Neutrophil-lymphocyte Count Ratio Research Articles

Assessment of Sepsis Risk at Admission to the Emergency Department: Clinical Interpretable Prediction Model.

This study aims to develop an interpretable prediction model based on explainable artificial intelligence to predict bacterial sepsis and discover important biomarkers. A total of 1572 adult patients, 560 of whom were sepsis positive and 1012 of whom were negative, who were admitted to the emergency department with suspicion of sepsis, were examined. We investigated the performance characteristics of sepsis biomarkers alone and in combination for confirmed sepsis diagnosis using Sepsis-3 criteria. Three different tree-based algorithms-Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost)-were used for sepsis prediction, and after examining comprehensive performance metrics, descriptions of the optimal model were obtained with the SHAP method. The XGBoost model achieved accuracy of 0.898 (0.868-0.929) and area under the ROC curve (AUC) of 0.940 (0.898-0.980) with a 95% confidence interval. The five biomarkers for predicting sepsis were age, respiratory rate, oxygen saturation, procalcitonin, and positive blood culture. SHAP results revealed that older age, higher respiratory rate, procalcitonin, neutrophil-lymphocyte count ratio, C-reactive protein, plaque, leukocyte particle concentration, as well as lower oxygen saturation, systolic blood pressure, and hemoglobin levels increased the risk of sepsis. As a result, the Explainable Artificial Intelligence (XAI)-based prediction model can guide clinicians in the early diagnosis and treatment of sepsis, providing more effective sepsis management and potentially reducing mortality rates and medical costs.

Construction of a risk prediction model for lung infection after chemotherapy in lung cancer patients based on the machine learning algorithm.

The objective of this study was to create and validate a machine learning (ML)-based model for predicting the likelihood of lung infections following chemotherapy in patients with lung cancer. A retrospective study was conducted on a cohort of 502 lung cancer patients undergoing chemotherapy. Data on age, Body Mass Index (BMI), underlying disease, chemotherapy cycle, number of hospitalizations, and various blood test results were collected from medical records. We used the Synthetic Minority Oversampling Technique (SMOTE) to handle unbalanced data. Feature screening was performed using the Boruta algorithm and The Least Absolute Shrinkage and Selection Operator (LASSO). Subsequently, six ML algorithms, namely Logistic Regression (LR), Random Forest (RF), Gaussian Naive Bayes (GNB), Multi-layer Perceptron (MLP), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) were employed to train and develop an ML model using a 10-fold cross-validation methodology. The model's performance was evaluated through various metrics, including the area under the receiver operating characteristic curve (ROC), accuracy, sensitivity, specificity, F1 score, calibration curve, decision curves, clinical impact curve, and confusion matrix. In addition, model interpretation was performed by the Shapley Additive Explanations (SHAP) analysis to clarify the importance of each feature of the model and its decision basis. Finally, we constructed nomograms to make the predictive model results more readable. The integration of Boruta and LASSO methodologies identified Gender, Smoke, Drink, Chemotherapy cycles, pleural effusion (PE), Neutrophil-lymphocyte count ratio (NLR), Neutrophil-monocyte count ratio (NMR), Lymphocytes (LYM) and Neutrophil (NEUT) as significant predictors. The LR model demonstrated superior performance compared to alternative ML algorithms, achieving an accuracy of 81.80%, a sensitivity of 81.1%, a specificity of 82.5%, an F1 score of 81.6%, and an AUC of 0.888(95%CI(0.863-0.911)). Furthermore, the SHAP method identified Chemotherapy cycles and Smoke as the primary decision factors influencing the ML model's predictions. Finally, this study successfully constructed interactive nomograms and dynamic nomograms. The ML algorithm, combining demographic and clinical factors, accurately predicted post-chemotherapy lung infections in cancer patients. The LR model performed well, potentially improving early detection and treatment in clinical practice.

The Diagnostic Value of Kinetics of NLR to Identify Secondary Pulmonary Bacterial Infection Among COVID-19 Patients at Single Tertiary Hospital in Indonesia.

