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Characteristics, Treatment Patterns, and Clinical Outcomes After Heart Failure Hospitalizations in COVID-19 Pandemic, March – October 2020

Objective To compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the COVID-19 pandemic. Methods The study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations in COVID-19 pandemic (Mar- Oct 2020) and 6648 in the pre-COVID-19 (Oct 2018 – Feb 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether pre-specified study outcomes vary by timeframes. Results The adjusted 30-day readmission rate decreased from 13.1% in pre-COVID-19 to 10.0% in the COVID-19 pandemic period (relative risk reduction 23%, number needed to avoid one additional readmission 33, hazard ratio [HR] 0.77, 95% confidence interval [CI] 0.66 – 0.89). Conversely, all-cause mortality increased from 9.7% in pre-COVID-19 to 11.3% in the COVID-19 pandemic period (relative risk increase 16%, number of admissions needed for one additional death 62.5: HR 1.19, 95% CI 1.02 – 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study timeframes, the disease severity, heart failure subtypes, and treatment patterns remained unchanged. Conclusions The findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions, but higher incidence of 30-day mortality with broadly similar use of heart failure medication, surgical interventions, and devices during the COVID-19 pandemic compared with pre-COVID-19 timeframe.


Introduction
On March 13, 2020, COVID-19 was declared as a national emergency in the United States. Subsequently several states enacted lockdown measures to slow the spread of SARS-CoV-2 1, 2 . The effects of this proclamation were almost immediate for all disciplines of medicine with a sharp decline in emergency departments visits across the Nation for several life-threatening diagnostic categories and rates of hospitalizations for acute myocardial infarction (AMI) 3,4 , stroke 5 , and even surgical emergencies 6 with no evidence of decrease in incidence of these conditions. Heart failure (HF) patients are especially vulnerable for COVID-19-related disruptions in care process due to high-rates of hospitalizations, 30-day readmissions, and morality. [7][8][9] Before the pandemic, the trajectory was one of an increasing acute decompensated heart failure (ADHF) hospitalizations with higher comorbidity burden in association with a declining hospital mortality 10,11 . A few prior studies reported data on patients with ADHF recruited early in the COVID-19 pandemic and raised concern for adherence to quality metrics and clinical outcomes. These studies were largely based on administrative data lacking granular clinical information. With multiple surges in COVID-19 activity, the collateral effect of COVID-19 pandemic on ADHF hospitalization and its outcome warrant further investigations.
To address these knowledge gaps, we aimed to compare pre-pandemic (October 2018 -February 2020) to during the pandemic (March -October 2020) hospitalizations for HF severity and types, treatment patterns, in-hospital clinical outcomes, and 30-day readmissions and mortality. To examine the strength of the main analysis, a sensitivity analysis was performed using a second comparator cohort of ADHF admissions in the matched calendar months in 2019 (March -October 2019). Considering the potential geographical variations in these outcomes, we conducted a mixed study design that included a cohort of J o u r n a l P r e -p r o o f HF population from a large healthcare system (16 centers across three geographically dispersed US states) as well as a systematic review that provides data from other locations and places the findings of the present study in the context of previously published studies. This mixed study follows the framework by Lin and colleagues and can provide stronger conclusions and improved applicability 12 .

Data source
Data were abstracted from the inpatient database of the Mayo Clinic, one of the largest integrated healthcare networks in the United States, with three tertiary care centers and 13 community hospitals dispersed across Arizona, Florida, and Minnesota, from October 2018 to October 2020.

Study design and population
The unit of analysis was hospitalization for ADHF for at least 1 night. The diagnosis of ADHF was defined by the International Classification of Diseases, tenth revision (ICD-10) codes and subsequently verified by manual review of electronic medical records. The ICD-10 codes for these conditions are described in Supplement Table 1. Further details of data extraction were published previously 13

Baseline covariates
The following data were abstracted from electronic medical records (EMR).
J o u r n a l P r e -p r o o f Socio-demographic indicators. Data-related to age, sex at birth (male and female), race (white and nonwhite), marital status (married and others), and body mass index (BMI).

Physiological and laboratory measures.
Values for systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate, blood urea nitrogen (BUN), and creatinine on the day of admission. An average of 3 consecutive measurements of SBP, DBP, or heart rate were used for data analysis.

Measure of comorbidities.
A total of 16 of 20 comorbidities (Figure 1), specified by the Office of the Assistant Secretary for Health 16 were identified from the list of secondary diagnoses. The obstructive sleep apnea (OSA) was incorporated as a comorbidity due to increasing prevalence in heart failure population. 30-day all-cause readmission was defined as repeat hospitalization from any condition occurring within 30 days from the date of discharge. Heart failure treatment pattern (Figure 1). Divided in to four categories: 1) admission services: cardiology, internal medicine, family medicine, critical care, and other specialty services based on the premise that clinical outcome vary with hospitalization by sub-specialty service 21-23 , 2) guidelinedirected pharmacological therapy 17,18 , 3) guideline-directed non-pharmacological interventions, 4) discharge destination 17, 24-26 .

