In-hospital Mortality In COVID-19 Patients Research Articles

External validation of two clinical prediction models for mortality in COVID-19 patients (4C and NEWS2), in three centers in Medellín, Colombia: Assessing the impact of vaccination over time

ObjectivesExternal validation of the 4C and NEWS2 scores for the prediction of in-hospital mortality in COVID-19 patients, and evaluation of its operational performance in two time periods: before and after the start of the vaccination program in Colombia. MethodsRetrospective cohort in three high complexity hospitals in the city of Medellín, Colombia, between June 2020 and April 2022. ResultsThe areas under the ROC curve (AUC) for the 4C mortality risk score and the NEWS2 were 0.75 (95% CI 0.73–0.78) and 0.68 (95% CI 0.66–0.71), respectively. For the 4C score, the AUC for the first and second periods was 0.77 (95% CI 0.74–0.80) and 0.75 (95% CI 0.71–0.78); whilst for the NEWS2 score, it was 0.68 (95% CI 0.65–0.71) and 0.69 (95% CI 0.64–0.73). The calibration for both scores was adequate, albeit with reduced performance during the second period. ConclusionsThe 4C mortality risk score proved to be the more adequate predictor of in-hospital mortality in COVID-19 patients in this Latin American population. The operational performance during both time periods remained similar, which shows its utility notwithstanding major changes, including vaccination, as the pandemic evolved.

AB2CO risk score for in-hospital mortality of COVID-19 patients admitted to intensive care units

PurposeTo develop a mortality risk score for COVID-19 patients admitted to intensive care units (ICU), and to compare it with other existing scores. Materials and methodsThis retrospective observational study included consecutive adult patients with laboratory-confirmed COVID-19 admitted to ICUs of 18 hospitals from nine Brazilian cities, from September 2021 to July 2022. Potential predictors were selected based on the literature review. Generalized Additive Models were used to examine outcomes and predictors. LASSO regression was used to derive the mortality score. ResultsFrom 558 patients, median age was 69 years (IQR 58–78), 56.3 % were men, 19.7 % required mechanical ventilation (MV), and 44.8 % died. The final model comprised six variables: age, pO2/FiO2, respiratory function (respiratory rate or if in MV), chronic obstructive pulmonary disease, and obesity. The AB2CO had an AUROC of 0.781 (95 % CI 0.744 to 0.819), good overall performance (Brier score = 0.191) and an excellent calibration (slope = 1.063, intercept = 0.015, p-value = 0.834). The model was compared with other scores and displayed better discrimination ability than the majority of them. ConclusionsThe AB2CO score is a fast and easy tool to be used upon ICU admission.

The Association between Coagulation Parameters, C-Reactive Protein, D-Dimer and In-Hospital Mortality of Covid-19 Patients with Suspected Pulmonary Embolism

The Association between Coagulation Parameters, C-Reactive Protein, D-Dimer and In-Hospital Mortality of Covid-19 Patients with Suspected Pulmonary Embolism

Association Between Head Computed Tomography Findings and In-Hospital Mortality in COVID-19 Patients.

The present study investigated the association between head computed tomography (CT) findings and mortality in patients with COVID-19. Specifically, we focused on low-density lesions identified on head CT screenings. We performed a single-center, retrospective cohort study based on data obtained from the medical charts of inpatients admitted to the Tokyo Metropolitan Hiroo Hospital between January 1 and December 31, 2021. We focused on the basal ganglia--a representative anatomical region for assessing routine head CT in patients with COVID-19. Patients were divided into two groups based on the presence or absence of low-density lesions in the basal ganglia. The primary outcome was all-cause in-hospital mortality, and the secondary outcome was the length of hospital stay. We performed multivariable regression analyses for outcomes to adjust for patients' background and disease severity. During the study period, 1,906 COVID-19 patients were admitted to our facility. Among them, 1,203 patients underwent head CT evaluations and were included in this study. The median age was 56 years (interquartile range: 43-76 years) and 725 patients (60.3%) were male. A total of 235 (19.5%) patients required oxygen therapy on admission and 1,051 (87.4%) patients had pneumonia. Crude in-hospital mortality was 6.1% and the median length of hospital stay was 10 days (interquartile range: 8-14 days). The multivariate regression analyses showed that low-density lesions in the basal ganglia were significantly associated with increased in-hospital mortality and prolonged hospital stay. The presence of ischemic changes in the basal ganglia denoted by low-density findings may be a promising prognostic factor in patients with COVID-19.

