In-hospital Mortality In Coronavirus Disease 2019 Patients Research Articles

Impact of Diabetes Mellitus On In-Hospital Mortality of COVID-19 Patients in Japan Since COVID-19 Became a Common Infectious Disease.

The number of severe cases of coronavirus disease 2019 (COVID-19) has been decreasing since the emergence of the Omicron variant at the end of 2021. COVID-19 has become a common infectious disease in Japan and was downgraded to a category five infectious disease on May 8, 2023. This study aimed to compare the impact of diabetes mellitus on in-hospital mortality in COVID-19 patients since COVID-19 became a common infectious disease. We conducted a retrospective observational study using data from an advanced critical care center in Osaka, Japan. The study included 1,381 patients of COVID-19 admitted to the center between March 1, 2020, and May 7, 2023, before COVID-19 became a category five infectious disease in Japan. Individuals younger than 18 years and pregnant women were excluded. We divided the patients into two groups: pre- and post-Omicron epidemic groups. The primary endpoint of the study was the in-hospital mortality, and the prognostic impact of diabetes mellitus was compared between the groups. The Kaplan-Meier curve showed a significantly lower rate of in-hospital mortality in the post-Omicron epidemic group than in the pre-Omicron epidemic group. The hazard ratio (HR) was 1.83 (95% CI, 1.36-2.50; p < 0.0001). Patients with diabetes mellitus had higher in-hospital mortality in both the pre- and post-Omicron epidemic groups; their HRs were 1.39 (95% CI, 1.21-1.59; p < 0.0001) and 1.45 (95% CI, 1.15-1.83; p = 0.0012), respectively. Diabetes mellitus had no significant interaction effect on the association between the post-Omicron epidemic and in-hospital mortality (p for interaction = 0.2154). Diabetes mellitus may continue contributing to COVID-19 in-hospital mortality in the future, as the Omicron sub-strain may still be prevalent.

Association Between Hemoglobin-Albumin-Lymphocyte-Platelet Index and Mortality in Hospitalized COVID-19 Omicron BA.2 Infected Patients.

The hemoglobin-albumin-lymphocyte-platelet (HALP) index is a novel biomarker reflecting systemic inflammation and nutritional status which are important for coronavirus disease 2019 (COVID-19) mortality. However, the association between HALP and mortality in patients with COVID-19 has yet to be investigated. A cohort of COVID-19 Omicron BA.2 infected patients admitted to the Shanghai Fourth People's Hospital, School of Medicine, Tongji University from April 12, 2022 to June 17, 2022 was retrospectively analyzed. Laboratory examinations on hospital admission, including hemoglobin, albumin, and lymphocyte and platelet, were collected. The association between baseline HALP and in-hospital poor overall survival (OS) was assessed using Kaplan-Meier curves, Cox regression models, interaction, and stratified analyses. A total of 2147 patients with COVID-19 Omicron BA.2 infection were included in the final analyses, and mortality in the hospital was 2.65%. Multivariate analysis indicated that low HALP index was independently associated with in-hospital mortality of COVID-19 patients [hazard ratio (HR) = 2.08; 95% confidence interval (CI) = 1.17-3.73]. Subgroup analysis demonstrated that low HALP index was an independent risk factor for in-hospital mortality in COVID-19 patients with age ≥70 (HR = 2.22, CI = 1.18-4.15) and severe cases (HR = 2.09, CI = 1.13-3.86). HALP index is independently related to in-hospital poor OS for COVID-19 Omicron BA.2 infected patients, especially for age ≥70 and severe cases. HALP index on hospital admission is a useful candidate biomarker for identifying high risk of mortality in COVID-19 Omicron BA.2 infected patients.

Difference in mortality risk predicted by leukocyte and lymphocyte levels in COVID-19 patients infected with the Wild-type, Delta, and Omicron strains.

