Comparison of thromboembolic risk scores for evaluating in-hospital events of COVID-19 patients.

Aim: To compare the effectiveness of thromboembolic risk scores in determining in-hospital events of COVID-19 patients. Methods: This retrospective study included a total of 410 consecutive COVID-19 patients. Scores including CHA2DS2-VASc-HS (congestive heart failure, hypertension, age, diabetes mellitus, stroke/transient ischemic attack, vascular disease, sex, hyperlipidemia, smoking); modified R2CHA2DS2-VASc (CHA2DS2-VASc plus renal function), m-ATRIA (modified Anticoagulation and Risk Factors in Atrial Fibrillation score), ATRIA-HSV (ATRIA plus hyperlipidemia, smoking and vascular disease) and modified ATRIA-HSV were calculated. Participants were divided by in-hospital mortality status into two groups: alive and deceased. Results: Ninety-two (22.4%) patients died. Patients in the deceased group were older, predominantly male and had comorbid conditions. CHA2DS2-VASc-HS (adjusted odds ratio [aOR]: 1.31; p = 0.011), m-R2CHA2DS2-VASc (aOR: 1.33; p = 0.007), m-ATRIA (aOR: 1.18; p = 0.026), ATRIA-HSV (aOR: 1.18; p = 0.013) and m-ATRIA-HSV (aOR: 1.24; p = 0.001) scores were all associated with in-hospital mortality. m-R2CHA2DS2-VASc and modified ATRIA-HSV had the best discriminatory performance. Conclusion: We showed that m-R2CHA2DS2-VASc and m-ATRIA-HSV scores were better than the rest in predicting mortality among COVID-19 patients.

COVID-19 continues to be a pandemic that threatens human health all over the world. The main aim of our study was to examine the relationship between risk scores routinely used to determine the probability of clot formation in various cardiovascular diseases and in-hospital deaths of COVID-19 patients. The study comprised 410 adult patients hospitalized with a confirmed diagnosis of COVID-19. The clinical and laboratory data were obtained from the hospital registry system. All risk scores in the study were significantly greater in people who died from COVID-19 than in those who survived. Moreover, scoring systems that include kidney function outperformed the rest in determining in-hospital death. As a result, we discovered that specific risk scores used to indicate a person's likelihood of developing clot formation at a routine cardiology clinic are connected to in-hospital deaths among hospitalized COVID-19 patients.

HATCH Score for Predicting Mortality in COVID-19 Patients

Background: We aimed to evaluate the relationship between HATCH score [hypertension, age >75 yr, previous transient ischemic attack (TIA) or stroke (doubled), chronic obstructive pulmonary disease, heart failure (doubled)] and in-hospital mortality in COVID-19 patients. Methods: Overall, 572 COVID-19 patients hospitalized between Mar 15 and Apr 15, 2020, were included in this multicenter retrospective study, in Turkey. The HATCH score of each patient was calculated. Mortality results were followed for 50 days. The patients were divided into 2 groups developing mortality (n=267) and non-mortality (n=305). Clinical outcomes were defined as in-hospital mortality improvement status. Results: HATCH scores in non-survivors of COVID-19 were significantly higher than in survivors (P<0.001). In logistic regression analysis, HATCH score (OR: 1.253, 95% CI: 1.003–1.565;P=0.047), platelet count (OR: 0.995, 95% CI: 0.993–0.998;P<0.001), C-reactive protein level (OR: 1.010, 95% CI: 1.007–1.013, P<0.001) and estimated glomerular filtration ratio (eGFR) level (OR: 0.963, 95% CI: 0.953–0.973;P<0.001) were independent predictors of in-hospital mortality in COVID-19 patients. Conclusion: The HATCH score is useful in predicting in-hospital mortality in patients hospitalized with COVID-19.

Prognostic significance of temporal changes of lipid profile in COVID-19 patients.

