Impact of the COVID-19 pandemic on in-hospital mortality in cardiovascular disease: a meta-analysis

A nationwide, population-based study on specialized care for acute heart failure throughout the COVID-19 pandemic

AIMS

The COVID-19 pandemic disrupted the delivery of care for patients with heart failure (HF), leading to fewer HF hospitalizations and increased mortality. However, nationwide data on quality of care and long-term outcomes across the pandemic are scarce.

METHODS AND RESULTS

We used data from the National Heart Failure Audit (NHFA) linked to national records for hospitalization and deaths. We compared pre-COVID (2018-2019), COVID (2020), and late/post-COVID (2021-2022) periods. Data for 227 250 patients admitted to hospital with HF were analysed and grouped according to the admission year and the presence of HF with (HFrEF) or without reduced ejection fraction (non-HFrEF). The median age at admission was 81 years (interquartile range 72-88), 55% were men (n = 125 975), 87% were of white ethnicity (n = 102 805), and 51% had HFrEF (n = 116 990). In-hospital management and specialized cardiology care were maintained throughout the pandemic with an increasing percentage of patients discharged on disease-modifying medications over time (p < 0.001). Long-term outcomes improved over time (hazard ratio [HR] 0.92, 95% confidence interval [CI] 0.90-0.95, p < 0.001), mainly driven by a reduction in cardiovascular death. Receiving specialized cardiology care was associated with better long-term outcomes both for those who had HFrEF (HR 0.79, 95% CI 0.77-0.82, p < 0.001) and for those who had non-HFrEF (HR 0.87, 95% CI 0.85-0.90, p < 0.001).

CONCLUSIONS

Despite the disruption of healthcare systems, the clinical characteristics of patients admitted with HF were similar and the overall standard of care was maintained throughout the pandemic. Long-term survival of patients hospitalized with HF continued to improve after COVID-19, especially for HFrEF.

Differential Mortality Among Heart Failure Patients Across Different COVID-19 Surges in New York City

ABSTRACT

Learning from the healthcare system's response to the COVID-19 pandemic is essential to better prepare for potential future crises. We sought to assess mortality rates for patients admitted for acute decompensated heart failure (HF) and to analyze which factors demonstrated a statistically significant correlation with this primary endpoint. We performed a retrospective analysis of patients hospitalized with a primary diagnosis of acute decompensated HF within the New York City Health and Hospitals 11-hospital system across the different COVID surge periods. Mortality information was collected in 4,405 participants (mean [SD] age 70.54 [14.44] years, 1885 [42.87%] female).The highest mortality existed in the first surge (9.02%), then improved to near prepandemic levels (3.65%) in the second (3.91%) and third surges (5.94%, p < 0.0001). In-hospital mortality inversely correlated with receipt of a COVID-19 vaccination, but had no correlation with left ventricular ejection fraction or the number of vaccination doses. Mortality for acute decompensated HF patients improved after the first surge, suggesting that hospitals adequately adapted to provide quality care. As future infectious outbreaks may occur, emergency preparedness must ensure that adequate focus and resources remain for other clinical entities, such as HF, to ensure optimal care is delivered across all areas of illness.

Impact of the COVID-19 Pandemic on Global TAVR Activity: The COVID-TAVI Study

BACKGROUND

The COVID-19 pandemic adversely affected health care systems. Patients in need of transcatheter aortic valve replacement (TAVR) are especially susceptible to treatment delays.

OBJECTIVES

This study sought to evaluate the impact of the COVID-19 pandemic on global TAVR activity.

METHODS

This international registry reported monthly TAVR case volume in participating institutions prior to and during the COVID-19 pandemic (January 2018 to December 2021). Hospital-level information on public vs private, urban vs rural, and TAVR volume was collected, as was country-level information on socioeconomic status, COVID-19 incidence, and governmental public health responses.