This study aimed to investigate the changing trends, level differences, and prognostic performance of the leukocyte and lymphocyte levels of patients infected with the Wild strains, Delta strains and Omicron strains to provide a reference for prognostic assessment. In the current study, we conducted a retrospective cross-sectional study to evaluate the changing trends, level differences, and prognostic performance of leukocyte and lymphocyte of different strains at admission and discharge may already exist in patients with coronavirus disease-2019 (COVID-19) infected with the Wild type, Delta, and Omicron strains. A retrospective cross-sectional study was conducted. We recruited and screened the 243 cases infected with the Wild-type strains in Wuhan, the 629 cases infected with the Delta and 116 cases infected strains with the Omicron strains in Xi'an. The leukocyte and lymphocyte levels were compared the cohort of Wild-type infection with the cohort of Delta and the Omicron. The changes in the levels of leukocytes and lymphocytes exhibit a completely opposite trend in patients with COVID-19 infected with the different strains. The lymphocyte level at admission and discharge in patients with COVID-19 infected with Omicron strains (area under curve [AUC] receiver operating characteristic curve [ROC] 72.8-90.2%, 82.8-97.2%) presented better performance compared patients with COVID-19 infected with Wild type strains (AUC ROC 60.9-80.7%, 82.3-97.2%) and Delta strains (AUC ROC 56.1-84.7%, 40.3-93.3%). Kaplan-Meier curves showed that the leukocyte levels above newly established cutoff values and the lymphocyte levels below newly established cutoff values had a significantly higher risk of in-hospital mortality in COVID-19 patients with Wild-type and Omicron strains (P < .01). The levels of leukocyte and lymphocyte at admission and discharge in patients with COVID-19 infected with the Wild type, Delta, and Omicron strains may be differences among strains, which indicates different death risks. Our research may help clinicians identify patients with a poor prognosis for severe acute respiratory syndrome coronavirus 2 infection.

Analysis of altered level of blood-based biomarkers in prognosis of COVID-19 patients.

Immune and inflammatory responses developed by the patients with Coronavirus Disease 2019 (COVID-19) during rapid disease progression result in an altered level of biomarkers. Therefore, this study aimed to analyze levels of blood-based biomarkers that are significantly altered in patients with COVID-19. A cross-sectional study was conducted among COVID-19 diagnosed patients admitted to the tertiary care hospital. Several biomarkers-biochemical, hematological, inflammatory, cardiac, and coagulatory-were analyzed and subsequently tested for statistical significance at P<0.01 by using SPSS version 17.0. A total of 1,780 samples were analyzed from 1,232 COVID-19 patients (median age 45 years [IQR 33-57]; 788 [63.96%] male). The COVID-19 patients had significantly (99% Confidence Interval, P<0.01) elevated levels of glucose, urea, alanine transaminase (ALT), aspartate aminotransaminase (AST), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), white blood cell (WBC), C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), ferritin, D-Dimer, and creatinine phosphokinase-MB (CPK-MB) compared to the control group. However, the levels of total protein, albumin, and platelets were significantly (P<0.01) lowered in COVID-19 patients compared to the control group. The elevated levels of glucose, urea, WBC, CRP, D-Dimer, and LDH were significantly (P<0.01) associated with in-hospital mortality in COVID-19 patients. Assessing and monitoring the elevated levels of glucose, urea, ALT, AST, ALP, WBC, CRP, PCT, IL-6, ferritin, LDH, D-Dimer, and CPK-MB and the lowered levels of total protein, albumin, and platelet could provide a basis for evaluation of improved prognosis and effective treatment in patients with COVID-19.

Serum IL-23, IL-10, and TNF-α predict in-hospital mortality in COVID-19 patients.

