Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis

Comprehensive mapping of immune perturbations associated with secondary hemophagocytic lymphohistiocytosis

Secondary hemophagocytic lymphohistiocytosis (sHLH) is a hyperinflammatory syndrome characterized by immune disorders. It is imperative to elucidate the immunophenotypic panorama and the interactions among these cells in patients. Human peripheral blood mononuclear cells were collected from healthy donors and sHLH patients and tested using multicolor flow cytometry. We used FlowSOM to explore and visualize the immunophenotypic characteristics of sHLH. By demonstrating the phenotypes of immune cells, we discovered that sHLH patients had significantly higher levels of CD56+ monocytes, higher levels of myeloid-derived suppressor cells, low-density neutrophil-to-T cell ratio, and higher heterogeneous T cell activation than healthy donors. However, natural killer cell cytotoxicity and function were impaired. We then assessed the correlations among 30 immune cell types and evaluated metabolic analysis. Our findings demonstrated polymorphonuclear myeloid-derived suppressor cells, CD56+ monocytes, and neutrophil-to-T cell ratio were elevated abnormally in sHLH patients, which may indicate an association with immune overactivation and inflammatory response. We are expected to confirm that they are involved in the occurrence of the disease through further in-depth research.

Prognostic significance of oxygen saturation/fraction of inspired oxygen 3 days after initiation of tocilizumab treatment in patients with COVID-19

BACKGROUND

Tocilizumab is effective in treating severe coronavirus disease 2019 (COVID-19). However, the specific time point it acts as a valid indicator of treatment efficacy remains unclear. This study aimed to determine the optimal day for assessing the prognostic value of the oxygen saturation/fraction of inspired oxygen (SpO2/FiO2) and ratio of respiratory rate-oxygenation (ROX) index in patients receiving tocilizumab for COVID-19.

METHODS

All patients admitted to our hospital from March 2020 to July 2021 who received tocilizumab for COVID-19 were retrospectively identified from hospital charts. Biodata, medical history, and laboratory tests results were obtained from medical records. The prognostic values of the SpO2/FiO2 and ROX index for predicting mortality were assessed. Cox proportional hazard and receiver operating characteristic curve models were utilized.

RESULTS

Of the 84 included patients, 34 died within 7 days after discharge. The patients who recovered had a mean age of 65 years and were younger than those who died. The multivariate analysis indicated that multiple comorbidities, cancer history, CURB-65 score, neutrophil and lymphocyte counts, neutrophil/lymphocyte ratio, and lactate dehydrogenase levels were higher in those who died compared with those who survived. No significant differences were found in dyspnea or total bilirubin levels between the two groups. The SpO2/FiO2 at 3 days post-tocilizumab initiation was strongly associated with survival.

CONCLUSIONS

The SpO2/FiO2 on day 3 post-tocilizumab initiation was a predictor of COVID-19 prognosis, which could be employed in determining clinical decisions. Prompt alternative interventions should be considered when this ratio does not improve.

Association of COVID-19 with acute and post-acute risk of multiple different complications and mortality in patients infected with omicron variant stratified by initial disease severity: a cohort study in Hong Kong

BACKGROUND

Few studies have attempted to use clinical and laboratory parameters to stratify COVID-19 patients with severe versus non-severe initial disease and evaluate age-specific differences in developing multiple different COVID-19-associated disease outcomes.

METHODS

A retrospective cohort included patients from the electronic health database of Hong Kong Hospital Authority between 1 January 2022 and 15 August 2022 until 15 November 2022. The cohort was divided into three cohorts by age (≤ 40, 41-64, and ≥ 65 years old). Each age cohort was stratified into four groups: (1) COVID-19 critically exposed group (ICU admission, mechanical ventilation support, CRP > 80 mg/L, or D-dimer > 2 g/mL), (2) severely exposed group (CRP 30-80 mg/L, D-dimer 0.5-2 g/mL, or CT value < 20), (3) mildly-moderately exposed group (COVID-19 positive-tested but not fulfilling the criteria for the aforementioned critically and severely exposed groups), and (4) unexposed group (without COVID-19). The characteristics between groups were adjusted with propensity score-based marginal mean weighting through stratification. Cox regression was conducted to determine the association of COVID-19 disease severity with disease outcomes and mortality in the acute and post-acute phase (< 30 and ≥ 30 days from COVID-19 infection) in each age group.

RESULTS

A total of 286,114, 320,304 and 194,227 patients with mild-moderate COVID-19 infection; 18,419, 23,678 and 31,505 patients with severe COVID-19 infection; 1,168, 2,261 and 10,178 patients with critical COVID-19 infection, and 1,143,510, 1,369,365 and 1,012,177 uninfected people were identified in aged ≤ 40, 40-64, and ≥ 65 groups, respectively. Compared to the unexposed group, a general trend tending towards an increase in risks of multiple different disease outcomes as COVID-19 disease severity increases, with advancing age, was identified in both the acute and post-acute phases. Notably, the mildly-moderately exposed group were associated with either insignificant risks (aged ≤ 40) or the lowest risks (aged > 40) for the disease outcomes in the acute phase of infection (e.g., mortality risk HR (aged ≤ 40): 1.0 (95%CI: 0.5,2.0), HR (aged 41-64): 2.1 (95%CI: 1.8, 2.6), HR (aged > 65): 4.8 (95%CI: 4.6, 5.1)); while in the post-acute phase, these risks were largely insignificant in those aged < 65, remaining significant only in the elderly (age ≥ 65) (e.g., mortality risk HR (aged ≤ 40): 0.8 (95%CI: (0.5, 1.0)), HR (aged 41-64): 1.1 (95%CI: 1.0,1.2), HR (aged > 65): 1.5 (95%CI: 1.5,1.6)). Fully vaccinated patients were associated with lower risks of disease outcomes than those receiving less than two doses of vaccination.

CONCLUSIONS

The risk of multiple different disease outcomes in both acute and post-acute phases increased significantly with the increasing severity of acute COVID-19 illness, specifically among the elderly. Moreover, future studies could improve by risk-stratifying patients based on universally accepted thresholds for clinical parameters, particularly biomarkers, using biological evidence from immunological studies.

Pharmacodynamic, prognostic, and predictive biomarkers in severe and critical COVID-19 patients treated with sirukumab

We examined candidate biomarkers for efficacy outcomes in hospitalized COVID-19 patients who were treated with sirukumab, an IL-6 neutralizing antibody, in a randomized, double-blind, placebo-controlled, phase 2 trial. Between May 2020 and March 2021, 209 patients were randomized (sirukumab, n = 139; placebo, n = 70); 112 had critical COVID-19. Serum biomarkers were evaluated for the pharmacodynamic effect of sirukumab and for their potential prognostic and predictive effect on time to sustained clinical improvement up to Day 28, clinical improvement at Day 28, and mortality at Day 28. The absence of detectable IL-4 increase and smaller increases in CCL13 post-baseline were most significantly associated with better response to sirukumab (versus placebo) treatment for all clinical efficacy outcomes tested, especially in patients with critical COVID-19. These data suggest that patients with critical COVID-19 without detectable sirukumab-induced IL-4 levels are more likely to benefit from sirukumab treatment. ClinicalTrials.gov Identifier: NCT04380961.

Aging enhances pro-atrogenic gene expression and skeletal muscle loss following respiratory syncytial virus infection

Aging and many age-related health conditions are associated with skeletal muscle loss. Furthermore, older adults are more susceptible to severe respiratory infections, which can in turn lead to muscle wasting. The mechanisms by which respiratory viral infection can impact skeletal muscle in older adults are not well understood. We determined the effects of acute infection with respiratory syncytial virus (RSV) on the lung and skeletal muscle of aged mice. RSV infection caused more severe disease in aged mice with enhanced weight loss, reduced feeding, higher viral load, and greater airway inflammation. Aged but not young mice showed decreased leg muscle weight at the peak of illness and decreased size of leg muscle fibers. Aged mice increased muscle-specific expression of atrophy-promoting enzymes (Atrogin-1 and MuRF-1) and failed to increase the rate of muscle protein synthesis during RSV infection. In aged mice, the changes in Atrogin-1 and MuRF-1 gene expression in skeletal muscle correlated with IL-6 levels in the lungs. These findings indicate that RSV infection of aged mice provides a model for studying the diverse adverse systemic consequences of respiratory viral infections on health and wellbeing in older adults.

Assessment of oral tissue alterations in patients diagnosed with SARS-CoV-2

BACKGROUND

The aim of this study was to investigate oral mucosal changes in patients with confirmed moderate-scale severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

We analyzed 85 COVID-19 patients (50 males, 35 females) with an average age of 53.6 years, treated at the prehospital infectious disease center and Aldent University Clinic in Tirana, Albania, from May 2021 to June 2022.

RESULTS

Elevated C-reactive protein levels were observed in 82 patients (±44.20), with 20 patients showing significant fibrinogen increase (mean ± 5.85 g/L), and 22 patients having elevated D-Dimer (mean ± 336.6 mg/mL). Despite the absence of anticoagulant history, 13 patients exhibited bleeding. Xerodermia, xerostomia, and angular cheilitis were noted, with 41 patients displaying angular cheilitis. In 82 patients, oral mucosal and tongue examinations revealed color changes from white to bright yellow, with brown edema. Pigmentation in the fixed gingiva of upper and lower front teeth was observed in 35 patients.