RESULTS

We included 130 centers from 61 countries, including 65,980 TAVR procedures. The first and second pandemic waves were associated with a significant reduction of 15% (P < 0.001) and 7% (P < 0.001) in monthly TAVR case volume, respectively, compared with the prepandemic period. The third pandemic wave was not associated with reduced TAVR activity. A greater reduction in TAVR activity was observed in Africa (-52%; P = 0.001), Central-South America (-33%; P < 0.001), and Asia (-29%; P < 0.001). Private hospitals (P = 0.005), urban areas (P = 0.011), low-volume centers (P = 0.002), countries with lower development (P < 0.001) and economic status (P < 0.001), higher COVID-19 incidence (P < 0.001), and more stringent public health restrictions (P < 0.001) experienced a greater reduction in TAVR activity.

CONCLUSIONS

TAVR procedural volume declined substantially during the first and second waves of the COVID-19 pandemic, especially in Africa, Central-South America, and Asia. National socioeconomic status, COVID-19 incidence, and public health responses were associated with treatment delays. This information should inform public health policy in case of future global health crises.

Hospitalization and hospital mortality rates during the first and second waves of the COVID-19 pandemic in Quebec: interrupted time series and decomposition analysis

OBJECTIVES

We investigated hospitalization and hospital mortality rates by cause during the first year of the COVID-19 pandemic in Quebec, Canada.

STUDY DESIGN

Interrupted time series and decomposition analysis.

METHODS

We analyzed hospital mortality during the first (February 25-August 22, 2020) and second waves (August 23, 2020-March 31, 2021), compared with 2019. We identified the cause of death and examined trends using: 1) interrupted time series analysis; 2) log-binomial regression; and 3) decomposition of cause-specific mortality.

RESULTS

Hospitalization rates decreased; however, the proportion of deaths increased from 27.0 per 1000 in 2019 to 35.0 per 1000 in the first wave, for an excess of 8.0 deaths per 1000 admissions. COVID-19 was the cause of a third of excess deaths (2.6 per 1000). Other drivers of excess deaths included respiratory conditions (1.6 deaths per 1000), circulatory disorders (0.6 deaths per 1000), and cancer (0.9 deaths per 1000). COVID-19 was the cause of 58% of excess deaths in the second wave. Interrupted time series regression indicated that the proportion of deaths increased at the outset of the first wave but returned to prepandemic levels before increasing again in the second wave. Compared with 2019, the first wave was associated with 1.31 times (95% confidence interval [CI] 1.28-1.33) and the second wave with 1.17 times (95% CI 1.15-1.19) the risk of death during hospitalization.

CONCLUSIONS

The pandemic was associated with a greater risk of hospital mortality. Excess deaths were driven by COVID-19 but also other causes, including respiratory conditions, circulatory disorders, and cancer.

Cardiovascular Complications of COVID-19: A Scoping Review of Evidence

This scoping review sought to identify the nature and extent of clinical evidence regarding the acute and long-term cardiovascular complications associated with COVID-19. Forty-nine studies published between 2020 and 2023 were selected for review. The studies were divided into two groups. The referential group included 22 studies. The second group of 27 studies was used for a detailed review to assess the strength of the evidence. The aggregate evidence indicates that the most common cardiac complications associated with COVID-19 include but are not limited to acute pericarditis, acute myocardial injury, acute myocarditis, various arrhythmias, microvascular angiopathy, left ventricular dysfunction, heart failure, acute cardiac injury, and acute coronary syndrome. Clinical and epidemiological implications of the findings are investigated, and future research recommendations are proposed.

Telemedicine for the treatment of heart failure: new opportunities after COVID-19

ABSTRACT

During the Coronavirus Disease 2019 (COVID-19) pandemic, the epidemiology of heart failure significantly changed with reduced access to health system resources and a worsening of patients' outcome. Understanding the causes of these phenomena could be important to refine the management of heart failure during and after the pandemic. Telemedicine was associated with an improvement in heart failure outcomes in several studies; therefore, it may help in refining the out-of-hospital care of heart failure. In this review, the authors describe the changes in heart failure epidemiology during the COVID-19 pandemic; analyse available evidence on use and benefit of telemedicine during the pandemic and prepandemic periods; and discuss approaches to optimize the home-based or outpatient heart failure management in the future, beyond the pandemic.

