Severity-associated markers and assessment model for predicting the severity of COVID-19: a retrospective study in Hangzhou, China

Vital Signs as Predictors of Oxygen Requirements in COVID-19 Outpatients: The Development of a Streamlined Risk Score

BACKGROUND

With COVID-19 becoming a common disease, primary care facilities such as clinics are required to efficiently triage patients at high risk of severe illness within the constraints of limited medical resources. However, existing COVID-19 severity risk scores require detailed medical history assessments, such as evaluating the severity of pneumonia via chest CT and accounting for past and comorbid conditions. Therefore, they may not be suitable for practical use in clinical settings with limited medical resources, including personnel and equipment.

PURPOSE

 The goal is to identify key variables that predict the need for oxygen therapy in COVID-19 patients and develop a simplified clinical risk score based solely on vital signs to predict oxygen requirements.

PATIENTS AND METHODS

A retrospective observational study of 584 outpatients with COVID-19 confirmed by polymerase chain reaction test visited Sasebo Chuo Hospital between April 28, 2022, and August 18, 2022. Analyses were conducted after adjustment for background factors of age and sex with propensity score matching. We used the Fisher test for nominal variables and the Kruskal-Wallis test for continuous variables.

RESULTS

After adjusting for age and sex, several factors significantly correlated with the need for oxygen within seven days including body temperature (p < 0.001), respiratory rate (p = 0.007), SpO2 (p < 0.001), and the detection of pneumonia on CT scans (p = 0.032). The area under the receiver-operating characteristic curve for the risk score based on these vital signs and CT was 0.947 (95% confidence interval: 0.911-0.982). The risk score based solely on vital signs was 0.937 (0.900-0.974), demonstrating the ability to predict oxygen administration with no significant differences.

CONCLUSIONS

Body temperature, advanced age, increased respiratory rate, decreased SpO2, and the presence of pneumonia on CT scans were significant predictors of oxygen need within seven days among the study participants. The risk score, based solely on vital signs, effectively and simply assesses the likelihood of requiring oxygen therapy within seven days with high accuracy. The risk score, which utilizes only age and vital signs and does not require a detailed patient history or CT scans, could streamline hospital referral processes for admissions.

Illness Experiences of Brazilian People Who Were Hospitalized Due to COVID-19 and Faced Long COVID Repercussions in Their Daily Life: A Constructivist Grounded Theory Study

Long COVID is a multisystem condition that has multiple consequences for the physical, mental, and social health of COVID-19 survivors. The impact of the long COVID condition remains unclear, particularly among middle-aged and older adults, who are at greater risk than younger people of persisting symptoms associated with COVID-19. Therefore, we aimed to understand the experiences of middle-aged and older people who had been hospitalized for COVID-19 and the repercussions of long-term COVID symptoms in their daily lives. A qualitative study was carried out, adopting the framework of the constructivist grounded theory (CGT) proposed by Kathy Charmaz. Fifty-six middle-aged and older adult participants from the southern region of Brazil were recruited. Data were gathered from semi-structured telephone interviews. Concomitantly a comparative analysis was performed to identify categories and codes using the MaxQDA® software (version 2022). Three subcategories were identified: (1) experiencing COVID-19 in the acute phase; (2) oscillating between 'good days' and 'bad days' in long COVID; and (3) (re)constructing identity. These concepts interact with each other and converge upon the central category of this study: recasting oneself to the uniqueness of the illness experience of long COVID. Our findings provided insights related to the disruption in the lives of long COVID-19 sufferers who still live with persistent symptoms of the disease, including physical, social, family, emotional and spiritual repercussions. Likewise, this study may aid in developing friendly and welcoming social environments, lowering stigma and prejudice towards patients with long COVID, and fostering prompt and suitable policy support and mental health care for these individuals.

Hematological and Biochemical Laboratory Parameters in COVID-19 Patients: A Retrospective Modeling Study of Severity and Mortality Predictors

Background

It is well known that laboratory markers could help in identifying risk factors of severe illness and predicting outcomes of diseases. Here, we performed a retrospective modeling study of severity and mortality predictors of hematological and biochemical laboratory parameters in Iranian COVID-19 patients.

Methods

Data were obtained retrospectively from medical records of 564 confirmed Iranian COVID-19 cases. According to the disease severity, the patients were categorized into two groups (severe or nonsevere), and based on the outcome of the disease, patients were divided into two groups (recovered or deceased). Demographic and laboratory data were compared between groups, and statistical analyses were performed to define predictors of disease severity and mortality in the patients.