CONCLUSIONS

Oral mucosal changes during COVID-19 appear more influenced by drug treatment and disease progression than the infection itself, suggesting that secondary factors play a significant role. Despite the oral cavity's potential for viral entry, these changes seem connected to other underlying causes.

Zinc deficiency is a potential risk factor for COVID-19 progression to pneumonia requiring oxygen therapy

INTRODUCTION

Various risk factors for developing severe coronavirus disease 2019 (COVID-19) have been reported. However, studies on the nutritional-related risk factors are limited. In this study, we investigated the effects of serum zinc deficiency on the severity of COVID-19.

METHODS

The study included a total of 60 COVID-19 patients who were admitted to Tsuyama Chuo Hospital between March 2020 and April 2021. We divided the patients into two categories based on serum levels of zinc (normal and latent zinc deficiency vs. zinc deficiency [<60 μg/dL]) at the time of diagnosis. Severity of COVID-19 was defined as the most exaggerated disease status during admission. The associations between serum zinc deficiency and the severity of COVID-19 were examined using a logistic regression model adjusted for potential confounders.

RESULTS

Patients who required oxygen therapy had a higher prevalence of comorbidities and poorer nutritional status, including zinc deficiency, than those who did not require oxygen therapy. Zinc deficiency was associated with an increased risk of COVID-19 severity, with an adjusted odds ratio of 7.29 (95% confidence interval: 1.70-31.18). This result remained significant in the sensitivity analyses conducted after adjusting for patient background factors.

CONCLUSIONS

Zinc deficiency at the time of COVID-19 diagnosis is an independent risk factor for severe disease. Our findings need to be validated in external studies.

Comparative analysis of COVID-19 pneumonia in pregnant versus matched non-pregnant women: radiologic, laboratory, and clinical perspectives

This study aimed to assess the severity and outcomes of COVID-19 in pregnant women, focusing on laboratory and radiological discrepancies between pregnant women and matched nonpregnant women. In this retrospective cross-sectional analysis, we matched 107 nonpregnant women with 66 pregnant women in terms of age, comorbidities, and the interval between symptom onset and hospital admission. Demographic, clinical, laboratory, and radiological data were collected, and chest CT scans were evaluated using a severity scale ranging from 0 to 5. Logistic regression and adjusted Cox regression models were used to assess the impact of various factors on pregnancy status and mortality rates. Differences in several laboratory parameters, including the neutrophil-to-lymphocyte ratio, liver aminotransferases, alkaline phosphatase, urea, triglycerides, cholesterol, HbA1c, ferritin, coagulation profiles, and blood gases, were detected. Radiologic exams revealed that nonpregnant women had sharper opacities, whereas pregnant women presented with hazy opacities and signs of crypt-organizing pneumonia. A notable difference was also observed in the pulmonary artery diameter. The mortality rate among pregnant women was 4.62%, which was comparable to the 5.61% reported in nonpregnant patients. Compared with nonpregnant patients, pregnancy did not significantly affect the severity or mortality of COVID-19. Our study revealed discernible differences in specific laboratory and imaging markers between pregnant and nonpregnant COVID-19 patients.

The Role of Dynamic Changes in Hematologic and Biochemical Parameters in Predicting Mortality in Covid-19 Patients

Objectives

The role of hematologic, inflammatory and biochemical parameters as biomarkers, their role in identifying risky patients in the early stage and their role in prognosis in COVID-19 Coronavirus disease 2019 (COVID-19) were investigated.

Methods

The study included patients who were hospitalized and followed up with a prediagnosis of COVID-19 in the first wave in our country at the University of Health Sciences, Sisli Hamidiye Etfal Training and Research Hospital Demographic and clinical characteristics as well as complete blood count, C reactive protein (CRP), procalcitonin (PCT), fibrinogen (FIB), ferritin, albumin (ALB), lactate dehydrogenase (LDH) levels on admission, third, seventh and 14th days were analyzed. Patients were grouped and compared according to the occurrence of death during hospital follow-up. Variables considered significant on mortality were analyzed with univariate and multivariate logistic regression models.

Results

The study was conducted with 485 patients, 273 (56.3%) males and 212 (43.72%) females. The mean age of the patients was 58±16.2 years, and 71% were in the mild-moderate and 29% in the severe-critical disease group. Disease severity, the need for intensive care unit (ICU) follow-up, and the development of death were positively correlated with age, comorbidity, neutrophil (NE), leukocyte, neutrophil-lymphocyte ratio (NLR), PCT, CRP, ferritin, LDH values, and negatively correlated with lymphocyte (LE), ALB and hemoglobin (HGB) values. In multivariate analysis, elevated PCT at hospital admission (OR: 6.96 [1.63;39.65]), LDH ≥ 352U/L (OR: 4.35 [1.23;16.61]), LE<0.810 × 109/L (OR: 3.0 [1.16;7.85]) and advanced age (OR: 1.08 [1.03;1.14]) were independently associated with in-hospital death. In hemogram and acute phase reactant monitoring, PCT, CRP and LDH were the most valuable markers for predicting death, respectively (third-day AUC: 0.90;0.83;0.83 and seventh-day AUC: 0.95;0.90;0.89, respectively).

Conclusion

In our study, leukocytes, lymphocytes, NLR, CRP, PCT, ferritin, albumin and LDH at admission were valuable in predicting poor prognosis. In addition, it was determined that increases in PCT, LDH and CRP during follow-up could be used to predict in-hospital death and to identify patients requiring close follow-up.

Advancing insights in critical COVID-19: unraveling lymphopenia through propensity score matching - Findings from the Multicenter LYMPH-COVID Study

OBJECTIVE

To elucidate the impact of lymphopenia on critical COVID-19 patient outcomes.

METHODS

We conducted a multicenter prospective cohort study across five hospitals in Portugal and Brazil from 2020 to 2021. The study included adult patients admitted to the intensive care unit with SARS-CoV-2 pneumonia. Patients were categorized into two groups based on their lymphocyte counts within 48 hours of intensive care unit admission: the Lymphopenia Group (lymphocyte serum count < 1 × 109/L) and the Nonlymphopenia Group. Multivariate logistic regression, propensity score matching, Kaplan‒Meier survival curve analysis and Cox proportional hazards regression analysis were used.

RESULTS

A total of 912 patients were enrolled, with 191 (20.9%) in the Nonlymphopenia Group and 721 (79.1%) in the Lymphopenia Group. Lymphopenia patients displayed significantly elevated disease severity indices, including Sequential Organ Failure Assessment and Simplified Acute Physiology Score 3 scores, at intensive care unit admission (p = 0.001 and p < 0.001, respectively). Additionally, they presented heightened requirements for vasopressor support (p = 0.045) and prolonged intensive care unit and in-hospital stays (both p < 0.001). Multivariate logistic regression analysis after propensity score matching revealed a significant contribution of lymphopenia to mortality, with an odds ratio of 1,621 (95%CI: 1,275 - 2,048; p < 0.001). Interaction models revealed an increase of 8% in mortality for each decade of longevity in patients with concomitant lymphopenia. In the subanalysis utilizing three-group stratification, the Severe Lymphopenia Group had the highest mortality rate, not only in direct comparisons but also in Kaplan‒Meier survival analysis (log-rank test p = 0.0048).

CONCLUSION

Lymphopenia in COVID-19 patients is associated with increased disease severity and an increased risk of mortality, underscoring the need for prompt support for critically ill high-risk patients. These findings offer important insights into improving patient care strategies for COVID-19 patients.

Clinical Course and Factors Correlated with Severe Morbidity and Mortality in Patients with Coronavirus Disease 2019 Undergoing Maintenance Dialysis in Kanagawa, Japan

Objective Patients undergoing maintenance dialysis are at a higher risk of morbidity and mortality due to severe coronavirus disease 2019 (COVID-19) than the general population. However, longitudinal data regarding this subpopulation of patients are lacking. We therefore examined the prognosis of patients with COVID-19 undergoing maintenance dialysis between 2020 and 2023. In addition, we explored the factors correlated with COVID-19 severity, focusing on the transition thereof throughout the observational period. Methods The primary outcome was the progression to severe or fatal COVID-19. We evaluated the correlation between the primary outcome and baseline demographic and clinical characteristics of patients. Patients undergoing maintenance dialysis who were hospitalized for mild-to-moderate COVID-19 between February 2020 and April 2023 were enrolled at four institutions in Kanagawa, Japan. Results Of the 173 patients, 7 (4.0%) developed severe COVID-19, and 12 (6.9%) died. The severe/death cohort was significantly older, with a higher percentage of unvaccinated patients than the non-severe cohort (58.2% and 25.0%, respectively; p=0.016). Thymus and activation-regulated chemokine levels on admission were lower in the severe/death cohort than in the non-severe cohort, albeit not to a statistically significant degree (148±84 mg/dL and 342±657 pg/mL, respectively; p=0.082). A multivariate logistic regression analysis revealed that the odds ratio for severe morbidity or death was 0.23 (95% confidence interval: 0.07-0.75) for vaccinated patients. Conclusion In patients undergoing maintenance dialysis, the severity rate of COVID-19 is approximately 10%. Vaccination was correlated with a reduced risk of severe COVID-19.