Coronavirus disease 2019 (COVID-19) is a new respiratory tract infection caused by severe acute respiratory syndrome coronavirus-2. The presence of secondary pulmonary bacterial infection (SPBI) made COVID-19 difficult to treat. Neutrophil-lymphocyte count ratio (NLR) is a systemic inflammatory marker used in the diagnosis and prognosis of viral or bacterial infection. At the first 3-5 days after hyperinflammation, it occurs in relation to clinical outcome. Therefore, this study aimed to evaluate the diagnostic value of NLR based on leukocyte kinetics upon admission and after 72 hours among COVID-19 patients with or without SPBI. This retrospective cross-sectional study analyzed medical records data of admitted patients with COVID-19 according to the International Classification of Disease 10th Revision (ICD-10) between January and December 2021. The list of patients was extracted and followed by a hand search to identify the inclusion or exclusion criteria and stratified into proven and non-proven SPBI based on clinical data. The study distinguished between SPBI by means of a cut-off value (COV) on the first (D1) and third day (D3), assessed using receiver operating characteristics (ROC), as well as determined the magnitude of sensitivity, specificity, and prevalence ratio. A screening process was conducted on 2902 COVID-19 patients, of which 236 were included, accounting for 8.1%. Among these patients, 87 (36.9%) were found to have proven SPBI. A considerable difference in NLR value between proven and non-proven SPBI was observed on both D1 (11.1 vs 4.2) and D3 (15.3 vs 5.2), with optimal COV of NLR on D1, D3 was found to be 5.29, 9.47, respectively (p < 0.001). NLR on the D1 and D3 distinguished the occurrence of SPBI among COVID-19 patients. The application of NLR assisted in the early determination of bacterial infection and helped in controlling the empirical use of antibiotics.

The effect of diabetes mellitus on COVID-19 mortality among patients in a tertiary-level hospital in Bandung, Indonesia.

Immune system dysregulation in people with diabetes mellitus (DM) increases the risk of acquiring severe infection. We compared the clinical characteristics and laboratory parameters of coronavirus disease 2019 (COVID-19) patients with and without DM and estimated the effect of DM on mortality among COVID-19 patients. A retrospective cohort study collecting patients' demographic, clinical characteristics, laboratory parameters and treatment outcomes from medical records was conducted in a hospital in Bandung City from March to December 2020. Univariable and multivariable logistic regression was performed to determine the association between DM and death. A total of 664 COVID-19 patients with positive real-time reverse transcription polymerase chain reaction for severe acute respiratory syndrome coronavirus 2 were included in this study, of whom 147 were with DM. Half of DM patients presented HbA1c ≥10%. DM patients were more likely to present with comorbidities and severe to critical conditions at admission (P <0.001). Laboratory parameters such as neutrophil-lymphocyte count ratio, C-reactive protein, D-dimer, ferritin, and lactate dehydrogenase were higher in the DM group. In the univariate analysis, variables associated with death were COVID-19 severity at baseline, neurologic disease, DM, age ≥60 years, hypertension, cardiovascular disease, and chronic kidney disease. DM remained associated with death (aOR 1.82; 95% CI 1.13-2.93) after adjustment with sex, age, hypertension, cardiovascular disease, and chronic kidney disease. In conclusion, COVID-19 patients with DM are more likely to present with a very high HbA1c, comorbidities, and severe-critical illness. Chronic inflammation in DM patients may be aggravated by the disruption of immune response caused by COVID-19, leading to worse laboratory results and poor outcomes.

The Relationship Between Decreased CD-8 T-Cells and Mortality in Patients with COVID-19 Pneumonia in the Intensive Care Unit, A Retrospective Study.

CD-8 T-cells are responsible for the clearance of virally infected cells. In patients with Coronavirus disease-2019 (COVID-19) pneumonia, there are quantitative reductions and functional impairments in T-cells. Low CD-8 T-cell levels cause worse clinical situations. In this study, the relationship between decreased CD-8 T-cells and mortality in patients with COVID-19 pneumonia in the intensive care unit (ICU) was investigated. In this multicenter retrospective study, 277 patients were analyzed. Demographic data, ICU admission scores, blood gas levels, laboratory samples, and outcomes were recorded. Statistical Package for the Social Sciences version 28 was used for statistical analysis. Two hundred forty of 277 patients were included in the study. The mortality rate was 43.3%. In non-survivors, median values of age, Charlson comorbidity index, Acute Physiology and Chronic Health Evaluation II (APACHE-II), procalcitonin, leukocyte count, neutrophil count, neutrophil-lymphocyte count ratio, and duration of invasive mechanical ventilation were significantly higher, whereas median values of PaO2-FiO2 ratio, lymphocyte count, CD-4, and CD-8 T-cells were significantly lower than those in survivors. In the multivariate Cox regression model, the risk of mortality increased 1.04-fold (1.02-1.06) and 1.05-fold (1.01-10.8) by every one unit increase in age and APACHE-II, respectively, whereas it decreased 0.71-fold (0.58-0.87) by every hundred increase in CD-8 T-cells P < 0.001, P=0.007 and P=0.001 respectively. According to our findings, age, APACHE-II, and CD-8 T-cell levels seem to be independent risk factors for mortality in patients with COVID-19 pneumonia in the ICU.