Results

The study identified a panel of hematological and biochemical markers associated with the severe outcome of COVID-19 and constructed different predictive models for severity and mortality. The disease severity and mortality rate were significantly higher in elderly inpatients, whereas gender was not a determining factor of the clinical outcome. Age-adjusted white blood cells (WBC), platelet cells (PLT), neutrophil-to-lymphocyte ratio (NLR), red blood cells (RBC), hemoglobin (HGB), hematocrit (HCT), erythrocyte sedimentation rate (ESR), mean corpuscular hemoglobin (MCHC), blood urea nitrogen (BUN), and creatinine (Cr) also showed high accuracy in predicting severe cases at the time of hospitalization, and logistic regression analysis suggested grouped hematological parameters (age, WBC, NLR, PLT, HGB, and international normalized ratio (INR)) and biochemical markers (age, BUN, and lactate dehydrogenase (LDH)) as the best models of combined laboratory predictors for severity and mortality.

Conclusion

The findings suggest that a panel of several routine laboratory parameters recorded on admission could be helpful for clinicians to predict and evaluate the risk of disease severity and mortality in COVID-19 patients.

Efficacy of N-acetyl Cysteine in Severe COVID-19 Patients: A Randomized Controlled Phase III Clinical Trial

Background: Today, various drugs have been investigated as the primary or complementary treatment for coronavirus disease 2019 (COVID-19). N-acetylcysteine (NAC) has been used as a mucolytic in pulmonary diseases. This drug apparently contributes to the retrieval of the intracellular antioxidant system. Objectives: This study aimed to determine the efficacy of NAC in severe COVID-19 patients admitted to the intensive care unit (ICU). Methods: This single-blinded randomized controlled phase III clinical trial included 40 patients with confirmed COVID-19 (based on polymerase chain reaction) admitted to the Shahid Mohammadi Hospital’s ICU, Bandar Abbas, Iran, in 2020. All cases had severe COVID-19. They were allocated randomly to two equal groups. Patients in the control group received standard drug therapy based on the treatment protocol of the national COVID-19 committee, while those in the NAC group received a single dose of intravenous NAC (300 mg/kg) upon admission to the ICU in addition to standard drug treatment. Clinical status and laboratory tests were done on admission to the ICU and then 14 days later or at discharge without knowing the patient grouping. Results: The two groups were comparable regarding age, gender, and other baseline laboratory and clinical parameters. At the final evaluation, respiratory rate (21.25 ± 4.67 vs. 27.37 ± 6.99 /min) and D-dimer (186.37 ± 410.23 vs. 1339.04 ± 2183.87 ng/mL) were significantly lower in the NAC group (P = 0.004 and P = 0.030, respectively). Also, a lower percentage of patients in the NAC group had lactate dehydrogenase (LDH) ≤ 245 U/L (0% vs. 25%, P = 0.047). Although the length of ward and ICU stay was shorter in the NAC group than in controls, the difference was statistically insignificant (P = 0.598 and P = 0.629, respectively). Mortality, on the other hand, was 75% in the control group and 50% in the NAC group, with no statistically significant difference (P = 0.102). Concerning the change in the study parameters, only the decrease in diastolic blood pressure (DBP) was significantly higher with NAC (P = 0.042). The intubation and mechanical ventilation rates were higher, while oxygen with mask and nasal oxygen rates were lower with NAC, but the difference was statistically insignificant. Conclusions: Based on the current research, NAC is related to a significant decrease in RR, D-dimer, and DBP in severe COVID-19. Also, LDH was significantly lower in the NAC group than in the controls. More research with larger sample sizes is needed to validate the current study results.

Impaired SARS-CoV-2 specific T-cell response in patients with severe COVID-19

Cellular immune responses are of pivotal importance to understand SARS-CoV-2 pathogenicity. Using an enzyme-linked immunosorbent spot (ELISpot) interferon-γ release assay with wild-type spike, membrane and nucleocapsid peptide pools, we longitudinally characterized functional SARS-CoV-2 specific T-cell responses in a cohort of patients with mild, moderate and severe COVID-19. All patients were included before emergence of the Omicron (B.1.1.529) variant. Our most important finding was an impaired development of early IFN-γ-secreting virus-specific T-cells in severe patients compared to patients with moderate disease, indicating that absence of virus-specific cellular responses in the acute phase may act as a prognostic factor for severe disease. Remarkably, in addition to reactivity against the spike protein, a substantial proportion of the SARS-CoV-2 specific T-cell response was directed against the conserved membrane protein. This may be relevant for diagnostics and vaccine design, especially considering new variants with heavily mutated spike proteins. Our data further strengthen the hypothesis that dysregulated adaptive immunity plays a central role in COVID-19 immunopathogenesis.

Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai

Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.

Platelet-to-lymphocyte ratio and mean platelet volume-to-platelet count ratio for predicting mortality in critical COVID-19 patients

Introduction: Defining the markers that can be used in clinical practice for predicting the mortality of critical patients will be cautionary for taking necessary measures in high-risk cases. Although there are a large number of studies conducted during the pandemic, no mortality marker to predict the prognosis of intensive care unit (ICU) patients with COVID-19 has yet been defined. Platelet indices can be easily evaluated with a complete blood count (CBC) analysis, one of the most accessible tests worldwide. This study aimed to evaluate the role of platelet indices such as mean platelet volume (MPV), platelet distribution width (PDW), plateletcrit (PCT), platelet-to-lymphocyte ratio (PLR), and MPV-to-platelet count ratio (MPV/PLT) in predicting the mortality of ICU patients with COVID-19. Material and Method: This single-center, retrospective, cross-sectional study included 201 critical COVID-19 patients over 18 years of age who were hospitalized in ICU between August 2020 and February 2021. Patients were divided into two groups as survivors and non-survivors. The relationship of MPV, PDW, PCT, PLR, and MPV/PLT parameters evaluated at ICU admission with mortality was investigated. Results: There was no significant difference between the survivor and non-survivor groups in terms of platelet count, MPV, PCT, and PDW. The comparison of the platelet ratios revealed higher PLR and MPV/PLT ratio in the non-survivor group than in the survivor group (p

Remnant cholesterol levels are associated with severity and death in COVID-19 patients

Coronavirus disease-19 (COVID-19) patients with severe complications present comorbidities like cardiovascular-disease, hypertension and type-2 diabetes mellitus (DM), sharing metabolic alterations like insulin resistance (IR) and dyslipidemia. Our objective was to evaluate the association among different components of the lipid-lipoprotein profile, such as remnant lipoprotein (RLP)-cholesterol, in patients with COVID-19, and to analyze their associations with the severity of the disease and death. We studied 193 patients (68 (29-96) years; 49.7% male) hospitalized for COVID-19 and 200 controls (46 (18-79) years; 52.5% male). Lipoprotein profile, glucose and procalcitonin were assessed. Patients presented higher glucose, TG, TG/HDL-cholesterol and RLP-cholesterol levels, but lower total, LDL, HDL and no-HDL-cholesterol levels (p < 0.001). When a binary logistic regression was performed, age, non-HDL-cholesterol, and RLP-cholesterol were associated with death (p = 0.005). As the COVID-19 condition worsened, according to procalcitonin tertiles, a decrease in all the cholesterol fractions (p < 0.03) was observed with no differences in TG, while levels of RLP-cholesterol and TG/HDL-cholesterol increased (p < 0.001). Lower levels of all the cholesterol fractions were related with the presence and severity of COVID-19, except for RLP-cholesterol levels and TG/HDL-cholesterol index. These alterations indicate a lipid metabolic disorder, characteristic of IR states in COVID-19 patients. RLP-cholesterol levels predicted severity and death in these patients.

Gal-3BP in Viral Infections: An Emerging Role in Severe Acute Respiratory Syndrome Coronavirus 2

Galectin-3 binding protein (Gal-3BP) is a multifunctional glycoprotein involved in cell–cell and cell–matrix interactions known to be upregulated in cancer and various viral infections, including HIV-1, HCV, and SARS-CoV-2, with a key role in regulating the antiviral immune response. Studies have identified a direct correlation between circulating levels of Gal-3BP and the severity of disease and/or disease progression for some viral infections, including SARS-CoV-2, suggesting a role of Gal-3BP in these processes. Due to Gal-3BP’s complex biology, the molecular mechanisms underlying its role in viral diseases have been only partially clarified. Gal-3BP induces the expression of interferons (IFNs) and proinflammatory cytokines, including interleukin-6 (IL-6), mainly interacting with galectin-3, targeting the TNF receptor-associated factors (TRAF-6 and TRAF-3) complex, thus having a putative role in the modulation of TGF-β signaling. In addition, an antiviral activity of Gal-3BP has been ascribed to a direct interaction of the protein with virus components. In this review, we explored the role of Gal-3BP in viral infections and the relationship between Gal-3BP upregulation and disease severity and progression, mainly focusing on SARS-CoV-2. Augmented knowledge of Gal-3BP’s role in virus infections can be useful to evaluate its possible use as a prognostic biomarker and as a putative target to block or attenuate severe disease.