Impact of the COVID-19 pandemic on incidence and mortality of emergency cardiovascular diseases in Tokyo

BACKGROUND

The impact of the coronavirus disease 2019 (COVID-19) pandemic on the incidence and in-hospital mortality of emergency cardiovascular disease (CVD) has not been clarified in Japan.

METHODS

We compared the number of admissions and in-hospital mortality for emergency CVD during the pandemic (from January to December 2020) with those of pre-pandemic periods (from January 2018 to December 2019), using quarterly data from the Tokyo Cardiovascular Care Unit Network. The incidence rate in 2020 is compared with the average incidence rate observed in the same quarter of 2018 and 2019 and is presented as an incidence rate ratio (IRR) with 95 % confidence interval (CI).

RESULTS

The number of admissions for acute myocardial infarction during the pandemic was significantly lower than before the pandemic, with an IRR of 0.93 (95 % CI; 0.88-0.98). Similarly, the IRR for unstable angina was 0.78 (95 % CI; 0.72-0.83), for acute heart failure was 0.84 (95 % CI; 0.76-0.91), for acute aortic dissection was 0.88 (95 % CI; 0.78-0.98), and for ruptured aortic aneurysm was 0.75 (95 % CI; 0.62-0.88). In quarterly comparisons, the numbers of acute aortic diseases and emergency arrhythmia significantly decreased from July to September 2020, while those of other emergency CVDs significantly declined in the 2020 April-June period, which includes the first wave period in Japan. In-hospital mortality of emergency CVDs was unchanged from the pre-pandemic period, except for acute aortic dissection, which increased in odds ratio of 1.31 (95 % CI 1.10-1.57).

CONCLUSIONS

The COVID-19 pandemic significantly reduced the number of admissions for all emergency CVDs in all or part of the year. In-hospital mortality was unchanged from the pre-pandemic period, except for acute aortic dissection, which increased.

Changes in the Utilization of Health Care Services by Cancer Patients during the COVID-19 Pandemic

PURPOSE

The first year of the COVID-19 pandemic in Korea elicited changes in healthcare service utilization. This study aimed to report changes in healthcare service utilization among cancer patients during the first year of the COVID-19 pandemic in Korea.

MATERIALS AND METHODS

We analyzed records from National Health Insurance Service Database and identified cancer patients as those with specific beneficiary codes ("V193" or "V194") assigned to cancer patients. We calculated percentage changes in the number of patients between 2019 and 2020 based on claims records for outpatient clinic visits, hospitalization, and emergency room visits by month, age group, residential areas, and hospital location.

RESULTS

The number of newly diagnosed cancer patients in 2020 decreased by 3.2%, compared to the previous year. The number of patients who visited an outpatient clinic, were hospitalized, and visited the emergency room decreased by 2.6%, 4.0%, and 3.5%, respectively, in 2020, compared to the year 2019.

CONCLUSION

During the first year of the COVID-19 pandemic, the number of newly diagnosed cancer patients decreased by 3.2%, compared to the previous year, and their utilization of healthcare services declined significantly after the outbreak of COVID-19.

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

Background

The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England.

Methods

In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020.

Findings

Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences.

Interpretation

Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes.

Funding

LSHTM COVID-19 Response Grant (DONAT15912).

Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: evidence from 55,500 individuals from 28 European countries

BACKGROUND

Pandemics such as the COVID-19 pandemic and other severe health care disruptions endanger individuals to miss essential care. Machine learning models that predict which patients are at greatest risk of missing care visits can help health administrators prioritize retentions efforts towards patients with the most need. Such approaches may be especially useful for efficiently targeting interventions for health systems overburdened during states of emergency.