The hyperinflammatory response, caused by severe acute respiratory syndrome-2 (SARS-CoV-2), is the most common cause of death in patients with coronavirus disease 2019 (COVID-19). The etiopathogenesis of this illness is not fully understood. Macrophages appear to play a key part in COVID-19's pathogenic effects. Therefore, this study aims to examine serum inflammatory cytokines associated with the activation state of macrophages in COVID-19 patients and attempt to find accurate predictive markers for disease severity and mortality risk in hospital. 180 patients with COVID-19 and 90 healthy controls (HCs) participated in this study. Patients were divided into three different subgroups, mild (n=81), severe (n=60), and critical groups (n=39). Serum samples were collected and IL (Interleukin)-10, IL-23, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), IL-17, monocyte chemoattractant protein-1 (MCP-1) and chemokine ligand 3 (CCL3) were determined by ELISA. In parallel, myeloperoxidase (MPO) and C-reactive protein (CRP) were measured using colorimetric and electrochemiluminescence methods, respectively. Data were collected, and their associations with disease progression and mortality were assessed using regression models and receiver operating characteristic (ROC) curves. Compared to HCs, a significant increase in IL-23, IL-10, TNF-α, IFN-γ and MCP-1, were observed in COVID-19 patients. Serum levels of IL-23, IL-10, and TNF-α were significantly higher in COVID-19 patients with critical cases compared to mild and severe cases, and correlated positively with CRP level. However, non-significant changes were found in serum MPO and CCL3 among the studied groups. Moreover, significant positive association has been observed among increased IL-10, IL-23 and TNF-α in serum of COVID-19 patients. Furthermore, a binary logistic regression model was applied to predict death's independent factors. Results showed that IL-10 alone or in combination with IL23 and TNF-α are strongly linked with non-survivors in COVID-19 patients. Finally, ROC curve results uncovered that IL-10, IL-23 and TNF-α were excellent predictors for prognosing COVID-19. The elevations of IL-10, IL-23, and TNF-α levels were seen in severe and critical cases of COVID-19 patients and their elevations were linked to the in-hospital mortality of the disease. A prediction model shows that the determination of these cytokines upon admission is important and should be done on COVID-19 patients as a way of evaluating the prognosis of the disease. COVID-19 Patients with high IL-10, IL-23, and TNF-α on admission are more likely to experience a severe form of the disease; therefore, those patients should be cautionary monitored and treated.

Evaluation of Early Warning Scores on In-Hospital Mortality in COVID-19 Patients: A Tertiary Hospital Study from Taiwan.

Coronavirus disease 2019 (COVID-19) remains a global pandemic. Early warning scores (EWS) are used to identify potential clinical deterioration, and this study evaluated the ability of the Rapid Emergency Medicine score (REMS), National Early Warning Score (NEWS), and Modified EWS (MEWS) to predict in-hospital mortality in COVID-19 patients. This study retrospectively analyzed data from COVID-19 patients who presented to the emergency department and were hospitalized between 1 May and 31 July 2021. The area under curve (AUC) was calculated to compare predictive performance of the three EWS. Data from 306 COVID-19 patients (61 ± 15 years, 53% male) were included for analysis. REMS had the highest AUC for in-hospital mortality (AUC: 0.773, 95% CI: 0.69-0.85), followed by NEWS (AUC: 0.730, 95% CI: 0.64-0.82) and MEWS (AUC: 0.695, 95% CI: 0.60-0.79). The optimal cut-off value for REMS was 6.5 (sensitivity: 71.4%; specificity: 76.3%), with positive and negative predictive values of 27.9% and 95.4%, respectively. Computing REMS for COVID-19 patients who present to the emergency department can help identify those at risk of in-hospital mortality and facilitate early intervention, which can lead to better patient outcomes.

Effectiveness and Safety of Lianhua Qingwen Capsules for COVID-19: A Propensity-Score Matched Cohort Study.

As a traditional Chinese medicine, Lianhua Qingwen capsules have been widely used to treat Coronavirus Disease 2019 (COVID-19). This study was aimed to demonstrate the association between treatment with Lianhua Qingwen capsules and the clinical outcomes of hospitalized patients with COVID-19. This retrospective study was conducted at four hospitals in Central China. Data of hospitalized COVID-19 patients were collected between December 19, 2019 and April 26, 2020. Based on whether Lianhua Qingwen capsules were used, patients were classified into Lianhua Qingwen and non-Lianhua Qingwen (control) groups. To control for confounding factors, we used conditional logistic regression in a propensity-score matched (PSM) cohort (1 : 1 balanced), as well as logistic regression without matching as sensitivity analysis. A total of 4918 patients were included, 2760 of whom received Lianhua Qingwen capsules and 2158 of whom did not. In the PSM model, after adjusting for confounders, the in-hospital mortality was similar between the Lianhua Qingwen group and the control group (6.8% vs. 3.3%, adjusted OR, 0.66 [95% CI, 0.38-1.15], p = 0.138). The negative conversion rate of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection was higher in the Lianhua Qingwen group (88.3% vs. 96.1%, adjusted OR, 4.02 [95% CI, 2.58-6.25], p < 0.001). The incidence of acute liver injury was comparable between the two groups (14.0% vs. 11.5%, adjusted OR: 0.85 [95% CI, 0.71-1.02], p = 0.083), and the incidence of acute kidney injury was lower in the Lianhua Qingwen group (5.3% vs. 3.0%, adjusted OR: 0.71 [95% CI, 0.50-1.00], p = 0.048). Treatment with Lianhua Qingwen capsules was not significantly associated with in-hospital mortality in COVID-19 patients. In the Lianhua Qingwen group, the negative conversion rate of SARS-CoV-2 infection was higher and the incidence of acute kidney injury was lower than in the control group.

