Unveiling COVID-19 Secrets: Harnessing Cytokines as Powerful Biomarkers for Diagnosis and Predicting Severity.

Introduction: In coronavirus disease (COVID-19), inflammation takes center stage, with a cascade of cytokines released, contributing to both inflammation and lung damage. The objective of this study is to identify biomarkers for diagnosing and predicting the severity of COVID-19. Materials and Methods: Cytokine levels were determined in the serum from venous blood samples collected from 100 patients with COVID-19 and 50 healthy controls. COVID-19 patients classified based on the Modified Early Warning (MEWS) score. Cytokine concentrations were determined with a multiplex ELISA kit (Bio-Plex Pro™ Human Cytokine Screening Panel). Results: The concentrations of all analyzed cytokines were elevated in the serum of COVID-19 patients relative to the control group, but no significant differences were observed in interleukin-9 (IL-9) and IL-12 p70 levels. In addition, the concentrations of IL-1α, IL-1ß, IL-1ra, IL-2Rα, IL-6, IL-12 p40, IL-18, and tumor necrosis factor alpha (TNFα) were significantly higher in symptomatic patients with accompanying pneumonia without respiratory failure (stage 2) than in asymptomatic/mildly symptomatic patients (stage 1). Conclusion: The study revealed that IL-1ra, IL-2Rα, IL-6, IL-8, IL-12 p40, IL-16, and IL-18 levels serve as potential diagnostic biomarkers in COVID-19 patients. Furthermore, elevated IL-1α levels proved to be valuable in assessing the severity of COVID-19.

Evaluation of an adjusted MEWS (Modified Early Warning Score) for COVID-19 patients to identify risk of ICU admission or death in the Kingdom of Bahrain.

BACKGROUND: While most COVID-19 cases have uncomplicated infection, a small proportion has the potential to develop life-threatening disease, as such development of a prediction tool using patients baseline characteristics at the time of diagnosis should aid in early identification of high-risk groups and devise pertinent management. Hence, we set up this retrospective study to determine preadmission triaging tool to predict the development of severe COVID-19 in the Kingdom of Bahrain MATERIALS AND METHODS: A retrospective study was conducted from 1 September 2020 to 30 November 2020 with enrolment of all SARS-CoV-2 PCR-confirmed persons aged ≥ 14 years who attended Al-Shamil Field Hospital (SFH) in the Kingdom of Bahrain for triaging and assessment with recording of the following parameters: systolic blood pressure, heart rate, respiratory rate, temperature, the alert, verbal, pain, unresponsive neurological score, age, oxygen saturation, comorbidities, Body Mass Index (BMI), duration of symptoms and living with immunocompromised populations to develop our local adjusted MEWS as predictor for ICU admission & for consideration of suitable isolation at home. Follow up data of all patients was obtained from the electronic medical records system including CXR findings, treatments/medications received, need of oxygen supplements /intubation, needs of ICU care, and the outcome (death /discharged alive) IBM SPSS statistic version 21 program was used for data analysis. RESULTS: Our study showed that using the locally developed adjusted MEWS score, there was an significant association between high value of this adjusted MEWS score and abnormal radiographic finding (49.7 % Vs. 17 % for patients with high score Vs. those with low score respectively). Out of the 181 patients with high scores on adjusted MEWS; 38.7 % required oxygen via nasal cannula, 14.4 % required face mask and 8.3 % non-rebreather mask; this proportion was significantly higher than their counterpart patients who score low on adjusted MEWS (20.9 %, 7.7 %, 4.8 %respectively) with statistically significance difference between the two groups (p value of 0.00, 0.00,.004 respectively) Requirement of ICU admission was significantly higher among patients with high score in comparison to those with low score (14.4 % vs. 3 %) with significant p value (0.00) But higher score value was not associated significantly with increase mortality rate among COVID patients. CONCLUSION: Development of our new Adjusted MEWS score system by adding the additional elements of age, oxygen saturation, comorbidities, Body Mass Index (BMI) and duration of symptoms found to be very useful predictor tool for preadmission triaging of COVID patients based on their risk assessment to help clinician to decide on the appropriate placement to different level of isolation facilities.

Clinical Study of a New Modified Early Warning Scoring System for Rapidly Evaluating Shock in Adults.

