Clinical characteristics and risk factors of fatal patients with COVID-19: a retrospective cohort study in Wuhan, China

Case-control study on risk factors for in-hospital mortality in patients with severe COVID-19

Objective

The purpose of this study was to identify independent risk factors affecting patient survival and explore predictors of severe cases of coronavirus disease 2019 (COVID-19).

Methods

We conducted a retrospective, observational, case-control study on adult patients with severe COVID-19 who were admitted to affiliated hospitals in Tianjin between December 18, 2022, and January 31, 2023. We used univariate and multifactorial logistic regression analyses to analyze demographic indicators, comorbidity profiles, and laboratory parameters in two groups of patients (deceased and surviving) to identify independent risk factors for death in patients with severe COVID-19.

Results

Patients in the deceased group were older than those in the survival group (p = 0.018), and there were more cases of coexisting respiratory insufficiency in the deceased group (p = 0.002). Additionally, laboratory test results for white blood cell count (WBC) and creatine kinase (CK) showed significantly higher values in the deceased group (p = 0.047 and p = 0.029, respectively), while arterial oxygen partial pressure (PAO2) showed significantly lower values compared to the survival group (p = 0.021). Age, respiratory insufficiency, WBCH (highest WBC value), CKH (highest CK value), and PAO2F (first PAO2 value) had area under curve (AUC) values of 0.698, 0.838, 0.721, 0.744, and 0.633, respectively.

Conclusion

The main risk factors for mortality in patients with severe COVID-19 that we identified in this study were the advanced age of patients, coexisting respiratory insufficiency, elevated levels of WBC and CK, and decreased levels of PAO2. Elevated WBC and CK laboratory parameters, in particular, demonstrated good predictive value for in-hospital mortality risk.

Development and validation of a scoring system to predict the mortality of hospitalized patients with SARS-CoV-2 Omicron: a nationwide, multicentre study

BACKGROUND

The Omicron variant broke out in China at the end of 2022, causing a considerable number of severe cases and even deaths. The study aimed to identify risk factors for death in patients hospitalized with SARS-CoV-2 Omicron infection and to establish a scoring system for predicting mortality.

METHODS

1817 patients were enrolled at eight hospitals in China from December 2022 to May 2023, including 815 patients in the training group and 1002 patients in the validation group. Forty-six clinical and laboratory features were screened using LASSO regression and multivariable logistic regression.

RESULTS

In the training set, 730 patients were discharged and 85 patients died. In the validation set, 918 patients were discharged and 84 patients died. LASSO regression identified age, levels of interleukin (IL) -6, blood urea nitrogen (BUN), lactate dehydrogenase (LDH), and D-dimer; neutrophil count, neutrophil-to-lymphocyte ratio (NLR) as associated with mortality. Multivariable logistic regression analysis showed that older age, IL-6, BUN, LDH and D-dimer were significant independent risk factors. Based on these variables, a scoring system was developed with a sensitivity of 83.6% and a specificity of 83.5% in the training group, and a sensitivity of 79.8% and a sensitivity of 83.0% in the validation group.

CONCLUSIONS

A scoring system based on age, IL-6, BUN, LDH and D-dime can help clinicians identify patients with poor prognosis early.

NT-proBNP cardiac value in COVID-19: a focus on the paediatric population

NT-proBNP is a peptide related to brain natriuretic peptide, a cardiac biomarker and a member of the natriuretic family of peptides. NT-proBNP has demonstrated its clinical utility in the assessment of a wide spectrum of cardiac manifestations. It is also considered a more precise diagnostic and prognostic cardiac biomarker than brain natriuretic peptide. With the appearance of the Severe Acute Respiratory Syndrome Coronavirus 2 virus and the subsequent COVID-19 pandemic, diagnosis of heart implications began to pose an increasing struggle for the physician. Echocardiography is considered a central means of evaluating cardiac disorders like heart failure, and it is considered a reliable method. However, other diagnostic methods are currently being explored, one of which involves the assessment of NT-proBNP levels. In the literature that involves the adult population, significant positive correlations were drawn between the levels of NT-proBNP and COVID-19 outcomes such as high severity and fatality. In the paediatric population, however, the literature is scarce, and most of the investigations assess NT-proBNP in the context of Multiple Inflammatory Syndrome in Children, where studies have shown that cohorts with this syndrome had elevated levels of NT-proBNP when compared to non-syndromic cohorts. Thus, more large-scale studies on existing COVID-19 data should be carried out in the paediatric population to further understand the prognostic and diagnostic roles of NT-proBNP.