Is Chronic Kidney Disease, a Predictor of In-Hospital Mortality in Coronavirus Disease 2019 (COVID-19) Patients?

Chronic kidney disease (CKD) is an important comorbidity in Coronavirus Disease 2019 (COVID-19) patients considering its high prevalence. We aimed to figure out the relationship between CKD and COVID-19 mortality in this study. In total, 116 CKD patients (estimated glomerular filtration rate [eGFR] lower than 60 mL/min/1.73 m2) and 147 control subjects confirmed with COVID-19 were studied. Data regarding demographics, sign and symptoms, laboratory findings, and chest computed tomography were collected. Association between CKD and in-hospital mortality were analyzed using logistic regression models adjusted for confounders. Mortality rate was significantly higher in CKD than non-CKD (30.17 vs 4.76, P < 0.001) COVID-19 patients. Multivariate logistic regression showed that CKD was significantly correlated with in-hospital mortality in the total sample (Odds ratio (OR) = 8.64, confidence interval (CI): 3.67-20.35) and gender subgroups (females: OR = 4.77, CI: 1.38-16.40, males: OR = 13.43, CI: 3.85-46.87) (P < 0.05) of COVID-19 patients in the crude model. Whereas, the correlation did not remain significant in the fully adjusted model in the total sample (OR = 1.70, CI: 0.35-8.19) and gender subgroups (females: OR = 1.07 CI: 0.06-19.82, males: OR = 0.87, CI: 0.07-10.33) (P > 0.05) of COVID-19 patients. This study suggested an independent association between CKD and in-hospital mortality in COVID-19 patients. Therefore, more intensive surveillance of COVID-19 patients with CKD is to be warranted.

Ambroxol for the treatment of COVID-19 among hospitalized patients: A multicenter retrospective cohort study.

Ambroxol is a commonly used mucolytic agent principally used to treat respiratory diseases, which may have a role as adjunctive therapy for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, but there is lack of evidence about its effectiveness on coronavirus disease-2019 (COVID-19) patients. To study the association between ambroxol use and clinical outcomes among hospitalized patients of COVID-19 infection. We conducted a multicenter retrospective cohort study involving 3,111 patients with confirmed SARS-CoV-2 infection from three hospitals in Wuhan from 19 December 2019 to 15 April 2020, and the primary outcome was in-hospital mortality. COVID-19 patients were classified into ambroxol and non-ambroxol groups based on the administration of ambroxol during hospitalization. Two analyses including propensity score matching (PSM) to obtain a 1:1 balanced cohort and logistic regression were used to control for confounding factors. The average age of 3,111 patients was 57.55 ± 14.93 years old, 127 of them died during hospitalization, and 924 of them used ambroxol. Treatment with ambroxol did not have a significant effect on in-hospital mortality of COVID-19 patients when compared with non-ambroxol in PSM model after adjusting for confounders (8.0% vs. 3.5%, adjusted OR, 1.03 [95% CI, 0.54–1.97], p = 0.936). Adverse events such as nausea/vomiting, headache, and rash were comparable between the two groups. Our results suggest that the use of ambroxol is not significantly associated with in-hospital mortality in COVID-19 patients, which provides evidence for evaluating the effects of ambroxol on COVID-19 patient outcomes and may be helpful for physicians considering medication alternatives for COVID-19 patients.

Coronavirus disease 2019 death prediction by electrocardiographic abnormalities and elevated D-dimer levels.