Thrombocytopenia Secondary to COVID-19: Outcomes Analysis in Terms of Thrombotic Microangiopathy, Acute Kidney Injury, and Mortality.

Background: COVID-19 usually complicates respiratory failure; microvascular, macrovascular, and renal complications are common. Both micro and macrovascular complications are associated with multi-organ dysfunction and in-hospital mortality. Thrombotic microangiopathy (TMA) causes microvascular thromboses associated with organ failure, including acute kidney injury (AKI). Materials and Methods: This Retrospective Cohort study included 100 COVID-19 patients with thrombocytopenia, followed up in a university hospital's intensive care unit (ICU). The primary endpoints were in-hospital mortality or discharge from the hospital and assessing the occurrence of TMA and AKI during the hospitalization. The effect of thrombotic microangiopathy and acute kidney injury on mortality was investigated using logistic regression models in Stata software version 12.1. Results: The TMA and AKI were associated with in-hospital mortality in COVID-19 patients presenting with thrombocytopenia in multivariate regression analysis, adjusted for other variables. The effect of AKI on mortality was obtained (adjusted OR 4.09, 95% CI: 1.33-12.53, p = 0.01). Moreover, the odds of mortality due to TMA were ten-fold higher in the patients who had TMA than those who did not (adjusted OR 10.26, 95% CI: 1.26-83.76, p = 0.03). Conclusion: We outlined TMA in COVID-19 patients, which could be responsible for kidney injury and mortality in critically COVID-19 patients.

Association of New-Onset Atrial Fibrillation With All-Cause Mortality in COVID-19 Patients.

Background The COVID-19 pandemic has brought about unprecedented global health challenges, with its impact extending beyond respiratory manifestations to encompass cardiovascular complications, including arrhythmias. Dysrhythmias in COVID-19 are multifactorial, ranging from direct myocardial insult due to the cytokine storm to metabolic derangements. Objective In this study, we aim to examine the incidence of new-onset atrial fibrillation and to study its association with all-cause mortality of COVID-19. Methods A cross-sectional study was conducted at Cabell Huntington Hospital, West Virginia, utilizing electronic medical records of COVID-19 patients from 2020 to 2021. Inclusion criteria comprised patients aged >18 years with COVID-19 diagnosis and cardiac arrhythmias during hospitalization. Logistic regression analysis was employed to examine the relationship between demographic and clinical variables and in-hospital mortality. Results Of the 264 eligible patients, those aged >66 years had lower odds of in-hospital mortality (p < 0.001), while gender, ejection fraction, and diabetes mellitus did not significantly predict mortality. Atrial fibrillation (p = 0.011) and heart failure (p = 0.030) were associated with increased odds of mortality, while hypertension showed no significant predictive power (p = 0.791). Conclusion This study highlights the significance of atrial fibrillation and heart failure as predictors of in-hospital mortality in COVID-19 patients. Our findings underscore the importance of recognizing and managing arrhythmias in COVID-19 and call for further research on the mechanisms and long-term effects of these cardiac complications in the context of the pandemic. These insights can guide clinical practice and interventions to optimize patient outcomes.

Azvudine reduces the in-hospital mortality of COVID-19 patients: A retrospective cohort study

Azvudine reduces the in-hospital mortality of COVID-19 patients: A retrospective cohort study

Sex differences in ischemic stroke during COVID-19 first outbreak in northern Italy

