Awareness and Knowledge of Pneumococcal Vaccination in Cardiology Outpatient Clinics and the Impact of Physicians' Recommendations on Vaccination Rates.

AIM: We aimed to evaluate the awareness of pneumococcal vaccination (PCV13, PPSV23) in general cardiology outpatient clinics and impact of physicians' recommendations on vaccination rates. METHODS: This was a multicenter, observational, prospective cohort study. Patients over the age of 18 from 40 hospitals in different regions of Turkey who applied to the cardiology outpatient clinic between September 2022 and August 2021 participated. The vaccination rates were calculated within three months of follow-up from the admitting of the patient to cardiology clinics. RESULTS: The 403 (18.2%) patients with previous pneumococcal vaccination were excluded from the study. The mean age of study population (n = 1808) was 61.9 ± 12.1 years and 55.4% were male. The 58.7% had coronary artery disease, hypertension (74.1%) was the most common risk factor, and 32.7% of the patients had never been vaccinated although they had information about vaccination before. The main differences between vaccinated and unvaccinated patients were related to education level and ejection fraction. The physicians' recommendations were positively correlated with vaccination intention and behavior in our participants. Multivariate logistic regression analysis showed a significant correlation between vaccination and female sex [OR = 1.55 (95% CI = 1.25-1.92), p < 0.001], higher education level [OR = 1.49 (95% CI = 1.15-1.92), p = 0.002] patients' knowledge [OR = 1.93 (95% CI = 1.56-2.40), p < 0.001], and their physician's recommendation [OR = 5.12 (95% CI = 1.92-13.68), p = 0.001]. CONCLUSION: To increase adult immunization rates, especially among those with or at risk of cardiovascular disease (CVD), it is essential to understand each of these factors. Even if during COVID-19 pandemic, there is an increased awareness about vaccination, the vaccine acceptance level is not enough, still. Further studies and interventions are needed to improve public vaccination rates.

Plasminogen activator inhibitor-1 levels as an indicator of severity and mortality for COVID-19

OBJECTIVE Coronavirus disease-19 (COVID-19) is a multisystemic disease that can cause severe illness and mortality by exacerbating symptoms such as thrombosis, fibrinolysis, and inflammation. Plasminogen activator inhibitor-1 (PAI-1) plays an important role in regulating fibrinolysis and may cause thrombotic events to develop. The goal of this study is to examine the relationship between PAI-1 levels and disease severity and mortality in relation to COVID-19. METHODS A total of 71 hospitalized patients were diagnosed with COVID-19 using real time-polymerase chain reaction tests. Each patient underwent chest computerized tomography (CT). Data from an additional 20 volunteers without COVID-19 were included in this single-center study. Each patient's PAI-1 data were collected at admission, and the CT severity score (CT-SS) was then calculated for each patient. RESULTS The patients were categorized into the control group (n=20), the survivor group (n=47), and the non-survivor group (n=24). In the non-survivor group, the mean age was 75.3±13.8, which is higher than in the survivor group (61.7±16.9) and in the control group (59.5±11.2), (p=0.001). When the PAI-1 levels were compared between each group, the non-survivor group showed the highest levels, followed by the survivor group and then the control group (p<0.001). Logistic regression analysis revealed that age, PAI-1, and disease severity independently predicted COVID-19 mortality rates. In this study, it was observed that PAI-1 levels with >10.2 ng/mL had 83% sensitivity and an 83% specificity rate when used to predict mortality after COVID-19. Then, patients were divided into severe (n=33) and non-severe (n=38) groups according to disease severity levels. The PAI-1 levels found were higher in the severe group (p<0.001) than in the non-severe group. In the regression analysis that followed, high sensitive troponin I and PAI-1 were found to indicate disease severity levels. The CT-SS was estimated as significantly higher in the non-survivor group compared to the survivor group (p<0.001). When comparing CT-SS between the severe group and the non-severe group, this was significantly higher in the severe group (p<0.001). In addition, a strong statistically significant positive correlation was found between CT-SS and PAI-1 levels (r: 0.838, p<0.001). CONCLUSION Anticipating poor clinical outcomes in relation to COVID-19 is crucial. This study showed that PAI-1 levels could independently predict disease severity and mortality rates for patients with COVID-19.

Evaluation of COVID-19 Patients According to the Survival Time.