METHODS

We use data on missed health care visits from over 55,500 respondents of the Survey of Health, Ageing and Retirement in Europe (SHARE) COVID-19 surveys (June - August 2020 and June - August 2021) with longitudinal data from waves 1-8 (April 2004 - March 2020). We compare the performance of four machine learning algorithms (stepwise selection, lasso, random forest, and neural networks) to predict missed health care visits during the first COVID-19 survey based on common patient characteristics available to most health care providers. We test the prediction accuracy, sensitivity, and specificity of the selected models for the first COVID-19 survey by employing 5-fold cross-validation, and test the out-of-sample performance of the models by applying them to the data from the second COVID-19 survey.

RESULTS

Within our sample, 15.5% of the respondents reported any missed essential health care visit due to the COVID-19 pandemic. All four machine learning methods perform similarly in their predictive power. All models have an area under the curve (AUC) of around 0.61, outperforming random prediction. This performance is sustained for data from the second COVID-19 wave one year later, with an AUC of 0.59 for men and 0.61 for women. When classifying all men (women) with a predicted risk of 0.135 (0.170) or higher as being at risk of missing care, the neural network model correctly identifies 59% (58%) of the individuals with missed care visits, and 57% (58%) of the individuals without missed care visits. As the sensitivity and specificity of the models are strongly related to the risk threshold used to classify individuals, the models can be calibrated depending on users' resource constraints and targeting approach.

CONCLUSIONS

Pandemics such as COVID-19 require rapid and efficient responses to reduce disruptions in health care. Based on characteristics available to health administrators or insurance providers, simple machine learning algorithms can be used to efficiently target efforts to reduce missed essential care.

Hospital admission and mortality rates for non-Covid diseases among residents of the long-term care facilities before and during the pandemic: a cohort study in two Italian regions

Aim

Long-term-care facility residents are a vulnerable population who experienced reduced healthcare access during the pandemic. This study aimed to assess the indirect impact of the COVID-19 pandemic, in terms of hospitalisation and mortality rates, among this population in two Italian Regions, Tuscany and Apulia, during 2020 in comparison with the pre-pandemic period.

Subject and methods

We conducted a retrospective cohort study on people residing in long-term-care facilities from 1 January 2018 to 31 December 2020 (baseline period: 1 January 2018-8 March 2020; pandemic period: and 9 March-31 December 2020). Hospitalisation rates were stratified by sex and major disease groups. Standardised weekly rates were estimated with a Poisson regression model. Only for Tuscany, mortality risk at 30 days after hospitalisation was calculated with the Kaplan-Meier estimator. Mortality risk ratios were calculated using Cox proportional regression models.

Results

Nineteen thousand two hundred and fifty individuals spent at least 7 days in a long-term-care facility during the study period. The overall mean non-Covid hospital admission rate per 100 000 residents/week was 144.1 and 116.2 during the baseline and pandemic periods, with a decrease to 99.7 and 77.3 during the first (March-May) and second lockdown (November-December). Hospitalisation rates decreased for all major disease groups. Thirty-day mortality risk ratios for non-Covid conditions increased during the pandemic period (1.2, 1.1 to 1.4) compared with baseline.

Conclusion

The pandemic resulted in worse non-COVID-related health outcomes for long-term-care facilities' residents. There is a need to prioritise these facilities in national pandemic preparedness plans and to ensure their full integration in national surveillance systems.

Supplementary information

The online version contains supplementary material available at 10.1007/s10389-023-01925-1.

A Review of Heart Failure in patients with COVID-19

The interplay of COVID-19 and heart failure is complex and involves direct and indirect effects. Patients with existing heart failure develop more severe COVID-19 symptoms and have worse clinical outcomes. Pandemic-related policies and protocols have negatively affected care for cardiovascular conditions and established hospital protocols, which is particularly important for patients with heart failure.