IntroductionCOVID-19 pandemic had a great impact on outcome in SARS-CoV-2 positive patients with ischemic stroke during the first wave in Italy. Few data are available on outcome stratified by sex. MethodsThe Italian Society of Hospital Neuroscience conducted a multi-center, retrospective, observational study on neurological complications in COVID-19 patients with ischemic stroke. All the patients admitted from March 1st to April 30th, 2020 in 20 Neurology Units in Northern Italy were recruited. Demographical and clinical features, treatment and outcome data were compared focusing on sex differences. Results812 patients with ischemic stroke were enrolled, of whom 129 with COVID-19; males were 53.8%. In-hospital mortality in COVID-19 patients was 35.3% in males and 27.9% in females while 8.5% in male and 5.8% in female patients without COVID-19. SARS-CoV-2 positive patients had a higher frequency of stroke of undetermined etiology, than negative ones (32.8% vs 22.5%; p = 0.02), especially in females compared to males (36.1% vs 27.9%), albeit without statistical significance. Male patients with SARS-CoV-2 were more likely to require cPAP (30.9% vs 14.8%; p = 0.03), endotracheal tube (14.9% vs 3.3%; p = 0.02) and reperfusion strategies (29.4% vs 11.5%; p = 0.01) than females, as well as to have a higher CRP and D-dimer. These elements together with older age, a total anterior circulation stroke and lymphopenia were predictors of a worse outcome. DiscussionOur study detected some differences due to sex in ischemic stroke with and without COVID-19, supporting the possibility to perform sex analyses for SARS-CoV-2 positive patients for a better clinical management.

AF and in-hospital mortality in COVID-19 patients

There are conflicting data on whether new-onset atrial fibrillation (AF) is independently associated with poor outcomes in COVID-19 patients. This study represents the largest dataset curated by manual chart review comparing clinical outcomes between patients with sinus rhythm, pre-existing AF, and new-onset AF. The primary aim of this study was to assess patient outcomes in COVID-19 patients with sinus rhythm, pre-existing AF, and new-onset AF. The secondary aim was to evaluate predictors of new-onset AF in patients with COVID-19 infection. This was a single-center retrospective study of patients with a confirmed diagnosis of COVID-19 admitted between March and September 2020. Patient demographic data, medical history, and clinical outcome data were manually collected. Adjusted comparisons were performed following propensity score matching between those with pre-existing or new-onset AF and those without AF. The study population comprised of 1241 patients. A total of 94 (7.6%) patients had pre-existing AF and 42 (3.4%) patients developed new-onset AF. New-onset AF was associated with increased in-hospital mortality before (odds ratio [OR] 3.58, 95% confidence interval [CI] 1.78-7.06, P < .005) and after (OR 2.80, 95% CI 1.01-7.77, P < .005) propensity score matching compared with the no-AF group. However, pre-existing AF was not independently associated with in-hospital mortality compared with patients with no AF (postmatching OR: 1.13, 95% CI 0.57-2.21, P = .732). New-onset AF, but not pre-existing AF, was independently associated with elevated mortality in patients hospitalised with COVID-19. This observation highlights the need for careful monitoring of COVID-19 patients with new-onset AF. Further research is needed to explain the mechanistic relationship between new-onset AF and clinical outcomes in COVID-19 patients.

Temporal validation of the MMCD score to predict kidney replacement therapy and in-hospital mortality in COVID-19 patients

BackgroundAcute kidney injury has been described as a common complication in patients hospitalized with COVID-19, which may lead to the need for kidney replacement therapy (KRT) in its most severe forms. Our group developed and validated the MMCD score in Brazilian COVID-19 patients to predict KRT, which showed excellent performance using data from 2020. This study aimed to validate the MMCD score in a large cohort of patients hospitalized with COVID-19 in a different pandemic phase and assess its performance to predict in-hospital mortality.MethodsThis study is part of the “Brazilian COVID-19 Registry”, a retrospective observational cohort of consecutive patients hospitalized for laboratory-confirmed COVID-19 in 25 Brazilian hospitals between March 2021 and August 2022. The primary outcome was KRT during hospitalization and the secondary was in-hospital mortality. We also searched literature for other prediction models for KRT, to assess the results in our database. Performance was assessed using area under the receiving operator characteristic curve (AUROC) and the Brier score.ResultsA total of 9422 patients were included, 53.8% were men, with a median age of 59 (IQR 48–70) years old. The incidence of KRT was 8.8% and in-hospital mortality was 18.1%. The MMCD score had excellent discrimination and overall performance to predict KRT (AUROC: 0.916 [95% CI 0.909–0.924]; Brier score = 0.057). Despite the excellent discrimination and overall performance (AUROC: 0.922 [95% CI 0.914–0.929]; Brier score = 0.100), the calibration was not satisfactory concerning in-hospital mortality. A random forest model was applied in the database, with inferior performance to predict KRT requirement (AUROC: 0.71 [95% CI 0.69–0.73]).ConclusionThe MMCD score is not appropriate for in-hospital mortality but demonstrates an excellent predictive ability to predict KRT in COVID-19 patients. The instrument is low cost, objective, fast and accurate, and can contribute to supporting clinical decisions in the efficient allocation of assistance resources in patients with COVID-19.