Decoding acute myocarditis in patients with COVID-19: Early detection through machine learning and hematological indices

During the persistent COVID-19 pandemic, the swift progression of acute myocarditis has emerged as a profound concern due to its augmented mortality, underscoring the urgency of prompt diagnosis. This study analyzed blood samples from 5,230 COVID-19 individuals, identifying key blood and myocardial markers that illuminate the relationship between COVID-19 severity and myocarditis. A predictive model, applying Bayesian and random forest methodologies, was constructed for myocarditis' early identification, unveiling a balanced gender distribution in myocarditis cases contrary to a male predominance in COVID-19 occurrences. Particularly, older men exhibited heightened vulnerability to severe COVID-19 strains. The analysis revealed myocarditis was notably prevalent in younger demographics, and two subvariants COVID-19 progression paths were identified, characterized by symptom intensity and specific blood indicators. The enhanced myocardial marker model displayed remarkable diagnostic accuracy, advocating its valuable application in future myocarditis detection and treatment strategies amidst the COVID-19 crisis.

Inflammatory biomarkers to predict the prognosis of acute bacterial and viral infections

Mortality in acute infections is mostly associated with sepsis, defined as 'life-threatening organ dysfunction caused by a dysregulated host response to infection'. It remains challenging to identify the patients with increased mortality risk due to the high heterogeneity in the dysregulated host immune response and disease progression. Biomarkers reflecting different pathways involved in the inflammatory response might improve prediction of mortality risk (prognostic enrichment) among patients with acute infections by reducing heterogeneity of the host response, as well as suggest novel strategies for patient stratification and treatment (predictive enrichment) through precision medicine approaches. The predictive value of inflammatory biomarkers has been extensively investigated in bacterial infections and the recent COVID-19 pandemic caused an increased interest in inflammatory biomarkers in this viral infection. However, limited research investigated whether the prognostic potential of these biomarkers differs between bacterial and viral infections. In this narrative review, we provide an overview of the value of various inflammatory biomarkers for the prediction of mortality in bacterial and viral infections.

Red blood cell distribution width at admission predicts outcome in critically ill patients with kidney failure: a retrospective cohort study based on the MIMIC-IV database

PURPOSE

We aimed to explore whether red blood cell distribution width (RDW) could serve as a biomarker to predict outcomes in critically ill patients with kidney failure in this study.

MATERIALS AND METHODS

This retrospective study was conducted with the Medical Information Mart for Intensive Care IV (MIMIC-IV).A total of 674 patients were divided into three groups based on tertiles of RDW. We used the generalized additive model, Kaplan-Meier curve, and Cox proportional hazards models to evaluate the association between RDW and clinical outcomes. We then performed subgroup analyses to investigate the stability of the associations between RDW and all-cause mortality.

RESULTS

Nonlinear and J-shaped curves were observed in the generalized additive model. Kaplan-Meier analysis showed that patients with elevated RDW had a lower survival rate. The Cox regression model indicated that high levels of RDW were most closely associated with ICU mortality and 30-day mortality (HR = 4.71, 95% CI: 1.69-11.64 and HR = 6.62, 95% CI: 2.84-15.41). Subgroup analyses indicated that the associations between RDW and all-cause mortality were stable.

CONCLUSIONS

Elevated levels of RDW were associated with an increased risk of all-cause mortality, and RDW could be an independent prognostic factor for kidney failure.