BackgroundElectrocardiography (ECG) plays a very important role in various cardiovascular diseases and elevated D-dimer in serum associated with thrombosis. In patients with coronavirus disease 2019 (COVID-19), immense pieces of evidence showed that ECG abnormalities or elevated D-dimer in serum occurred frequently. However, it remains unclear whether ECG abnormalities combined with elevated D-dimer could be a new risk predictor in patients with COVID-19.Methods and resultsThis retrospective cohort study enrolled 416 patients with COVID-19 at Wuhan Tongji Hospital from 1 February to 20 March 2020. ECG manifestations, D-dimer levels, and in-hospital deaths were recorded for all patients. Logistic regression analysis was performed to examine the association between ECG manifestations and in-hospital mortality in patients with elevated D-dimer levels. In patients hospitalized for COVID-19, ST-T abnormalities (34.3%) were the most frequent ECG manifestations, whereas sinus tachycardia (ST) (13.3%) and atrial arrhythmias with rapid rhythms (8.5%) were the two most common cardiac arrhythmias. Compared to severely ill patients with COVID-19, ST-T abnormalities, ST and atrial arrhythmias (p<0.001) with rapid rhythms, D-dimer levels, and in-hospital deaths were significantly more frequent in critically ill patients with COVID-19. Moreover, elevated D-dimer levels were observed in all the patients who died. In the subgroup of 303 patients with elevated serum D-dimer levels, the patient's age, the incidence of ST-T abnormalities, ST, atrial fibrillation (AF), and atrial premature beat were significantly higher than those in the non-elevated D-dimer subgroup. Multivariate logistic regression analysis further revealed that ST and AF were risk factors for in-hospital mortality in COVID-19 patients with elevated D-dimer levels.ConclusionsECG abnormalities and elevated D-dimer levels were associated with a higher risk of critical illness and death in patients hospitalized for COVID-19. ECG abnormalities, including ST and AF, combined with elevated D-dimer levels, can be used to predict death in COVID-19.

Does procalcitonin play a role as a predictor of in-hospital mortality among COVID-19 patients admitted to intensive care unit?

Introduction: Inflammatory response plays a key role in coronavirus disease 2019 (COVID-19) as it has been shown that the resulting cytokine storm increases its severity. Objectives: To investigate the role of procalcitonin (PCT) as a predictor of in-hospital mortality in patients with severe to critical COVID-19. Patients and Methods: In a retrospective cohort study, 150 patients with severe to critical COVID-19 consecutively admitted to the intensive care unit (ICU) were investigated. Patients’ demographics, clinical and laboratory findings, and PCT level were collected upon their admission to the hospital and from the disease outcome data. Results: Of the 150 patients who entered the study, 77 were discharged alive from the hospital. The mean age of the patients was 60.9 ±16.3 years and 51.3% of them were male. The mean PCT level was significantly higher in the deceased patients than in survivors (2.4 ± 3.4 versus 0.7±1.3, P&lt;0.005). The logistic regression analysis indicated that PCT, creatinine and urea levels were independently associated with in-hospital mortality. Conclusion: Serum PCT levels are associated with in-hospital mortality in COVID-19 patients admitted to ICU and could be used as a simple tool to predict adverse outcomes and expedite timely and appropriate interventions.

Renin-Angiotensin-System Inhibitors Are Associated With Lower In-hospital Mortality in COVID-19 Patients Aged 80 and Older.

BackgroundOlder adults are at higher risk of morbidity and mortality for coronavirus disease 2019 (COVID-19). Renin-angiotensin-system inhibitors (RASi) were found to have a neutral or protective effect against mortality in COVID-19 adult patients.AimsWe investigated whether this association was confirmed also in COVID-19 older patients.MethodsThis is a prospective observational study on 337 hospitalized older adults (aged 80 years and older). We classified the study population according to usage of RASi before and during hospitalization. A propensity score analysis was also performed to confirm the findings.ResultsThe mean age was 87.4 ± 6.1 years. Patients taking RASi at home were 147 (43.6%). During hospitalization, 38 patients (11.3% of the entire study population) discontinued RASi, while 57 patients (16.9% of the entire study population) started RASi. In-hospital mortality was 43.9%. Patients taking RASi during hospitalization (patients who maintained their home RASi therapy + patients who started RASi during hospitalization) had a significantly lower in-hospital mortality than untreated patients [HR 0.48 (95% CI: 0.34–0.67)], even after adjustment for required respiratory support, functional status, albumin, inflammation, and cardiac biomarkers. The analysis of the groups derived from the “propensity score matching” (58 patients in each group) confirmed these results [HR 0.46 (95% CI: 0.23–0.91)].DiscussionDespite the high risk of death in older COVID-19 patients, RASi therapy during hospitalization was associated with a clinically relevant lower in-hospital mortality, likely due to the benefit of RAS modulation on the cardiopulmonary system during the acute phase of the disease.ConclusionOur findings confirm the protective role of RASi even in COVID-19 patients aged 80 years and older.