Correlation between Chest Computed Tomography Score and Laboratory Biomarkers in the Risk Stratification of COVID-19 Patients Admitted to the Emergency Department.

It has been reported that mid-regional proadrenomedullin (MR-proADM) could be considered a useful tool to stratify the mortality risk in COVID-19 patients upon admission to the emergency department (ED). During the COVID-19 outbreak, computed tomography (CT) scans were widely used for their excellent sensitivity in diagnosing pneumonia associated with SARS-CoV-2 infection. However, the possible role of CT score in the risk stratification of COVID-19 patients upon admission to the ED is still unclear. The main objective of this study was to assess if the association of the CT findings alone or together with MR-proADM results could ameliorate the prediction of in-hospital mortality of COVID-19 patients at the triage. Moreover, the hypothesis that CT score and MR-proADM levels together could play a key role in predicting the correct clinical setting for these patients was also evaluated. Epidemiological, demographic, clinical, laboratory, and outcome data were assessed and analyzed from 265 consecutive patients admitted to the triage of the ED with a SARS-CoV-2 infection. The accuracy results by AUROC analysis and statistical analysis demonstrated that CT score is particularly effective, when utilized together with the MR-proADM level, in the risk stratification of COVID-19 patients admitted to the ED, thus helping the decision-making process of emergency physicians and optimizing the hospital resources.

High Prevalence of Diabetes Among Hospitalized COVID-19 Minority Patients: Data from a Single Tertiary Hospital.

Type 2 diabetes mellitus (DM) is a common comorbidity in the minority population and is associated with poor outcomes in COVID-19 patients. We hypothesized that COVID-19 patients with pre-existing diabetes mellitus are prone to fatal outcomes compared to non-diabetic patients. We aimed to illustrate the characteristics and outcomes and identify the risk factors for in-hospital mortality of COVID-19 patients with DM. In this single-center retrospective study, electronic medical records of hospitalized patients with confirmed COVID-19 diagnosis at Howard University Hospital (HUH) from March 2020 to Dec 2021 were analyzed. Clinical, demographic, and serological information, as well as outcomes, were recorded and analyzed. Among 463 COVID-19 patients, 66.3% (n = 307) were African Americans (AA) and 35.9% (n = 166) had diabetes, with a mean age of 64years. The majority of the diabetic patients were AA (n = 123, 74.1%) and had a higher mortality rate (n = 26, 74.3%) compared to others. Length of stay in the hospital is significantly more for the diabetic than for the non-diabetic patients (11.3 vs. 8.3days, p = 0.03). A higher proportion of ICU admission (32.3% vs. 17.9%, p = < 0.001), intubation (17% vs. 11.7%, p = 0.04), and increased mortality (21.1% vs. 12.2%, p = 0.01) were identified in COVID-19 patients with DM than in those with no DM. Among DM patients, non-survivors were older (69.9 vs. 62.9years). DM patients were more likely to have underlying hypertension (72.3% vs. 43.3%, p = < 0.001), obesity (44.8% vs. 32.1%, p = 0.007), chronic kidney disease (23.6 vs. 11.8%, p = 0.001), and cardiovascular disease (29.5% vs. 14.3%, p = 0.001) than the non-DM patients. HbA1C above 9%, indicating poorly controlled hyperglycemia, was associated with poor outcome among the DM subjects. AST (23.5% vs. 31.3%) and creatinine (61.4% vs. 37.9%) were significantly more elevated in DM COVID-19 patients (all p-values < 0.05). The levels of serum troponin (42.5% vs. 30.9%, p = 0.03), interleukin-6 (67.2 vs. 50%, p = 0.04), ferritin (65.6% vs. 44.6%, p = 0.03), procalcitonin (58.1% vs. 46.1, p = 0.03), and D-dimers (92.8% vs. 86.5%, p = 0.04) were significantly higher in DM patients as compared to those in non-DM COVID-19 patients, indicating more susceptibility of diabetic COVID-19 patients to coagulation dysfunction and inflammatory storm. The prevalence of DM is high among hospitalized COVID-19 patients in our cohort. While DM patients have a higher mortality rate and ICU admission than non-DM patients, other factors such as underlying comorbidities, old age, elevated creatinine, AST, serum inflammatory markers, and D-dimer are more significant predictors of fatal outcomes. DM patients had higher metabolic derangements, hypercoagulability, and severe inflammatory response. No significant difference of outcome was noted between DM patients of different races in our cohort. In the diabetic group, it appears that race may not significantly contribute to the observed mortality disparity. This could be attributed to the significant influence of diabetes, which acts as a major effector, potentially overshadowing the significance of race in this context.

