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Objective: To evaluate the effect of the modified systemic inflammation score (mSIS) on prognosis in patients diagnosed with COVID-19. Method(s): In this retrospective cross-sectional study, 181 patients were selected and divided into two groups: patients with and without admission to the intensive care unit (ICU). An albumin level of >=4.0 g/dL and lymphocyte-to-monocyte ratio (LMR) of >=3.4 was scored 0, an albumin level of <4.0 g/dL or LMR of <3.4 was scored 1, and an albumin level of <4.0 g/dL and LMR of <3.4 was scored 2. Result(s): A total of 242 COVID-19 positive patients were initially included in this study. Of these patients, 61 were excluded and 181 patients remained. Among the 181 participants, 94 (51.9%) were female, and the median age was 61 (51, 75) years. The mSIS scale ranged from 0 to 2. After analysis, the median score was 0 (0, 0) in the non-ICU group and 2 (0, 2) in the ICU group (P<0.001). The median white blood cell, lymphocyte counts, and albumin levels were lower in the ICU group (P<0.001, P<0.001, and P<0.001, respectively). In logistic regression analysis lymphocytopenia (OR=5.158, 95% CI=1.249-21.304, P=0.023), hypoalbuminemia (OR=49.921, 95% CI=1.843-1 352.114, P=0.020), AST elevation (OR=3.939, 95% CI=1.017-15.261, P=0.047), and mSIS=2 (OR=5.853, 95% CI=1.338-25.604, P=0.019) were identified as independent predictors of ICU admission. Conclusion(s): The mSIS can be used as an independent parameter for establishing the intensive care needs of patients with COVID-19.Copyright © 2023 Authors. All rights reserved.
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Background: Our understanding of the pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still evolving and is limited for prognostication. The study was performed to predict severity and mortality based on hematology parameters in coronavirus disease (COVID-19). Material and Methods: The study was a single-center retrospective analysis of 240 patients with COVID-19. The hematological parameters were compared between different grades of severity. The receiver operating characteristics (ROC) curve along with the Classification and Regression Trees (CART) methods were used for the analysis. Result: The total leukocyte count, absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), and neutrophil-monocyte ratio (NMR) were increasing along with an increase in severity; while the absolute lymphocyte count and lymphocyte-monocyte ratio (LMR) were decreasing (P < 0.001). For prediction of severity and mortality on admission, the NLR, NMR, and LMR were significant (P < 0.001). The NLR, NMR, and LMR had an area under the receiver operating characteristics curve (AUROC) of 0.86 (95% CI of 0.80-0.91), 0.822 (95% CI of 0.76-0.88), and 0.69 (95% CI of 0.60-0.79), respectively, for severity. While the NLR, NMR, and LMR had an AUROC value of 0.85 (95% CI of 0.79-0.92), 0.83 (95% CI of 0.77-0.89), and 0.67 (95% CI of 0.57-0.78), respectively, for mortality. Conclusion: With the increase in severity there was an increase in the total leukocyte count and absolute neutrophil count while the absolute lymphocyte count decreased. On admission, the cut-off value of NLR >5.2, NMR >12.1, while LMR <2.4 may predict severity and mortality in COVID-19.
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Background and purpose: In this study we want to evaluate the efficacy of yoga practice on dysfunctional stress, inflammation and QOL in breast cancer patients undergoing adjuvant radiotherapy. Patients and methods: Patients with stage 0 to III breast cancer were recruited before starting radiotherapy (XRT) and were randomly assigned to yoga group (YG) two times a week during XRT or control group (CG). Self-report measures of QOL, fatigue and sleep quality, and blood samples were collected at day 1 of treatment, day 15, end of treatment and 1, 3 and 6 months later. Cortisol blood level, IL6, IL10, IL1RA, TNFα and lymphocyte-to-monocyte ratio were analyzed as measures of dysfunctional stress and inflammation. Results: Patients started XRT and yoga classes in October 2019. Due to COVID-19 pandemic we closed the enrollment in March 2020. We analysed 24 patients, 12 YG and 12 CG. The analysis of blood cortisol levels revealed an interaction (p = 0.04) between yoga practice and time, in particular YG had lower cortisol levels at the end of XRT respect to CG (p-adj = 0.02). The analysis of IL-1RA revealed an interaction effect (p = 0.04) suggesting differences between groups at some time points that post-hoc tests were not able to detect. Conclusions: To our knowledge, this is the first study to evaluate the effects of yoga in a cancer population studying inflammation markers, cortisol trend and QOL during and until 6 months after XRT. This study suggests that yoga practice is able to reduce stress and inflammation levels over time. Besides including a larger number of patients to increase the power, future studies should consider other inflammatory or pro inflammatory factors and long-term yoga program to gain more evidence on yoga practice benefits.