Relationship Between Platelet Count and In-hospital Mortality in Adult Patients With COVID-19: A Retrospective Cohort Study.

BackgroundThe coronavirus disease 2019 (COVID-19) has become a global pandemic. Systemic inflammation in COVID-19 patients has been associated with poor clinical outcome. This study aims to determine the relationship between platelet count and in-hospital mortality.MethodsThe original data of this study were from article development and validation of a predictive model of in-hospital mortality in COVID-19 patients. In this secondary analysis, we adopted multi-variable logistic regression analyses and smooth curve fitting to assess the independent association between platelet count and in-hospital mortality. We further applied a two-piecewise linear regression model to examine the nonlinear association between platelet count and in-hospital mortality.ResultsOf the 2006 patients, the average age of the participants was 65.9 ± 16.5 years and 42.6% were women. We observed a U-shaped relationship between platelet count and in-hospital mortality. We found two different slopes, the correlations between platelet count and in-hospital mortality of COVID-19 patients were totally different below and above the inflection point which was around 370 × 109/L. On the left side of the inflection point, the OR was 0.996 (OR: 0.996, 95%CI: 0.994–0.998, p < 0.001). On the right side of the inflection point, the OR was 1.011 (OR: 1.011, 95%CI: 1.001–1.021, p = 0.029).ConclusionsA U-shaped association between platelet count and in-hospital mortality was found in the patients with COVID-19. The optimal of platelet count associated with the lowest risk of in-hospital mortality was around 370 × 109/L.

Blood Urea Nitrogen/Albumin Ratio and Mortality Risk in Patients with COVID-19

IntroductionWe researched blood urea nitrogen (BUN), albumin and their ratio (BAR), and compared them with C-reactive protein (CRP), D-dimer, and computed tomography severity scores (CT-SS), to predict in-hospital mortality.MethodsOne-hundred and thirty-one coronavirus disease-2019 (COVID-19) confirmed patients brought to the emergency department (ED) were dispensed to the survivor or non-survivor group, in light of in-hospital mortality. Information on age, gender, complaints, comorbidities, laboratory parameters, and outcome were gathered from the patient's record files.ResultsThe median BUN, mean total protein, mean albumin, median BAR, median creatinine, median CRP, and median D-dimer were recorded. CT-SS were utilized in categorizing the patient as mild, moderate, and severe. In-hospital mortality occurred in 42 (32.06%) patients (non-survivor group) and did not occur in 89 (67.94%) patients (survivor group). The median BUN (mg/dL) and BAR (mg/gm) values were significantly raised in the non-survivor group than in the survivor group [BUN: 23.48 (7.51–62.75) and 20.66 (4.07–74.67), respectively (p = 0.009); BAR: 8.33 mg/g (2.07–21.86) and 6.11 mg/g (1.26–23.33); (p = 0.0003)]. The mean albumin levels (gm/dL) in the non-survivor group were significantly lower than in the survivor group [2.96 ± 0.35 and 3.27 ± 0.35, respectively (p <0.0001)]. Albumin with an odd's ratio of 6.14 performed the best in predicting in-hospital mortality, followed by D-dimer (4.98). BAR and CRP had similar outcome of 3.75; BUN showed an OR of 3.13 at the selected cutoff value.ConclusionThe BUN, albumin, and BAR were found to be dependable predictors of in-hospital mortality in COVID-19 patients, with albumin (hypoalbuminemia) performing even better.How to cite this articleSingh S, Singh K. Blood Urea Nitrogen/Albumin Ratio and Mortality Risk in Patients with COVID-19. Indian J Crit Care Med 2022;26(5):626–631.

Multi-inflammatory Index as a Novel Mortality Predictor in Critically Ill COVID-19 Patients.