Bacterial co-infection raises in-hospital mortality of COVID-19 patients: a retrospective study.

We aim to explore whether the bacterial co-infection with COVID-19 will raise the in-hospital mortality. COVID-19 patients' information were collected for analysis in our retrospective study. Neutrophil count and procalcitonin (PCT) were used to estimate whether there was a suspected bacterial co-infection. The main baselines between the suspected bacterial infection (SBI) and no evidence of bacterial infection (NBI) groups were no significant differences. In SBI group, patients required more therapies than NBI group. There was significantly higher in-hospital mortality (26% vs.9%, P < 0.001) between SBI and NBI groups in overall population. And in each subgroup based on pneumonia inflammation index (PII), it also showed higher in-hospital mortality of COVID-19 patients with bacterial co-infection. With logistic regression models, it showed that bacterial co-infection was associated with significantly higher in-hospital mortality in overall population (OR 1.694, 95% CI 1.179-2.434, p = 0.004) and mild subgroup (OR 2.374, 95% CI 1.249-4.514, p = 0.008). The rate of bacterial co-infection in overall population was 51%. At the same time, it showed a significantly higher rate of bacterial co-infection in critical subgroup than severe subgroup (63% vs. 49%, p = 0.003), and than that in moderate subgroup (63% vs. 48%, p = 0.002) based on clinical classification. It showed a significantly higher rates of bacterial co-infection in severe subgroup than moderate subgroup (66% vs. 49%, p = 0.001) based on PII. The result showed that the risk factor associated with significantly higher in-hospital mortality was PII (OR 1.018, 95%CI 1.012 to 1.024, P < 0.001) with logistic regression models. Bacterial co-infection estimated by Neutrophil count and procalcitonin significantly raises in-hospital mortality of COVID-19 patients in overall population in our study. Its impact is more significant in mild and moderate PII subgroups. PII based on CT imaging combined with neutrophil count and PCT is beneficial for accurate differentiation of bacterial co-infection of COVID-19.

Delirium and IL-6 added to clinical scores improves their performance: a prospective analysis of CALL, PREDI-CO, MRS score applied to a population of patients admitted to internal medicine ward

This study aimed to evaluate the effectiveness of various scoring systems in predicting in-hospital mortality for COVID-19 patients admitted to the internal medicine ward. We conducted a prospective collection of clinical data from patients admitted to the Internal Medicine Unit at Santa Maria Nuova Hospital in Florence, Italy, with confirmed pneumonia caused by SARS-CoV-2. We calculated three scoring systems: the CALL score, the PREDI-CO score, and the COVID-19 in-hospital Mortality Risk Score (COVID-19 MRS). The primary endpoint was in-hospital mortality. : A total of 681 patients were enrolled in the study, with a mean age of 68.8 ± 16.1 years, and 54.8% of them were male. Non-survivors had significantly higher scores in all prognostic systems compared to survivors (MRS: 13 [12- 15] vs. 10 [8-12]; CALL: 12 [10-12] vs. 9 [7-11]; PREDI-CO: 4 [3-6] vs. 2 [1-4]; all p<0.001). The receiver operating characteristic (ROC) analysis yielded the following area under the curve (AUC) values: MRS 0.85, CALL 0.78, PREDI-CO 0.77. The addition of Delirium and IL6 to the scoring systems improved their discriminative ability, resulting in AUC values of 0.92 for MRS, 0.87 for CALL, and 0.84 for PREDI-CO. The mortality rate increased significantly across increasing quartiles (p<0.001). In conclusion the COVID-19 in-hospital Mortality Risk Score (MRS) demonstrated reasonable prognostic stratification for patients admitted to the internal medicine ward with SARS-CoV-2-induced pneumonia. The inclusion of Delirium and IL6 as additional prognostic indicators in the scoring systems enhanced their predictive performance, specifically in determining in-hospital mortality among COVID-19 patients.