BACKGROUND: COVID-19 is a multisystemic disease that affects many organs and has metabolic effects. AIMS: This study aims to investigate the effect of the temporal changes of lipid levels on the prognosis during the course of the disease. STUDY DESIGN: Retrospective cross-sectional study. METHODS: For this single-center study, data of patients who were treated for COVID-19 were collected. Fasting lipid parameters including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels were collected within 24 h of hospitalization. For investigation of temoral changes in lipid parameters, the results of the same parameters in the one-year period before COVID-19 were collected from medical records. A total number of 324 eligible COVID-19 patients were included in this study. The association of changes of lipid parameters with COVID-19 symptom severity and in-hospital mortality were investigated. RESULTS: The mean age of the severe group (n = 139) was 65.4 ± 15.5 years, and 60% were male. TC, LDL-C and HDL-C levels were significantly lower compared to pre-COVID measurements in the study population. Multiple linear regression analysis determined age, acute kidney injury, hs-Troponin, D-dimer, temporal changes in TC, and TG levels were determined as independent predictors for the development of COVID-19 mortality. CONCLUSION: Our findings showed that temporal changes in lipid parameters before and after COVID-19 may be associated with mortality and in-hospital adverse outcomes.

Elevated D-dimer levels on admission are associated with severity and increased risk of mortality in COVID-19: A systematic review and meta-analysis.

BACKGROUND: In this systematic review and meta-analysis, we aimed to investigate the correlation of D-dimer levels measured on admission with disease severity and the risk of death in patients with coronavirus disease 2019 (COVID-19) pneumonia. MATERIALS AND METHODS: We performed a comprehensive literature search from several databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in abstracting data and assessing validity. Quality assessment was performed using the Newcastle-Ottawa quality assessment scale (NOS). D-dimer levels were pooled and compared between severe/non-severe and surviving/non-surviving patient groups. Weighted mean difference (WMD), risk ratios (RRs) and 95% confidence intervals (CIs) were analyzed. RESULTS: Thirty-nine studies reported on D-dimer levels in 5750 non-severe and 2063 severe patients and 16 studies reported on D-dimer levels in 2783 surviving and 697 non-surviving cases. D-dimer levels were significantly higher in patients with severe clinical status (WMD: 0.45 mg/L, 95% CI: 0.34-0.56; p < 0.0001). Non-surviving patients had significantly higher D-dimer levels compared to surviving patients (WMD: 5.32 mg/L, 95% CI: 3.90-6.73; p < 0.0001). D-dimer levels above the upper limit of normal (ULN) was associated with higher risk of severity (RR: 1.58, 95% CI: 1.25-2.00; p < 0.0001) and mortality (RR: 1.82, 95% CI: 1.40-2.37; p < 0.0001). CONCLUSION: Increased levels of D-dimer levels measured on admission are significantly correlated with the severity of COVID-19 pneumonia and may predict mortality in hospitalized patients.

The effect of the severity COVID-19 infection on electrocardiography.

OBJECTIVE: Acute myocardial damage is detected in a significant portion of patients with coronavirus 2019 disease (COVID-19) infection, with a reported prevalence of 7-28%. The aim of this study was to investigate the relationship between electrocardiographic findings and the indicators of the severity of COVID-19 detected on electrocardiography (ECG). METHODS: A total of 219 patients that were hospitalized due to COVID-19 between April 15 and May 5, 2020 were enrolled in this study. Patients were divided into two groups according to the severity of COVID-19 infection: severe (n = 95) and non-severe (n = 124). ECG findings at the time of admission were recorded for each patient. Clinical characteristics and laboratory findings were retrieved from electronic medical records. RESULTS: Mean age was 65.2 ± 13.8 years in the severe group and was 57.9 ± 16.0 years in the non-severe group. ST depression (28% vs. 14%), T-wave inversion (29% vs. 16%), ST-T changes (36% vs. 21%), and the presence of fragmented QRS (fQRS) (17% vs. 7%) were more frequent in the severe group compared to the non-severe group. Multivariate analysis revealed that hypertension (odds ratio [OR]: 2.42, 95% confidence interval [CI]:1.03-5.67; p = 0.041), the severity of COVID-19 infection (OR: 1.87, 95% CI: 1.09-2.65; p = 0.026), presence of cardiac injury (OR: 3.32, 95% CI: 1.45-7.60; p = 0.004), and d-dimer (OR: 3.60, 95% CI: 1.29-10.06; p = 0.014) were independent predictors of ST-T changes on ECG. CONCLUSION: ST depression, T-wave inversion, ST-T changes, and the presence of fQRS on admission ECG are closely associated with the severity of COVID-19 infection.