AimSystemic inflammation has a crucial role in the pathogenesis and mortality of Coronavirus disease 2019 (COVID-19). Multi-inflammatory index (MII) is a novel index related with systemic inflammation. In this study, we investigated the relationship between MII and in-hospital mortality in COVID-19 patients admitted to the intensive care unit (ICU).MethodsWe retrospectively analyzed the medical records of COVID-19 patients followed-up in the ICU of our institution between 01.04.2020 and 01.10.2021. Patients were classified into two groups according to mortality status as survivors and non-survivors. Various inflammatory parameters of the groups were compared and their efficacy in predicting mortality was investigated.ResultsOut of 348 study patients, 86 cases (24.7%) were in the survived group and 262 cases (75.3%) were in the dead group. The median age of the mortal group was significantly higher than that of the survived group (65.5 vs 76, P < .001). Multiple logistic regression analysis revealed that among all the included inflammatory parameters, MII showed the best efficacy for predicting mortality (OR: 0.999; 95% CI: 0.9991-0.9998; P = .003).ConclusionMII, a new combination of Neutrophil to lymphocyte ratio (NLR) and C-reactive protein (CRP), is a simple and practical biomarker that can help us in the prediction of mortality in COVID-19 patients followed-up in the ICU.

Association between hypertension and prognosis of patients with COVID-19: A systematic review and meta-analysis

ABSTRACT Background To investigate the association between hypertension and clinical outcomes, including in-hospital mortality, intensive care unit (ICU) admission, and invasive ventilation in patients with coronavirus disease 2019 (COVID-19) pneumonia. Methods We implemented a systematic search of PubMed for articles that assessed clinical outcomes of hypertensive patients infected with SARS-CoV-2. The primary outcomes evaluated included: in-hospital mortality, ICU admission, and the use of invasive ventilation. Results A total of 18 studies were included, involving 13,293 patients and covering from January 25, 2020, to April 20, 2020. The relationship between hypertension and prognosis in COVID-19 patients was evaluated. Results showed that hypertension was a risk factor for in-hospital mortality in COVID-19 patients (RR: 2.20, 95% CI, 1.83–2.65, P < .001). Moreover, patients with hypertension were more likely to be admitted to ICU (RR: 1.86, 95% CI, 1.13–3.07, P = .001) and to use invasive ventilation (RR: 2.99, 95% CI, 1.73–5.17, P < .001). Conclusions Among COVID-19 patients, those combined with hypertension had a significantly higher risk of in-hospital deaths, admission to ICU, and need for invasive ventilation.

Inflammasome-related Markers upon ICU Admission do not Correlate with Outcome in Critically Ill COVID-19 Patients.

The development of targeted biological therapies for coronavirus disease 2019 (COVID-19) requires reliable biomarkers that could help indicate how patients are responding. The hyperactivation of inflammasomes by the SARS-CoV2 virus is hypothesized to contribute to a more severe course of the COVID-19 disease. Therefore, we aimed to evaluate the prognostic value of several inflammasome-related cytokines and proteins upon admission to the intensive care unit (ICU). We performed a prospective cohort study. Plasma samples were obtained from 45 critically ill COVID-19 patients and 10 patients without any signs of infection (traumatic brain injury [TBI]) on admission to the ICU. Concentrations of IL-1a, IL-1β, IL-18, IL-1RA, galectin-1, apoptosis-associated speck-like proteins, LDH, ferritin, and gasdermin D were analyzed. A cell-free caspase-1 plasma assay was done by inhibitor-based immunoprecipitation followed by a Western Blot. Demographic and clinical characteristics were recorded. Inhospital mortality in COVID-19 patients was 62%. Galectin-1 was 1.8-fold lower in COVID-19 than in TBI patients (17101.84 pg/mL vs. 30764.20 pg/mL, P = 0.007), but other inflammasome-related biomarkers had similar concentrations. Patients with a Sequential Organ Failure Assessment (SOFA) score of > 9 on admission who were at high risk of death had significantly higher galectin-1 but lower IL-1RA in comparison with low-risk patients (25551.3 pg/mL vs. 16302.7 pg/mL, P = 0.014; 14.5 pg/mL vs. 39.4pg/mL, P = 0.04, respectively). Statistically significant correlations were observed between: IL-1a and platelets (r = -0.37), IL-1 β and platelets (r = -0.36), ferritin and INR (r = 0.39). Activated caspase-1 p35, whose presence was related to higher fibrinogen and lower D-dimers, was detected in 12 out of 22 COVID-19 patients and in none of the TBI patients. Moreover, densitometric analysis showed a significantly higher amount of p35 in patients with a SOFA score > 9. We found that the systemic markers of activation of inflammasomes in critically ill COVID-19 patients were not directly related to outcome. Therefore, potential interventions aimed at the inflammasome pathway in this group of patients may be of limited effectiveness and should be biomarker-guided.