STAVER: a standardized benchmark dataset-based algorithm for effective variation reduction in large-scale DIA-MS data

Mass spectrometry (MS)-based proteomics has become instrumental in comprehensively investigating complex biological systems. Data-independent acquisition (DIA)-MS, utilizing hybrid spectral library search strategies, allows for the simultaneous quantification of thousands of proteins, showing promise in enhancing protein identification and quantification precision. However, low-quality profiles can considerably undermine quantitative precision, resulting in inaccurate protein quantification. To tackle this challenge, we introduced STAVER, a novel algorithm that leverages standardized benchmark datasets to reduce non-biological variation in large-scale DIA-MS analyses. By eliminating unwanted noise in MS signals, STAVER significantly improved protein quantification precision, especially in hybrid spectral library searches. Moreover, we validated STAVER's robustness and applicability across multiple large-scale DIA datasets, demonstrating significantly enhanced precision and reproducibility of protein quantification. STAVER offers an innovative and effective approach for enhancing the quality of large-scale DIA proteomic data, facilitating cross-platform and cross-laboratory comparative analyses. This advancement significantly enhances the consistency and reliability of findings in clinical research. The complete package is available at https://github.com/Ran485/STAVER.

Unbiased plasma profiling using pre-selected RNA aptamer pools predicts mortality in COVID-19 and identifies protein risk factors

The impact of the COVID-19 pandemic demands effective prognostic tools for precise risk evaluation and timely intervention. This study utilized the APTASHAPE technology to profile plasma proteins in COVID-19 patient samples. Employing a highly diverse 2'-fluoro-protected RNA aptamer pool enriched toward proteins in the plasma samples from COVID-19 patients, we performed a single round of parallel selection on the derivation cohort and identified 93 discriminatory aptamers capable of distinguishing COVID-19 and healthy plasma samples. A subset of these aptamers was then used to predict 30-day mortality with high sensitivity and specificity in a validation cohort of 165 patients. We predicted 30-day mortality with areas under the curve (AUCs) of 0.91 in females and 0.68 in males. Affinity purification coupled with mass spectrometry analysis of the aptamer-targeted proteins identified potential biomarkers associated with disease severity, including complement system components. The study demonstrates the APTASHAPE technology as an unbiased approach that not only aids in predicting disease outcomes but also offers insights into gender-specific differences, shedding light on the nuanced aspects of COVID-19 pathophysiology. In conclusion, the findings highlight the promise of APTASHAPE as a valuable tool for estimating risk factors in COVID-19 patients and enabling stratification for personalized treatment management.

Guidelines on deep vein thrombosis of the Brazilian Society of Angiology and Vascular Surgery

Deep vein thrombosis is one of the main causes of inpatient and outpatient morbidity, both in medical and surgical patients, significantly impacting mortality statistics and requiring prompt diagnosis so that treatment can be initiated immediately. This document was prepared and reviewed by 11 specialists certified by the Brazilian Society of Angiology and Vascular Surgery, who searched the main databases for the best evidence on the diagnostic (physical examination, imaging) and therapeutic approaches (heparin, coumarins, direct oral anticoagulants, fibrinolytics) to the disease.

A NONPARAMETRIC MIXED-EFFECTS MIXTURE MODEL FOR PATTERNS OF CLINICAL MEASUREMENTS ASSOCIATED WITH COVID-19

Some patients with COVID-19 show changes in signs and symptoms such as temperature and oxygen saturation days before being positively tested for SARS-CoV-2, while others remain asymptomatic. It is important to identify these subgroups and to understand what biological and clinical predictors are related to these subgroups. This information will provide insights into how the immune system may respond differently to infection and can further be used to identify infected individuals. We propose a flexible nonparametric mixed-effects mixture model that identifies risk factors and classifies patients with biological changes. We model the latent probability of biological changes using a logistic regression model and trajectories in the latent groups using smoothing splines. We developed an EM algorithm to maximize the penalized likelihood for estimating all parameters and mean functions. We evaluate our methods by simulations and apply the proposed model to investigate changes in temperature in a cohort of COVID-19-infected hemodialysis patients.

Neopterin production in relation to COVID-19 in the Haut-Ogooué Province, Gabon

BACKGROUND

In sub-Saharan Africa, understanding of the immune process associated with the COVID-19 pandemic remains scarce. This study aimed to investigate the relationship between plasma neopterin concentrations and COVID-19 infection, focusing on changes over time and age-related changes in immune response.

METHODS

A retrospective case study was conducted during the first wave of COVID-19 from March to August 2020. Whole blood and associated symptoms and comorbidities were collected from patients of all ages and sexes. Concentrations of plasma neopterin were measured using a commercial competitive neopterin ELISA (Neopterin ELISA, IBL International GmbH, Germany).

RESULTS

We analyzed data for 325 patients: 38% (n = 124) with COVID-19, and 62% (n = 201) without COVID-19, as a control group. We found that plasma neopterin concentrations were significantly higher in the COVID-19 group (mean value 45.1 nmol/L (SD 19)) than in the control group (mean value 33.8 nmol/L (SD 13)) (p = 0.004). In addition, neopterin levels decreased gradually over time in patients with COVID-19 (p < 0.001). Moreover, ROC analysis found that the best cut-off value for diagnosing COVID-19 patients based on plasma neopterin levels was 38.85 nmol/L with 70% sensitivity and 82% specificity (AUC, 0.74 [0.69-0.82], p < 0.05). We also found an increase in neopterin production with increasing age (p < 0.001).

CONCLUSION

Our findings contribute to our growing understanding of neopterin levels as a promising biomarker for the detection of COVID-19 cases in sub-Saharan Africa.

The cost-effectiveness of procalcitonin for guiding antibiotic prescribing in individuals hospitalized with COVID-19: part of the PEACH study

BACKGROUND

Many hospitals introduced procalcitonin (PCT) testing to help diagnose bacterial coinfection in individuals with COVID-19, and guide antibiotic decision-making during the COVID-19 pandemic in the UK.

OBJECTIVES

Evaluating cost-effectiveness of using PCT to guide antibiotic decisions in individuals hospitalized with COVID-19, as part of a wider research programme.

METHODS

Retrospective individual-level data on patients hospitalized with COVID-19 were collected from 11 NHS acute hospital Trusts and Health Boards from England and Wales, which varied in their use of baseline PCT testing during the first COVID-19 pandemic wave. A matched analysis (part of a wider analysis reported elsewhere) created groups of patients whose PCT was/was not tested at baseline. A model was created with combined decision tree/Markov phases, parameterized with quality-of-life/unit cost estimates from the literature, and used to estimate costs and quality-adjusted life years (QALYs). Cost-effectiveness was judged at a £20 000/QALY threshold. Uncertainty was characterized using bootstrapping.

RESULTS

People who had baseline PCT testing had shorter general ward/ICU stays and spent less time on antibiotics, though with overlap between the groups' 95% CIs. Those with baseline PCT testing accrued more QALYs (8.76 versus 8.62) and lower costs (£9830 versus £10 700). The point estimate was baseline PCT testing being dominant over no baseline testing, though with uncertainty: the probability of cost-effectiveness was 0.579 with a 1 year horizon and 0.872 with a lifetime horizon.

CONCLUSIONS

Using PCT to guide antibiotic therapy in individuals hospitalized with COVID-19 is more likely to be cost-effective than not, albeit with uncertainty.

Has the Coronavirus Disease 2019 Pandemic Played a Role in the Early Detection of Pulmonary Embolism in Children?

OBJECTIVE

Pulmonary embolism (PE) poses a significant threat to children, and nonspecific symptoms lead to delayed diagnosis. The emergence of coronavirus disease 2019 (COVID-19) has increased the complexity as it is associated with similar symptoms and increased risk of thrombotic complications. This study aimed to assess the risk factors, clinical presentations, and diagnostic features of PE in pediatric patients and to examine the impact of the COVID-19 pandemic on children with PE.

MATERIALS AND METHODS

We conducted a retrospective descriptive study examining the clinical and diagnostic data of 44 pediatric patients with radiologically confirmed PE. The study compared and analyzed patients diagnosed before and during the COVID-19 pandemic.

RESULTS

In the study, 21 of 44 pediatric patients were diagnosed in the 4 years before the COVID-19 pandemic, and 23 were diagnosed with PE during the COVID-19 pandemic. The mean time to diagnosis was 8 (2 to 14) days before the pandemic and 1 (1 to 2) days during the pandemic ( P < 0.001). The most common associated condition in both groups was infection (65.9%). Dyspnea (65.9%) and tachypnea (50.0%) were common symptoms. Except for deep vein thrombosis, there were no significant differences according to associated conditions between the groups ( P = 0.001). Pulmonary emboli were anatomically detected using computed tomography angiography, showing bilateral involvement in 45.4% of patients, segmental artery involvement in 38.6%, and main artery involvement in 15.9%.

CONCLUSION

The COVID-19 pandemic heightened suspicion of pediatric PE and accelerated diagnosis. Standardized diagnostic guidelines are increasingly necessary to balance accurate diagnosis with avoiding excessive imaging.

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

AIM

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.

PATIENTS AND METHODS

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.

RESULTS

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).

CONCLUSION

Diabetes mellitus may continue contributing to COVID-19 in-hospital mortality in the future, as the Omicron sub-strain may still be prevalent.

