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

Assessment of the Negative Factors for the Clinical Outcome in Patients with SARS-CoV-2 Infection and Type 2 Diabetes Mellitus

Purpose

Patients with diabetes mellitus (DM) are more susceptible to viral and bacterial infections, facing a more severe prognosis and higher mortality rates. The study's main aim was to evaluate the survival and mortality rates of patients with type 2 diabetes (T2DM) and SARS-CoV-2 virus infection alongside the main factors influencing the prognosis.

Patients and Methods

The present study included 186 patients with T2DM and SARS-CoV-2 virus infection admitted to the COVID-19 Department of the "Pius Brînzeu" Emergency Clinical County University Hospital between November 2020 and March 2021. Patients had investigations performed upon arrival in the emergency room and during hospitalization. We analyzed the risk of negative prognosis based on clinical data (oxygen saturation (SatO2), respiratory rate (RR), lung damage), glycemic control (HbA1c, glycemia at hospital admission), and the duration of T2DM.

Results

The mortality rate in the studied group was 36.6%. All deceased patients had previously been diagnosed with hypertension; 95.58% had a body mass index (BMI) greater than 25 kg/m2, and 79.41% presented with cardiovascular disease (CVD). Compared to those who recovered, statistically significant differences were observed in BMI, glycemic levels at admission, glycosylated hemoglobin levels (HbA1c), SatO2, RR, and lung damage. Valid statistically significant predictors for death in T2DM patients with COVID-19 were hyperglycemia at admission > 198mg/dl, HbA1c> 8.6%, and SatO2≤ 87%.

Conclusion

SatO2, glycemia at hospital admission, and HbA1c had the highest sensitivity and specificity to predict the prognosis of T2DM patients with SARS-CoV-2 infection. Glycemic control is essential in the prognosis of patients with DM and COVID-19 infection. The prognosis was worse if other comorbidities were associated, especially hypertension and CVD.

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.

Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital

BACKGROUND

In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact.

MATERIALS AND METHODS

We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network.

RESULTS

We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30-39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%.

CONCLUSION

The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology "Marius Nasta" in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation.

COVID-19 and Laboratory Markers from Romanian Patients-A Narrative Review

COVID-19 has significantly impacted the whole world, and Romania was no exception. Biomarkers play a crucial role in understanding and managing the disease. However, research regarding laboratory analyses for patients with COVID-19 is fairly limited. For detection, PCR testing is still considered the golden standard, while antibodies are still useful for monitoring both patients and their vaccination status. In our country, biomarkers such as CRP, LDH, transaminases, cardiac, and iron markers have been used to assess the status of patients and even predict illness outcome. CRP, IL-6, LDH, FER, fibrinogen, creatinine, and vitamin D levels have been associated with increased severity, risk of ICU admission, and death. Cardiac markers and D-dimers are also good predictors, but their role seems more important in patients with complications. HDL cholesterol and BUN levels were also suggested as potential biomarkers. Hematological issues in SARS-CoV-2 infections include neutrophilia, lymphopenia and their ratio, while PCT, which is a marker of bacterial infections, is better to be used in patients with co- or supra-infections. The current research is a narrative review that focuses on the laboratory results of Romanian COVID-19 patients. The goal of this article is to provide an update on the research on biomarkers and other laboratory tests conducted inside the borders of Romania and identify gaps in this regard. Secondly, options for further research are discussed and encouraged.

Systemic inflammation index, disease severity, and mortality in patients with COVID-19: a systematic review and meta-analysis

Introduction

An excessive systemic pro-inflammatory state increases the risk of severe disease and mortality in patients with coronavirus disease 2019 (COVID-19). However, there is uncertainty regarding whether specific biomarkers of inflammation can enhance risk stratification in this group. We conducted a systematic review and meta-analysis to investigate an emerging biomarker of systemic inflammation derived from routine hematological parameters, the systemic inflammation index (SII), in COVID-19 patients with different disease severity and survival status.

Methods

A systematic literature search was conducted in PubMed, Web of Science, and Scopus, between the 1st of December 2019 and the 15th of March 2023. Risk of bias and certainty of evidence were assessed using the Joanna Briggs Institute Critical Appraisal Checklist and the Grades of Recommendation, Assessment, Development and Evaluation, respectively (PROSPERO registration number: CRD42023420517).

Results

In 39 studies, patients with a severe disease or non-survivor status had significantly higher SII values on admission compared to patients with a non-severe disease or survivor status (standard mean difference (SMD)=0.91, 95% CI 0.75 to 1.06, p<0.001; moderate certainty of evidence). The SII was also significantly associated with the risk of severe disease or death in 10 studies reporting odds ratios (1.007, 95% CI 1.001 to 1.014, p=0.032; very low certainty of evidence) and in six studies reporting hazard ratios (1.99, 95% CI 1.01 to 3.92, p=0.047; very low certainty of evidence). Pooled sensitivity, specificity, and area under the curve for severe disease or mortality were 0.71 (95% CI 0.67 to 0.75), 0.71 (95% CI 0.64 to 0.77), and 0.77 (95% CI 0.73 to 0.80), respectively. In meta-regression, significant correlations were observed between the SMD and albumin, lactate dehydrogenase, creatinine, and D-dimer.

