Impact of Covid-19 outbreak on clinical presentation of patients admitted for acute heart failure in India
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ABSTRACT:
SUBMITTER: Choudhary R
PROVIDER: S-EPMC7563576 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionSince the beginning of the COVID-19 pandemic in March 2020, an intimate relationship between this disease and cardiovascular diseases has been seen. However, few studies assess the development of heart failure during this infection. This study aims to determine the predisposing factors for the development of heart failure (HF) during hospital admission of COVID-19 patients.MethodologyA retrospective and multicenter study of patients with HF admitted for COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry). A bivariate analysis was performed to relate the different variables evaluated in patients developing heart failure during hospital admission. A multivariate analysis including the most relevant clinical variables obtained in bivariate analyses to predict the outcome of heart failure was performed.ResultsA total of 16.474 patients hospitalized for COVID-19 were included (57.5% men, mean age 67 years), 958 of them (5.8%) developed HF during hospitalization. The risk factors for HF development were: age (odds ratio [OR]): 1.042; confidence interval 95% (CI 95%): 1.035-1.050; p < 0.001), atrial fibrillation (OR: 2.022; CI 95%: 1.697-2.410; p < 0.001), BMI > 30 kg/m2 (OR: 1.460 CI 95%: 1.230-1.733; p < 0001), and peripheral vascular disease (OR: 1.564; CI 95%: 1.217-2.201; p < 0.001). Patients who developed HF had a higher rate of mortality (54.1% vs. 19.1%, p < 0.001), intubation rate (OR: 2,36; p < 0.001), and ICU admissions (OR: 2.38; p < 0001).ConclusionsPatients who presented a higher risk of developing HF were older with cardiovascular risk factors. The risk factors for HF development were age, atrial fibrillation, obesity, and peripheral vascular disease. In addition, patients who developed HF more frequently required to be intubated or admitted to the ICU.
| S-EPMC10380653 | biostudies-literature
Project description:Background Excess mortality from cardiovascular disease during the COVID-19 pandemic has been reported. The mechanism is unclear but may include delay or deferral of care, or differential treatment during hospitalization because of strains on hospital capacity. Methods and Results We used emergency department and inpatient data from a 12-hospital health system to examine changes in volume, patient age and comorbidities, treatment (right- and left-heart catheterization), and outcomes for patients with acute myocardial infarction (AMI) and heart failure (HF) during the COVID-19 pandemic compared with pre-COVID-19 (2018 and 2019), controlling for seasonal variation. We analyzed 27 427 emergency department visits or hospitalizations. Patient volume decreased during COVID-19 for both HF and AMI, but age, race, sex, and medical comorbidities were similar before and during COVID-19 for both groups. Acuity increased for AMI as measured by the proportion of patients with ST-segment elevation. There were no differences in right-heart catheterization for patients with HF or in left heart catheterization for patients with AMI. In-hospital mortality increased for AMI during COVID-19 (odds ratio [OR], 1.46; 95% CI, 1.21-1.76), particularly among the ST-segment-elevation myocardial infarction subgroup (OR, 2.57; 95% CI, 2.24-2.96), but was unchanged for HF (OR, 1.02; 95% CI, 0.89-1.16). Conclusions Cardiovascular volume decreased during COVID-19. Despite similar patient age and comorbidities and in-hospital treatments during COVID-19, mortality increased for patients with AMI but not patients with HF. Given that AMI is a time-sensitive condition, delay or deferral of care rather than changes in hospital care delivery may have led to worse cardiovascular outcomes during COVID-19.
| S-EPMC9075301 | biostudies-literature
Project description: Not available
| S-EPMC7835600 | biostudies-literature
Project description:High throughput sequencing is performed on mRNA isolated from whole blood of adult Covid-19 patients, bacterial coinfection with Covid-19 and healthy controls in a South Indian cohort. Samples were collected from individuals at the time of hospitalization or visit to clinic. The Covid-19 samples are categorized by severeity.
2022-02-22 | GSE196822 | GEO
Project description:PurposeStudies performed in spontaneously breathing patients with mild to moderate respiratory failure suggested that prone position (PP) in COVID-19 could be beneficial.Materials and methodsConsecutive critically ill patients with COVID-19 were enrolled in four ICUs. PP sessions lasted at least 3 h each and were performed twice daily. A Cox proportional hazard model identified factors associated with the need of intubation. A propensity score overlap weighting analysis was performed to assess the association between spontaneous breathing PP (SBPP) and intubation.ResultsAmong 379 patients, 40 underwent SBPP. Oxygenation was achieved by high flow nasal canula in all but three patients. Duration of proning was 2.5 [1.6;3.4] days. SBPP was well tolerated hemodynamically, increased PaO2/FiO2 (78 [68;96] versus 63 [53;77] mm Hg, p = 0.004) and PaCO2 (38 [34;43] versus 35 [32;38] mm Hg, p = 0.005). Neither day-28 survival (HR 0.51, 95% CI 0.16-1.16] nor risk of invasive ventilation [sHR 0.96; 95% CI 0.49;1.88] differed between patients who underwent PP and others.ConclusionsSBPP in COVID-19 is feasible and well tolerated in severely hypoxemic patients. It did not induce any effect on risk of intubation and day-28 mortality.