Peripheral biomarkers as a predictor of poor prognosis in severe cases of COVID-19

We evaluated glycemia and triglyceride, hepatic, muscular, and renal damage markers, redox profile, and leptin and ghrelin hormone levels in COVID-19 patients. We also conducted statistical analysis to verify the potential of biomarkers to predict poor prognosis and the correlation between them in severe cases. We assessed glycemia and the levels of triglycerides, hepatic, muscular, and renal markers in automatized biochemical analyzer. The leptin and ghrelin hormones were assessed by the ELISA assay. Severe cases presented high glycemia and triglyceride levels. Hepatic, muscular, and renal biomarkers were altered in severe patients. Oxidative stress status was found in severe COVID-19 patients. Severe cases also had increased levels of leptin. The ROC curves indicated many biomarkers as poor prognosis predictors in severe cases. The Spearman analysis showed that biomarkers correlate between themselves. Patients with COVID-19 showed significant dysregulation in the levels of several peripheral biomarkers. We bring to light that a robust panel of peripheral biomarkers and hormones predict poor prognosis in severe cases of COVID-19 and biomarkers correlate with each other. Early monitoring of these biomarkers may lead to appropriate clinical interventions in patients infected by SARS-CoV2.

The association between potential predictors and death of patients during the COVID-19 pandemic in Shiraz: a hierarchical multiple regression analysis

INTRODUCTION

Identifying clinical factors that increase the risk of mortality in COVID-19 patients is crucial. This enables targeted screening, optimizing treatment, and prevention of severe complications, ultimately reducing death rates. This study aimed to develop prediction models for the death of patients (i.e., survival or death) during the COVID-19 pandemic in Shiraz, exploring the main influencing factors.

METHOD

We conducted a retrospective cohort study using hospital-based records of 1030 individuals diagnosed with COVID-19, who were hospitalized for treatment between March 21, 2021, and March 21, 2022, in Shiraz, Iran. Variables related to the final outcome were selected based on criteria and univariate logistic regression. Hierarchical multiple logistic regression and classification and regression tree (CART) models were utilized to explore the relationships between potential influencing factors and the final outcome. Additionally, methods were employed to identify the high-risk population for increased mortality rates during COVID-19. Finally, accuracy was evaluated the performance of the models, with the area under the receiver operator characteristic curve(AUC), sensitivity, and specificity metrics.

RESULTS

In this study, 558 (54.2%) individuals infected with COVID-19 died. The final model showed that the type of medicine antiviral (OR: 11.10, p = 0.038) than reference (antiviral and corticosteroid), and discharge oxygen saturation(O2) (OR: 1.10, p < 0.001) had a positive association with the chance of survival, but other variables were not considered as predictive variables. Predictive models for the final outcome(death) achieved accuracies ranging from 81 to 87% for hierarchical multiple logistic regression and from 87 to 94% for the CART model. Therefore, the CART model performed better than the hirerical multiple logistic regression model.

CONCLUSION

These findings firstly elucidate the incidence and associated factors of the outcome (death) among patients in Shiraz, Iran. Furthermore, we demonstrated that antiviral medication alone (without corticosteroids) and high O2 increase the survival chances of COVID patients.

Anti-inflammatory therapy with nebulized dornase alfa for severe COVID-19 pneumonia: a randomized unblinded trial

Background

Prinflammatory extracellular chromatin from neutrophil extracellular traps (NETs) and other cellular sources is found in COVID-19 patients and may promote pathology. We determined whether pulmonary administration of the endonuclease dornase alfa reduced systemic inflammation by clearing extracellular chromatin.

Methods

Eligible patients were randomized (3:1) to the best available care including dexamethasone (R-BAC) or to BAC with twice-daily nebulized dornase alfa (R-BAC + DA) for seven days or until discharge. A 2:1 ratio of matched contemporary controls (CC-BAC) provided additional comparators. The primary endpoint was the improvement in C-reactive protein (CRP) over time, analyzed using a repeated-measures mixed model, adjusted for baseline factors.

Results

We recruited 39 evaluable participants: 30 randomized to dornase alfa (R-BAC +DA), 9 randomized to BAC (R-BAC), and included 60 CC-BAC participants. Dornase alfa was well tolerated and reduced CRP by 33% compared to the combined BAC groups (T-BAC). Least squares (LS) mean post-dexamethasone CRP fell from 101.9 mg/L to 23.23 mg/L in R-BAC +DA participants versus a 99.5 mg/L to 34.82 mg/L reduction in the T-BAC group at 7 days; p=0.01. The anti-inflammatory effect of dornase alfa was further confirmed with subgroup and sensitivity analyses on randomised participants only, mitigating potential biases associated with the use of CC-BAC participants. Dornase alfa increased live discharge rates by 63% (HR 1.63, 95% CI 1.01-2.61, p=0.03), increased lymphocyte counts (LS mean: 1.08 vs 0.87, p=0.02) and reduced circulating cf-DNA and the coagulopathy marker D-dimer (LS mean: 570.78 vs 1656.96 μg/mL, p=0.004).

Conclusions

Dornase alfa reduces pathogenic inflammation in COVID-19 pneumonia, demonstrating the benefit of cost-effective therapies that target extracellular chromatin.

Funding

LifeArc, Breathing Matters, The Francis Crick Institute (CRUK, Medical Research Council, Wellcome Trust).

Clinical trial number

NCT04359654.

Magnetic resonance imaging screening for osteonecrosis of the femoral head after coronavirus disease 2019

OBJECTIVES

Systemic steroid administration has been suggested for the treatment of coronavirus disease 2019 (COVID-19), but the occurrence of osteonecrosis of the femoral head (ONFH) was one of the concerns for this treatment. This study aimed to use magnetic resonance imaging (MRI) to assess the incidence of ONFH after the treatment for COVID-19.

METHODS

The study included 41 patients who were hospitalized and treated for pneumonia or other COVID-19-induced diseases. We conducted interviews with these patients regarding hip pain and performed MRI screenings for ONFH. The incidence and timing of ONFH after COVID-19 treatment were investigated.

RESULTS

Of the 41 patients, one died of pneumonia and the remaining patients did not complain of hip pain. MRI screening was performed for 26 patients, and asymptomatic ONFH was detected in one patient (3.8%) whose ONFH appeared 1 month after the COVID-19 infection.

CONCLUSIONS

Our MRI screening of ONFH in post-COVID-19 patients revealed asymptomatic ONFH, which would not have been identified without active screening. Physicians should be aware that ONFH may occur in patients after treating COVID-19.

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.

Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm

It is important to determine the risk for admission to the intensive care unit (ICU) in patients with COVID-19 presenting at the emergency department. Using artificial neural networks, we propose a new Data Ensemble Refinement Greedy Algorithm (DERGA) based on 15 easily accessible hematological indices. A database of 1596 patients with COVID-19 was used; it was divided into 1257 training datasets (80 % of the database) for training the algorithms and 339 testing datasets (20 % of the database) to check the reliability of the algorithms. The optimal combination of hematological indicators that gives the best prediction consists of only four hematological indicators as follows: neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase, ferritin, and albumin. The best prediction corresponds to a particularly high accuracy of 97.12 %. In conclusion, our novel approach provides a robust model based only on basic hematological parameters for predicting the risk for ICU admission and optimize COVID-19 patient management in the clinical practice.

Syndecan-1 as a prognostic biomarker in COVID-19 patients: a retrospective study of a Japanese cohort

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a profound global impact, with millions of confirmed cases and deaths worldwide. While most cases are mild, a subset progresses to severe respiratory complications and death, with factors such as thromboembolism, age, and underlying health conditions increasing the risk. Vascular endothelial damage has been implicated in severe outcomes, but specific biomarkers remain elusive. This study investigated syndecan-1 (SDC-1), a marker of endothelial damage, as a potential prognostic factor for COVID-19, focusing on the Japanese population, which is known for its aging demographics and high prevalence of comorbidities.

METHODS

A multicenter retrospective study of COVID-19 patients in Fukushima Prefecture in Japan who were admitted between February 2020 and August 2021 was conducted. SDC-1 levels were measured along with other clinical and laboratory parameters. Outcomes including thrombosis, 28-day survival, and disease severity were assessed, and disease severity was categorized according to established guidelines.

RESULTS

SDC-1 levels were correlated with disease severity. Patients who died from COVID-19 had greater SDC-1 levels than survivors, and the area under the receiver operating characteristic curve (AUC) analysis suggested the potential of the SDC-1 level as a predictor of mortality (AUC 0.714). K‒M analysis also revealed a significant difference in survival based on an SDC-1 cutoff of 10.65 ng/mL.

DISCUSSION

This study suggested that SDC-1 may serve as a valuable biomarker for assessing COVID-19 severity and predicting mortality within 28 days of hospitalization, particularly in the Japanese population. However, further investigations are required to assess longitudinal changes in SDC-1 levels, validate its predictive value for long-term survival, and consider its applicability to new viral variants.

CONCLUSIONS

SDC-1 is emerging as a potential biomarker for assessing the severity and life expectancy of COVID-19 in the Japanese population, offering promise for improved risk stratification and patient management in the ongoing fight against the virus.

COVID-19 in three waves in a tertiary referral hospital in Belgium: a comparison of patient characteristics, management, and outcome

PURPOSE

Few studies have compared patient characteristics, clinical management, and outcome of patients with COVID-19 between the different epidemic waves. In this study, we describe patient characteristics, treatment, and outcome of patients admitted for COVID-19 in the Antwerp University Hospital over the first three epidemic waves of 2020-2021.

METHODS

Retrospective observational study of COVID-19 patients in a Belgian tertiary referral hospital. All adult patients with COVID-19, hospitalized between February 29, 2020, and June 30, 2021, were included. Standardized routine medical data was collected from patient records. Risk factors were assessed with multivariable logistic regression.