Follow-up
All patients were followed up until readmission, death, or censoring at 30-days after discharge whichever occurred first.

Systematic review
The systematic review protocol was registered with PROSPERO (CRD42022310307) and conducted in accordance with Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement 27 . Search details were previously published 28 . Briefly, we searched multiple databases with no language restriction through October 11, 2021, for studies that compared ADHF hospitalizations between COVID-19 and pre-COVID periods and reported following outcomes: trends in ADHF hospitalization, treatment patterns, in-hospital mortality, readmissions or 30-day mortality. The detailed search strategy is described in the Supplement. Two investigators (MY, AS), independently screened search results, selected studies, abstracted data, and assessed the risk of bias by the Newcastle-Ottawa Scale for cohort studies 29 .

APPROACHES FOR MAIN ANALYSES
J o u r n a l P r e -p r o o f Descriptive statistics We described continuous variables with normal distribution as mean and standard deviation (SD), variables with non-normal distribution as median and interquartile range, and categorical variables as number of patients and percentages. We used unpaired t-test for parametric data, Wilcoxon rank-sum test for non-parametric data, and  2 and Fisher exact tests for categorical variable to compare demographics, social indicators, anthropometric measure, physiological data, and key laboratory measures between time periods.
Logistic regression models. Separate logistic regression models were developed to evaluate whether odds of comorbidities, measures of treatment patterns, or clinical outcomes differed by time frame accounting for patient-level characteristics. Due to large number of independent variables and the features of some of the variables, we customized each regression to include the most relevant variables only.
Poisson regression models. Incidence rate ratios (IRR) and 95% confidence interval (CI) were estimated to assess time trends in hospitalizations. we included both age and exposure of months as covariates in the Poisson model. Hospitalizations were included as an offset variable.

Kaplan-Meier analyses.
Cumulative event rates were evaluated with censoring time 30 days and differences were assessed by log-rank test.
Cox proportional hazard models. Separate multivariable Cox proportional hazard models were generated to estimate hazard ratio (HR) and 95% CI for readmission (all-cause and HF-specific readmission) and all-cause mortality for patients hospitalized in COVID-19 pandemic vs pre-COVID-19 period. Three sequential Cox regression models were fitted: model 1 adjusted for age, sex, race, marital

Study population
From October 2018 to October 2020, a combined total of 8989 ADHF hospitalizations occurred among 6769 unique patients including 2341 ADHF hospitalizations in the COVID-19 pandemic, 6648 in prepandemic, and 3094 in the matched calendar months in 2019.

Baseline characteristics (Table 1)
Overall mean age was 74 (±14.7) years with 5033 (56%) men, 8270 (92%) white, and 4584 (51%) married. Patients who were hospitalized during COVID-19 pandemic were not different from those hospitalized in baseline or matching comparison periods in sex, race, marital status, BMI, heart failure types, SBP, and heart rate. Although age, BUN, and creatinine showed between group significant statistical differences due to the size of the population and may have no clinical relevance and the directionality of the data. However, ADHF patients hospitalized during COVID-19 pandemic, compared to pre-pandemic timeframe had lower prevalence of atrial fibrillation, chronic kidney disease (CKD), cancer, dementia, dyslipidemia, hypertension, and other psychiatric illnesses as shown in Figure 1.

J o u r n a l P r e -p r o o f
In-hospital outcome (Figure 1). we found no between timeframe differences in the incidence of AMI or shock. However, in-hospital mortality was lower in COVID-19 pandemic than in pre-COVID-19 period.
Treatment patterns (Figure 1). Proportions of patients directly admitted to services other than internal medicine, cardiovascular medicine, critical care, and family medicine were increased during the COVID-19 pandemic vs. pre-pandemic period. Conversely, patients who were discharged home with home care, nursing home, hospice, or long-term acute care were decreased compared to those dismissed home with self-care during the COVID-19 pandemic vs. pre-pandemic periods. Except for statin and anticoagulants, the prescription of which were increased in pandemic vs. pre-pandemic period, exposure to other guideline-directed therapy remained unchanged across the timeframes.

30-day outcome measures (Figure 3)
Upper panels in Figure 3 show Kaplan-Meier estimates for all-cause readmissions and all-cause mortality by timeframes. Multivariable Cox regression analysis (lower panel in Figure 3) demonstrated that allcause readmission was lower during COVID-19 pandemic (10.0%) than in the pre-pandemic period (13.1%), which implied a 3.1% absolute risk reduction, 23% relative risk reduction (RRR), and number needed to avoid one additional readmission was 33.3. Conversely, all-cause mortality was higher in the COVID-19 pandemic (11.3%) than in pre-pandemic period (9.7%), which translated to a 1.6% absolute and 16% RRR increased risk of death, and number of index admissions needed for one additional death was 62.5.

