Variations and Associated Factors in Symptom-to-Balloon (STB) Time and Door-to-Balloon (DTB) Time Before and After the COVID-19 Lockdown: A Hospital-Based Cross-Sectional Study

INTRODUCTION

During the COVID-19 lockdown, India saw a major restriction in the movement of people. Patients with acute myocardial infarction (MI) required early interventions and follow-up of independent predictors like symptom-to-balloon (STB) time and door-to-balloon (DTB) time. This study aimed to determine changes in STB and DTB time before and after the COVID-19 lockdown and its associated risk factors.

METHODS

A hospital-based cross-sectional study of 105 patients admitted to the cardiac care units (CCU) of two tertiary care centers in a district of Southern India for six months was conducted to compare the changes in STB and DTB time before and after the COVID-19 lockdown (three months before March 2020 and three months after March 2020), and data was collected from medical records. The data collected was then entered into Microsoft Excel (Microsoft Corporation, Washington, USA), numerically coded, and analyzed using SPSS Statistics version 21 (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.). The Chi-square and Mann-Whitney U tests assessed the association between the dependent and independent variables. The STB/DTB time (before and after the COVID-19 lockdown) was the dependent variable, while the age, gender, co-morbidities, smoking status, and date of admission of patients (before and after the COVID-19 lockdown) were taken as the independent variables. A p-value of <0.05 was considered statistically significant. The predictor variables were identified using the regression method, where all variables with a significance of <0.2 were taken.

RESULTS

The overall mean (±SD) STB time was 408.7 (±307.1) minutes, and the mean (±SD) DTB time was 161.7 (±261.6) minutes. The pre-lockdown mean STB time was 404.6 minutes, and the mean DTB time was 153 minutes, whereas the post-lockdown mean STB and DTB time were higher at 413.3 minutes and 171.6 minutes, respectively. Out of the total 105 patients, 95 (90.5%) had an STB time of ≥120 minutes, and 77 (73.3%) had an ideal DTB time of <90 minutes. There was no statistically significant variation in the STB and DTB time before and after the lockdown. Only the age group >60 years (38 (97.4%)) was found to be statistically significant with an STB time of ≥120 minutes after the lockdown (p-value=0.040), and patients referred from primary and secondary care centers (AOR (95% CI)=4.669 (1.129-19.298)) were found to be an independent factor in reducing DTB time before and after the COVID-19 lockdown.

CONCLUSION

The efficiency of the health system, irrespective of the COVID-19 lockdown, was observed; nevertheless, a delay in the overall recognition of symptoms of MI was perceived. The importance of time factors in identifying the symptoms of non-communicable diseases (NCDs), especially MI and stroke, has to be ascertained among the general population.

Pulmonary Hypertension Registry of Kerala, India (PRO-KERALA): One-year outcomes

BACKGROUND

Short term outcomes of patients with pulmonary hypertension are not available from low and middle-income countries including India.

METHODS

We conducted a prospective study of 2003 patients with pulmonary hypertension, from 50 centres (PROKERALA) in Kerala, who were followed up for one year. Pulmonary hypertension (PH) was mainly diagnosed on the basis of Doppler echocardiography. The primary outcome was a composite end-point of all-cause death and hospital admission for heart failure. All cause hospitalisation events constituted the secondary outcome.

RESULTS

Mean age of study population was 56 ± 16 years. Group 1 and Group 2 PH categories constituted 21.2% and 59% of the study population, respectively. Nearly two-thirds (65%) of the study participants had functional class II symptoms. 31% of Group 1 PH patients were on specific vasodilator drugs.In total, 83 patients (4.1%) died during the one-year follow-up period. Further, 1235 re-hospitalisation events (61.7%) were reported. In the multivariate model, baseline NYHA class III/IV (OR 1.87, 95% C.I. 1.35-2.56), use of calcium channel blockers (OR 0.18, 95% C.I. 0.04-0.77), vasodilator therapy (OR 0.5, 95% C.I. 0.28-0.87) and antiplatelet agents (OR 1.80, 95% C.I. 1.29-2.51) were associated with primary composite outcome at one-year (p < 0.05).

CONCLUSION

In the PROKERALA registry, annual mortality rate was 4%. More than half of the patients reported re-hospitalisation events on follow up. Uptake of guideline directed therapies were suboptimal in the study population. Quality improvement programmes to improve guideline directed therapy may improve clinical outcomes of PH patients in India.