RESULTS

We included 722 patients, during the first (n = 179), second (n = 347) and third (n = 194) wave. We observed the lowest disease severity at admission during the first wave, and more elderly and comorbid patients during the second wave. Throughout the subsequent waves we observed an increasing use of corticosteroids and high-flow oxygen therapy. In spite of increasing number of complications throughout the subsequent waves, mortality decreased each wave (16.6%,15.6% 11.9% in 1st, 2nd and 3rd wave respectively). C-reactive protein above 150 mg/L was predictive for the need for intensive care unit admission (odds ratio (OR) 3.77, 95% confidence interval (CI) 2.32-6.15). A Charlson comorbidity index ≥ 5 (OR 5.68, 95% CI 2.54-12.70) and interhospital transfers (OR 3.78, 95% CI 2.05-6.98) were associated with a higher mortality.

CONCLUSIONS

We observed a reduction in mortality each wave, despite increasing comorbidity. Evolutions in patient management such as high-flow oxygen therapy on regular wards and corticosteroid use may explain this favorable evolution.

Dysregulated Leukotriene Metabolism in Patients with COVID-19

This study aimed to examine the leukotriene metabolism during COVID-19. In total, 180 participants were included in this study, of which 60 were healthy controls, 60 required intensive care units (ICU), and 60 did not require intensive care (non-ICU). The serum levels of 5-lipoxygenase (5-LO), 5-LO activating protein (ALOX5AP), and cysteinyl leukotriene (CYSLT) were measured, and the mRNA expression levels of 5-LO, ALOX5AP, and cysteinyl leukotriene receptor 1 (CYSLTR1) were investigated. Compared with the control group, both the non-ICU and ICU groups had lower levels of 5-LO and mRNA expression. ICU patients had lower levels of 5-LO and mRNA expression than non-ICU patients. CYSLTR1 mRNA expression was highest in the ICU group, followed by the non-ICU group, and healthy controls had the lowest mRNA expression levels. CYSLT levels were higher in the control group than in the non-ICU and ICU groups. CYSLTR1 expression was higher in patients than in controls; therefore, selective leukotriene receptor blockers can be used as treatment options. CYSLTR1 expression was higher in the ICU group than in the non-ICU group. Furthermore, CYSLTR1 mRNA expression may be a promising biomarker of COVID-19 severity.

Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

Effect of Immunosuppression on the Immune Response to SARS-CoV-2 Infection and Vaccination

Immunosuppressive treatment in patients with rheumatic diseases can maintain disease remission but also increase risk of infection. Their response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is frequently blunted. In this study we evaluated the effect of immunosuppression exposure on humoral and T cell immune responses to SARS-CoV-2 infection and vaccination in two distinct cohorts of patients; one during acute SARS-CoV-2 infection and 3 months later during convalescence, and another prior to SARS-CoV-2 vaccination, with follow up sampling 6 weeks after vaccination. Results were compared between rituximab-exposed (in previous 6 months), immunosuppression-exposed (in previous 3 months), and non-immunosuppressed groups. The immune cell phenotype was defined by flow cytometry and ELISA. Antigen specific T cell responses were estimated using a whole blood stimulation interferon-γ release assay. A focused post-vaccine assessment of rituximab-treated patients using high dimensional spectral cytometry was conducted. Acute SARS-CoV-2 infection was characterised by T cell lymphopenia, and a reduction in NK cells and naïve CD4 and CD8 cells, without any significant differences between immunosuppressed and non-immunosuppressed patient groups. Conversely, activated CD4 and CD8 cell counts increased in non-immunosuppressed patients with acute SARS-CoV-2 infection but this response was blunted in the presence of immunosuppression. In rituximab-treated patients, antigen-specific T cell responses were preserved in SARS-CoV-2 vaccination, but patients were unable to mount an appropriate humoral response.

Logistic regression analysis of the value of biomarkers, clinical symptoms, and imaging examinations in COVID-19 for SARS-CoV-2 nucleic acid detection

The detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) nucleic acid detection provides a direct basis for diagnosing Coronavirus Disease 2019. However, nucleic acid test false-negative results are common in practice and may lead to missed diagnosis. Certain biomarkers, clinical symptoms, and imaging examinations are related to SARS-CoV-2 nucleic acid detection and potential predictors. We examined nucleic acid test results, biomarkers, clinical symptoms, and imaging examination data for 116 confirmed cases and asymptomatic infections in Zhuhai, China. Patients were divided into nucleic acid-positive and -false-negative groups. Predictive values of biomarkers, symptoms, and imaging for the nucleic acid-positive rate were calculated by Least Absolute Shrinkage and Selection Operators regression analysis and binary logistic regression analysis, and areas under the curve of these indicators were calculated. Hemoglobin (OR = 1.018, 95% CI: 1.006-1.030; P = .004) was higher in the respiratory tract-positive group than the nucleic acid-negative group, but platelets (OR = 0.996, 95% CI: 0.993-0.999; P = .021) and eosinophils (OR = 0.013, 95% CI: 0.001-0.253; P = .004) were lower; areas under the curve were 0.563, 0.614, and 0.642, respectively. Some biomarkers can predict SARS-CoV-2 viral nucleic acid detection rates in Coronavirus Disease 2019 and are potential auxiliary diagnostic tests.

Prediction of acute lung injury assessed by chest computed tomography, oxygen saturation/fraction of inspired oxygen ratio, and serum lactate dehydrogenase in patients with COVID-19

INTRODUCTION

In treating acute hypoxemic respiratory failure (AHRF) caused by coronavirus disease 2019 (COVID-19), clinicians choose respiratory therapies such as low-flow nasal cannula oxygenation, high-flow nasal cannula oxygenation, or mechanical ventilation after assessment of the patient's condition. Chest computed tomography (CT) imaging contributes significantly to diagnosing COVID-19 pneumonia. However, the costs and potential harm to patients from radiation exposure need to be considered. This study was performed to predict the quantitative extent of COVID-19 acute lung injury using clinical indicators such as an oxygenation index and blood test results.

METHODS

We analyzed data from 192 patients with COVID-19 AHRF. Multiple logistic regression was used to determine correlations between the lung infiltration volume (LIV) and other pathophysiological or biochemical laboratory parameters.

RESULTS

Among 13 clinical parameters, we identified the oxygen saturation/fraction of inspired oxygen ratio (SF ratio) and serum lactate dehydrogenase (LD) concentration as factors associated with the LIV. In the binary classification of an LIV of ≥20 % or not and with the borderline LD = 2.2 × [SF ratio]-182.4, the accuracy, precision, diagnostic odds ratio, and area under the summary receiver operating characteristic curve were 0.828, 0.818, 23.400, and 0.870, respectively.

CONCLUSIONS

These data suggest that acute lung injury due to COVID-19 pneumonia can be estimated using the SF ratio and LD concentration without a CT scan. These findings may provide significant clinical benefit by allowing clinicians to predict acute lung injury levels using simple, minimally invasive assessment of oxygenation capacity and biochemical blood tests.

Coronavirus disease 19 (Covid-19): A comparative study of pattern of liver injury in adult patients in different waves of Covid-19 infection

BACKGROUND AND STUDY AIMS

Liver dysfunction is a common manifestation of the COVID-19 infection. We aimed to study transaminase abnormalities through different waves of COVID-19 and their relations to disease severity or mortality.

PATIENTS AND METHODS

A retrospective study included 521 Egyptian patients diagnosed with COVID-19. Data was retrieved from the medical records of patients who were admitted from April 2020 to October 2021 in Kasr Al-Ainy Hospitals, Cairo University, with categorization according to disease severity in correspondence to the four waves.

RESULTS

The median age was lower in the first wave compared to other waves, with male predominance across all waves. The most commonly encountered comorbidity overall was hypertension, followed by diabetes mellitus. White blood cells, ferritin, and interleukin-6 showed the highest median values in the second wave, with significantly higher median C-reactive protein on day 1 in the first wave. Forty percent of the patients showed elevated hepatic transaminases on admission in four waves, with no statistically significant difference between waves. On day 5, around half of the patients had elevated transaminases, with no significant difference between waves. Most CT findings were of moderate severity. Clinical severity was higher in the second wave. It was observed that the higher the disease severity, the greater the proportion of patients with elevated hepatic transaminases. The mortality rate was markedly high in cases who had elevated ALT or AST on day 5. The association between elevated enzymes on admission and mortality was seen in the first wave only, with a fatality rate of 22.5% in cases with increased baseline ALT and AST versus 5% in those with normal baseline enzymes.

CONCLUSION

There was no significant difference in transaminases between the four waves. Elevated transaminases were positively associated with increased mortality and severity, reflecting their prognostic value.

Deregulated expression of autophagy genes; PIK3C3 and RAB7A in COVID-19 patients

BACKGROUND

The role of autophagy in coronaviruses infection and replication has a lot of debate. Autophagy involves the catalytic breakdown of intracellular components to be subsequently recycled by the lysosome. The aim of the study was to evaluate autophagy genes; PIK3C3 and RAB7A expressions in COVID-19 patients, and identify if PIK3C3 and RAB7A can be used as markers for monitoring COVID-19 patients.

METHODS

A case-control study was carried out on 50 patients and 50 healthy controls. Genes expression was performed using quantitative real-time polymerase chain reaction.