Discussion

Our systematic review and meta-analysis has shown that the SII on admission is significantly associated with severe disease and mortality in patients with COVID-19. Therefore, this inflammatory biomarker derived from routine haematological parameters can be helpful for early risk stratification in this group.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420517.

Advances in Alpha Herpes Viruses Vaccines for Human

Alpha herpes simplex viruses are an important public health problem affecting all age groups. It can produce from common cold sores and chicken pox to severe conditions like encephalitis or newborn mortality. Although all three subtypes of alpha herpes viruses have a similar structure, the produced pathology differs, and at the same time, the available prevention measures, such as vaccination. While there is an available and efficient vaccine for the varicella-zoster virus, for herpes simplex virus 1 and 2, after multiple approaches from trivalent subunit vaccine to next-generation live-attenuated virus vaccines and bioinformatic studies, there is still no vaccine available. Although there are multiple failed approaches in present studies, there are also a few promising attempts; for example, the trivalent vaccine containing herpes simplex virus type 2 (HSV-2) glycoproteins C, D, and E (gC2, gD2, gE2) produced in baculovirus was able to protect guinea pigs against vaginal infection and proved to cross-protect against HSV-1. Another promising vaccine is the multivalent DNA vaccine, SL-V20, tested in a mouse model, which lowered the clinical signs of infection and produced efficient viral eradication against vaginal HSV-2. Promising approaches have emerged after the COVID-19 pandemic, and a possible nucleoside-modified mRNA vaccine could be the next step. All the approaches until now have not led to a successful vaccine that could be easy to administer and, at the same time, offer antibodies for a long period.

SARS-CoV-2 Infection Anxiety, Knowledge and Attitudes in University Degree Pregnant Women from Romania-A Cross-Sectional Observational Survey in the First Two Pandemic Years

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic had a high economic cost, morbidity, and death toll. Due to high rates of mortality and morbidity from coronavirus disease 2019 (COVID-19), pregnant women were at particular risk during this pandemic. We designed and conducted a cross-sectional observational survey in Romanian pregnant women to evaluate the outcome of the SARS-CoV-2 pandemic along with the preventive measures taken by authorities. We applied a 43-item questionnaire. We included 147 women over 18 years old from Romania who were pregnant or gave birth between March 2020 and March 2022. All pregnancies were monitored, most of them by a gynecologist, and only 23% faced rescheduled pregnancy visits. The majority (84%) were screened through the TORCH panel, 95.91% felt anxious because of the pandemic, 87% followed SARS-CoV2 preventive recommendations, and 82% were not infected with the coronavirus. Additionally, 80% were vaccinated against COVID-19. They felt the consequences of the pandemic through anxiety, and their level of anxiety influenced their vaccination decisions, the TORCH testing and the method of giving birth despite the level of education. Fortunately, their pregnancies were monitored properly, and there were no consequences noticed for fetuses at birth.

Prognostic Nutritional Index, Controlling Nutritional Status (CONUT) Score, and Inflammatory Biomarkers as Predictors of Deep Vein Thrombosis, Acute Pulmonary Embolism, and Mortality in COVID-19 Patients

Background: Numerous tools, including nutritional and inflammatory markers, have been evaluated as the predictors of poor outcomes in COVID-19 patients. This study aims to verify the predictive role of the prognostic nutritional index (PNI), CONUT Score, and inflammatory markers (monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in cases of deep vein thrombosis (DVT) and acute pulmonary embolism (APE) risk, as well as mortality, in COVID-19 patients. Methods: The present study was designed as an observational, analytical, retrospective cohort study, and included 899 patients over the age of 18 who had a COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and were admitted to the County Emergency Clinical Hospital and Modular Intensive Care Unit of UMFST “George Emil Palade” of Targu Mures, Romania between January 2020 and March 20212. Results: Non-Surviving patients were associated with a higher incidence of chronic kidney disease (p = 0.01), cardiovascular disease (atrial fibrillation (AF) p = 0.01; myocardial infarction (MI) p = 0.02; peripheral arterial disease (PAD) p = 0.0003), malignancy (p = 0.0001), tobacco (p = 0.0001), obesity (p = 0.01), dyslipidemia (p = 0.004), and malnutrition (p < 0.0001). Multivariate analysis showed that both nutritional and inflammatory markers had a high baseline value and were all independent predictors of adverse outcomes for all enrolled patients (for all p < 0.0001). The presence of PAD, malignancy, and tobacco, were also independent predictors of all outcomes. Conclusions: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, CONUT Score, and lower PNI values at admission strongly predict DVT risk, APE risk, and mortality in COVID-19 patients. Moreover, PAD, malignancy, and tobacco, all predicted all outcomes, while CKD predicts APE risk and mortality, but not the DVT risk.

