Longitudinal Trends in Cardiovascular Risk Factor Profiles and Complications Among Patients Hospitalized for COVID-19 Infection: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry

BACKGROUND

The COVID-19 pandemic has evolved through multiple phases characterized by new viral variants, vaccine development, and changes in therapies. It is unknown whether rates of cardiovascular disease (CVD) risk factor profiles and complications have changed over time.

METHODS

We analyzed the American Heart Association COVID-19 CVD registry, a national multicenter registry of hospitalized adults with active COVID-19 infection. The time period from April 2020 to December 2021 was divided into 3-month epochs, with March 2020 analyzed separately as a potential outlier. Participating centers varied over the study period. Trends in all-cause in-hospital mortality, CVD risk factors, and in-hospital CVD outcomes, including a composite primary outcome of cardiovascular death, cardiogenic shock, new heart failure, stroke, and myocardial infarction, were evaluated across time epochs. Risk-adjusted analyses were performed using generalized linear mixed-effects models.

RESULTS

A total of 46 007 patient admissions from 134 hospitals were included (mean patient age 61.8 years, 53% male, 22% Black race). Patients admitted later in the pandemic were younger, more likely obese, and less likely to have existing CVD (P_trend ≤0.001 for each). The incidence of the primary outcome increased from 7.0% in March 2020 to 9.8% in October to December 2021 (risk-adjusted P_trend=0.006). This was driven by an increase in the diagnosis of myocardial infarction and stroke (P_trend<0.0001 for each). The overall rate of in-hospital mortality was 14.2%, which declined over time (20.8% in March 2020 versus 10.8% in the last epoch; adjusted P_trend<0.0001). When the analysis was restricted to July 2020 to December 2021, no temporal change in all-cause mortality was seen (adjusted P_trend=0.63).

CONCLUSIONS

Despite a shifting risk factor profile toward a younger population with lower rates of established CVD, the incidence of diagnosed cardiovascular complications of COVID increased from the onset of the pandemic through December 2021. All-cause mortality decreased during the initial months of the pandemic and thereafter remained consistently high through December 2021.

Enriching the American Heart Association COVID-19 Cardiovascular Disease Registry Through Linkage With External Data Sources: Rationale and Design

Background The AHA Registry (American Heart Association COVID-19 Cardiovascular Disease Registry) captures detailed information on hospitalized patients with COVID-19. The registry, however, does not capture information on social determinants of health or long-term outcomes. Here we describe the linkage of the AHA Registry with external data sources, including fee-for-service (FFS) Medicare claims, to fill these gaps and assess the representativeness of linked registry patients to the broader Medicare FFS population hospitalized with COVID-19. Methods and Results We linked AHA Registry records of adults ≥65 years from March 2020 to September 2021 with Medicare FFS claims using a deterministic linkage algorithm and with the American Hospital Association Annual Survey, Rural Urban Commuting Area codes, and the Social Vulnerability Index using hospital and geographic identifiers. We compared linked individuals with unlinked FFS beneficiaries hospitalized with COVID-19 to assess the representativeness of the AHA Registry. A total of 10 010 (47.0%) records in the AHA Registry were successfully linked to FFS Medicare claims. Linked and unlinked FFS beneficiaries were similar with respect to mean age (78.1 versus 77.9, absolute standardized difference [ASD] 0.03); female sex (48.3% versus 50.2%, ASD 0.04); Black race (15.1% versus 12.0%, ASD 0.09); dual-eligibility status (26.1% versus 23.2%, ASD 0.07); and comorbidity burden. Linked patients were more likely to live in the northeastern United States (35.7% versus 18.2%, ASD 0.40) and urban/metropolitan areas (83.9% versus 76.8%, ASD 0.18). There were also differences in hospital-level characteristics between cohorts. However, in-hospital outcomes were similar (mortality, 23.3% versus 20.1%, ASD 0.08; home discharge, 45.5% versus 50.7%, ASD 0.10; skilled nursing facility discharge, 24.4% versus 22.2%, ASD 0.05). Conclusions Linkage of the AHA Registry with external data sources such as Medicare FFS claims creates a unique and generalizable resource to evaluate long-term health outcomes after COVID-19 hospitalization.

Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure

Importance

Traditional models for predicting in-hospital mortality for patients with heart failure (HF) have used logistic regression and do not account for social determinants of health (SDOH).

Objective

To develop and validate novel machine learning (ML) models for HF mortality that incorporate SDOH.