Is Mean Platelet Volume a Useful Predictor of Hospital Mortality in Covid-19 Patients?

Background: Elevated Mean Platelet Volume (MPV) can indicate the activation of platelets and the coagulation cascade, which has been suggested as a predictor of mortality in some diseases. The aim of this study was to investigate the role of MPV in predicting hospital mortality in patients with Covid-19.&#x0D; Methods: This was a cross-sectional single-center retrospective study. The data of all patients with a PCR-confirmed diagnosis of Covid-19 hospitalized within a 3-month period were analyzed. The patients’ files were reviewed, and the data were recorded into a checklist, including demographic characteristics, underlying diseases, and laboratory test results. Hospital mortality was designated as the main outcome of the study.&#x0D; Results: A total of 201 Covid-19 patients, confirmed by PCR, were included in this study. In-hospital mortality was observed in 28 patients (13.9%). The results of univariate regression analysis revealed that the triage level, history of chronic pulmonary disease, age, oxygen saturation, lymphocyte count, BUN, Cr, and CRP were significantly related to in-hospital mortality. However, MPV showed no significant relationship with in-hospital mortality.&#x0D; Conclusion: Low triage level, advanced age and hypoxia predicted a higher risk of in-hospital mortality in Covid-19 patients. The role of MPV as a predictor of patient outcome in Covid-19 remains inconclusive, necessitating further studies with larger sample sizes.

Atrial fibrillation and in-hospital mortality in Covid-19 patients

Abstract Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Wellcome/EPSRC Centre for Medical Engineering Background Although primarily considered a respiratory virus, cardiovascular manifestations have been reported in patients with Covid-19 infection. Atrial fibrillation has been observed as the most common arrhythmia with the prevalence rate reportedly as high as 16.5%(1). Purpose The aim of the study was to establish the incidence of atrial fibrillation in patients hospitalised with Covid-19 and evaluate the relationship between patient characteristics and disease severity with new-onset atrial fibrillation in patients with Covid-19. Methods A single centre, retrospective study of 1241 patients with a confirmed PCR diagnosis of Covid-19 admitted during the 1st wave of the pandemic (1st March to 31st September 2020). Patient demographic data, medical history and clinical outcome data were manually collected. Results The study population comprised of 1241 patients hospitalised with Covid-19. Of these, 94 (7.6%) patients were known to have pre-existing atrial fibrillation. In an unadjusted analysis, in-hospital mortality was twice as likely in patients with pre-existing atrial fibrillation compared to patients with no history of atrial fibrillation (odds ratio (OR): 2.18; 95% CI 1.29-3.59, p=0.002). However, after multi-variable matching for age, sex and CHA2DS2VASc score there was no significant difference between groups (OR: 1.13, 95% CI 0.57-2.21, p=0.732). During their admission, 42 (3.4%) patients developed new-onset atrial fibrillation. New-onset atrial fibrillation was associated with an increased risk of mechanical­­­ ventilation (OR: 4.59, 95% CI 2.34-9.06, p&amp;lt;0.005), intensive care admission (OR: 7.19, 95% CI 3.52-15.61, p&amp;lt;0.005) and in-hospital mortality (OR: 3.58; 95% CI 1.78-7.06, p&amp;lt;0.005). Statistical significance remained after matched analysis (mechanical ventilation OR: 14.00, 95% CI 1.84-106.5, p=0.01; intensive care admission OR: 18, 95% CI 2.40-134.83, p&amp;lt;0.005, in-hospital mortality OR: 2.80, 95% CI 1.01-7.77, p=0.048). New-onset atrial fibrillation was associated with older age (p&amp;lt;0.005), higher CHA2DS2VASc score (p&amp;lt;0.005), elevated white cell count (p=0.046), neutrophil count (p=0.010), C-reactive protein ( p&amp;lt;0.005), ferritin (p=0.020), lower albumin (p&amp;lt;0.005) and eGFR (p=0.013) at the time of hospital admission. No association was found with gender (p=0.683) or race (p=0.080). Conclusion New-onset atrial fibrillation during admission with Covid-19 is associated with both co-morbidity status and markers of disease severity at the time of hospital admission. New-onset atrial fibrillation is associated with elevated in-hospital mortality compared with patients with either pre-existing or no history of atrial fibrillation.