Excess cardiovascular mortality across multiple COVID-19 waves in the United States from March 2020 to March 2022

The COVID-19 pandemic has limited the access of patients with cardiovascular diseases to healthcare services, causing excess deaths. However, a detailed analysis of temporal variations of excess cardiovascular mortality during the COVID-19 pandemic has been lacking. Here we estimate time-varied excess cardiovascular deaths (observed deaths versus expected deaths predicted by the negative binomial log-linear regression model) in the United States. From March 2020 to March 2022 there were 90,160 excess cardiovascular deaths, or 4.9% more cardiovascular deaths than expected. Two large peaks of national excess cardiovascular mortality were observed during the periods of March-June 2020 and June-November 2021, coinciding with two peaks of COVID-19 deaths, but the temporal patterns varied by state, age, sex and race and ethnicity. The excess cardiovascular death percentages were 5.7% and 4.0% in men and women, respectively, and 3.6%, 8.8%, 7.5% and 7.7% in non-Hispanic White, Black, Asian and Hispanic people, respectively. Our data highlight an urgent need for healthcare services optimization for patients with cardiovascular diseases in the COVID-19 era.

Reshaping care in the aftermath of the pandemic. Implications for cardiology health systems

In the last two years, the COVID-19 pandemic has undeniably changed everyday life and significantly reshaped the healthcare systems. Besides the direct effect on daily care leading to significant excess mortality, several collateral damages have been observed during the pandemic. The impact of the pandemic led to staff shortages, disrupted education, worse healthcare professional well-being, and a lack of proper clinical training and research. In this review we highlight the results of these important changes and how can the healthcare systems can adapt to prevent unprecedented events in case of future catastrophes.

Increased national mortality in acute myocardial infarction hospitalization during the COVID-19 pandemic

This retrospective study describes the effect of the COVID-19 pandemic on epidemiologic trends and highlights disparities in outcomes among acute myocardial infarction (AMI) hospitalizations. The National Inpatient Sample database from 2016 to 2020 was searched for hospitalizations of adult patients with AMI as a principal diagnosis using Clinical Classifications Software Refined codes. The admission rate for each calendar year was obtained as admission per 1000 adults hospitalized. The primary outcome was a comparison of inpatient mortality, and the secondary outcomes were the length of hospital stay and total hospital charge between prepandemic and pandemic years. During the pandemic (2020), the admission rate for AMI was 31.1 admissions per 1000 adults hospitalized compared to 33.4 admissions in 2019 (prepandemic) (P  < 0.001). When compared to the prepandemic admissions, those admitted during the pandemic had a lower mean age (66.5 ± 13.2 vs 66.9 ± 13.4, P  < 0.001), with more women (36.3% vs 37.3%, P  < 0.001). The inpatient mortality during the pandemic was 5.0% compared to 4.5% in 2019 (P  < 0.001). Mortality increased 12.0% in women vs 9.5% in men, 13.2% in Blacks vs 8.9% in Whites, and 6.5% in low-income vs 4.3% in high-income household hospitalizations. In conclusion, our study showed a statistically significant reduction in AMI admission rates during the pandemic and an increase in inpatient mortality. There were significant disparities in the increase in mortality across sociodemographic groups.

Role of fibrinogen, albumin and fibrinogen to albumin ratio in determining angiographic severity and outcomes in acute coronary syndrome

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic unmasked the huge deficit in healthcare resources worldwide. It highlighted the need for efficient risk stratification in management of cardiovascular emergencies.

AIM

To study the applicability of the old, available and affordable nonconventional biomarkers: albumin and fibrinogen in their ability to predict angiographic severity and clinical outcomes in patients with acute coronary syndrome (ACS).

METHODS

In this prospective, observational study, 166 consecutive patients with ACS were enrolled. Fibrinogen, albumin and their ratio were determined from serum. Patients with underlying chronic liver disease, active malignancy, autoimmune disease, active COVID-19 infection and undergoing thrombolysis were excluded.

RESULTS

Mean age of the population was 60.5 ± 1.5 years, 74.1% being males. ST elevation myocardial infarction (STEMI) was most common presentation of ACS seen in 57% patients. Fibrinogen albumin ratio (FAR) ≥ 19.2, had a sensitivity of 76.9% and specificity of 78.9 % [area under the receiver operating characteristic curves (AUROC) = 0.8, P = 0.001] to predict ≤ thrombolysis in myocardial infarction (TIMI) 1 flow in culprit artery in STEMI patients. Even in non-STEMI patients, FAR ≥ 18.85 predicted the same with 80% sensitivity and 63% specificity (AUROC = 0.715, P = 0.006).