Design, Setting, and Participants

This retrospective study used the data from the Get With The Guidelines-Heart Failure (GWTG-HF) registry to identify HF hospitalizations between January 1, 2010, and December 31, 2020. The study included patients with acute decompensated HF who were hospitalized at the GWTG-HF participating centers during the study period. Data analysis was performed January 6, 2021, to April 26, 2022. External validation was performed in the hospitalization cohort from the Atherosclerosis Risk in Communities (ARIC) study between 2005 and 2014.

Main Outcomes and Measures

Random forest-based ML approaches were used to develop race-specific and race-agnostic models for predicting in-hospital mortality. Performance was assessed using C index (discrimination), regression slopes for observed vs predicted mortality rates (calibration), and decision curves for prognostic utility.

Results

The training data set included 123 634 hospitalized patients with HF who were enrolled in the GWTG-HF registry (mean [SD] age, 71 [13] years; 58 356 [47.2%] female individuals; 65 278 [52.8%] male individuals. Patients were analyzed in 2 categories: Black (23 453 [19.0%]) and non-Black (2121 [2.1%] Asian; 91 154 [91.0%] White, and 6906 [6.9%] other race and ethnicity). The ML models demonstrated excellent performance in the internal testing subset (n = 82 420) (C statistic, 0.81 for Black patients and 0.82 for non-Black patients) and in the real-world-like cohort with less than 50% missingness on covariates (n = 553 506; C statistic, 0.74 for Black patients and 0.75 for non-Black patients). In the external validation cohort (ARIC registry; n = 1205 Black patients and 2264 non-Black patients), ML models demonstrated high discrimination and adequate calibration (C statistic, 0.79 and 0.80, respectively). Furthermore, the performance of the ML models was superior to the traditional GWTG-HF risk score model (C index, 0.69 for both race groups) and other rederived logistic regression models using race as a covariate. The performance of the ML models was identical using the race-specific and race-agnostic approaches in the GWTG-HF and external validation cohorts. In the GWTG-HF cohort, the addition of zip code-level SDOH parameters to the ML model with clinical covariates only was associated with better discrimination, prognostic utility (assessed using decision curves), and model reclassification metrics in Black patients (net reclassification improvement, 0.22 [95% CI, 0.14-0.30]; P < .001) but not in non-Black patients.

Conclusions and Relevance

ML models for HF mortality demonstrated superior performance to the traditional and rederived logistic regressions models using race as a covariate. The addition of SDOH parameters improved the prognostic utility of prediction models in Black patients but not non-Black patients in the GWTG-HF registry.

Heart Failure Quality of Care and In-Hospital Outcomes During the COVID-19 Pandemic Findings from the Get With The Guidelines-Heart Failure Registry

Aims

To assess heart failure (HF) in‐hospital quality of care and outcomes before and during the COVID‐19 pandemic.

Methods and results

Patients hospitalized for HF with ejection fraction (EF) <40% in the American Heart Association Get With The Guidelines©‐HF (GWTG‐HF) registry during the COVID‐19 pandemic (3/1/2020–4/1/2021) and pre‐pandemic (2/1/2019–2/29/2020) periods were included. Adherence to HF process of care measures, in‐hospital mortality, and length of stay (LOS) were compared in pre‐pandemic vs. pandemic periods and in patients with vs. without COVID‐19. Overall, 42 004 pre‐pandemic and 37 027 pandemic period patients (median age 68, 33% women, 58% White) were included without observed differences across clinical characteristics, comorbidities, vital signs, or EF. Utilization of guideline‐directed medical therapy at discharge was comparable across both periods, with rates of implantable cardioverter defibrillator (ICD) placement or prescription lower during the pandemic (vs. pre‐pandemic period). In‐hospital mortality (3.0% vs. 2.5%, p <0.0001) and LOS (mean 5.7 vs. 5.4 days, p <0.0004) were higher during the pandemic vs. pre‐pandemic. The highest in‐hospital mortality during the pandemic was observed among patients hospitalized in the Northeast region (3.4%). Among patients concurrently diagnosed with COVID‐19 (n = 549; 1.5%), adherence to ICD placement or prescription, prescription of aldosterone antagonist or angiotensin‐converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor–neprilysin inhibitor at discharge were lower, and in‐hospital mortality (8.2% vs. 3.0%, p <0.0001) and LOS (mean 7.7 vs. 5.7 days, p <0.0001) were higher than those without COVID‐19.

Conclusion

Among GWTG‐HF participating hospitals, patients hospitalized for HF with reduced EF during the pandemic received similar care quality but experienced higher in‐hospital mortality than the pre‐pandemic period.

