusumo Hospital. The emerging coronavirus disease 2019 (COVID-19) outbreak brought about many changes in the management of healthcare services, including the code STEMI program. This study aimed to evaluate the healthcare service quality of the Code STEMI program during the COVID-19 pandemic based on the Donabedian concept.  Methods: This was a mixed-methods study using quantitative and qualitative analyses. It was conducted at the Dr. Cipto Mangunkusumo Hospital, a national referral hospital in Indonesia. We compared the data of each patient, including response time, clinical outcomes, length of stay, and cost, from two years between 2018–2020 and 2020–2022 as the pre-COVID-19 code STEMI and COVID-19 Code STEMI periods, respectively. Interviews were conducted to determine the quality of services from the perspectives of stakeholders. Results: A total of 195 patients participated in the study: 120 patients in pre-COVID-19 code STEMI and 75 patients in COVID-19 code STEMI. Our results showed that there was a significant increase in patient’s length of stay during the COVID-19 pandemic (4 days vs. 6 days, p < 0.001). Meanwhile, MACE (13% vs. 11%, p = 0.581), the in-hospital mortality rate (8% vs. 5%, p = 0.706), door-to-wire crossing time (161 min vs. 173 min, p = 0.065), door-to-needle time (151 min vs. 143 min p = 0.953), and hospitalization cost (3,490 USD vs. 3,700 USD, p = 0.945) showed no significant changes. In terms of patient satisfaction, patients found code STEMI during COVID-19 to be responsive and excellent. Conclusion: The implementation of the code STEMI program during the COVID-19 pandemic revealed that modified pathways were required because of the COVID-19 screening process. According to the Donabedian model, during the pandemic, the code STEMI program’s healthcare service quality decreased because of a reduction in efficacy, effectiveness, efficiency, and optimality. Despite these limitations attributed to the pandemic, the code STEMI program was able to provide good services for STEMI patients

Impacts of the COVID-19 Pandemic on the CODE ST-Segment Elevation Myocardial Infarction Program: A Quantitative and Qualitative Analysis

Background: The CODE ST-segment elevation myocardial infarction (STEMI) program is an operational standard of integrated service for STEMI patients carried out by Dr. Cipto Mangunkusumo Hospital. The emerging coronavirus disease 2019 (COVID-19) outbreak brought about many changes in the management of healthcare services, including the CODE STEMI program. This study aimed to evaluate the healthcare service quality of the CODE STEMI program during the COVID-19 pandemic based on the Donabedian concept.  Methods: This was a mixed-methods study using quantitative and qualitative analyses. It was conducted at the Dr. Cipto Mangunkusumo Hospital, a national referral hospital in Indonesia. We compared the data of each patient, including response time, clinical outcomes, length of stay, and cost, from a two-year period between 2018–2020 and 2020–2022 as the pre-COVID-19 CODE STEMI and COVID-19 CODE STEMI periods, respectively. Interviews were conducted to determine the quality of services from the perspectives of stakeholders. Results: A total of 195 patients participated in the study: 120 patients in pre-COVID-19 CODE STEMI and 75 patients in COVID-19 CODE STEMI. Our results showed that there was a significant increase in patient’s length of stay during the COVID-19 pandemic (4 days vs. 6 days, p < 0.001). Meanwhile, MACE (13% vs. 11%, p = 0.581), the in-hospital mortality rate (8% vs. 5%, p = 0.706), door-to-wire crossing time (161 min vs. 173 min, p = 0.065), door-to-needle time (151 min vs. 143 min p = 0.953), and hospitalization cost (3,490 USD vs. 3,700 USD, p = 0.945) showed no significant changes. In terms of patient satisfaction, patients found CODE STEMI during COVID-19 to be responsive and excellent. Conclusion: The implementation of the CODE STEMI program during the COVID-19 pandemic revealed that modified pathways were required because of the COVID-19 screening process. According to the Donabedian model, during the pandemic, the CODE STEMI program’s healthcare service quality decreased because of a reduction in efficacy, effectiveness, efficiency, and optimality. Despite these limitations attributed to the pandemic, the CODE STEMI program was able to provide good services for STEMI patients

Detecting Left Heart Failure in Echocardiography through Machine Learning: A Systematic Review

Background: Heart failure remains a considerable burden to healthcare in Asia. Early intervention, mainly using echocardiography, to assess cardiac function is crucial. However, due to limited resources and time, the procedure has become more challenging during the COVID-19 pandemic. On the other hand, studies have shown that artificial intelligence (AI) is highly potential in complementing the work of clinicians to diagnose heart failure accurately and rapidly. Methods: We systematically searched Europe PMC, ProQuest, Science Direct, PubMed, and IEEE following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and our inclusion and exclusion criteria. The 14 selected works of literature were then assessed for their quality and risk of bias using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). Results: A total of 2105 studies were retrieved, and 14 were included in the analysis. Five studies posed risks of bias. Nearly all studies included datasets in the form of 3D (three dimensional) or 2D (two dimensional) images, along with apical four-chamber (A4C) and apical two-chamber (A2C) being the most common echocardiography views used. The machine learning algorithm for each study differs, with the convolutional neural network as the most common method used. The accuracy varies from 57% to 99.3%. Conclusions: To conclude, current evidence suggests that the application of AI leads to a better and faster diagnosis of left heart failure through echocardiography. However, the presence of clinicians is still irreplaceable during diagnostic processes and overall clinical care; thus, AI only serves as complementary assistance for clinicians