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Introduction: Coronavirus disease 2019 (COVID-19) is a pandemic caused by the novel coronavirus SARS-CoV2, causing an enormous strain on the already burdened healthcare systems. The clinical course of COVID-19 is variable;those with a poor prognosis tend to develop severe viral pneumonia requiring ventilator support and intensive care unit (ICU) admission. Aim & Objectives: The aim of this study is to correlate the Cycle Threshold (Ct) score of RT-PCR reaction with different biomarkers like White cell count (WCC), Neutrophils%, Lymphocytes%, Monocytes%, Neutrophil-Lymphocyte ratio(NLR), Lymphocyte – Monocyte ratio (LMR), Platelet count, Prothrombin time(PT), Interleukin 6(IL-6), C-Reactive protein (CRP), Blood sugar level(BSL) .Thus enabling if a low Ct score can help early identification of patients at a high risk to progress to a severe disease. Method: A prospective analytical study conducted at a tertiary care hospital, included 114 severe COVID-19 positive patients, admitted in ICU. The medical history, comorbidities, clinical findings, and laboratory data of each patient were obtained with data analyzed to identify and correlate significant laboratory parameters leading to the severe outcome. Results: Total 114 patients were studied. The mean age of the study population was 59 years with a male predominance. Significant positive correlation of Ct values was seen with Total WBC counts (p=0.004), Neutrophil % (p=0.001), NLR (p<0.001), IL-6 (p=0.010), Procalcitonin (p=0.015) and D-dimer (p=0.041). Significant negative correlation of Ct value with Lymphocyte % (p=0.001) and monocyte % (p<0.001). And no significant correlation was seen with Age, Gender, LMR, CRP, Platelet counts, Prothrombin time and Blood Sugar levels. Conclusion: It is known that biomarkers help in identifying the disease severity and mortality and help in proper diagnosis and patient treatment. Ct scores can be used as a surrogate marker of disease severity, although further studies are required to validate the same.
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BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or COVID-19 has been spread quickly and caused 5 million deaths until February 2022. Severe symptoms of the infection may lead to death that prompts appropriate clinical diagnosis and adequate treatment going to be necessary. COVID-19 shows a severe inflammatory response which causes an imbalance in the immune response. Therefore, circulating biomarkers that can represent inflammation and immune status are potential predictors for the prognosis of COVID-19 patients. AIM: The purpose of this study was to discover the role of neutrophil-lymphocyte ratio (NLR), neutrophil-monocyte ratio (NMR), and lymphocyte-monocyte ratio (LMR) as inflammatory biomarkers for the severity of COVID-19. METHODOLOGY: This study is a single-center retrospective cohort study. The sample of this study was taken by consecutive sampling with complete clinical data from 1035 patients from Andalas University Teaching Hospital from April 2020 to September 2021. This study used SPSS Version 25.0 for data management and analysis. RESULTS: There was a relationship between the degree of COVID-19 infection and the NLR value (p = 0.001), as well as the LMR (p = 0.001), NMR (p = 0.001), and ANC (p = 0.001). There was no relationship between the degree of infection in the negative PCR patient group and the NLR value (p = 0.144), as well as the LMR (p = 0.700), NMR (p = 0.120), and ANC (p = 0.90). CONCLUSION: The severity of COVID-19 symptoms could be predicted through inflammatory biomarkers such as NLR, LMR, and NMR.
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Aim: To evaluate neutrophilic lymphocyte ratio and lymphocyte monocyte ratio as prognostic markers in COVID 19. Material and method: The present retrospective observational studyconducted in the department of Medicine, Government Medical College, Jammu for a period of one year. The study comprised of 100 Covid 19 RT PCR positive cases admitted patient in ICU as well as Ward, in covid care centre of Government Medical College, Jammu. Patients characteristics were obtained from the hospital covid care centre satisfying inclusion criteria from electronic medical records and demographic, clinical, laboratory data were extracted included age, sex clinical features, signs and symptoms, comorbidities, exposure history, oxygen support during hospitalization, duration of oxygen support during hospitalization,imaging features of the chest (CT scoring), laboratory findings (Hemogram, Total leucocyte count, differential counts, NLR and LMR. Complete blood count including NLR and LMR collected at day of admission and day 3 of admission and documented on a standardized proforma. Two outcomes were evaluated: “discharge” or “died.” Results:In majority (53%) of patients, ventilation given was high flow followed by bipap (21%), ventimask (19%) and ventilator (5%). Ventilation given was room air in only 2 out of 100 patients (2%). In present study, only 10 out of 100 patients (10.00%) died.Discriminatory power of neutrophil lymphocyte ratio (AUC 0.865;95% CI: 0.781 to 0.925) was excellent and discriminatory power of lymphocyte monocyte ratio (AUC 0.791;95% CI: 0.698 to 0.867) was acceptable. Among both the parameters, neutrophil lymphocyte ratio was the best predictor of CTSI severity at cut off point of >3.57 with 86.50% chances of correctly predicting CTSI severity. Conclusion: It can be concluded from the results that NLR may be a rapid, widely available, useful prognostic factor in the early screening of critical illness in patients with confirmed COVID-19.