CONCLUSION

Novel biomarkers, with their high cost, lack of availability and long turn over time are impractical for real-world use. Identifying ≤ TIMI 1 flow in the culprit artery has significant impact of management and outcome. Our study has shown that readily available biomarkers like fibrinogen and albumin can help identify these high-risk patients with good accuracy. This allows risk-stratification and individualization of treatment in ACS.

Type of hospitalisations and in-hospital outcomes in the Italian coronary care unit network at the time of COVID-19 pandemic: the BLITZ-COVID19 Registry

OBJECTIVE

The aim of the study was to describe the epidemiology and outcome of patients hospitalised during the COVID-19 pandemic in intensive cardiac care units (ICCs).

DESIGN

Non-interventional, retrospective and prospective, nationwide study.

SETTING

109 private or public ICCs in Italy.

PARTICIPANTS

6054 consecutive patients admitted to Italian ICCs during COVID-19 pandemic.

PRIMARY AND SECONDARY OUTCOME MEASURES

To obtain accurate and up-to-date information on epidemiology and outcome of patients admitted to ICCs during the COVID-19 pandemic, the impact that the COVID-19 infection may have determined on the organisational pathways and in-hospital management of the various clinical conditions being admitted to ICCs.

RESULTS

Acute coronary syndromes were the most frequent ICC discharge diagnoses followed by heart failure and hypokinetic arrhythmias. The prevalence of COVID-19 positivity was approximately 3%. Most patients with a COVID-19 diagnosis at discharge (52%) arrived to ICC from other wards, in particular 22% from non-cardiology ICCs. The overall mortality was 4.2% during ICC and 5.8% during hospital stay. The cause of in-hospital death was cardiac in 74.4% of the cases, non-cardiovascular in 13.5%, vascular in 5.8% and related to COVID-19 in 6.3% of the patients.

CONCLUSIONS

This study provides a unique nationwide picture of current ICC care during COVID-19 pandemic.

TRIAL REGISTRATION NUMBER

NCT04744415.

Cardiovascular Damage in COVID-19: What We Know Two Years Later

PURPOSE OF THE REVIEW

The Coronavirus disease 2019 (COVID-19) pandemic has profoundly influenced cardiological clinical and basic research in the past two years. In the present review, we summarize the current knowledge on myocardial involvement in COVID-19, providing an overview on the incidence, the pathogenetic mechanisms, and the clinical implications of cardiac injury in this setting.

RECENT FINDINGS

The possibility of heart involvement in patients with COVID-19 has received great attention since the beginning of the pandemic. After more than two years, several steps have been taken in understanding the mechanisms and the incidence of cardiac injury during COVID-19 infection. Similarly, studies globally have clarified the implications of co-existing heart disease and COVID-19. Severe COVID-19 infection may be complicated by myocardial injury. To date, a direct damage from the virus has not been demonstrated. The presence of myocardial injury should be systematically assessed for a prognostication purpose and for possible therapeutic implications.

The collateral damage of COVID-19 to cardiovascular services: a meta-analysis

AIMS

The effect of the COVID-19 pandemic on care and outcomes across non-COVID-19 cardiovascular (CV) diseases is unknown. A systematic review and meta-analysis was performed to quantify the effect and investigate for variation by CV disease, geographic region, country income classification and the time course of the pandemic.