BACKGROUND: Coronavirus disease 2019 (COVID-19) was first detected as a form of atypical pneumonia. COVID-19 is a highly contagious virus, and some patients may experience acute respiratory distress syndrome (ARDS) and acute respiratory failure leading to death. We aim to evaluate the clinical, imaging, and laboratory parameters according to survival time to predict mortality in fatal COVID-19 patients. METHODS: Fatal 350 and survived 150 COVID-19 patients were included in the study. Fatal patients were divided into three groups according to the median value of the survival days. Demographic characteristics and in-hospital complications were obtained from medical databases. RESULTS: Of the non-survived patients, 30% (104) died within three days, 32% (110) died within 4-10 days, and 39% (136) died within over ten days. Pneumonia on computational tomography (CT), symptom duration before hospital admission (SDBHA), intensive care unit (ICU), hypertension (HT), C-reactive protein (CRP), D-dimer, multi-organ dysfunction syndrome (MODS), cardiac and acute kidney injury, left ventricular ejection fraction (LVEF), right ventricular fractional area change (RV-FAC), and Tocilizumab/Steroid therapy were independent predictors of mortality within three days compared to between 4-10 days and over ten days mortality.  A combined diagnosis model was evaluated for the age, CT score, SDBHA, hs-TnI, and D-dimer. The combined model had a higher area under the ROC curve (0.913). CONCLUSION: This study showed that age, pneumonia on CT, SDBHA, ICU, HT, CRP, d-dimer, cardiac injury, MODS, acute kidney injury, LVEF, and RV-FAC were independently associated with short-term mortality in non-surviving COVID-19 patients in the Turkish population. Moreover, Tocilizumab/Steroid therapy was a protective and independent predictor of mortality within three days.

Coronary microvascular dysfunction is common in patients hospitalized with COVID-19 infection.

BACKGROUND AND AIMS: Microvascular disease is considered as one of the main drivers of morbidity and mortality in severe COVID-19, and microvascular dysfunction has been demonstrated in the subcutaneous and sublingual tissues in COVID-19 patients. The presence of coronary microvascular dysfunction (CMD) has also been hypothesized, but direct evidence demonstrating CMD in COVID-19 patients is missing. In the present study, we aimed to investigate CMD in patients hospitalized with COVID-19, and to understand whether there is a relationship between biomarkers of myocardial injury, myocardial strain and inflammation and CMD. METHODS: 39 patients that were hospitalized with COVID-19 and 40 control subjects were included to the present study. Biomarkers for myocardial injury, myocardial strain, inflammation, and fibrin turnover were obtained at admission. A comprehensive echocardiographic examination, including measurement of coronary flow velocity reserve (CFVR), was done after the patient was stabilized. RESULTS: Patients with COVID-19 infection had a significantly lower hyperemic coronary flow velocity, resulting in a significantly lower CFVR (2.0 ± 0.3 vs. 2.4 ± 0.5, p < .001). Patients with severe COVID-19 had a lower CFVR compared to those with moderate COVID-19 (1.8 ± 0.2 vs. 2.2 ± 0.2, p < .001) driven by a trend toward higher basal flow velocity. CFVR correlated with troponin (p = .003, r: -.470), B-type natriuretic peptide (p < .001, r: -.580), C-reactive protein (p < .001, r: -.369), interleukin-6 (p < .001, r: -.597), and d-dimer (p < .001, r: -.561), with the three latter biomarkers having the highest areas-under-curve for predicting CMD. CONCLUSIONS: Coronary microvascular dysfunction is common in patients with COVID-19 and is related to the severity of the infection. CMD may also explain the "cryptic" myocardial injury seen in patients with severe COVID-19 infection.

Clinical features and major bleeding predictors for 161 fatal cases of COVID-19: A retrospective observational study.

The aim of this study was to investigate the patient characteristics and laboratory parameters for COVID-19 non-survivors as well as to find risk factors for major bleeding complications. For this retrospective study, the data of patients who died with COVID-19 in our intensive care unit were collected in the period of March 20 - April 30, 2020. D-dimer, platelet count, C-reactive protein (CRP), troponin, and international normalized ratio (INR) levels were recorded on the 1st, 5th, and 10th days of hospitalization in order to investigate the possible correlation of laboratory parameter changes with in-hospital events. A total of 161 non-survivors patients with COVID-19 were included in the study.  The median age was 69.8±10.9 years, and 95 (59%) of the population were male. Lung-related complications were the most common in-hospital complications. Patients with COVID-19 had in-hospital complications such as major bleeding (39%), hemoptysis (14%), disseminated intravascular coagulation (13%), liver failure (21%), ARDS (85%), acute kidney injury (40%), and myocardial injury (70%). A multiple logistics regression analysis determined that age, hypertension, diabetes mellitus, use of acetylsalicylic acid (ASA) or low molecular weight heparin (LMWH), hemoglobin, D-dimer, INR, and acute kidney injury were independent predictors of major bleeding. Our results showed that a high proportion of COVID-19 non-survivors suffered from major bleeding complications.

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.

Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study.

