Impact of Preinfection Left Ventricular Ejection Fraction on Outcomes in COVID-19 Infection

Morin, Daniel P.; Manzo, Marc; Pantlin, Peter G.; Verma, Rashmi; Bober, Robert; Krim, Selim R.; Lavie, Carl J.; Qamruddin, Salima; Shah, Sangeeta; Soto, Jose D. Tafur; Ventura, Héctor O.; Price‐Haywood, Eboni G.

doi:10.1016/j.cpcardiol.2021.100845

Cited by 7 publications

(9 citation statements)

References 27 publications

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“…335 of these patients had LVEF information available, and in this subgroup, LVEF lower than 40% was associated with the highest risk 32 . On the contrary, another retrospective study of 396 patients with an echo prior to admission due to COVID-19 did not find a significant association between LVEF and outcomes 33 . Important to note, in both studies, no other echo information was evaluated, and, thus, they had the limitation of excluding diastolic function and its potential interaction with heart failure on in-hospital mortality.…”

Section: Discussionmentioning

confidence: 88%

Impact of previous cardiac function status assessed by echocardiography on the outcome of COVID-19

Carrión

Olmos

Luaces

et al. 2022

Sci Rep

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More than 91,000 fatalities due to Coronavirus Disease 2019 (COVID-19) have occurred in Spain. Several factors are associated with increased mortality in this disease, including cardiovascular risk factors (CVRF). However, information on the cardiac function of patients prior to the onset of COVID-19 is scarce and the potential impact it may have is uncertain. The aim of the EchoVID study was to describe the potential association between CVRF and cardiac function status prior to SARS-CoV-2 infection and in-hospital mortality. We studied clinical characteristics and cardiac function of patients admitted during the first wave of COVID-19. All patients had a transthoracic echocardiogram performed in the previous 12 months prior to diagnosis; conventional systolic and diastolic function parameters were analyzed. Logistic regression analysis was performed to identify predictors of in-hospital mortality. We included 296 individuals. Median age was higher in the group of patients who died (81.0 vs 76.1 years; p = 0.007). No significant differences were found in CVRF. Survivors were more frequently receiving anticoagulation therapy (52.9% vs 70.8%; p = 0.003). LVEF, although preserved on average in both groups, was significantly lower in the group of deceased patients (56.9% vs 61.1%; p = 0.017). Average E/e′ ratio was higher in the deceased group (11.1 vs 10.1; p = 0.049). Five variables were found to be independently associated with in-hospital mortality due to COVID-19: Age, male gender, LVEF, E/e′ ratio and anticoagulation therapy. A model including these variables had an area under the ROC curve of 0.756 (CI 0.669–0.843). The echocardiographic variables included in the model significantly improved the discriminative power, compared to a model including only demographic data. Left ventricular ejection fraction and E/e′ ratio prior to SARS-CoV-2 infection are two easily-obtained echocardiographic parameters that provide additional prognostic information over clinical factors when assessing patients admitted for SARS-CoV-2 infection.

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Section: Discussionmentioning

confidence: 88%

Impact of previous cardiac function status assessed by echocardiography on the outcome of COVID-19

Carrión

Olmos

Luaces

et al. 2022

Sci Rep

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“…A systematic review of COVID-19 prediction models found that all available prediction models were at high risk of bias. 7 A low event rate in the studies' validation cohorts was one of the major concerns in the majority of these prediction models. 7 Another study evaluated 22 models (including 17 models developed specifically for COVID-19) and found that no prognostic model offered higher net benefit than univariable predictors (specifically, age and admission oxygen saturation).…”

Section: Discussionmentioning

confidence: 99%

“…7 A low event rate in the studies' validation cohorts was one of the major concerns in the majority of these prediction models. 7 Another study evaluated 22 models (including 17 models developed specifically for COVID-19) and found that no prognostic model offered higher net benefit than univariable predictors (specifically, age and admission oxygen saturation). 11 Moreover, 10 of 17 models were developed in the Chinese population; therefore, they may not be as robust in a different population.…”