| S-EPMC8087575 | biostudies-literature
Project description:BackgroundPatients with pre-existing heart failure (HF) are likely at higher risk for adverse outcomes in coronavirus disease-2019 (COVID-19), but data on this population are sparse.ObjectivesThis study described the clinical profile and associated outcomes among patients with HF hospitalized with COVID-19.MethodsThis study conducted a retrospective analysis of 6,439 patients admitted for COVID-19 at 1 of 5 Mount Sinai Health System hospitals in New York City between February 27 and June 26, 2020. Clinical characteristics and outcomes (length of stay, need for intensive care unit, mechanical ventilation, and in-hospital mortality) were captured from electronic health records. For patients identified as having a history of HF by International Classification of Diseases-9th and/or 10th Revisions codes, manual chart abstraction informed etiology, functional class, and left ventricular ejection fraction (LVEF).ResultsMean age was 63.5 years, and 45% were women. Compared with patients without HF, those with previous HF experienced longer length of stay (8 days vs. 6 days; p < 0.001), increased risk of mechanical ventilation (22.8% vs. 11.9%; adjusted odds ratio: 3.64; 95% confidence interval: 2.56 to 5.16; p < 0.001), and mortality (40.0% vs. 24.9%; adjusted odds ratio: 1.88; 95% confidence interval: 1.27 to 2.78; p = 0.002). Outcomes among patients with HF were similar, regardless of LVEF or renin-angiotensin-aldosterone inhibitor use.ConclusionsHistory of HF was associated with higher risk of mechanical ventilation and mortality among patients hospitalized for COVID-19, regardless of LVEF.
| S-EPMC7598769 | biostudies-literature
Project description:BackgroundSarcoidosis with cardiac involvement, although rare, has a worse prognosis than sarcoidosis involving other organ systems.ObjectiveWe used a large dataset to train machine learning models to predict in-hospital mortality among sarcoidosis patients admitted with heart failure (HF).MethodUtilizing the National Inpatient Sample, we identified 4659 patients hospitalized with a primary diagnosis of HF. In this cohort, we identified patients with a secondary diagnosis of sarcoidosis using International Statistical Classification of Disease, Tenth Revision (ICD-10) codes. Patients were separated into a training group and a testing group in a 7:3 ratio. Least absolute shrinkage and selection operator regression was used to select variables to prevent model overfitting or underfitting. For machine learning models, logistic regression, random forest, and XGBoosting were applied in the training group. Parameters in each of the models were tuned using the GridSearchCV function. After training, all models were further validated in the testing group. Models were then evaluated using the area under curve (AUC) score, sensitivity, and specificity.ResultsA total of 2.3% of sarcoidosis patients died in HF admission. Our machine learning model analysis found the RF model to have the highest AUC score and sensitivity. Feature analysis found that comorbid arrhythmias and fluid electrolyte disorders were the strongest factors in predicting in-hospital mortality.ConclusionMachine learning methods can be useful in identifying predictors of in-hospital mortality in a given dataset.
| S-EPMC9795270 | biostudies-literature
Project description:During the COVID-19 pandemic, reductions in heart failure (HF) hospitalizations have been widely reported, and there is an urgent need to understand how HF care has been reorganized in countries with different infection levels, vaccination rates and healthcare services. The OPTIMIZE Heart Failure Care program has a global network of investigators in 42 countries, with first-hand experience of the impact of the pandemic on HF management in different care settings. The national coordinators were surveyed to assess: 1) the challenges of the COVID-19 pandemic for continuity of HF care, from both a hospital and patient perspective; 2) the organizational changes enacted to ensure continued HF care; and 3) lessons learned for the future of HF care. Contributions were obtained from 37 national coordinators in 29 countries. We summarize their input, highlighting the issues raised and using the example of three very different settings (Italy, Brazil, and Taiwan) to illustrate the similarities and differences across the OPTIMIZE program.
| S-EPMC9217066 | biostudies-literature
Project description:AimsThe coronavirus disease-2019 (COVID-19) pandemic has changed the landscape of medical care delivery worldwide. We aimed to assess the influence of COVID-19 pandemic on hospital admissions and in-hospital mortality rate in patients with acute heart failure (AHF) in a retrospective, multicentre study.Methods and resultsFrom 1 January 2019 to 31 December 2020, a total of 101 433 patients were hospitalized in 24 Cardiology Departments in Poland. The number of patients admitted due to AHF decreased by 23.4% from 9853 in 2019 to 7546 in 2020 (P < 0.001). We noted a significant reduction of self-referrals in the times of COVID-19 pandemic accounting 27.8% (P < 0.001), with increased number of AHF patients brought by an ambulance by 15.9% (P < 0.001). The length of hospital stay was overall similar (7.7 ± 2.8 vs. 8.2 ± 3.7 days; P = not significant). The in-hospital all-cause mortality in AHF patients was 444 (5.2%) in 2019 vs. 406 (6.5%) in 2020 (P < 0.001). A total number of AHF patients with concomitant COVID-19 was 239 (3.2% of AHF patients hospitalized in 2020). The rate of in-hospital deaths in AHF patients with COVID-19 was extremely high accounting 31.4%, reaching up to 44.1% in the peak of the pandemic in November 2020.ConclusionsOur study indicates that the COVID-19 pandemic led to (i) reduced hospital admissions for AHF; (ii) decreased number of self-referred AHF patients and increased number of AHF patients brought by an ambulance; and (iii) increased in-hospital mortality for AHF with very high mortality rate for concomitant AHF and COVID-19.
| S-EPMC8652676 | biostudies-literature