Ivermectin: A Controversial Focal Point during the COVID-19 Pandemic

The SARS-CoV-2 pandemic has confirmed the apocalyptic predictions that virologists have been making for several decades. The challenge the world is facing is that of trying to find a possible treatment, and a viable and expedient option for addressing this challenge is the repurposing of drugs. However, in some cases, although these drugs are approved for use in humans, the mechanisms of action involved are unknown. In this sense, to justify its therapeutic application to a new disease, it is ideal, but not necessary, to know the basic mechanisms of action involved in a drug's biological effects. This review compiled the available information regarding the various effects attributed to Ivermectin. The controversy over its use for the treatment of COVID-19 is demonstrated by this report that considers the proposal unfeasible because the therapeutic doses proposed to achieve this effect cannot be achieved. However, due to the urgent need to find a treatment, an exhaustive and impartial review is necessary in order to integrate the knowledge that exists, to date, of the possible mechanisms through which the treatment may be helpful in defining safe doses and schedules of Ivermectin.

Rare case of pneumoperitoneum in nonintubated COVID-19 patient

We report a rare case of a 50-year-old female patient with COVID-19 presented to the emergency department where supplementary oxygen is delivered via noninvasive face mask ventilation. X-ray imaging confirmed the existence of pneumoperitoneum. CT scan was not applicable due to the advanced status of the patient.

Preexisting coronary artery disease among coronavirus disease 2019 patients: a systematic review and meta-analysis

AIMS

The prevalence and prognostic implications of coronary artery disease (CAD) in patients infected by the novel coronavirus 2019 (COVID-19) disease remain unclear.

METHODS

We conducted a systematic review and meta-analysis to investigate the prevalence and mortality risk in COVID-19 patients with preexisting CAD. We searched Medline and Scopus to locate all articles published up to December 8, 2021, reporting data of COVID-19 survivors and nonsurvivors with preexisting CAD. Data were pooled using the Mantel-Haenszel random effects models with odds ratio (OR) as the effect measure with the related 95% confidence interval (CI).

RESULTS

Thirty-eight studies including 27 435 patients (mean age 61.5 and 70.9 years) were analysed. The pooled prevalence of preexisting CAD was 12.6% (95% CI: 11.2-16.5%, I2 : 95.6%), and resulted as higher in intensive care unit patients (17.5%, 95% CI: 11.9-25.1, I2 : 88.4%) and in European cohorts (13.1%, 95% CI: 7.8-21.6%, P  < 0.001, I2 : 98.4%). COVID-19 patients with preexisting CAD had a two-fold risk of short-term mortality (OR 2.61, 95% CI 2.10-3.24, P  < 0.001, I2  = 73.6%); this risk was higher among Asian cohorts (OR: 2.66, 95% CI: 1.79-3.90, P  < 0.001, I2 : 77.3%) compared with European (OR: 2.44, 95% CI: 1.90-3.14, P  < 0.001, I2 : 56.9%) and American (OR: 1.86, 95% CI: 1.41-2.44, P  < 0.001, I2 : 0%) populations. The association between CAD and poor short-term prognosis was influenced by age, prevalence of hypertension (HT), DM and CKD.

CONCLUSIONS

Preexisting CAD is present in approximately 1 in 10 patients hospitalized for COVID-19 and significantly associated with an increased risk of short-term mortality, which is influenced by age, HT, DM and CKD.

A Brief Analysis of a New Device to Prevent Early Intubation in Hypoxemic Patients: An Observational Study

The need for mechanical ventilation is one of the main concerns related to the care of patients with COVID-19. The aim of this study is to evaluate the efficacy of a bubble device for oxygen supplementation. This device was implemented for the selected patients hospitalized with severe COVID-19 pneumonia with persistent low oxygen saturation. Patients were selected in three major COVID-19 hospitals of Bahia state in Brazil from July to November 2020, where they remained with the device for seven days and were monitored for different factors, such as vital signs, oximetry evaluation, and arterial blood gasometry. Among the 51 patients included in the study, 68.63% successfully overcame hypoxemia without the necessity to be transferred to mechanical ventilation, whereas 31.37% required tracheal intubation (p value < 0.05). There was no difference of note on the analysis of the clinical data, chemistry, and hematological evaluation, with the exception of the SpO2 on follow-up days. Multivariate analysis revealed that the independent variable, male sex, SpO2, and non-inhaled mask, was associated with the necessity of requiring early mechanical ventilation. We concluded that this bubble device should be a prior step to be utilized before indication of mechanical ventilation in patients with persistent hypoxemia of severe COVID-19 pneumonia.

Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study

Our study objective was to construct models using 20 routine laboratory parameters on admission to predict disease severity and mortality risk in a group of 254 hospitalized COVID-19 patients. Considering the influence of confounding factors in this single-center study, we also retrospectively assessed the correlations between the risk of death and the routine laboratory parameters within individual comorbidity subgroups. In multivariate regression models and by ROC curve analysis, a model of three routine laboratory parameters (AUC 0.85; 95% CI: 0.79-0.91) and a model of six laboratory factors (AUC 0.86; 95% CI: 0.81-0.91) were able to predict severity and mortality of COVID-19, respectively, compared with any other individual parameter. Hierarchical cluster analysis showed that inflammatory laboratory markers grouped together in three distinct clusters including positive correlations: WBC with NEU, NEU with neutrophil-to-lymphocyte ratio (NLR), NEU with systemic immune-inflammation index (SII), NLR with SII and platelet-to-lymphocyte ratio (PLR) with SII. When analyzing the routine laboratory parameters in the subgroups of comorbidities, the risk of death was associated with a common set of laboratory markers of systemic inflammation. Our results have shown that a panel of several routine laboratory parameters recorded on admission could be helpful for early evaluation of the risk of disease severity and mortality in COVID-19 patients. Inflammatory markers for mortality risk were similar in the subgroups of comorbidities, suggesting the limited effect of confounding factors in predicting COVID-19 mortality at admission.

Predicting progression to severe COVID-19 using the PAINT score

Objectives

One of the major challenges in treating patients with coronavirus disease 2019 (COVID-19) is predicting the severity of disease. We aimed to develop a new score for predicting progression from mild/moderate to severe COVID-19.

Methods

A total of 239 hospitalized patients with COVID-19 from two medical centers in China between February 6 and April 6, 2020 were retrospectively included. The prognostic abilities of variables, including clinical data and laboratory findings from the electronic medical records of each hospital, were analysed using the Cox proportional hazards model and Kaplan–Meier methods. A prognostic score was developed to predict progression from mild/moderate to severe COVID-19.

Results

Among the 239 patients, 216 (90.38%) patients had mild/moderate disease, and 23 (9.62%) progressed to severe disease. After adjusting for multiple confounding factors, pulmonary disease, age > 75, IgM, CD16⁺/CD56⁺ NK cells and aspartate aminotransferase were independent predictors of progression to severe COVID-19. Based on these five factors, a new predictive score (the ‘PAINT score’) was established and showed a high predictive value (C-index = 0.91, 0.902 ± 0.021, p < 0.001). The PAINT score was validated using a nomogram, bootstrap analysis, calibration curves, decision curves and clinical impact curves, all of which confirmed its high predictive value.

Conclusions

The PAINT score for progression from mild/moderate to severe COVID-19 may be helpful in identifying patients at high risk of progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07466-4.

SARS-CoV-2 triggered oxidative stress and abnormal energy metabolism in gut microbiota

Specific roles of gut microbes in COVID-19 progression are critical. However, the circumstantial mechanism remains elusive. In this study, shotgun metagenomic or metatranscriptomic sequencing was performed on fecal samples collected from 13 COVID-19 patients and controls. We analyzed the structure of gut microbiota, identified the characteristic bacteria, and selected biomarkers. Further, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations were employed to correlate the taxon alterations and corresponding functions. The gut microbiota of COVID-19 patients was characterized by the enrichment of opportunistic pathogens and depletion of commensals. The abundance of Bacteroides spp. displayed an inverse relationship with COVID-19 severity, whereas Actinomyces oris, Escherichia coli, and Streptococcus parasanguini were positively correlated with disease severity. The genes encoding oxidoreductase were significantly enriched in gut microbiome of COVID-19 group. KEGG annotation indicated that the expression of ABC transporter was upregulated, while the synthesis pathway of butyrate was aberrantly reduced. Furthermore, increased metabolism of lipopolysaccharide, polyketide sugar, sphingolipids, and neutral amino acids were found. These results suggested the gut microbiome of COVID-19 patients was in a state of oxidative stress. Healthy gut microbiota may enhance antiviral defenses via butyrate metabolism, whereas the accumulation of opportunistic and inflammatory bacteria may exacerbate COVID-19 progression.