Assessing the Preoperative Neutrophil-Lymphocyte Count Ratio's Predictive Ability for Postoperative Sepsis in Percutaneous Nephrolithotomy Patients

Background: The present study aimed to evaluate whether neutrophil lymphocyte count ratio (NLCR) can be used to detect post- PCNL sepsis.The objective of this study was to assess the potential of neutrophil-lymphocyte count ratio (NLCR) in detecting post-percutaneous nephrolithotomy (PCNL) sepsis. Methodology: The Department of Urology, Sindh Institute of Urology and Transplantation, Karachi, conducted a cross-sectional study between 05-Oct-2019 to 04-April-2020. Patients of renal stone planned for PCNL, All adult patients of age 18-65 years, irrespective of gender, those with the preoperative total leukocyte count of between 4 and 12 x109 cells/L, and those patients with ASA class 1 were made to take part in the study. After involving the patients in the study, CT KUB was used to calculate stone size. Complete blood Count was done one week before PCNL and NLCR was calculated for all patients. After PCNL, patients were followed for 1 week. All the gathered information including demographic details (age, gender), preoperative findings (NLCR, Stone size, staghorn), intraoperative findings (operating time, tracts, blood transfusion) and postoperative findings (temperature, heart rate, respiratory rate, total leukocyte count, blood and urine cultures) was noted on a pre-designed Proforma. Results: In this study, a total of 256 patients with a mean age of 41.17±10.18 years and a mean stone size of 29.1±6.3 mm were evaluated. The patients' mean operative time was 62.28±8.85 minutes. The area under the curve (AUC) was 0.824 in the ROC analysis, with the ideal cut-off value of NLCR being 2.5. The sensitivity and specificity of NLCR in predicting sepsis after PCNL were 50.0% and 98.0%, respectively, while the positive predictive value (PPV) was 80% and the negative predictive value (NPV) was 95.02%. The diagnostic accuracy was found to be 94.1%. Conclusion: The risk of sepsis following percutaneous nephrolithotomy (PCNL) can be predicted with success using a cut-off value of ≥2.5 for neutrophil-lymphocyte count ratio (NLCR). Moreover, it is a simple, cost-effective, and noninvasive test and readily available in hospital laboratories. Keywords: neutrophil lymphocyte count ratio, sepsis, percutaneous nephrolithotomy

Assessment of Serum Neopterin Levels in patients hospitalized with severe COVID-19

Background: COVID-19 has caused a considerable number of hospital admissions in China since December 2019. Many COVID-19 patients experience signs of acute respiratory distress syndrome, and some are even in danger of dying. Objective: to measure the serum levels of D-dimer, Neutrophil-Lymphocyte count ratio (NLR), and neopterin in patients hospitalized with severe COVID-19 in Baghdad, Iraq. And to determine the cut-off values (critical values) of these markers for the distinction between the severe patients diagnosed with COVID‐19 and the controls. Materials and methods: In this case-control study, we collect blood from 89 subjects, 45 were severe patients hospitalized in many Baghdad medical centers who were diagnosed with COVID-19 infection, and 44 were apparently healthy subjects as a control. The time of collection is from September 15 th to December 31 th, 2021. The optimal cut-off points (critical values) and prognostic relevance of D-dimer, Neutrophil-Lymphocyte count ratio (NLR), and neopterin were investigated using (ROC) curves analysis. Results: In severe patients hospitalized with COVID-19 the levels of D-dimer, NLR, and neopterin were statistically significantly higher than in control participants (P&lt; 0.005). The D-dimer, NLR, and neopterin tests have areas under the receiver operating characteristic (ROC) curves of 0.920, 0.90, and 0.74 respectively, and their critical values for the differentiation between the severe patients and control were 0.22 μg/ml, 2.56, and 3.02 nmol/L. Conclusions: D-dimer, NLR, and neopterin levels in sever COVID-19 patients were higher than control, with values of greater than 0.22μg/ml, 2.56 and 3.02nmol/L respectively was linked to a severe COVID-19infection with good sensitivity and selectivity.

A prospective cohort study evaluated the significance of the neutrophil-lymphocyte count ratio in determining if a patient being admitted to an intensive care unit has sepsis.

A prospective cohort study evaluated the significance of the neutrophil-lymphocyte count ratio in determining if a patient being admitted to an intensive care unit has sepsis.

White blood count and inflammatory markers in the patients with COVID-19 infection and severity of illness.