METHODS AND RESULTS

From January 2019 to December 2021, Medline and Embase databases were searched for observational studies comparing a pandemic and pre-pandemic period with relation to CV disease hospitalisations, diagnostic and interventional procedures, outpatient consultations, and mortality. Observational data were synthesised by incidence rate ratios (IRR) and risk ratios (RR) for binary outcomes and weighted mean differences for continuous outcomes with 95% confidence intervals. The study was registered with PROSPERO (CRD42021265930). A total of 158 studies, covering 49 countries and 6 continents, were used for quantitative synthesis. Most studies (80%) reported information for high-income countries (HICs). Across all CV disease and geographies there were fewer hospitalisations, diagnostic and interventional procedures, and outpatient consultations during the pandemic. By meta-regression, in low-middle income countries (LMICs) compared to HICs the decline in ST-segment elevation myocardial infarction (STEMI) hospitalisations (RR 0.79, 95% confidence interval [CI] 0.66-0.94) and revascularisation (RR 0.73, 95% CI 0.62-0.87) was more severe. In LMICs, but not HICs, in-hospital mortality increased for STEMI (RR 1.22, 95% CI 1.10-1.37) and heart failure (RR 1.08, 95% CI 1.04-1.12). The magnitude of decline in hospitalisations for CV diseases did not differ between the first and second wave.

CONCLUSIONS

There was substantial global collateral CV damage during the COVID-19 pandemic with disparity in severity by country income classification.

Dynamic changes of atrioventricular conduction during Covid-19 infection: Does inflammation matter?

Background

The primary manifestation of COVID-19 infection was pulmonary involvement. However, it can also manifest as a cardiovascular problem.

Methods

We report a case of 82-year-old male COVID-19 patient who experienced atrioventricular (AV) conduction disturbance.

Results

The rhythm was degenerated from sinus rhythm to complete AV block. We observe dynamic AV node dysfunction associated with inflammatory response. His bundle pacing successfully captured distal His region.

Conclusion

The severe inflammatory response during COVID-19 infection might permanently damage cardiac conduction system resulted in a complete AV node block.

The Potential Impact of COVID-19 Virus on the Heart and the Circulatory System

Heart attacks, arrhythmias, and cardiomyopathy are all linked to the 2019 coronavirus disease (COVID-19), which has been identified as a risk factor for cardiovascular disease. Nothing can be held accountable in the current state of affairs. Undiagnosed chronic systolic heart failure (CSHF) develops when the heart’s second half of the cardiac cycle does not function properly. As a result, the heart’s blood pumping function is interrupted. Stress-induced cardiomyopathy may be caused by a variety of factors inside the body (SICM). Cytokine storm and microvascular dysfunction are among the issues. There is inflammation in the heart muscle, which may lead to stress-induced cardiomyopathy. A major part of our study is going to be devoted to understanding the effects of coronavirus on the cardiovascular system and blood vessels. A lot of time and effort has been put into figuring out the health effects of radiation exposure. The heart and circulatory system are shown to be affected by the coronavirus in this research. COVID-19 is shown to influence persons with heart disease, heart failure, arrhythmias, microvascular angiopathy, and cardiac damage in this study.

Continuous Decline in Myocardial Infarction and Heart Failure Hospitalizations during the First 12 Months of the COVID-19 Pandemic in Israel

Background: A decline in cardiovascular hospitalizations was observed during the initial phases of the COVID-19 pandemic. We examine the continuous effect of the COVID-19 pandemic in reducing cardiovascular hospitalization and associated mortality rates during the first year of the pandemic in Israel. Methods: We conduct a retrospective cohort study using the data of Clalit Health Services, the largest healthcare organization in Israel. We divide the Corona year into six periods (three lockdowns and three post-lockdowns) and compare the incidence rates of cardiovascular hospitalizations and 30-day all-cause mortality during each period to the previous three years. Results: The number of non-STEMI hospitalizations during the first year of the pandemic was 13.7% lower than the average of the previous three years (95% CI 11–17%); STEMI hospitalizations were 15.7% lower (95% CI 13–19%); CHF (Congestive heart failure) hospitalizations were 23.9% lower (95%, CI 21–27%). No significant differences in 30-day all-cause mortality rates were observed among AMI (acute myocardial infarction) patients during most of the periods, whereas the annual 30-day all-cause mortality rate among CHF patients was 23% higher. Conclusions: AMI and CHF hospitalizations were significantly lower during the first year of the pandemic relative to 2017–9. Mortality rates were higher in the case of CHF patients but not in the case of AMI patients, possibly due to a change in the clinical acuity of patients arriving at the hospitals. We conclude that targeted public health messaging should be implemented together with proactive monitoring, in order to identify residual disability in patients who may have received non-optimal treatment during the pandemic.