Microeconomic Costs, Insurance, and Catastrophic Health Spending Among Patients With Acute Myocardial Infarction in India: Substudy of a Randomized Clinical Trial

IMPORTANCE

Ischemic heart disease is the leading cause of death in India, and treatment can be costly.

OBJECTIVE

To evaluate individual- and household-level costs and impoverishing effects of acute myocardial infarction among patients in Kerala, India.

DESIGN, SETTING, AND PARTICIPANTS

This investigation was a prespecified substudy of the Acute Coronary Syndrome Quality Improvement in Kerala study, a stepped-wedge, cluster randomized clinical trial conducted between November 2014 and November 2016 across 63 hospitals in Kerala, India. In this cross-sectional substudy, individual- and household-level cost data were collected 30 days after hospital discharge from a sample of 2114 respondents from November 2014 to July 2016. Data were analyzed from July through October 2018 and in March 2019.

EXPOSURES

Health insurance status.

MAIN OUTCOMES AND MEASURES

The primary outcomes were detailed direct and indirect cost data associated with acute myocardial infarction and respondent ability to pay as well as catastrophic health spending and distress financing. Catastrophic health spending was defined as 40% or more of household expenditures minus food costs spent on health, and distress financing was defined as borrowing money or selling assets to cover health costs. Hierarchical regression models were used to evaluate the association between health insurance and measures of financial risk. Costs were converted from Indian rupees to international dollars (represented herein as "$").

RESULTS

Among 2114 respondents, the mean (SD) age was 62.3 (12.7) years, 1521 (71.9%) were men, 1144 (54.1%) presented with an ST-segment elevation myocardial infarction, and 1600 (75.7%) had no health insurance. The median (interquartile range) expenditure among respondents was $480.4 ($112.5-$1733.0) per acute myocardial infarction encounter, largely driven by in-hospital expenditures. There was greater than 15-fold variability between the 25th and 75th percentiles. Individuals with or without health insurance had similar monthly incomes and annual household expenditures, yet individuals without health insurance had approximately $400 higher out-of-pocket cardiovascular health care costs (median [interquartile range] total cardiovascular expenditures among uninsured, $560.3 [$134.1-$1733.6] vs insured, $161.4 [$23.2-$1726.9]; P < .001). Individuals without health insurance also had a 24% higher risk of catastrophic health spending (adjusted risk ratio, 1.24; 95% CI, 1.07-1.43) and 3-fold higher risk of distress financing (adjusted risk ratio; 3.05; 95% CI, 1.45-6.44).

CONCLUSIONS AND RELEVANCE

The results of this study indicate that acute myocardial infarction carries substantial financial risk for patients in Kerala. Expansion of health insurance may be an important strategy for financial risk protection to disrupt the poverty cycle associated with cardiovascular diseases in India.

Presentation, management, and outcomes of 25 748 acute coronary syndrome admissions in Kerala, India: results from the Kerala ACS Registry

AIMS

There are limited contemporary data on the presentation, management, and outcomes of acute coronary syndrome (ACS) admissions in India. We aimed to develop a prospective registry to address treatment and health systems gaps in the management of ACSs in Kerala, India.

METHODS AND RESULTS

We prospectively collected data on 25 748 consecutive ACS admissions from 2007 to 2009 in 125 hospitals in Kerala. We evaluated data on presentation, management, and in-hospital mortality and major adverse cardiovascular events (MACE). We created random-effects multivariate regression models to evaluate predictors of outcomes while accounting for confounders. Mean (SD) age at presentation was 60 (12) years and did not differ among ACS types [ST-segment myocardial infarction (STEMI) = 37%; non-STEMI = 31%; unstable angina = 32%]. In-hospital anti-platelet use was high (>90%). Thrombolytics were used in 41% of STEMI, 19% of non-STEMI, and 11% of unstable angina admissions. Percutaneous coronary intervention rates were marginally higher in STEMI admissions. Discharge medication rates were variable and generally suboptimal (<80%). In-hospital mortality and MACE rates were highest for STEMI (8.2 and 10.3%, respectively). After adjustment, STEMI diagnosis (vs. unstable angina) [odds ratio (OR) (95% confidence interval = 4.06 (2.36, 7.00)], symptom-to-door time >6 h [OR = 2.29 (1.73, 3.02)], and inappropriate use of thrombolysis [OR = 1.33 (0.92, 1.91)] were associated with higher risk of in-hospital mortality and door-to-needle time <30 min [OR = 0.44 (0.27, 0.72)] was associated with lower mortality. Similar trends were seen for risk of MACE.

CONCLUSION

These data represent the largest ACS registry in India and demonstrate opportunities for improving ACS care.