Carotid Plaque Features and Inflammatory Biomarkers as Predictors of Restenosis and Mortality Following Carotid Endarterectomy

BACKGROUND

Carotid endarterectomy (CEA) is the first-line surgical intervention for cases of severe carotid stenoses. Unfortunately, the restenosis rate is high after CEA. This study aims to demonstrate the predictive role of carotid plaque features and inflammatory biomarkers (monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in carotid restenosis and mortality at 12 months following CEA.

METHODS

The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with a minimum of 70% carotid stenosis and surgical indications for CEA admitted to the Vascular Surgery Clinic, Emergency County Hospital of Targu Mures, Romania between 2018 and 2021.

RESULTS

According to our results, the high pre-operative values of inflammatory biomarkers-MLR (OR: 10.37 and OR: 6.11; p < 0.001), NLR (OR: 34.22 and OR: 37.62; p < 0.001), PLR (OR: 12.02 and OR: 16.06; p < 0.001), SII (OR: 18.11 and OR: 31.70; p < 0.001), SIRI (OR: 16.64 and OR: 9.89; p < 0.001), and AISI (OR: 16.80 and OR: 8.24; p < 0.001)-are strong independent factors predicting the risk of 12-month restenosis and mortality following CEA. Moreover, unstable plaque (OR: 2.83, p < 0.001 and OR: 2.40, p = 0.04) and MI (OR: 3.16, p < 0.001 and OR: 2.83, p = 0.005) were independent predictors of all outcomes. Furthermore, AH (OR: 2.30; p = 0.006), AF (OR: 1.74; p = 0.02), tobacco (OR: 2.25; p < 0.001), obesity (OR: 1.90; p = 0.02), and thrombotic plaques (OR: 2.77; p < 0.001) were all independent predictors of restenosis, but not for mortality in all patients. In contrast, antiplatelet (OR: 0.46; p = 0.004), statin (OR: 0.59; p = 0.04), and ezetimibe (OR:0.45; p = 0.03) therapy were protective factors against restenosis, but not for mortality.

CONCLUSIONS

Our data revealed that higher preoperative inflammatory biomarker values highly predict 12-month restenosis and mortality following CEA. Furthermore, age above 70, unstable plaque, cardiovascular disease, and dyslipidemia were risk factors for all outcomes. Additionally, AH, AF, smoking, and obesity were all independent predictors of restenosis but not of mortality in all patients. Antiplatelet and statin medication, on the other hand, were protective against restenosis but not against mortality.

Inflammatory Biomarkers as Prognostic Factors of Acute Deep Vein Thrombosis Following the Total Knee Arthroplasty

Background and objectives: Deep vein thrombosis (DVT) is one of the most serious post-operative complications in the case of total knee arthroplasty (TKA). This study aims to verify the predictive role of inflammatory biomarkers [monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)] in acute DVT following TKA. Materials and methods: The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with surgical indications for TKA, admitted to the Department of Orthopedics, Regina Maria Health Network, Targu Mures, Romania, and the Department of Orthopedics, Humanitas MedLife Hospital, Cluj-Napoca, Romania between January 2017 and July 2022. The primary endpoint was the risk of acute DVT following the TKA, and the secondary endpoint was the length of hospital stay, and the outcomes were stratified for the baseline’s optimal MLR, NLR, PLR, SII, SIRI, and AISI cut-off value. Results: DVT patients were associated with higher age (p = 0.01), higher incidence of cardiac disease [arterial hypertension (p = 0.02), atrial fibrillation (p = 0.01)], malignancy (p = 0.005), as well as risk factors [smoking (p = 0.03) and obesity (p = 0.02)]. Multivariate analysis showed a high baseline value for all hematological ratios: MLR (OR: 11.06; p < 0.001), NLR (OR: 10.15; p < 0.001), PLR (OR: 12.31; p < 0.001), SII (OR: 18.87; p < 0.001), SIRI (OR: 10.86; p < 0.001), and AISI (OR: 14.05; p < 0.001) was an independent predictor of DVT after TKA for all recruited patients. Moreover, age above 70 (OR: 2.96; p = 0.007), AH (OR: 2.93; p = 0.02), AF (OR: 2.71; p = 0.01), malignancy (OR: 3.98; p = 0.002), obesity (OR: 2.34; p = 0.04), and tobacco (OR: 2.30; p = 0.04) were all independent predictors of DVT risk. Conclusions: Higher pre-operative hematological ratios MLR, NLR, PLR, SII, SIRI, and AISI values determined before operations strongly predict acute DVT following TKA. Moreover, age over 70, malignancy, cardiovascular disease, and risk factors such as obesity and tobacco were predictive risk factors for acute DVT.