Association of COVID-19 Hospitalization Volume and Case Growth at US Hospitals with Patient Outcomes

BACKGROUND

Whether the volume of coronavirus disease 2019 (COVID-19) hospitalizations is associated with outcomes has important implications for the organization of hospital care both during this pandemic and future novel and rapidly evolving high-volume conditions.

METHODS

We identified COVID-19 hospitalizations at US hospitals in the American Heart Association COVID-19 Cardiovascular Disease Registry with ≥10 cases between January and August 2020. We evaluated the association of COVID-19 hospitalization volume and weekly case growth indexed to hospital bed capacity, with hospital risk-standardized in-hospital case-fatality rate (rsCFR).

RESULTS

There were 85 hospitals with 15,329 COVID-19 hospitalizations, with a median hospital case volume was 118 (interquartile range, 57, 252) and median growth rate of 2 cases per 100 beds per week but varied widely (interquartile range: 0.9 to 4.5). There was no significant association between overall hospital COVID-19 case volume and rsCFR (rho, 0.18, P = .09). However, hospitals with more rapid COVID-19 case-growth had higher rsCFR (rho, 0.22, P = 0.047), increasing across case growth quartiles (P trend = .03). Although there were no differences in medical treatments or intensive care unit therapies (mechanical ventilation, vasopressors), the highest case growth quartile had 4-fold higher odds of above median rsCFR, compared with the lowest quartile (odds ratio, 4.00; 1.15 to 13.8, P = .03).

CONCLUSIONS

An accelerated case growth trajectory is a marker of hospitals at risk of poor COVID-19 outcomes, identifying sites that may be targets for influx of additional resources or triage strategies. Early identification of such hospital signatures is essential as our health system prepares for future health challenges.

Stroke Among Patients Hospitalized With COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry

Supplemental Digital Content is available in the text.

Coronavirus disease 2019 (COVID-19) may be associated with increased risk for ischemic stroke. We present prevalence and characteristics of strokes in patients with laboratory-confirmed severe acute respiratory syndrome coronavirus-2 infection enrolled in the American Heart Association COVID-19 Cardiovascular Disease Registry.

Treatment and Outcomes of Patients With Ischemic Stroke During COVID-19: An Analysis From Get With The Guidelines-Stroke

Supplemental Digital Content is available in the text.

The coronavirus disease 2019 (COVID-19) pandemic has created challenges in the delivery of acute stroke care. In this study, we analyze the characteristics, evaluation, treatment, and in-hospital outcomes of patients presenting with acute ischemic stroke (AIS) pre-COVID-19 and during COVID-19.

Association of Kidney Disease With Outcomes in COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry

Background

Emerging evidence links acute kidney injury (AKI) in patients with COVID‐19 with higher mortality and respiratory morbidity, but the relationship of AKI with cardiovascular disease outcomes has not been reported in this population. We sought to evaluate associations between chronic kidney disease (CKD), AKI, and mortality and cardiovascular outcomes in patients hospitalized with COVID‐19.

Methods and Results

In a large multicenter registry including 8574 patients with COVID‐19 from 88 US hospitals, data were collected on baseline characteristics and serial laboratory data during index hospitalization. Primary exposure variables were CKD (categorized as no CKD, CKD, and end‐stage kidney disease) and AKI (classified into no AKI or stages 1, 2, or 3 using a modification of the Kidney Disease Improving Global Outcomes guideline definition). The primary outcome was all‐cause mortality. The key secondary outcome was major adverse cardiac events, defined as cardiovascular death, nonfatal stroke, nonfatal myocardial infarction, new‐onset nonfatal heart failure, and nonfatal cardiogenic shock. CKD and end‐stage kidney disease were not associated with mortality or major adverse cardiac events after multivariate adjustment. In contrast, AKI was significantly associated with mortality (stage 1 hazard ratio [HR], 1.72 [95% CI, 1.46–2.03]; stage 2 HR, 1.83 [95% CI, 1.52–2.20]; stage 3 HR, 1.69 [95% CI, 1.44–1.98]; versus no AKI) and major adverse cardiac events (stage 1 HR, 2.17 [95% CI, 1.74–2.71]; stage 2 HR, 2.70 [95% CI, 2.07–3.51]; stage 3 HR, 3.06 [95% CI, 2.52–3.72]; versus no AKI).

Conclusions

This large study demonstrates a significant association between AKI and all‐cause mortality and, for the first time, major adverse cardiovascular events in patients hospitalized with COVID‐19.