Post COVID-19 Syndrome Monitoring in Confirmed COVID-19 Patients with Telemedicine at Cipto Mangunkusumo Hospital

Background: The incidence of post-covid-19 syndrome is quite high and requires further monitoring after the patient is discharged from treatment. So we need a proper monitoring method and description of the Covid-19 syndrome in Indonesia.  Methods: This retrospective cohort study with total sampling method uses data from medical records and telemedicine observations of confirmed COVID-19 patients who received treatment in the Kiara room at Cipto Mangunkusumo. The data were then analyzed using chi-squared and multinomial logistic regression techniques. Results: A total of 133 samples were used, including 44.4% male and 55.6% female, with an average age Standard Deviation (SD) of 40.36 (17.94). The severity levels of Covid-19 were mild (66.9%). The most common post-Covid-19 symptom manifestations was cough expressed at the first follow-up (first week after recovery) and second follow-up (the fourth week after recovery). Furthermore, the significant relationship between severity levels and post-Covid-19 symptomatic syndrome outcomes is the critical headache or vertigo symptoms with an RR of 8.70 (95% CI, 1.10-68.69,). In comparison, the telemedicine quality assessment was declared good, as shown by 98.7% of an examined sample. Conclusion: The most manifestation shown in the first and fourth week of follow-up is cough. Other symptoms tend to decrease in the second follow-up. The severity level associated with post-Covid-19 manifestations are severe-critical with headache or vertigo as a risk factor and mild with symptoms of headache or vertigo as a preventative. Meanwhile, the quality of telemedicine services was recognized as good by the majority of the sample

Incidence and Associated Factors of SARS-CoV-2 Infection Post-mRNA-1273 Booster Vaccination in Health-Care Workers

The COVID-19 pandemic has caused significant morbidity and mortality worldwide, especially among health-care workers. One of the most important preventive measures is vaccination. This study examined factors associated with the incidence rate of SARS-CoV-2 infection after mRNA-1273 booster vaccination (preceded by the CoronaVac primary vaccination) and the antibody profile of health-care workers at one of the tertiary hospitals in Indonesia. This was a combined retrospective cohort and cross-sectional study. Three hundred health-care workers who were given the mRNA-1273 booster vaccine a minimum of 5 months prior to this study were randomly selected. Participants were then interviewed about their history of COVID-19 vaccination, history of SARS-CoV-2 infection, and comorbidities. Blood samples were taken to assess IgG sRBD antibody levels. The median antibody level was found to be 659 BAU/mL (min 37 BAU/mL, max 5680 BAU/mL, QIR 822 BAU/mL) after the booster, and this was not related to age, sex, comorbidities, or adverse events following immunization (AEFI) after the booster. SARS-CoV-2 infection after the booster was correlated with higher antibody levels. In sum, 56 participants (18.6%) experienced SARS-CoV-2 infection after the mRNA-1273 booster vaccination within 5 months. Incidence per person per month was 3.2%. Age, sex, diabetes mellitus type 2, hypertension, obesity, and post-booster AEFI were not related to COVID-19 incidence after the booster. History of SARS-CoV-2 infection before the booster vaccination was significantly associated with a reduced risk of SARS-CoV-2 infection after booster vaccination, with a relative risk (RR) of 0.21 (95% CI 0.09–0.45, p < 0.001)

Learning Intelligent for Effective Sonography (LIFES) Model for Rapid Diagnosis of Heart Failure in Echocardiography

Background: The accuracy of an artificial intelligence model based on echocardiography video data in the diagnosis of heart failure (HF) called LIFES (Learning Intelligent for Effective Sonography) was investigated. Methods: A cross-sectional diagnostic test was conducted using consecutive sampling of HF and normal patients’ echocardiography data. The gold-standard comparison was HF diagnosis established by expert cardiologists based on clinical data and echocardiography. After pre-processing, the AI model is built based on Long-Short Term Memory (LSTM) using independent variable estimation and video classification techniques. The model will classify the echocardiography video data into normal and heart failure category. Statistical analysis was carried out to calculate the value of accuracy, area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR). Results: A total of 138 patients with HF admitted to Harapan Kita National Heart Center from January 2020 to October 2021 were selected as research subjects. The first scenario yielded decent diagnostic performance for distinguishing between heart failure and normal patients. In this model, the overall diagnostic accuracy of A2C, A4C, PLAX-view were 92,96%, 90,62% and 88,28%, respectively. The automated ML-derived approach had the best overall performance using the 2AC view, with a misclassification rate of only 7,04%. Conclusion: The LIFES model was feasible, accurate, and quick in distinguishing between heart failure and normal patients through series of echocardiography images