RESULTS

Compared to controls, PIK3C3 and RAB7A gene expression levels were significantly lower in patients (p < 0.001) with approximately with 9.4 and 2.3 decreased fold in PIK3C3 and RAB7A respectively. The ROC curve of PIK3C3 and RAB7A expressions showed sensitivity of 84 % and 74 % and specificity of 98 % and 78 % respectively. There was a positive correlation between PIK3C3 expression and WBCs, absolute neutrophil count, interleukin-6, D-dimer, and ALT among patients and between RAB7A expression and WBCs, CRP, IL-6, D-dimer and ALT in patients.

CONCLUSIONS

The study showed reduction of PIK3C3 and RAB7A expressions in COVID-19 patients. However, further studies are recommended to clarify their roles in the disease pathogenies as autophagy genes.

Utility of Serum Procalcitonin and Its Clearance in Predicting Outcomes in COVID-19 Patients

Introduction Identification of coronavirus disease 2019 (COVID-19) patients at risk of worse clinical outcomes is crucial to improving patient care. Various biochemical markers have been used to predict outcomes in such patients. We aimed to evaluate the role of serum PCT (procalcitonin) and the utility of PCT clearance (PCTc) in predicting the outcome of patients with COVID-19 illness. Methods We prospectively included 39 patients with severe or critical COVID-19 illness with an age equal to more than 18 years. In addition to routine baseline investigations, serum PCT was measured at admission (PCT1) and day 5 of hospitalization (PCT2). PCTc was calculated using the formula [Formula: see text]. Results We observed that serum PCT at admission was significantly higher in non-survivors (median: 1.9 ng/ml IQR: 0.51-4.23) compared to survivors (median 0.35 (IQR: 0.1-1.2), p 0.002). On serial serum-PCT estimation, non-survivors had persistently elevated serum-PCT (median PCT1:1.9 ng/ml (IQR: 0.51-4.23) to median PCT2: 1.9ng/ml (IQR: 0.83-2.72), p 0.51) than survivors (median PCT1:0.35ng/ml (IQR: 0.1-1.19) to median PCT2: 0.15ng/ml (IQR: 0.05-0.29), p 0.01). However, no difference in serum PCTc was observed between the two groups (median: 35.3% (IQR: 12.5-84.9) in survivors vs. 71.7% (33.3-91.7) in non-survivors, p = 0.165). Conclusion Serum PCT is a potential biochemical marker that could predict outcomes in COVID-19 patients. Measurement of serial serum PCT and estimation of PCT clearance may serve as better predictors than a single value; however, well-designed studies are required to identify the definite role of serum PCT in COVID-19 patients of varying severity.

Characteristics, Outcomes, and Associations of Venous Thromboembolism in Diabetic Patients Infected With COVID-19 in Riyadh, Saudi Arabia

Background The associations and risk factors for venous thromboembolism (VTE) among hospitalized COVID-19 patients remain ambiguous in the literature, with some conflicting findings, especially in Saudi Arabia. In this study, we aim to elaborate on these data by examining regional patient populations and exploring the incidence, lab findings, and outcomes of VTE among hospitalized COVID-19 patients known to have diabetes mellitus (DM). Methodology This cross-sectional study was conducted at King Abdulaziz Medical City in Riyadh. The BestCare system was used to collect patients' data between September 2020 and February 2022. JMP15 was used for data analysis. Frequencies and percentages were used for categorical data, and median and interquartile ranges were used for quantitative data. The chi-square and Kruskal-Wallis rank-sum tests were used to assess the difference between categorical and quantitative variables, respectively. Nominal logistical regression was used to assess diabetes as a risk factor for developing VTE among COVID-19 patients. Results Data from 153 admitted patients were collected after they satisfied the inclusion criteria. Of these patients, 39 (25.49%) developed VTE. The demographic data included age group, gender, and DM status presented as frequencies and percentages. Through bivariate analysis, patients with longer hospital stays had at least one episode of VTE (p = 0.0072). Using nominal logistic regression analysis, diabetes as a risk factor (odds ratio = 4.11, confidence interval = 0.955-5.05, p = 0.0287) was significantly associated with the development of VTE in COVID-19 patients. Conclusions Based on our study, diabetes proved significant when evaluating the possible factors regarding VTE development in COVID-19 patients. In addition, the length of stay also played a critical role in the severity of VTE in COVID-19 patients. Similar studies should be conducted on a national scale in Saudi Arabia to accomplish two goals: first, to gain further understanding of the impact of the variables investigated in our population, and second, to publish data that are more generalizable to the larger population of Saudi Arabia.

Development and validation of machine learning-based models for predicting healthcare-associated bacterial/fungal infections among COVID-19 inpatients: a retrospective cohort study

BACKGROUND

COVID-19 and bacterial/fungal coinfections have posed significant challenges to human health. However, there is a lack of good tools for predicting coinfection risk to aid clinical work.

OBJECTIVE

We aimed to investigate the risk factors for bacterial/fungal coinfection among COVID-19 patients and to develop machine learning models to estimate the risk of coinfection.

METHODS

In this retrospective cohort study, we enrolled adult inpatients confirmed with COVID-19 in a tertiary hospital between January 1 and July 31, 2023, in China and collected baseline information at admission. All the data were randomly divided into a training set and a testing set at a ratio of 7:3. We developed the generalized linear and random forest models for coinfections in the training set and assessed the performance of the models in the testing set. Decision curve analysis was performed to evaluate the clinical applicability.

RESULTS

A total of 1244 patients were included in the training cohort with 62 healthcare-associated bacterial/fungal infections, while 534 were included in the testing cohort with 22 infections. We found that patients with comorbidities (diabetes, neurological disease) were at greater risk for coinfections than were those without comorbidities (OR = 2.78, 95%CI = 1.61-4.86; OR = 1.93, 95%CI = 1.11-3.35). An indwelling central venous catheter or urinary catheter was also associated with an increased risk (OR = 2.53, 95%CI = 1.39-4.64; OR = 2.28, 95%CI = 1.24-4.27) of coinfections. Patients with PCT > 0.5 ng/ml were 2.03 times (95%CI = 1.41-3.82) more likely to be infected. Interestingly, the risk of coinfection was also greater in patients with an IL-6 concentration < 10 pg/ml (OR = 1.69, 95%CI = 0.97-2.94). Patients with low baseline creatinine levels had a decreased risk of bacterial/fungal coinfections(OR = 0.40, 95%CI = 0.22-0.71). The generalized linear and random forest models demonstrated favorable receiver operating characteristic curves (ROC = 0.87, 95%CI = 0.80-0.94; ROC = 0.88, 95%CI = 0.82-0.93) with high accuracy, sensitivity and specificity of 0.86vs0.75, 0.82vs0.86, 0.87vs0.74, respectively. The corresponding calibration evaluation P statistics were 0.883 and 0.769.

CONCLUSIONS

Our machine learning models achieved strong predictive ability and may be effective clinical decision-support tools for identifying COVID-19 patients at risk for bacterial/fungal coinfection and guiding antibiotic administration. The levels of cytokines, such as IL-6, may affect the status of bacterial/fungal coinfection.

Association of biomarkers with successful ventilatory weaning in COVID-19 patients: an observational study

OBJECTIVE

To evaluate the association of biomarkers with successful ventilatory weaning in COVID-19 patients.

METHODS

An observational, retrospective, and single-center study was conducted between March 2020 and April 2021. C-reactive protein, total lymphocytes, and the neutrophil/lymphocyte ratio were evaluated during attrition and extubation, and the variation in these biomarker values was measured. The primary outcome was successful extubation. ROC curves were drawn to find the best cutoff points for the biomarkers based on sensitivity and specificity. Statistical analysis was performed using logistic regression.

RESULTS

Of the 2,377 patients admitted to the intensive care unit, 458 were included in the analysis, 356 in the Successful Weaning Group and 102 in the Failure Group. The cutoff points found from the ROC curves were -62.4% for C-reactive protein, +45.7% for total lymphocytes, and -32.9% for neutrophil/lymphocyte ratio. These points were significantly associated with greater extubation success. In the multivariate analysis, only C-reactive protein variation remained statistically significant (OR 2.6; 95%CI 1.51 - 4.5; p < 0.001).

CONCLUSION

In this study, a decrease in C-reactive protein levels was associated with successful extubation in COVID-19 patients. Total lymphocytes and the neutrophil/lymphocyte ratio did not maintain the association after multivariate analysis. However, a decrease in C-reactive protein levels should not be used as a sole variable to identify COVID-19 patients suitable for weaning; as in our study, the area under the ROC curve demonstrated poor accuracy in discriminating extubation outcomes, with low sensitivity and specificity.