Estimated plasma volume status is an independent predictor for in-hospital mortality in COVID-19 patients with hypoxemic respiratory failure and heart failure

Abstract Funding Acknowledgements Type of funding sources: None. Background Heart failure and hypoxemic respiratory failure were the leading causes for hospital admission and death in COVID-19 patients. Frequently, it is challenging to assess the plasma volume status in limited resource settings especially in times of COVID-19 pandemics. Thus, a practical and simple evaluation of congestion status is of importance to guide early management and risk stratification. Estimated plasma volume status (ePVS) has been associated with mortality in heart failure population. However, no study investigated the association between ePVS and prognosis in COVID-19 patients with hypoxemic respiratory failure and heart failure. Purpose To study the association between ePVS and in-hospital mortality in COVID-19 patients with hypoxemic respiratory failure and heart failure. We hypothesized that higher ePVS level which reflected a congested status could worsen the prognosis in severe COVID-19 patients with hypoxemic respiratory failure and heart failure. Methods We included severe COVID-19 subjects with hypoxemic respiratory failure and heart failure using our institution COVID-19 registry. Sample size was calculated using comparing two means hypothesis testing accordingly. The calculation of ePVS was performed using simple Duarte Formula; (100-hematocrit)/hemoglobin, which were taken at the time of admission. A logistic regression model was used to demonstrate the association between ePVS levels and in-hospital mortality. ROC curve analysis was used to assess the discrimination of ePVS for predicting in-hospital mortality. Results We enrolled 53 eligible subjects with an average age of 61 ± 10.3 years old with predominant male (69.8%). Thirty five patients died in hospital with the prevalence of in-hospital mortality was 66%. The ROC curve indicated that ePVS has acceptable discrimination for predicting in-hospital mortality. The AUC value was found to be 0.665 and ePVS value cut off was 4.5 ml/g with sensitivity of 77.8% and specificity of 65.7%. In the unadjusted model, high-level of ePVS (&amp;gt; 4.5 ml/g) was associated with higher OR (6.7; 95% CI 1.8–24.9; P 0.003) compared with low-level of ePVS (≤ 4.5 ml/g).After adjusted the vital signs data, laboratory and echocardiogram data, and treatment, high-level of ePVS was independently associated with increased OR of in-hospital mortality, 21.6 (95% CI 2.6–177.9; P &amp;lt; 0.004). Conclusions This study demonstrated that high ePVS level, calculated with a simple Duarte Formula, was associated with higher in-hospital mortality in COVID-19 patients with hypoxemic respiratory failure and heart failure. Thus, this finding could help physicians for a better risk stratification in managing COVID-19 patients in limited resource settings or in early phase of hospitalization.

Evaluation of Inflammation-Based Prognostic Risk Scores in Predicting in-Hospital Mortality Risk in COVID-19 Patients: A Cross-Sectional Retrospective Study.