The Neutrophil to Lymphocyte Ratio and In-Hospital All-Cause Mortality in Patients with COVID-19

Objective: In December 2019, pneumonia associated with severe acute respiratory syndrome coronavirus 2 emerged in China, and has been spread worldwide eventuating the coronavirus disease 2019 (COVID-19) pandemic. As of June 27, 2020, 195,883 people have been diagnosed with COVID-19 in Turkey, among them 5082 are dead. Moreover, 9,999,606 people were infected worldwide. The neutrophil-to-lymphocyte ratio (NLR) has been reported as an inflammatory biomarker. This study aimed to evaluate the relationship between NLR on admission and in-hospital all-cause mortality in adult patients with COVID-19. Methods: This retrospective cohort study included a total of 455 COVID-19 patients from Turkey. The diagnosis of COVID-19 was made according to the World Health Organization's interim guidance and confirmed by RNA detection of SARS-CoV-2. The NLR was calculated for each patient. Results: The NLR on admission was found to be significantly higher in nonsurvivor COVID-19 patients than survivors (12.3 [0.8-137.3] vs. 3.2 [0.6-79.0], p<0.001). Forward stepwise logistic regression analysis was carried out to determine the independent predictors of in-hospital all-cause mortality of patients with COVID-19. The analysis demonstrated that age [odds ratio (OR)=1.203, 95% confidence interval (CI): 1.027-1.408, p=0.022], NLR (OR=1.261, 95% CI: 1.054-1.509, p=0.011), lactate dehydrogenase level (OR=1.013, 95% CI: 1.004-1.022, p=0.005), glomerular filtration rate (OR=0.920, 95% CI: 0.853-0.992, p=0.030), alanine transaminase level (OR=1.107, 95% CI: 1.011-1.212, p=0.028), and aspartate transaminase level on admission (OR=0.939, 95% CI: 0.8880.993, p=0.027) were independent predictors of in-hospital all-cause mortality of patients with COVID-19. In the receiver operating characteristic curve analysis, the sensitivity and specificity of the NLR for predicting in-hospital all-cause mortality were found to be 92% and 53%, respectively, at the cut-off value of 3. Conclusion: The NLR on admission predicts in-hospital all-cause mortality of patients with COVID-19.

The CHA2DS2-VASc score and in-hospital mortality in patients with COVID-19: A multicenter retrospective cohort study.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is an infectious disease that was first reported in December 2019 in Wuhan, China, and has since spread rapidly around the world, resulting in the ongoing COVID-19 pandemic. The CHA2DS2-VASc score is a well-validated risk stratification tool for predicting stroke in atrial fibrillation (AFib), as well as morbidity and mortality in several entities. The aim of this study was to evaluate the relationship between the CHA2DS2-VASc score and in-hospital mortality in patients with COVID-19, regardless of AFib. METHODS: This multicenter, retrospective study included a total of 349 patients with COVID-19 who were hospitalized between March 15 and April 15, 2020. The CHA2DS2-VASc score of each patient was calculated. Mortality outcomes were followed up until April 25, 2020. RESULTS: The CHA2DS2-VASc score was significantly higher in non-survivor COVID-19 patients than in survivor COVID-19 patients (p<0.001). Forward stepwise logistic regression analysis demonstrated that a CHA2DS2-VASc score of ≥3 (odds ratio [OR]: 12.613, 95% confidence interval [CI]: 3.092-51.451; p<0.001), and the leukocyte count (OR: 1.327, 95% CI: 1.145-1.538; p<0.001), C-reactive protein level (OR: 1.010, 95% CI: 1.002-1.018; p=0.012), and ferritin level (OR: 1.005, 95% CI: 1.003-1.007; p<0.001) on admission were independent predictors of in-hospital mortality of COVID-19 patients. CONCLUSION: The CHA2DS2-VASc score predicted in-hospital mortality in patients with COVID-19, regardless of AFib.