The effect of COVID-19 vaccination status on all-cause mortality in patients hospitalised with COVID-19 in Hungary during the delta wave of the pandemic

The high mortality of patients with coronavirus disease 2019 (COVID-19) is effectively reduced by vaccination. However, the effect of vaccination on mortality among hospitalised patients is under-researched. Thus, we investigated the effect of a full primary or an additional booster vaccination on in-hospital mortality among patients hospitalised with COVID-19 during the delta wave of the pandemic. This retrospective cohort included all patients (n = 430) admitted with COVID-19 at Semmelweis University Department of Medicine and Oncology in 01/OCT/2021-15/DEC/2021. Logistic regression models were built with COVID-19-associated in-hospital/30 day-mortality as outcome with hierarchical entry of predictors of vaccination, vaccination status, measures of disease severity, and chronic comorbidities. Deceased COVID-19 patients were older and presented more frequently with cardiac complications, chronic kidney disease, and active malignancy, as well as higher levels of inflammatory markers, serum creatinine, and lower albumin compared to surviving patients (all p < 0.05). However, the rates of vaccination were similar (52-55%) in both groups. Based on the fully adjusted model, there was a linear decrease of mortality from no/incomplete vaccination (ref) through full primary (OR 0.69, 95% CI: 0.39-1.23) to booster vaccination (OR 0.31, 95% CI 0.13-0.72, p = 0.006). Although unadjusted mortality was similar among vaccinated and unvaccinated patients, this was explained by differences in comorbidities and disease severity. In adjusted models, a full primary and especially a booster vaccination improved survival of patients hospitalised with COVID-19 during the delta wave of the pandemic. Our findings may improve the quality of patient provider discussions at the time of admission.

Laboratory biomarkers associated with COVID-19 mortality among inpatients in a Peruvian referral hospital

Aim

To evaluate the biochemical and hematological markers associated with the risk of death due to COVID-19 in a clinical cohort with a severe clinical profile.

Methods

A retrospective study was conducted among 215 anonymized inpatient records from the Hospital Nacional Almanzor Aguinaga Asenjo, Peru, between April and June 2020. The association between biomarkers and death due to COVID-19 was assessed using Cox regression, with a multivariable modeling of 1) biochemical and 2) hematological markers. Kaplan-Meier analyses and time-dependent receiver operating characteristic curves were calculated for each associated biomarker (p < 0.05).

Results

Data analysis of 215 inpatient records revealed an overall mortality rate of 51.30% (95% CI 44.70-58.50), a mean age of 63.90 ± 14.10 years, and a median oxygen saturation of 88% (interquartile range 82-92%). The best-fitted biochemical model included higher levels of C-reactive protein (CRP), D-dimer, fibrinogen, urea, and lactate dehydrogenase. Similarly, the best-fitted hematological model included higher absolute neutrophil and prothrombin time, and lower absolute platelet counts. The best area under the curve values in both models were found to be CRP and D-dimer values (>0.74) and the absolute neutrophil count (0.63).

Conclusions

Some specific biochemical markers outperformed hematological markers. Evaluated hematological counts analyzed in multivariable models proved to be better markers and could be useful to discriminate COVID-19 patients at high risk of death.

GDF-15 Levels and Other Laboratory Findings as Predictors of COVID-19 Severity and Mortality: A Pilot Study

Growth differentiation factor 15 (GDF-15) is a stress-induced cytokine associated with acute and chronic inflammatory states. This prospective observational study aimed to investigate the prognostic roles of GDF-15 and routine clinical laboratory parameters in COVID-19 patients. Upon the admission of 95 adult hospitalized COVID-19 patients in Croatia, blood analysis was performed, and medical data were collected. The patients were categorized based on survival, ICU admission, and hospitalization duration. Logistic regression and ROC curve methods were employed for the statistical analysis. Logistic regression revealed two independent predictors of negative outcomes: CURB-65 score (OR = 2.55) and LDH (OR = 1.005); one predictor of ICU admission: LDH (OR = 1.004); and one predictor of prolonged hospitalization: the need for a high-flow nasal cannula (HFNC) upon admission (OR = 4.75). The ROC curve showed diagnostic indicators of negative outcomes: age, CURB-65 score, LDH, and GDF-15. The largest area under the curve (AUC = 0.767, specificity = 65.6, sensitivity = 83.9) was represented by GDF-15, with a cutoff value of 3528 pg/mL. For ICU admission, significant diagnostic indicators were LDH, CRP, and IL-6. Significant diagnostic indicators of prolonged hospitalization were CK, GGT, and oxygenation with an HFNC upon admission. This study reaffirms the significance of the commonly used laboratory parameters and clinical scores in evaluating COVID-19. Additionally, it introduces the potential for a new diagnostic approach and research concerning GDF-15 levels in this widespread disease.

Epidemiology, clinical features and outcomes of hospitalized patients with COVID-19 by vaccination status: a multicenter historical cohort study

INTRODUCTION

COVID-19 disease resulted in over six million deaths worldwide. Although vaccines against SARS-CoV-2 demonstrated efficacy, breakthrough infections became increasingly common. There is still a lack of data regarding the severity and outcomes of COVID-19 among vaccinated compared to unvaccinated individuals.

METHODS

This was a historical cohort study of adult COVID-19 patients hospitalized in five Ascension hospitals in southeast Michigan. Electronic medical records were reviewed. Vaccine information was collected from the Michigan Care Improvement Registry. Data were analyzed using Student's t-test, analysis of variance, the chi-squared test, the Mann-Whitney and Kruskal-Wallis tests, and multivariable logistic regression.

RESULTS

Of 341 patients, the mean age was 57.9 ± 18.3 years, 54.8% (187/341) were female, and 48.7% (166/341) were black/African American. Most patients were unvaccinated, 65.7%, 8.5%, and 25.8% receiving one dose or at least two doses, respectively. Unvaccinated patients were younger than fully vaccinated (p = 0.001) and were more likely to be black/African American (p = 0.002). Fully vaccinated patients were 5.3 times less likely to have severe/critical disease (WHO classification) than unvaccinated patients (p < 0.001) after controlling for age, BMI, race, home steroid use, and serum albumin levels on admission. The case fatality rate in fully vaccinated patients was 3.4% compared to 17.9% in unvaccinated patients (p = 0.003). Unvaccinated patients also had higher rates of complications.

CONCLUSIONS

Patients who were unvaccinated or partially vaccinated had more in-hospital complications, severe disease, and death as compared to fully vaccinated patients. Factors associated with severe COVID-19 disease included advanced age, obesity, low serum albumin, and home steroid use.

Investigation of Serum Endocan Levels in SARS-CoV-2 Patients

Endocan is an endothelial-cell-specific proteoglycan (ESM-1) and has emerged as an endothelial dysfunction and inflammatory marker in recent years. Endocan can be used as a marker of inflammatory endothelial dysfunction in endothelium-dependent disease: cardiovascular disease, sepsis, lung and kidney disease and malignancies. Recent data suggest that endothelial dysfunction is a key mechanism in COVID-19 pathogenesis. Endotheliitis and thrombo-inflammation are associated with severe forms of SARS-CoV-2 infection, and endocan is currently under investigation as a potential diagnostic and prognostic marker. The aim of this study was to determine serum endocan levels in patients with COVID-19 to evaluate the correlation between endocan levels and clinical disease diagnosis and prognosis. This study enrolled 56 patients, divided into three groups depending on disease severity: mild (15), moderate (25) and severe (16). The biochemical, demographic, clinical and imagistic data were collected and evaluated in correlation with the endocan levels. Serum endocan levels were significantly higher in the COVID-19 patients compared to the control group; also, endocan concentration correlated with vaccination status. The results revealed significantly elevated serum endocan levels in COVID-19 patients compared to the control group, with a correlation observed between endocan concentration and vaccination status. These findings suggest that endocan may serve as a novel biomarker for detecting inflammation and endothelial dysfunction risk in COVID-19 patients. There was no significant relationship between serum endocan levels and disease severity or the presence of cardiovascular diseases. Endocan can be considered a novel biomarker for the detection of inflammation and endothelial dysfunction risk in COVID-19 patients.

Evaluation of hematological changes and immune response biomarkers as a prognostic factor in critical patients with COVID-19

COVID-19 disease has been a challenge for health systems worldwide due to its high transmissibility, morbidity, and mortality. Severe COVID-19 is associated with an imbalance in the immune response, resulting in a cytokine storm and a hyperinflammation state. While hematological parameters correlate with prognosis in COVID patients, their predictive value has not been evaluated specifically among those severely ill. Therefore, we aim to evaluate the role of hematological and immune response biomarkers as a prognostic factor in critically ill patients with COVID-19 admitted to the intensive care unit. From May 2020 to July 2021, a retrospective cohort study was conducted in a reference hospital in Manaus, which belongs to the Brazilian public health system. This study was carried out as single-center research. Clinical and laboratory parameters were analyzed to evaluate the association with mortality. We also evaluated the role of neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and C-reactive protein-to-lymphocyte ratio (CLR). We gathered information from medical records, as well as from prescriptions and forms authorizing the use of antimicrobial medications. During the study period, 177 patients were included, with a mean age of 62.58 ± 14.39 years. The overall mortality rate was 61.6%. Age, mechanical ventilation (MV) requirement, leukocytosis, neutrophilia, high c-reactive protein level, NLR, and CLR showed a statistically significant association with mortality in the univariate analysis. In the multivariate logistic regression analysis, only MV (OR 35.687, 95% CI: 11.084-114.898, p< 0.001) and NLR (OR 1.026, 95% CI: 1.003-1.050, p = 0.028) remained statistically associated with the outcome of death (AUC = 0.8096). While the need for mechanical ventilation is a parameter observed throughout the hospital stay, the initial NLR can be a primary risk stratification tool to establish priorities and timely clinical intervention in patients with severe COVID-19 admitted to the ICU.

dCROX and ROX Indices Predict Clinical Outcomes in Patients with COVID-19 Pneumonia Treated with High-Flow Nasal Cannula Oxygen Therapy

Background

High-flow nasal cannula (HFNC) therapy is a common respiratory support in patients with COVID-19 pneumonia. Predictive tools for the evaluation of successful weaning from HFNC therapy for COVID-19 pneumonia have been limited. This study aimed to develop a new predictor for weaning success from HFNC treatment in patients with COVID-19 pneumonia.