Patients hospitalised with heart failure across different waves of the COVID-19 pandemic show consistent clinical characteristics and outcomes

BACKGROUND

During the first wave of the COVID-19 pandemic, admissions for cardiovascular disease, including Heart Failure (HF), were reduced. Patients hospitalised for HF were sicker and with increased in-hospital mortality. So far, whether following waves had a different impact on HF patients is unknown.

METHODS

All consecutive patients hospitalised for acute heart failure during three different COVID-19 related national lockdowns were analysed. The lockdown periods were defined according to Government guidelines as 23/3/2020 to 4/7/2020 (First Lockdown), 4/11/2020 to 2/12/2020 (Second Lockdown) and 5/1/2021 to 28/2/2021 (Third Lockdown).

RESULTS

Overall, 184 patients hospitalised for HF were included in the study, 95 during the 1st lockdown, 30 during the 2nd lockdown and 59 during the 3rd lockdown. Across the three groups had comparable clinical characteristics, comorbidities and cardiovascular risk factors. Specialist in-hospital care was uninterrupted during the pandemic showing comparable mortality rates (p = 0.10). Although medical therapy for HF was comparable between the three lockdowns, a significantly higher proportion of patients received Angiotensin Receptor-Neprilysin Inhibitors (ARNI) in the second and third lockdowns (p < 0.001).

CONCLUSIONS

Although public health approaches changed throughout the pandemic, the clinical characteristics and outcomes of HF patients were consistent across different waves. For patients hospitalised in the subsequent waves, a more rapid optimization of medical therapy was observed during hospitalization. Particular attention should be devoted to prevent collateral cardiovascular damage during public health emergencies.

Cardiovascular Mortality During the COVID-19 Pandemics in a Large Brazilian City: A Comprehensive Analysis

Introduction:

The impact of COVID-19 pandemics on cardiovascular diseases (CVD) may be caused by health system reorganization and/or collapse, or from changes in the behaviour of individuals. In Brazil, municipalities were empowered to define regulatory measures, potentially resulting in diverse effects on CVD morbimortality.

Objective:

To analyse the impact of COVID-19 pandemics on CVD outcomes in Belo Horizonte (BH), the sixth greater capital city in Brazil, including: mortality, mortality at home, hospitalizations, intensive care unit utilization, and in-hospital mortality; and the differential effect according to sex, age range, social vulnerability, and pandemic’s phase.

Methods:

Ecological study analysing data from the Mortality and Hospital Information System of BH residents aged ≥30 years. CVD was defined as in Chapter IX from ICD-10. Social vulnerability was classified by a composite socioeconomic index as high, medium and low. The observed age-standardized rates for epidemiological weeks 10–48, 2020, were compared to the expected rates (mean of 2015–2019). Risk ratios (RiR) were analysed and 95% confidence intervals were calculated for all estimates. Population projected to 2020 for BH and its census tracts were used to calculate rates.

Results:

We found no changes in CVD mortality rates (RiR 1.01, 95%CI 0.96–1.06). However, CVD deaths occurred more at homes (RiR 1.32, 95%CI 1.20–1.46) than in hospitals (RiR 0.89, 95%CI 0.79–0.99), as a result of a substantial decline in hospitalization rates, even though proportional in-hospital deaths increased. The rise in home deaths was greater in older adults and in had an increasing gradient in those more socially vulnerable (RiR 1.45); for high (RiR 1.45), medium (RiR 1.32) and low vulnerability (RiR 1.21).

Conclusion:

The greater occurrence of CVD deaths at home, in parallel with lower hospitalization rates, suggests that CVD care was disrupted during the COVID-19 pandemics, which more adversely affected older and more socially vulnerable individuals, exacerbating health inequities in BH.