BACKGROUND: Shock is one of the most common severe syndromes requiring emergency treatment. Acute myocardial infarction guidelines, the surviving sepsis campaign, and low blood volume resuscitation guidelines indicate the prioritization of early identification of shock. APACHE II (Acute Physiology and Chronic Health Evaluation II), SOFA (Sequential Organ Failure Assessment), and MEWS (Modified Early Warning System) scores are used to predict mortality in ICU (intensive care unit) patients. However, similar to APACHE II, SOFA cannot be used for rapid assessment. Hence the need for a new scoring system that is simple, faster, and efficacious in predicting and preventing mortality among shock patients. The present study was conducted to evaluate a new MEWS scoring system for early identification and estimate mortality risk in patients with shock. METHODS: A total of 170 patients with shock meeting the inclusion criteria who presented to the ICU of Ramaiah Hospitals from November 2019 to August 2021 were included in the study. Baseline variables, laboratory parameters, APACHE II score, SOFA score, MEWS score, and new MEWS score were compared between the two groups. Patients were followed up till mortality or discharge from ICU. RESULTS: Among the 170 patients included in the study septic shock (69.4%) was the most common type of shock followed by cardiogenic (7.64%) and hypovolemic shock (7.64%). The requirement of inotropic support and mechanical ventilation was associated with significantly higher mortality (55.6% and 52.6% respectively). The AUROC (area under the curve) for SOFA in predicting mortality was 0.738 (p<0.001). The AUROC for APACHE II score in predicting mortality was 0.758 (p<0.001). The AUROC for MEWS score in predicting mortality was 0.655 (p=0.0002). The AUROC for the new MEWS score in predicting mortality was 0.684 which is more than that of the conventional MEWS score (p <0.001). CONCLUSION: New MEWS score is better than the MEWS score in predicting mortality. The new MEWS score is a simple, entirely clinical, inexpensive scoring system that can be done within a short time as a patient contact in an emergency. Hence, the new MEWS score can help in the quick identification of patients who are at high risk for developing shock and can be used as a better predictor of mortality.

Changes in chemokine and growth factor levels may be useful biomarkers for monitoring disease severity in COVID-19 patients; a pilot study.

Aim: The aim of the present study was to assess differences in the serum levels of chemokines and growth factors (GFs) between COVID-19 patients and healthy controls. The diagnostic utility of the analyzed proteins for monitoring the severity of the SARS-CoV- 2 infection based on the patients' MEWS scores was also assessed. Materials and methods: The serum levels of chemokines and growth factors were analyzed in hospitalized COVID-19 patients (50 women, 50 men) with the use of the Bio-Plex Pro™ Human Cytokine Screening Panel (Biorad) and the Bio-Plex Multiplex system. Results: The study demonstrated that serum levels of MIP-1α, RANTES, Eotaxin, CTACK, GRO-α, IP-10, MIG, basic-FGF, HGF, SCGF-ß, G-CSF, M-CSF, SCF, MIF, LIF, and TRAIL were significant higher in COVID-19 patients than in the control group. The concentrations of CTACK, GRO-α, IP-10, MIG, basic-FGF, HGF, PDGF- BB, GM-CSF, SCF, LIF, and TRAIL were higher in asymptomatic/mildly symptomatic COVID-19 patients (stage 1) and COVID-19 patients with pneumonia without respiratory failure (stage 2). The receiver operating characteristic (ROC) analysis revealed that IP-10, MIF, MIG, and basic-FGF differentiated patients with COVID-19 from healthy controls with the highest sensitivity and specificity, whereas GM-CSF, basic-FGF, and MIG differentiated asymptomatic/mildly symptomatic COVID-19 patients (stage 1) from COVID-19 patients with pneumonia without respiratory failure (stage 2) with the highest sensitivity and specificity. Conclusions: MIG, basic-FGF, and GM-CSF can be useful biomarkers for monitoring disease severity in patients with COVID-19.

Comparison of within 7 Day All-Cause Mortality among HDU Patients with Modified Early Warning Score of ≥5 with those with Score of <5.

OBJECTIVE: To compare 7-Day All-Cause Mortality among HDU Patients with Modified Early Warning Score of ≥5 with Those with Score of <5. METHODS: All patients of age more than 18 years, of either gender admitted in HDU of Medical Unit-II, CHK between September 2019 to February 2020 were included. MEWS was calculated for each patient at time of admission. Patients with MEWS score of ≥5 were allocated to Group-A and those with score of <5 were allocated to Group-B. Patients were followed for seven days and outcome status of alive, expired or discharged was noted. RESULTS: Total of 336 patients were selected out of which 168 patients was inducted in Group-A and 168 patients in Group-B. MEWS Score in patients who expired was significantly higher (Mdn=11) than in those who survived (Mdn=4), p <.001. 7-day mortality in Group-A was 62 (39.9%) while in Group-B was 40 (23.8%). ROC was plotted of MEWS Score for mortality, it showed significant area under curve of 68.4% (p <.001, 95% CI = .62 to .75). MEWS Score of 3.5 showed sensitivity of 89.2% and specificity of 65%. CONCLUSION: Our results show that MEWS has a positive trend to predict mortality. MEWS score of 3.5 is suggested cut off based on ROC in our study.