Systemic inflammatory parameters are predictors of poor prognosis in COVID-19 patients. This study evaluated whether the prognostic nutritional index, which was also related to nutrition risk and other inflammation-based prognostic scores, was predictive of in-hospital mortality in COVID-19 patients. This was a retrospective cross-sectional single-center study. Based on the exclusion criteria, 151 patients over 18 years old diagnosed with COVID-19 and hospitalized in the intensive care unit between March 2020 and December 2020 were eligible for this study. Multivariable logistic regression analysis was performed to evaluate the predictive value of the Glasgow Prognostic Score (GPS), Prognostic Index (PI), Prognostic Nutritional Index (PNI), and Systemic Inflammatory Index (SII). In the univariate analyses, age, diabetes mellitus (DM), chronic kidney disease, acute kidney injury, hypothyroidism, hospitalization stay, lactate dehydrogenase (LDH), aspartate aminotransferase (AST), D-dimer, ferritin, C-reactive protein (CRP), albumin, hemoglobin level, platelet count, urea, creatinine level, PNI, GPS were significantly associated with mortality. However, in the multivariable logistic regression analysis of the inflammation-based prognostic scores, only PNI was statistically significant in predicting in-hospital mortality (OR=0.83; [95% CI=0.71-0.97]; p =0.019). PNI is a more useful and powerful tool among these inflammation-based prognostic risk scores in predicting in-hospital mortality in COVID-19 patients.

The Value of Cardiac Biomarkers in Predicting in-Hospital Death in COVID-19 Patients

Given the strong evidence of direct invasion of coronavirus to myocardial tissue, as well as increasing the patient's susceptibility to inflammatory and thrombotic phenomena, it has been hypothesized that elevated levels of cardiac enzymes can predict disease severity and its poor prognosis. We aimed to determine the value of cardiac prognostic biomarkers along with other laboratory parameters in predicting in-hospital mortality of COVID-19 patients. This prospective study was performed on 30 consecutive patients with the definitive diagnosis of severe COVID-19. On admission, along with recording demographic characteristics, intravenous blood samples were extracted from the patients after at least 8 hours of fasting to evaluate other laboratory parameters. Comparing laboratory parameters across the survived and non-survived groups showed significantly higher mean CK-MB level in non-survived group than alive group (70.90±29.79 versus 43.56±22.02, P=0.020). Also, positive troponin I was reported in 38.1% of non-survived group, while in none of the patients in survived group (P=0.031). Using the logistic regression model, raised CK-MB could effectively predict in-hospital death among COVID-19 patients (OR=1.047, P=0.043). Area under the ROC curve analysis showed high value of raised CK-MB for predicting in-hospital death among COVID-19 patients. Raised CK-MB level on admission can predict in-hospital death in patients with severe COVID-19.

Evaluation of the effect of bun/albumin ratio on in-hospital mortality in hypertensive COVID-19 patients.

The impact of COVID-19 infection still continues all over the world and is an important cause of mortality. The mortality rate due to infection varies between 1-5%. The mortality rate is higher in those with cardiovascular risk factors, especially in cases with hypertension. Some studies have shown that blood urea nitrogen (BUN) and albumin levels are associated with worse prognosis in patients with COVID-19. In our study, we aimed to investigate whether the BUN/albumin (BAR) ratio has an effect on in-hospital mortality in hypertensive COVID-19 patients. A total of 800 hypertensive COVID-19 patients, (618 of whom were alive and 182 died) were included in our study. Patients with a history of heart failure, malignancy, acute coronary syndrome, and myocarditis were excluded. The median age of the study population was 69 (60-77 IQR) years, and 305 (38%) of these patients were men. There was no statistically significant difference between the patients who died during follow-up and cases that remained alive in terms of comorbidities except chronic obstructive pulmonary disease (COPD) which was significantly lower in surviving group (p=0.014). Multivariable logistic regression analysis revealed that age [OR: 1.04, CI (1.01-1.06); p=0.002], male gender [OR: 1.85, CI (1.13-3.02); p=0.010], lymphocyte count [OR: 0.63, CI (0.40-0.98); p=0.038], SaO2 [OR: 0.82, CI (0.79-0.85); p<0.001] and BAR level [OR: 1.09, CI (1.04-1.16); p=0.001] were independent predictors of in-hospital mortality. ROC analysis yielded that BAR is a better predictor of in-hospital mortality compared to albumin and BUN alone. BUN, albumin, and BAR levels were found to be reliable predictors of in-hospital mortality in COVID-19 patients, and BAR was also found to be a more reliable predictor than BUN and albumin levels. Hypertension is one of the major risk factors for morbidity and mortality in COVID-19 and, BAR presents additional prognostic data in hypertensive COVID-19 patients that may direct physicians for treatment intensification.