Objective: To assess whether hematological and inflammatory parameters can be useful in assessing severity of disease and predict mortality in patients with COVID-19. Study Design: Cross Sectional Comparative Retrospective. Setting: COVID ward and ICU, Central Park Teaching Hospital Lahore. Period: 23rd April 2021 to 23rd June 2021. Material &amp; Methods: The study population was selected by convenient sampling and all patients admitted to the COVID ward and ICU during this time span of two months with positive COVID PCR were included in the study. Results: Among the study population 29(58%) were males while 21(42%) were females with male to female ratio of 1.38:1 and the difference was not found to be statistically significant. The mean age of the patients was 65.2±08 years. The complete blood parameters white blood count, absolute neutrophil count, lymphocyte count and neutrophil lymphocyte ratio were compared between groups and it was found that white blood count, absolute neutrophil count and neutrophil lymphocyte ratio was significantly different between different groups. Inflammatory markers like IL-6, ferritin, C-reative protein and d-dimers were also assessed in different severity groups and all were found to be significantly high in severe/critical group. Conclusion: it is concluded that simple inexpensive parameters like White blood count, neutrophil lymphocyte ratio and neutrophil count can be used to evaluate the severity of disease and to predict those patients who are at increased risk of mortality. In the similar way inflammatory markers like C-reactive protein, D-dimers, IL-6 and ferritin can be used to group the disease severity and also to monitor the disease.

Role of neutrophil-lymphocyte ratio as a potential marker to differentiate between pulmonary tuberculosis and community-acquired pneumonia in children

Background: This is often creating challenge to differentiate pulmonary tuberculosis (TB) with community acquired pneumonia (CAP) particularly in children. The neutrophil-lymphocyte count ratio (NLR) as an indicator of inflammation has been used in various infectious diseases. The aim of this study was to investigate the role of NLR as a possible marker in differentiating pulmonary TB from CAP.Methods: In this retrospective record based analytic study, conducted from July 2020 to Dec 2021, patient aged 2 months to 18 years diagnosed as pulmonary TB or CAP were enrolled in this study i.e., 155 children after exclusion. The diagnostic ability of NLR in differentiating between pulmonary Tb and CAP were assessed.Results: Out of 155 children, 85 (54.8%) had CAP and 70 (45.1%) had pulmonary TB. Mean values of NLR were significantly lower in patients with TB than in pneumonia (3.16±1.9 vs 5.05±1.2, p&lt;0.000). Total WBC, neutrophil, Hb and CRP were also significantly lower in patients with pulmonary TB. On the other hand, lymphocyte count was significantly higher in children with pulmonary TB in compare to children with pneumonia (p=0.04).Conclusions: The NLR can be used as a useful simple laboratory marker in differentiating children with Pulmonary TB from CAP, especially in resource limited high TB disease burden countries.

The inflammatory cellular feature in the peripheral blood of chronic subdural hematoma patients.

BackgroundChronic subdural hematoma (CSDH) is a common neurosurgical disease with an increasing incidence. The absorption route of CSDH is not clear. Whether inflammatory factors enter the peripheral blood and cause systemic reactions is unknown.MethodsWe screened 105 CSDH patients and 105 control individuals. Their clinical characteristics and blood routine results were collected and compared. The blood routine changes of CSDH patients before and after treatment were compared. Age‐stratified analysis was performed due to age may affect the inflammatory markers.ResultsThe white blood cell count, absolute neutrophil count, neutrophil percentage, neutrophil‐lymphocyte count ratio (NLR), and platelet to lymphocyte count ratio (PLR) of CSDH patients before treatment were within the normal range, while were significantly higher than the control individuals (p < 0.001). The absolute lymphocyte count and lymphocyte percentage of control individuals were higher than those of patients (p < 0.001). The inflammatory cells in patients of different age groups were similar. After the patient was cured, the white blood cell count, the absolute value and percentage of neutrophils decreased (p < 0.05), while the number of monocytes increased.ConclusionsCSDH caused slight systemic inflammatory responses in the peripheral blood, implying that there is a non‐hematologic route for the absorption of hematoma.

Can neutrophil-to-lymphocyte ratio and proatherogenic risk factors improve the accuracy of pneumonia severity index in the prediction of community acquired pneumonia outcome in healthy individuals?