Section: Discussionmentioning

confidence: 99%

“…10 Identifying patients at high risk of adverse outcomes at the time of presentation plays an important role in allocating limited resources. 4,7 Various prediction models have been developed to risk stratify patients with COVID-19. However, the majority of these risk prediction models have been found to be at a high risk of bias.…”

mentioning

confidence: 99%

“…However, the majority of these risk prediction models have been found to be at a high risk of bias. 7,11 A combination of epidemiological factors had made urban Louisiana a nexus of early COVID-19 morbidity and mortality. There were 428,000 cases reported through February 2021, with a case fatality rate of 2.2%.…”

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confidence: 99%

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Development and Validation of a Multivariable Risk Prediction Model for COVID-19 Mortality in the Southern United States

Gupta

Kachur

Tafur

et al. 2021

Mayo Clinic Proceedings

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Objective: To evaluate clinical characteristics of patients admitted to the hospital with coronavirus disease 2019 in Southern United States and development as well as validation of a mortality risk prediction model. Patients and Methods: Southern Louisiana was an early hotspot during the pandemic, which provided a large collection of clinical data on inpatients with COVID-19. We designed a risk stratification model to assess the mortality risk for patients admitted to the hospital with COVID-19. Data from 1673 consecutive patients diagnosed with COVID-19 infection and hospitalized between March 1, 2020, and April 30, 2020, was used to create an 11-factor mortality risk model based on baseline comorbidity, organ injury, and laboratory results. The risk model was validated using a subsequent cohort of 2067 consecutive hospitalized patients admitted between June 1, 2020, and December 31, 2020.Results: The resultant model has an area under the curve of 0.783 (95% CI, 0.76 to 0.81), with an optimal sensitivity of 0.74 and specificity of 0.69 for predicting mortality. Validation of this model in a subsequent cohort of 2067 consecutively hospitalized patients yielded comparable prognostic performance. Conclusion:We have developed an easy-to-use, robust model for systematically evaluating patients presenting to acute care settings with COVID-19 infection.

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The impact of COVID-19 infection on heart transplant function

MacKay,

Tomcho,

Khalife

2023

Bull Natl Res Cent

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Background Heart transplant recipients are a subset of immunocompromised patients at particularly high risk of morbidity and mortality from COVID-19. Acute effects of the viral infection have been well-described in the literature but the chronic effects persisting after recovery from infection have not. The aim of this study is to determine the impact of COVID-19 on heart transplant function both during and after recovery from acute infection. Methods We retrospectively analyzed the data of 32 heart transplant recipients at the University of Texas Medical Branch (UTMB). Echocardiograms of patients with documented COVID-19 infection were analyzed at three time points including pre-infection, peri-infection, and post-infection. Echocardiograms of patients without history of infection were analyzed as control. Left Ventricular Ejection Fraction (LVEF) and presence or absence of valvular insufficiency were collected from echocardiograms to assess systolic and valvular function. Results 2 out of 10 COVID-19 positive heart transplant recipients had decreases in LVEF below 20% during the peri-infection period, and one of these patients passed away from complications of infection. Despite this, mean LVEF was not significantly different at peri-infection (p = .3, 95% CI − 11.5 to 27.6) or post-infection (p = .6, 95% CI − 3.6 to 5.8) time points when compared to pre-infection. A statistically significant increase in valvular dysfunction was found among COVID-19 positive patients without documented history of valvular dysfunction on pre-infection echocardiograms (p = .01, 95% CI 19.3% to 96.4%). COVID-19 negative heart transplant recipients did not experience statistically significant changes in LVEF 1, 2, or 3 years after baseline echocardiogram. Conclusion COVID-19 may induce myocardial dysfunction resulting in decreased systolic function and valvular dysfunction among heart transplant recipients. Severity of systolic dysfunction may be a useful prognostic indicator among this patient population. More research must be conducted to fully elucidate the effects of COVID-19 infection on heart transplant recipients.

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Impact of Preinfection Left Ventricular Ejection Fraction on Outcomes in COVID-19 Infection

Cited by 7 publications

References 27 publications

Impact of previous cardiac function status assessed by echocardiography on the outcome of COVID-19

Impact of previous cardiac function status assessed by echocardiography on the outcome of COVID-19

Development and Validation of a Multivariable Risk Prediction Model for COVID-19 Mortality in the Southern United States

The impact of COVID-19 infection on heart transplant function

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