Can Lung Imaging Scores and Clinical Variables Predict Severe Course and Fatal Outcome in COVID-19 Pneumonia Patients? A Single-Center Observational Study

COVID-19 prediction models mostly consist of combined clinical features, laboratory parameters, and, less often, chest X-ray (CXR) findings. Our main goal was to propose a prediction model involving imaging methods, specifically ultrasound. This was a single-center, retrospective cohort observational study of patients admitted to the University Hospital Split from November 2020 to May 2021. Imaging protocols were based on the assessment of 14 lung zones for both lung ultrasound (LUS) and computed tomography (CT), correlated to a CXR score assessing 6 lung zones. Prediction models for the necessity of mechanical ventilation (MV) or a lethal outcome were developed by combining imaging, biometric, and biochemical parameters. A total of 255 patients with COVID-19 pneumonia were included in the study. Four independent predictors were added to the regression model for the necessity of MV: LUS score, day of the illness, leukocyte count, and cardiovascular disease (χ2 = 29.16, p < 0.001). The model accurately classified 89.9% of cases. For the lethal outcome, only two independent predictors contributed to the regression model: LUS score and patient’s age (χ2 = 48.56, p < 0.001, 93.2% correctly classified). The predictive model identified four key parameters at patient admission which could predict an adverse outcome.

Prognostic value of albumin-to-globulin ratio in COVID-19 patients: A systematic review and meta-analysis

Background and aims

The albumin-to-globulin ratio (AGR) has been used to predict severity and mortality in infectious diseases. The aim of this study is to evaluate the prognostic value of the AGR in COVID-19 patients.

Methods

A systematic review and meta-analysis were conducted. We included observational studies assessing the association between the AGR values upon hospital admission and severity or all-cause mortality in COVID-19 patients. In the meta-analyses we used random effect models. Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS). The effect measures were expressed as mean difference (MD) and their 95% confidence intervals (CI). We performed Egger's test and funnel plots to assess the publication bias.

Results

The included studies had a total of 11356 patients corresponding to 31 cohort studies. Severe COVID-19 patients had lower AGR values than non-severe COVID-19 patients (mean difference (MD), −0.27; 95% IC, −0.32 to −0.22; p < 0.001; I² = 88%). Non-survivor patients with COVID-19 had lower AGR values than survivor patients (MD, −0.29; 95% IC, −0.35 to −0.24; p < 0.001; I² = 79%). In the sensitivity analysis, we only included studies with low risk of bias, which decreased the heterogeneity for both outcomes (severity, I² = 20%; mortality, I² = 5%).

Conclusions

Low AGR values upon hospital admission were found in COVID-19 patients with a worse prognosis.

Prognostic value of apolipoproteins in COVID-19 patients: A systematic review and meta-analysis

INTRODUCTION

Apolipoproteins are predictive biomarkers for cardiovascular, neoplasms and cerebrovascular diseases and are postulated as prognostic biomarkers in infectious diseases, as COVID-19. Thus, we assessed the prognosis value of apolipoproteins for COVID-19 severity and mortality.

METHODS

We conducted a systematic review and meta-analysis using observational studies that reported the association between apolipoproteins and severity or mortality in COVID-19 patients. Newcastle-Ottawa was used for the quality assessment of included studies. Effects measurements were shown as odds ratios (ORs) with 95% confidence intervals (CIs), and Egger-test was developed for assessing the risk of bias publication.

RESULTS

We analyzed 12 cohort studies (n = 3580). Patients with low ApoliproteinA1 (ApoA1) (OR 0.35; 95%CI 0.24 to 0.49; P < 0.001) and ApoliproteinB (ApoB) (OR = 0.78; 95%CI 0.69 to 0.87; P < 0.001) values had a higher risk of developing severe disease. ApoB/ApoA1 ratio showed no statistically significant association with higher odds of severity. Low ApoA1 levels were associated with higher odds of all-cause mortality (OR = 0.34; 95%CI 0.20 to 0.57; P < 0.001). ApoB values showed no statistically significant association with a high risk of all-cause mortality.

CONCLUSION

We suggest that adequate levels of ApoA1 and ApoB can be a protective factor for severity in COVID-19, and ApoB/ApoA1 ratio did not show predictive utility for severity.