Echocardiographic features of patients with COVID-19 infection: a cross-sectional study.

COVID-19 patients with cardiac involvement have a high mortality rate. The aim of this study was to investigate the echocardiographic features in COVID-19 patients between severe and non-severe groups. For this single-center study, data from patients who were treated for COVID-19 between March 25, 2020 and April 15, 2020 were collected. Two-dimensional echocardiography (2DE) images were obtained for all patients. Patients were divided into two groups based on the severity of their COVID-19 infections. 2DE parameters indicating right ventricular (RV) and left ventricular (LV) functions were compared between the two groups. A total of 90 patients hospitalized for COVID-19 were included in this study. The mean age of the severe group (n = 44) was 63.3 ± 15.7 years, and 54% were male. The mean age of non-severe group (n = 46) was 49.7 ± 21.4 years, and 47% were male. In the severe group, RV and LV diameters were larger (RV, 36.6 ± 5.9 mm vs. 33.1 ± 4.8 mm, p = 0.003; LV 47.3 ± 5.8 mm vs. 44.9 ± 3.8 mm, p = 0.023), the LE ejection fraction (LVEF) and the RV fractional area change (RV-FAC) were lower (LVEF, 54.0 ± 9.8% vs. 61.9 ± 4.8%, p < 0.001; RV-FAC, 41.4 ± 4.1% vs. 45.5 ± 4.5%, p < 0.001), and pericardial effusions were more frequent (23% vs. 0%) compared to patients in the non-severe group. A multiple linear regression analysis determined that LVEF, right atrial diameter, high-sensitivity troponin I, d-dimer, and systolic pulmonary artery pressure, were independent predictors of RV dilatation. The results demonstrate that both right and left ventricular functions decreased due to COVID-19 infection in the severe group. 2DE is a valuable bedside tool and may yield valuable information about the clinical status of patients and their prognoses.

Prognostic significance of cardiac injury in COVID-19 patients with and without coronary artery disease.

OBJECTIVE: COVID-19 is a disease with high mortality, and risk factors for worse clinical outcome have not been well-defined yet. The aim of this study is to delineate the prognostic importance of presence of concomitant cardiac injury on admission in patients with COVID-19. METHODS: For this multi-center retrospective study, data of consecutive patients who were treated for COVID-19 between 20 March and 20 April 2020 were collected. Clinical characteristics, laboratory findings and outcomes data were obtained from electronic medical records. In-hospital clinical outcome was compared between patients with and without cardiac injury. RESULTS: A total of 607 hospitalized patients with COVID-19 were included in the study; the median age was 62.5 ± 14.3 years, and 334 (55%) were male. Cardiac injury was detected in 150 (24.7%) of patients included in the study. Mortality rate was higher in patients with cardiac injury (42% vs. 8%; P < 0.01). The frequency of patients who required ICU (72% vs. 19%), who developed acute kidney injury (14% vs. 1%) and acute respiratory distress syndrome (71%vs. 18%) were also higher in patients with cardiac injury. In multivariate analysis, age, coronary artery disease (CAD), elevated CRP levels, and presence of cardiac injury [odds ratio (OR) 10.58, 95% confidence interval (CI) 2.42-46.27; P < 0.001) were found to be independent predictors of mortality. In subgroup analysis, including patients free of history of CAD, presence of cardiac injury on admission also predicted mortality (OR 2.52, 95% CI 1.17-5.45; P = 0.018). CONCLUSION: Cardiac injury on admission is associated with worse clinical outcome and higher mortality risk in COVID-19 patients including patients free of previous CAD diagnosis.