Graduate Trainee, Virginia Commonwealth University
1 active project
Predicting Major Adverse Cardiac Events in Heart Failure Patients with COVID-19
Scientific Questions Being Studied
Aim 1: Determine the predictors of mortality and hospitalization for patients with acute or chronic heart failure (A/CHF) that had a diagnosis of COVID-19. Rapid onset of new or worsening heart failure symptoms are characteristic of AHF. Concomitance of COVID-19 presents additional challenges towards treating A/CHF patients. Studies provide several candidate clinical and laboratory measures associated with worse clinical outcomes for patients with A/CHF and COVID-19. Identifying COVID-19 specific predictors of mortality and hospitalization for A/CHF patients would help explain the pathophysiology behind the progression of COVID-19 in A/CHF patients.
Aim 2: Stratify the risk for suboptimal guideline-directed medical therapy (GDMT) for A/CHF patients with COVID-19. COVID-19 obstructs A/CHF patients from reaching their optimal target doses. Assigning patients into different strata at risk of not achieving optimal GDMT targets may provide clinicians with more impactful treatment options.
- Disease Focused Research (severe acute respiratory syndrome, acute on chronic heart failure)
This retrospective study will include demographic characteristics and clinical features from the All of Us A/CHF and COVID-19 combined cohorts. Missing values will be imputed by multiple imputation. Dimensionality of the data will be reduced by supervised selection. Associations between demographic and clinical features will be made with the outcome of 1-year re-hospitalization with A/CHF as the primary diagnosis. Models generated will utilize standard regression, random forests, and gradient boosting, and will be evaluated by their predictive values, sensitivity, specificity, and c-statistics.
Combined clinical features at baseline will undergo k-means cluster analysis to subset groups. Features will undergo processing as described above. A predictive model will be developed, and a Cox proportional hazards regression analysis for re-hospitalization will be performed for each subgroup. All analyses are to be conducted on the All of Us workbench in the latest version of R and Python.
We may expect to find clinical features and laboratory parameters associated with elevated systemic inflammation, endothelial dysfunction, and hypercoagulation to be strong predictors of adverse outcomes for A/CHF patients who has contracted COVID-19. Clinical features like carbon dioxide and oxygen partial pressures in arterial blood may serve as correlates of worse outcomes. Predictive laboratory features may include high-sensitivity C-reactive protein (hs-CRP), brain and atrial natriuretic peptides (BNP/ANP), ferritin, interleukins, neutrophils, complete blood count and d-dimer quantities among others.
In stratifying patients at-risk of not adhering to GDMT, stratification we expect that data pertaining to a patient’s health care access and utilization, as well as the severity of their COVID-19 infection, may put them at greater risk of non-adherence. Severity of COVID-19 infection may be understood as a profile of high inflammation like elevated levels of hs-CRP or interleukins.
Demographic Categories of Interest
This study will not center on underrepresented populations.
- Joshua Morriss - Graduate Trainee, Virginia Commonwealth University
- Dayanjan Wijesinghe - Early Career Tenure-track Researcher, Virginia Commonwealth University
- Suad Alshammari - Graduate Trainee, Virginia Commonwealth University
- Silas Contaifer - Graduate Trainee, Virginia Commonwealth University
- Daniel Contaifer Junior - Project Personnel, Virginia Commonwealth University
- VIRGINIA UNIVERSITY - Graduate Trainee, Virginia Commonwealth University
- Kevin Ledezma - Graduate Trainee, Boston University
You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.