Cardiovascular signatures of COVID-19 predict mortality and identify barrier stabilizing therapies.

SummaryBackgroundEndothelial cell (EC) activation, endotheliitis, vascular permeability, and thrombosis have been observed in patients with severe coronavirus disease 2019 (COVID-19), indicating that the vasculature is affected during the acute stages of SARS-CoV-2 infection. It remains unknown whether circulating vascular markers are sufficient to predict clinical outcomes, are unique to COVID-19, and if vascular permeability can be therapeutically targeted.MethodsProspectively evaluating the prevalence of circulating inflammatory, cardiac, and EC activation markers as well as developing a microRNA atlas in 241 unvaccinated patients with suspected SARS-CoV-2 infection allowed for prognostic value assessment using a Random Forest model machine learning approach. Subsequent ex vivo experiments assessed EC permeability responses to patient plasma and were used to uncover modulated gene regulatory networks from which rational therapeutic design was inferred.FindingsMultiple inflammatory and EC activation biomarkers were associated with mortality in COVID-19 patients and in severity-matched SARS-CoV-2-negative patients, while dysregulation of specific microRNAs at presentation was specific for poor COVID-19-related outcomes and revealed disease-relevant pathways. Integrating the datasets using a machine learning approach further enhanced clinical risk prediction for in-hospital mortality. Exposure of ECs to COVID-19 patient plasma resulted in severity-specific gene expression responses and EC barrier dysfunction, which was ameliorated using angiopoietin-1 mimetic or recombinant Slit2-N.InterpretationIntegration of multi-omics data identified microRNA and vascular biomarkers prognostic of in-hospital mortality in COVID-19 patients and revealed that vascular stabilizing therapies should be explored as a treatment for endothelial dysfunction in COVID-19, and other severe diseases where endothelial dysfunction has a central role in pathogenesis.Funding InformationThis work was directly supported by grant funding from the Ted Rogers Center for Heart Research, Toronto, Ontario, Canada and the Peter Munk Cardiac Center, Toronto, Ontario, Canada.

Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019

BackgroundLow skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross‐sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)‐defined LSMM and fat areas on unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019 (COVID‐19) patients based on a large patient sample.MethodsMEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT‐defined LSMM as well as fat areas and in‐hospital mortality in COVID‐19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis.ResultsThe included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in‐hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07–31.83]. It was 2.73 (95% CI 0.54–13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57–4.47).ConclusionsComputed tomography‐defined LSMM and high visceral fat area have a relevant association with in‐hospital mortality in COVID‐19 patients and should be included as relevant prognostic biomarkers into clinical routine.

Assessment of National Early Warning Score 2 as a Tool to Predict the Outcome of COVID-19 Patients on Admission.

Introduction: The ongoing pandemic due to coronavirus disease 2019 (COVID-19) has put tremendous strain on the healthcare system around the world. There is a paucity of data describing the role of National Early Warning Score 2 (NEWS2) in the assessment of COVID-19 cases. This study aimed at identifying NEWS2 calculated on admission as a valuable tool for risk stratification and prediction of in-hospital mortality in COVID-19 patients.Materials and method: This prospective, observational study included 814 confirmed COVID-19 cases and was conducted over a period of three months. Vital parameters were assessed and NEWS2 was calculated on admission. Data were entered in excel format and statistical analysis was done in Python 3.8 statistical software (Wilmington, DE: Python Software Foundation). Pearson's chi-squared test was used following which a significant NEWS2 cut-off score to predict in-hospital mortality was determined by means of receiver operating characteristic (ROC) curve.Results: Mortality of 9.09% was noted and correlations were made with age, comorbidity, and NEWS2 score. For in-hospital deaths, comorbidities were present in 66.21% of patients, the mean age was 60.14 years, and average NEWS2 score was 9. For discharged patients only 21.89% had comorbidities, mean age was 42.96 years, and average NEWS2 score was 1.17. NEWS2 score of ≥ 6 had a sensitivity of 93.24% and specificity of 98.91%, and hence was a statistically significant cut-off value for predicting mortality on admission.Conclusion:Age, presence of comorbidities, and NEWS2 have a positive correlation with mortality in COVID-19 patients. NEWS2 score being easy, reliable, and quick to calculate, should be used to triage these patients on admission. Scores ≥ 6 should be considered to have a higher risk of adverse outcomes and hence should be managed prudently along with clinical judgment.