Trends in Patient Characteristics and COVID-19 In-Hospital Mortality in the United States During the COVID-19 Pandemic

IMPORTANCE

In-hospital mortality rates from COVID-19 are high but appear to be decreasing for selected locations in the United States. It is not known whether this is because of changes in the characteristics of patients being admitted.

OBJECTIVE

To describe changing in-hospital mortality rates over time after accounting for individual patient characteristics.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective cohort study of 20 736 adults with a diagnosis of COVID-19 who were included in the US American Heart Association COVID-19 Cardiovascular Disease Registry and admitted to 107 acute care hospitals in 31 states from March through November 2020. A multiple mixed-effects logistic regression was then used to estimate the odds of in-hospital death adjusted for patient age, sex, body mass index, and medical history as well as vital signs, use of supplemental oxygen, presence of pulmonary infiltrates at admission, and hospital site.

MAIN OUTCOMES AND MEASURES

In-hospital death adjusted for exposures for 4 periods in 2020.

RESULTS

The registry included 20 736 patients hospitalized with COVID-19 from March through November 2020 (9524 women [45.9%]; mean [SD] age, 61.2 [17.9] years); 3271 patients (15.8%) died in the hospital. Mortality rates were 19.1% in March and April, 11.9% in May and June, 11.0% in July and August, and 10.8% in September through November. Compared with March and April, the adjusted odds ratios for in-hospital death were significantly lower in May and June (odds ratio, 0.66; 95% CI, 0.58-0.76; P < .001), July and August (odds ratio, 0.58; 95% CI, 0.49-0.69; P < .001), and September through November (odds ratio, 0.59; 95% CI, 0.47-0.73).

CONCLUSIONS AND RELEVANCE

In this cohort study, high rates of in-hospital COVID-19 mortality among registry patients in March and April 2020 decreased by more than one-third by June and remained near that rate through November. This difference in mortality rates between the months of March and April and later months persisted even after adjusting for age, sex, medical history, and COVID-19 disease severity and did not appear to be associated with changes in the characteristics of patients being admitted.

Acute Ischemic Stroke in Patients With COVID-19: An Analysis From Get With The Guidelines-Stroke

[Figure: see text].

American Heart Association COVID-19 CVD Registry Powered by Get With The Guidelines

BACKGROUND

In response to the public health emergency created by the coronavirus disease 2019 (COVID-19) pandemic, American Heart Association volunteers and staff aimed to rapidly develop and launch a resource for the medical and research community to expedite scientific advancement through shared learning, quality improvement, and research. In <4 weeks after it was first announced on April 3, 2020, AHA's COVID-19 CVD Registry powered by Get With The Guidelines received its first clinical records.

METHODS AND RESULTS

Participating hospitals are enrolling consecutive hospitalized patients with active COVID-19 disease, regardless of CVD status. This hospital quality improvement program will allow participating hospitals and health systems to evaluate patient-level data including mortality rates, intensive care unit bed days, and ventilator days from individual review of electronic medical records of sequential adult patients with active COVID-19 infection. Participating sites can leverage these data for onsite, rapid quality improvement, and benchmarking versus other institutions. After 9 weeks, >130 sites have enrolled in the program and >4000 records have been abstracted in the national dataset. Additionally, the aggregate dataset will be a valuable data resource for the medical research community.

CONCLUSIONS

The AHA COVID-19 CVD Registry will support greater understanding of the impact of COVID-19 on cardiovascular disease and will inform best practices for evaluation and management of patients with COVID-19.

Utstein recommendation for emergency stroke care

Background

Recent advances in treatment for stroke give new possibilities for optimizing outcomes. To deliver these prehospital care needs to become more efficient.

Aim

To develop a framework to support improved delivery of prehospital care. The recommendations are aimed at clinicians involved in prehospital and emergency health systems who will often not be stroke specialists but need clear guidance as to how to develop and deliver safe and effective care for acute stroke patients.

Methods

Building on the successful implementation program from the Global Resuscitation Alliance and the Resuscitation Academy, the Utstein methodology was used to define a generic chain of survival for Emergency Stroke Care by assembling international expertise in Stroke and Emergency Medical Services (EMS). Ten programs were identified for Acute Stroke Care to improve survival and outcomes, with recommendations for implementation of best practice.

Conclusions

Efficient prehospital systems for acute stroke will be improved through public awareness, optimized prehospital triage and timely diagnostics, and quick and equitable access to acute treatments. Documentation, use of metrics and transparency will help to build a culture of excellence and accountability.