Competing risk analysis
Of 8989 patients 65 (0.72%) A 0.72% had both 30-day readmission and deaths. The rate was too low that a competing analysis might not be required.

Assessment of possible collinearity
We conducted correlation analysis between key variable with most variables had a weak correlation as shown in Supplement Table 3. The problems related to collinearity and overfitting were limited.

Main findings
This large, tristate, multicenter cohort study that compared 2341 ADHF hospitalizations in the COVID-19 pandemic with 6648 hospitalizations in pre-COVID-19 era, provides following key findings. First, a decline in index ADHF hospitalizations and fewer 30-day all-cause readmissions occurred concomitant with increased 30-day mortality during the COVID-19 pandemic compared with pre-pandemic control periods. Our findings imply that 3.1% fewer rehospitalizations occurred during the study COVID-19 pandemic period than would have admitted to hospital in pre-pandemic time. Conversely, an additional 1.6% HF patients died in 8 months through COVID-19 pandemic than would have died in pre-COVID-19 times. Second, decline in HF hospitalizations were consistent across HF subtypes by LVEF and HF severity ADHERE grading, and particularly evident in older adults with higher comorbidity burden. Third, admission to critical care unit, treatment patterns including drugs, surgical interventions and devices, incident AMI, shock, and in-hospital death did not vary across the pre-pandemic and pandemic timeframes. Lack of statistical significance in variables such as incident heart transplant between pre-COVI-19 and during the COVID-19 pandemic groups should be viewed with circumspection due to fewer events and a large 95 CI that may lead to a larger margin of error and less precise estimation. Fourth, a higher proportion of patients were admitted to services other than internal medicine, cardiology, and critical care or discharged home with self-care during the COVID-19 pandemic compared to pre- second wave in COVID-19 activity, a finding consistent with a report from California in AMI or stroke 51 but contradictory to data from England 52 attributable to geographical differences.
Patient and heart failure characteristics. HF patients have become progressively more complex over time due to increased accumulation of non-cardiovascular comorbidities based on pre-pandemic data 53 .
In reversal of this course, patients hospitalized for ADHF in COVID-19 pandemic tend to have lower comorbidity burden in our cohort consistent with findings in AMI or stroke 54 . Previous studies revealed mixed results regarding HF severity and HF types among HF patients hospitalized before and during the COVID-19 pandemic probably reflect differences in measurement of disease severity and LVEF cutoff used for classifying HF subtypes 34,35,38,[41][42][43]46 .
Treatment patterns. Analysis of receipt of in-hospital guideline-directed interventions according to pre-COVID and COVID-19 timeframes yielded comparable results in the present study. Except for an isolated report showing a reduction in angiotensin converting enzyme inhibitor prescription 46 during the pandemic other published studies corroborated our findings. 34,38,39 . The valve repair surgery was less frequently performed in patients with heart failure during the COVID-19 pandemic compared to prepandemic period. On the contrary, the frequency of pacemaker or ICD implantation, coronary artery J o u r n a l P r e -p r o o f revascularization by PCI or CABG, placement of LVAD, and heart transplantation were comparable across COVID-19 pandemic and pre-pandemic time frames, a finding in agreement with previous reports 38,41,43 These findings are contradictory to previous studies in AMI that showed a substantial reduction in adherence to quality care metrics, increased complications, and in-hospital mortality during the pandemic. 49,55,56 Readmissions and mortality. Decreases in hospital readmissions and in-hospital mortality in COVID-19 pandemic compared with pre-pandemic times observed in the present cohort study did not reach statistical significance in the accompanying meta-analysis. However, the present cohort study together with meta-analysis clearly demonstrated increased 30-day all-cause mortality following index ADHF hospitalization in the COVID-19 pandemic compared with pre-pandemic period, consistent with a recent report in AMI. 57 Increased mortality may persist beyond 30 days among patients with HF hospitalized during the COVID-19 pandemic. 45 A systematic review. The systematic review critically appraised published studies through October 2021 that evaluated in-hospital mortality, 30-day readmission, and 30-day mortality in AHDF patients hospitalized in COVID-19 pandemic compared to those admitted in pre-pandemic period. The increased 30-day mortality 37, 43 among patients hospitalized during the pandemic were consistent with our findings. the results associated with in-hospital mortality and 30-day readmission were divergent from those of the present study attributed to differences in study design, population, and geography.