Methods

We conducted a retrospective cohort study at Thammasat University Hospital, Thailand. Patients with COVID-19 pneumonia requiring HFNC therapy from April 2020 to September 2021 were included. The ROX index was defined as the ratio of oxygen saturation (SpO2)/fraction of inspired oxygen (FiO2) to respiratory rate. The CROX index was defined as the ratio of C-reactive protein (CRP) to the ROX index. dCROX was defined as the difference in CROX index between 24 hours and 72 hours. Weaning success was defined as the ability to sustain spontaneous breathing after separation from HFNC without any invasive or noninvasive ventilatory support for ≥48 hours or death.

Results

A total of 106 patients (49.1% male) were included. The mean age was 62.1 ± 16.2 years. Baseline SpO2/FiO2 was 276.1 ± 124.8. The rate of HFNC weaning success within 14 days was 61.3%. The best cutoff value of the dCROX index to predict HFNC weaning success was 3.15 with 66.2% sensitivity, 70.7% specificity, and an area under the ROC curve (AUC) of 0.71 (95% CI: 0.59-0.81, p < 0.001). The best cutoff value of the ROX index was 9.13, with 75.4% sensitivity, 78.0% specificity, and an AUC of 0.79 (95% CI: 0.69-0.88, p < 0.001).

Conclusions

ROX index has the highest accuracy for predicting successful weaning from HFNC in patients with COVID-19 pneumonia. dCROX index is the alternative tool for this setting. However, a larger prospective cohort study is needed to verify these indices for determining separation from HFNC therapy. This trial is registered with TCTR20221107004.

Blood urea nitrogen and clinical prognosis in patients with COVID-19: A retrospective study

The aim of this study was to estimate the association between blood urea nitrogen (BUN) and clinical prognosis in patients with COVID-19. A multicenter, retrospective study was conducted in adult patients with COVID-19 in 3 hospitals in Zhenjiang from January 2023 to May 2023. Patients were divided into survival and death group based on whether they survived at day 28. The demographic, comorbidities, and laboratory data were independently collected and analyzed, as well as clinical outcomes. Total 141 patients were enrolled and 23 (16.3%) died within 28 days. Patients who died within 28 days had a higher level of BUN compared with survivors. Bivariate logistic regression analysis showed that BUN was a risk factor for 28-day mortality in patients with COVID-19. ROC curve showed that BUN could predict 28-day mortality of COVID-19 patients (AUC = 0.796, 95%CI: 0.654-0.938, P < .001). When the cutoff value of BUN was 7.37 mmol/L, the sensitivity and specificity were 84.62% and 70.31%. Subgroup analysis demonstrated that hyper-BUN (≥7.37 mmol/L) was associated with increased 28-day mortality among COVID-19 patients. Patients with COVID-19 who died within 28 days had a higher level of BUN, and hyper-BUN (≥7.37 mmol/L) was associated with increased 28-day mortality.

Inflammatory biomarkers predict higher risk of hyperglycemic crises but not outcomes in diabetic patients with COVID-19

Background

Inflammation is a predictor of severe complications in patients with COVID-19 infection under a variety of clinical settings. A few studies suggested that COVID-19 infection was a trigger of hyperglycemic crises including diabetic ketoacidosis (DKA) and/or hyperglycemic hyperosmolar state (HHS). However, the association between inflammation and hyperglycemic crises in diabetic patients with COVID-19 infection is unclear.

Methods

One hundred and twenty-four patients with type 2 diabetes mellitus (T2DM) and COVID-19 infection from January 2023 to March 2023 were retrospectively analyzed. Demographic, clinical, and laboratory data, especially inflammatory markers including white blood cell (WBC), neutrophils, neutrophil-to-lymphocyte ratio (NLR), c-reactive protein (CRP) and procalcitonin (PCT) were collected and compared between patients with or without DKA and/or HHS. Multivariable logistic regression analysis was conducted to explore the association between inflammatory biomarkers and the prevalence of hyperglycemic crises. Patients were followed up 6 months for outcomes.

Results

Among 124 diabetic patients with COVID-19, 9 were diagnosed with DKA or HHS. Comparing COVID-19 without acute diabetic complications (ADC), patients with DKA or HHS showed elevated levels of c-reactive protein (CRP, P=0.0312) and procalcitonin (PCT, P=0.0270). The power of CRP and PCT to discriminate DKA or HHS with the area under the receiver operating characteristics curve (AUROC) were 0.723 and 0.794, respectively. Multivariate logistic regression indicated 1.95-fold and 1.97-fold increased risk of DKA or HHS with 1-unit increment of CRP and PCT, respectively. However, neither CRP nor PCT could predict poor outcomes in diabetic patients with COVID-19.

Conclusion

In this small sample size study, we firstly found that elevated serum CRP and PCT levels increased the risk of hyperglycemic crises in T2DM patients with COVID-19 infection. More study is needed to confirm our findings.

Predicting the Outcome of Patients with Severe COVID-19 with Simple Inflammatory Biomarkers: The Utility of Novel Combined Scores-Results from a European Tertiary/Referral Centre

Background: The clinical significance of combinations of inflammatory biomarkers in severe COVID-19 infection is yet to be proved. Although several studies have evaluated the prognostic value of biomarkers in patients with COVID-19, there are limited data regarding the value of the combination scores that could take full advantage of the prognostic value of several biomarkers and that could account for the heterogeneity of patients with severe COVID-19. We investigated the prognostic value of combination scores of admission values of inflammatory biomarkers in adults with severe COVID-19. Methods: Adults admitted to the Department of Respiratory Medicine of the UHL with severe COVID-19 (April-September 2021, NCT05145751) were included. Demographics, medical history, laboratory tests and outcome (high-flow nasal cannula (HFNC), admission to Intensive Care Unit (ICU) or death) were recorded. The optimal cut-off points of on admission values of C-reactive protein (CRP), CRP to lymphocyte ratio (CLR), lymphocyte to neutrophil ratio (LNR) and derived variation of neutrophil to lymphocyte ratio (dv-NLR (neutrophil/white blood count-lymphocyte)) for the predetermined outcome were defined. Based on the cut-off of CRP, LNR, dv-NLR and CLR, which were found to be predictors for HFNC, 3 scores were defined: CRP and LNR (C-CRP #1), CRP and dv-NLR (C-CRP #2), CRP and CLR (C-CRP #3). Likewise, based on the cut-off of CRP and CLR, which were found to be predictors for death, the score of CRP and CLR (C-CRP #3*) was defined. The combination scores were then classified as: 2 points (both biomarkers elevated); 1 point (one biomarker elevated) and 0 points (normal values). None of the biomarkers was predictive for the ICU admission, so no further analysis was performed. Binomial logistic regression analysis was used to establish the predictive role for each biomarker. Results: One hundred and fifteen patients (60% males, mean age 57.7 years) were included. Thirty-seven (32.2%) patients required HFNC, nine (7.8%) died and eight (7%) were admitted to ICU, respectively. As far as HFNC is concerned, the cut-off point was 3.2 for CRP, 0.231 for LNR, 0.90 for dv-NLR and 0.004 for CLR. Two points of C-CRP #1 and 2 points of C-CRP #3 predicted HFNC with a probability as high as 0.625 (p = 0.005) and 0.561 (p < 0.001), respectively. Moreover, 1 point of C-CRP #2 and 2 points of C-CRP #2 predicted HFNC with a probability of 0.333 and 0.562, respectively. For death, the optimal cut-off point for CRP was 1.11 and for CLR 3.2*1033. Two points of C-CRP #3* with an accuracy of 0.922 predicted mortality (p = 0.0038) in severe COVID-19. Conclusions: The combination scores of CRP and inflammatory biomarkers, based on admission values, are promising predictors for respiratory support using HFNC and for mortality in patients suffering from severe COVID-19 infection.

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

OBJECTIVE

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.

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Evaluation of three common scoring systems in COVID-19 patients: neutrophil-lymphocyte ratio (NLR), The Acute Physiology and Chronic Health Evaluation II (APACHE II), and C-reactive protein (CRP)

Background

As SARS-CoV-2 becomes a major global health, the authors aimed to predict the severity of the disease, the length of hospitalization, and the death rate of COVID-19 patients based on The Acute Physiology and Chronic Health Evaluation II (APACHE II) criteria, neutrophil-lymphocyte ratio (NLR), and C-reactive protein (CRP) levels to prioritize, and use them for special care facilities.

Methods

In a retrospective study, 369 patients with COVID-19 hospitalized in the ICU from March 2021 to April 2022, were evaluated. In addition to the APACHE II score, several of laboratory factors, such as CRP and NLR, were measured.

Results

The values of CRP, NLR, and APACHE II scores were significantly higher in hospitalized and intubated patients, as well as those who died 1 month and 3 months after hospital discharge than those in surviving patients. The baseline NLR levels were the strongest factor that adversely affected death in the hospital, death 1 month and 3 months after discharge, and it was able to predict death, significantly.

Conclusion

CRP, NLR, and APACHE II were all linked to prognostic factors in COVID-19 patients. NLR was a better predictor of disease severity, the need for intubation, and death than the other two scoring tools.