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Introduction: COVID-19 caused by SARS-CoV-2is a highly contagious disease. It is a complex systemic disease primarily involving therespiratory system. Patients usually have mild to moderate illness andpresent with flu like symptoms. However, a small group of patientsmay progress or present in a critical condition necessitating intensivecare. Early identification of risk factors associated with critical illnessmay aid in providing timely supportive care and access to theintensive care unit (ICU) when required.Aims &Objectives: To compare the CBC findings, NeutrophilLymphocyte Ratio (NLR), derived neutrophil lymphocyte ratio (dNLR), Platelet Lymphocyte Ratio (PLR) and Lymphocyte MonocyteRatio (LMR) in mild and severe categories of COVID 19 patients.Materials &Methods: Cases diagnosed as COVID 19 and admittedin the wards and ICU of GTB Hospital, Delhi were included. Sampleswere collected from 27 cases. The cases were divided in severe andmild categories. Blood was collected in EDTA vial and CBC wasdone using Automated Hematology Analyser. Data were entered inSPSS 26 and statistical analysis was done using same software.Result: NLR, dNLR values and TLC were found to be significantlyhigher (P< 0.05) in severe COVID-19 patients compared to mildCOVID-19 patients. Differences in platelet count, PLR and LMRvalues were not significant between the two groups. Using ROCcurve, a cut off value of 10,950 for TLC, 6.19 for NLR and 4.13 fordNLR were determined. Using these values TLC was found to be93.3% sensitive, 91.7% specific;NLR was found to be 73.3% sensitive, 72.7% specific;dNLR was found to be 80% sensitive, 81.8%specific in recognizing severe COVID 19 infections.Conclusions: NLR, d-NLR, PLR &LMR are readily accessiblebiomarker, which can be calculated based on a complete blood count.In our study, TLC, NLR and dNLR were found to be useful indetecting severe COVID 19 infections. TLC was the most sensitiveand specific marker in detecting severe COVID 19 patients followedby dNLR. NLR was less valuable than dNLR.
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Introduction: COVID-19 pandemic has placed the health systemworldwide in unprecedented stress, therefore, prompt identification and management of patients having severe disease is essential fortriaging of patients at the time of admission.Aims &Objectives: To identify hematological biomarkers ofCOVID-19 disease severity in patients admitted in a tertiary carehospital.Materials &Methods: A retrospective study was conducted over aperiod of 17 months (20th March 2020-19 August 2021) on 7416COVID-19 patients. Patients with cancers, pregnancy and chronichematological diseases were excluded from the study. Patients wereclassified clinically as per severity of disease as non-severe (asymptomatic, mild, moderate) or severe and their hematological parameterswere analyzed.Mann-Whitney test was used to compare between the groups. Optimal predictive cut off points for the variables were defined by receiveroperating characteristic (AUC) curve to dichotomize the variables.Univariate analysis was performed to screen out independent variables to be used in the binary logistic regression (BLR). A p valueof< = 0.05 was considered as statistically significant.Result: Age, duration of hospital stay, RBC count, WBC, Plateletcount, RDW, Neutrophils %, Absolute neutrophil count (ANC),Absolute monocyte count (AMC), NLR, PLR, NMR were statisticallyhigher whereas hemoglobin, hematocrit, MCHC, lymphocyte %,Absolute lymphocyte count (ALC), Eosinophils %, Absolute eosinophil count (AEC), Monocytes %, Basophils %, Absolute Basophilcount (ABC) and Lymphocyte Monocyte ratio (LMR) were lower insevere group. MCV and MCHC were not significant, so wereexcluded from the logistic regression model. All variables were significant in univariate analysis. Age (>42 yrs), duration of hospitalstay (>10 days), RBC count (B 4.33 106/lL),WBC count (> 7.73103/lL), RDW (>14.8%), Neutrophils (>71.7%), Eosinophils(B 0.3%), Monocytes (B 5%), ALC (B 1.01 103/lL), LMR(B 3.125) with adjusted odd ratio of 1.8, 1.5, 1.3,1.3, 1.4, 2.0, 2.1, 1.5,2.0 and 1.3 respectively were found to be significant predictors ofseverity.Conclusions: Age, duration of hospital stay, RBC count, WBC,RDW, Neutrophils %, Eosinophils %, Monocytes %, ALC, LMRshould be assessed and monitor at the earliest to halt unfavorableoutcome of mortality or morbidity.