Analysis of Deaths and Favorable Developments of Patients with SARS-CoV-2 Hospitalized in the Largest Hospital for Infectious Diseases and Pneumo-Phthisiology in the West of the Country

Purpose

Romania is one of the European countries that has been hit the hardest by the severe acute respiratory syndrome caused by the new coronavirus SARS-CoV-2, with over 1.91 million reported cases and over 59,257 deaths. The aim of this study was to identify the main predictors of death in hospitalized patients.

Patients and Methods

In the period from 1 March 2020 to 30 June 2021, an observational, retrospective, randomized, case-control study was conducted, which included a sample of 139 patients who died in hospital and another sample of 275 patients who had been discharged in an improved or healed condition. Confirmation of COVID-19 cases was performed by RT-PCR from nasopharyngeal and oropharyngeal exudates. Statistical data were analyzed by logistic regression, Cox regression and a comparison of survival curves by the log-rank (Mantel-Cox) test.

Results

The most powerful logistic regression model identified the following independent predictors of death: history of coagulopathy HR = 30.73 [1.94–487.09], p = 0.015; high percentage of neutrophils HR = 1.09 [1.01–1.19], p = 0.027; and decreased blood-oxygenation HR = 53881.97 [1762.24–1647489.44], p < 0.001. Cox regression identified the following factors that influenced the evolution of cases: history of coagulopathy HR = 2.44 [1.38–4.35], p = 0.000; O₂ saturation HR = 0.98 [0.96–0.99], p = 0.043; serum creatinine HR = 1.23 [1.08–1.39], p = 0.001; dyspnea on admission HR = 2.99 [1.42–6.30], p = 0.004; hospitalization directly in the ICU HR = 3.803 [1.97–7.33], p < 0.001; heart damage HR = 16.76 [1.49–188.56], p = 0.022; and decreased blood-oxygenation HR = 35.12 [5.92–208.19], p < 0.001.

Conclusion

Knowledge of the predictors of death in hospitalized patients allows for the future optimization of triage and therapeutic case management for COVID-19.

Epidemiology and Risk Factors of COVID-19-Related Mortality

Introduction

During the coronavirus disease 2019 (COVID-19) pandemic in India, several characteristics of hospitalized COVID-19 patients, based on demographics, mortality predictors, and presence of comorbidities, were found to be associated with poor outcomes. The objective of this study was to identify such epidemiological and clinical characteristics among the patients admitted at a tertiary-care center in India that may have predisposed them to COVID-19-related mortality.

Methods

This retrospective observational study conducted at the Department of Medicine, All India Institute of Medical Sciences, New Delhi, in May 2021 included 141 COVID-19 confirmed patients. The medical history, demographic characteristics, comorbidities, clinical findings, and laboratory data of each patient were obtained. The data were analyzed to identify significant clinical and laboratory parameters that led to the adverse final outcomes.

Results

Hypertension was the most common comorbidity and the presence of diabetes with hypertension led to poorer final outcomes. Lower oxygen saturation and requirement of oxygen supplementation at admission along with worse prognostic scores during admission led to poorer outcomes. Twenty-seven patients needed non-invasive ventilation (NIV) during the hospital course, and all ultimately landed up among the 56 patients who were managed on invasive mechanical ventilation (IMV). Multivariate logistic regression analysis performed identified COVID-19 severity at admission, co-existence of hypertension and diabetes mellitus, systolic blood pressure less than 90 mm Hg, and serum creatinine greater than 1.2 mg/dL to be associated with higher COVID-19 mortality.

Conclusion

COVID-19 patients having the co-existence of diabetes and hypertension constitute a high-risk group and may be targeted by prompt vaccination strategies. The presence of severe disease along with a need for oxygen therapy and other intensive care interventions ultimately led to unfavorable outcomes.