Attributes for decreased hospitalizations and increased mortality
Lower rates of readmissions might be attributable to restraints in seeking care for perceived threat of contracting COVID-19 in healthcare environment 58 , transition to telemedicine and device monitoring 59,60 , reduced triggers for decompensation due to a historic low level of influenza and other non-COVID viruses activity 61 . Plausible explanations for increased mortality in COVID-19 era are competing COVID-19 infection 37 , rise in out-of-hospital cardiac arrest 62,63 , an inverse association between readmissions J o u r n a l P r e -p r o o f and 30-day mortality 64 , missed opportunity to avert premature death, insufficient post-discharge care, and worsening socio-economic disparity in healthcare access due to COVID-19.

Strengths and limitations
Strengths of the study include large sample size of real-world patients from academic and rural community hospitals across three geographically dispersed states, comprehensive data collection especially of comorbidities and treatment patterns, sensitivity analysis, and data integration with that of

Implications for clinical practice
Patients with heart failure are at increased risk of death if they inadvertently avoid hospitalizations during the COVID-19 pandemic, particularly those with advanced age and higher comorbidity burden.
Our results indicate that treatment patterns have been consistent during COVID-19 pandemic vs prepandemic periods among hospitalized patients with ADHF with no decline in rates of provision of even J o u r n a l P r e -p r o o f specific advanced cardiovascular procedures. These results have important implications for shared decision for advanced heart failure and not to miss an opportunity to improve quality of care even during times, as challenging as COVID-19 pandemic.
We emphasize continued adherence to quality metrics, improved post-discharge care, and a broader patient education and behavioral interventions to promote timely access of care at the community level.
The study was performed during the pre-pandemic period; therefore, the value of COVID-19 vaccination could not be determined.

Implications for research
Further studies are needed to extend our findings in minority population and to determine what factors drive reductions in rates of heart failure hospitalization and readmissions and increase in mortality during COVID-19 pandemic requires further research.

Conclusions
This large tri-state multisite cohort study of ADHF hospitalizations together with meta-analysis suggest lower rates of 30-day readmission but higher rates of 30-day mortality with similar use of heart failure medication, surgical interventions, and devices during the COVID-19 pandemic compared with pre-COVID-19 times. Our findings conceptualize a COVID-19 HF phenotype with younger age, fewer comorbidities, and increased 30-day mortality.

Funding source
The study was funded by the Mayo Clinic Health System. The funding source had no role in the study design, data collection, data analysis, or manuscript drafting.

Declaration of Competing interest
Professor Fonarow disclosed consulting for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis, Dr. Sagar Dugani is being supported by the National Institute

Title
Results of comparative multivariable logistic regression analysis of patient-and hospital-level characteristic of hospitalized patients for acute decompensated heart failure presented as Forest plot with point estimates in odds ratio (OR) and corresponding 95% confidence intervals (CI).

Text at the bottom of the Figure 1
Comparisons of distribution of comorbidities, treatment patterns, hospital-level characteristics, and in-hospital clinical outcomes between COVID-19 and pre-COVID-19 timeframes. *Comorbidities were adjusted to age, sex, race, marital status, and body mass index (BMI) and **variables in other categories were adjusted to age, sex, race, marital status, BMI, and comorbidities. Text at the bottom of the Figure 2 Part A illustrates trends in cumulative hospitalizations for acute decompensated heart failure by calendar month (October 2018-October 2020) with each bar stacked to represent monthly aggregate of study population by study state. Trend line (black line on the top) was constructed using multivariate time-series estimation with age-adjusted rate as dependent variable and the calendar month as independent variable. The superimposed curved orange line displays trends in COVID-19 cases from March -October 2020 in the United States reported to Centers for Disease Control and Prevention.
Part B represent stacked bar diagram of % distribution of acute decompensated heart failure patients by three risk categories: low-(bottom), intermediate-(middle), and high-risk (top) categories for adverse in-hospital events in accordance with modified Acute Decompensated Heart Failure National Registry (ADHERE) risk stratification. No timeframes differences in proportions of hospitalizations by low-, intermediate-, or high-risk categories (P=0.35) Part C shows stacked bar diagram of % distribution of acute decompensated heart failure patients by three heart failure types: heart failure with reduced ejection fraction (HFrEF) displayed at the bottom, heart failure with mid-range ejection fraction (HFmrEF) in the middle, heart failure with preserved ejection fraction (HFpEF) in the top. No timeframes differences in proportions of hospitalizations by heart failure types (P=0.84)  Text at the bottom of the Figure 4 In these studies patients hospitalized with acute decompensated heart failure in the COVID-19 pandemic were compared with those in the pre-pandemic period for in-hospital mortality (A), 30-day mortality (B), and 30-day readmissions and the results are displayed in forest plot with point estimates and 95% confidence intervals (CI).