BACKGROUND: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including C-reactive protein/albumin ratio (CAR), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in patients with severe COVID-19. METHODS: This single-center, retrospective study included a total of 223 patients diagnosed with severe COVID-19. Primary outcome measure was mortality during hospitalization. Multivariate logistic regression analyses were performed to identify independent predictors associated with mortality in patients with severe COVID-19. Receiver operating characteristic (ROC) curve was used to determine cut-offs, and area under the curve (AUC) values were used to demonstrate discriminative ability of biomarkers. RESULTS: Compared to survivors of severe COVID-19, non-survivors had higher CAR, NLR, and PLR, and lower LMR and lower PNI (P < .05 for all). The optimal CAR, PNI, NLR, PLR, and LMR cut-off values for detecting prognosis were 3.4, 40.2, 6. 27, 312, and 1.54 respectively. The AUC values of CAR, PNI, NLR, PLR, and LMR for predicting hospital mortality in patients with severe COVID-19 were 0.81, 0.91, 0.85, 0.63, and 0.65, respectively. In ROC analysis, comparative discriminative ability of CAR, PNI, and NLR for hospital mortality were superior to PLR and LMR. Multivariate analysis revealed that CAR (⩾0.34, P = .004), NLR (⩾6.27, P = .012), and PNI (⩽40.2, P = .009) were independent predictors associated with mortality in severe COVID-19 patients. CONCLUSIONS: The CAR, PNI, and NLR are independent predictors of mortality in hospitalized severe COVID-19 patients and are more closely associated with prognosis than PLR or LMR.

Evaluation of Modified ATRIA Risk Score in Predicting Mortality in Hospitalized Patients With COVID-19.

BACKGROUND: As the Modified Anticoagulation and Risk Factors in Atrial Fibrillation Risk Score (M-ATRIA-RS) encompasses prognostic risk factors of novel coronavirus-2019 (COVID-19), it may be used to predict in-hospital mortality. We aimed to investigate whether M-ATRIA-RS was an independent predictor of mortality in patients hospitalized for COVID-19 and compare its discrimination capability with CHADS, CHA2DS2-VASc, and modified CHA2DS2-VASc (mCHA2DS2-VASc)-RS. METHODS: A total of 1,001 patients were retrospectively analyzed and classified into three groups based on M-ATRIA-RS, designed by changing sex criteria of ATRIA-RS from female to male: Group 1 for points 0-1 (n = 448), Group 2 for points 2-4 (n = 268), and Group 3 for points ≥5 (n = 285). Clinical outcomes were defined as in-hospital mortality, need for high-flow oxygen and/or intubation, and admission to intensive care unit. RESULTS: As the M-ATRIA-RS increased, adverse clinical outcomes significantly increased (Group 1, 6.5%; Group 2, 15.3%; Group 3, 34.4%; p <0.001 mortality for in-hospital). Multivariate logistic regression analysis showed that M-ATRIA-RS, malignancy, troponin increase, and lactate dehydrogenase were independent predictors of in-hospital mortality (p<0.001, per scale possibility rate for ATRIA-RS 1.2). In receiver operating characteristic (ROC) analysis, the discriminative ability of M-ATRIA-RS was superior to mCHA2DS2-VASc-RS and ATRIA-RS, but similar to that Charlson Comorbidity Index (CCI) score (AUCM-ATRIAvs AUCATRIA Z-test=3.14 p = 0.002, AUCM-ATRIAvs. AUCmCHA2DS2-VASc Z-test=2.14, p = 0.03; AUCM-ATRIAvs. AUCCCI Z-test=1.46 p = 0.14). CONCLUSIONS: M-ATRIA-RS is useful to predict in-hospital mortality among patients hospitalized with COVID-19. In addition, it is superior to the mCHA2DS2-VASc-RS in predicting mortality in patients with COVID-19 and is more easily calculable than the CCI score.

Prognostic value of right ventricular strain pattern on ECG in COVID-19 patients.

OBJECTIVE: COVID-19 spread worldwide, causing severe morbidity and mortality and this process still continues. The aim of this study to investigate the prognostic value of right ventricular (RV) strain in patients with COVID-19. METHODS: Consecutive adult patients admitted to the emergency room for COVID-19 between 1 and 30 April were included in this study. ECG was performed on hospital admission and was evaluated as blind. RV strain was defined as in the presence of one or more of the following ECG findings: complete or incomplete right ventricular branch block (RBBB), negative T wave in V1-V4 and presence of S1Q3T3. The main outcome measure was death during hospitalization. The relationship of variables to the main outcome was evaluated by multivariable Cox regression analysis. RESULTS: A total of 324 patients with COVID-19 were included in the study; majority of patients were male (187, 58%) and mean age was 64.2 ± 14.1. Ninety-five patients (29%) had right ventricular strain according to ECG and 66 patients (20%) had died. After a multivariable survival analysis, presence of RV strain on ECG (OR: 4.385, 95%CI: 2.226-8.638, p < 0.001), high-sensitivity troponin I (hs-TnI), d-dimer and age were independent predictors of mortality. CONCLUSION: Presence of right ventricular strain pattern on ECG is associated with in hospital mortality in patients with COVID-19.

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.

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.