Aim To investigate infl uence of neutrophil-to-lymphocyte ratio (NLR) and proatherogenic risk factors to improve the accuracy of pneumonia severity index (PSI) in the prediction of community acquired pneumonia (CAP) outcome in healthy individuals. Methods A retrospective observational cross-sectional study conducted at the Clinic for Pulmonary Diseases and Tuberculosis "Podhrastovi", University Clinical Centre Sarajevo, included 83 patients with the diagnosis of CAP during the period March 2019-March 2021. Once diagnosed with CAP, PSI score was calculated and according to its value the need for hospital treatment was identifi ed. Patients were divided in two groups: low risk of CAP (PSI <90), and high risk of CAP (PSI> 90). Results The overall average hospital stay was 22.76±10.154 days. In the patients diagnosed with CAP, a positive correlation was established between the following parameters PSI score and age (r=0.670; p<0.01), C-reactive protein-CRP (rho=0.287; p<0.01), leukocytes (rho=0.406; p<0.01), NLR (rho=0.313; p<0.01) and platelet to lymphocyte ratio (PLR) (0.296; p<0.05). CRP, leukocytes, NLR and PLR were statistically signifi cantly higher in patients with high risk of CAP compared to patients with low risk of CAP. Diastolic blood pressure, lymphocytes, eosinophils were signifi cantly lower in patients with high risk of CAP (p<0.05;) compared to patients with low risk of CAP (p<0.01). The optimal cut-off value of NLR for CAP patients was 3.089 with an estimated area under curve (AUC) of 0.664. Conclusion Proatherogenic parameters such as age, systolic blood pressure and leukocytes in combination with neutrophil-lymphocyte count ratio could improve accuracy of the pneumonia severity index in community acquired pneumonia outcome.

Value Research of NLR, PLR, and RDW in Prognostic Assessment of Patients with Colorectal Cancer.

Objective This study aimed to investigate the relevance of the study with the neutrophil count and lymphocyte count ratio (NLR), platelet count and lymphocyte count ratio (PLR), and red blood cell distribution width (RDW) in the prognostic evaluation of colorectal cancer patients. Methods 143 patients with colorectal cancer from January 2016 to January 2019 were selected by our hospital, and then, other 143 cases of physical examiners as normal groups were selecting to proceed colonoscopic biopsy to diagnose 106 cases of precancerous diseases related to colorectal cancer. Among them were the inflammatory bowel group (n = 56) and the colorectal polyp group (n = 50). Analysis of the survival impact factors of patients with carcinoma of the rectum, preoperative NLR, ROW, PLR, and prognostic relationship, and comparison of NLR, PLR, and RDW diagnostic rate and expression were performed. Results Tissue type, TNM stage, lymph node metastasis, NLR, RDW, and PLR had a predictive influence on patients with colorectal cancer (P0.05). There was no link between gender, age, aetiology, pathological type, and prognosis in patients with colorectal cancer (P > 0.05). Multiple variables in patients with colorectal cancer are affected by tissue categorization (poor differentiation), TNM stages (III, IV), lymph node metastases, NLR, ROW, and PLR (P0.05). When compared to solo NLR, Row, and PLR diagnostics, the combination diagnosis and malignancy rates were greater, and the differences were statistically significant (P0.05). Diagnostic sensitivity, specificity, and accuracy were greater when compared to single NLR, ROW, and PLR. When compared to the normal control group, NLR, ROW, and PLR have greater levels, and the differences are statistically significant (P0.05). The patient survival declines more slowly as PLR, NLR, and the severity of the condition rises. Conclusion NLR, ROW, and PLR combined diagnosis has high accuracy in colorectal cancer diagnosis, and the prognosis of patients with NLR, ROW, and PLR levels has a tight association; so, clinically, the above signs should be identified, and the optimal treatment time is grasped.

Study of Procalcitonin and neutrophil/ lymphocyte count ratio in children infected with Community-acquired pneumonia

Objective: Investigate the expression of procalcitonin (PCT) in children infected with Community-acquired pneumonia (CAP), and its correlation to the number of white blood cells (WBC), and neutrophil/ lymphocyte count ratio (NLR). The current study included sixty (60) patient suffering from acquired community pneumonia aged range between one year to larger than 6 years, gander (30) female and (30) male Childs in Al Zahara Teaching Hospitals in Najaf Provenance , during November 2020 – M arch 2021. The (30) control Child without suffering any of symptoms or criteria of acquired community pneumonia our results show a significant increment (p&lt;0.05) in total count of leukocytes, Neutrophils, N/L ratio, lymphocytes (10⁹/L) and PCT level in Pneumonia patients group compared with control group respectively, and non-significant (p&gt;0.05) different in biomarker procalcitonin level between female and male pneumonia child patients. Serum procalcitonin level demonstrate a statistically significant elevation (p &lt;0.05) in the pneumonia child patient among the age (1-3 y) when compare with other ages.

Neutrophil-lymphocyte Count Ratio as Section an Indicator of Culture Positive versus Culture Negative Sepsis: A Singlecentre Cross-sectional Study

Introduction: In sepsis patients, the Neutrophil-lymphocyte Count Ratio (NLCR) is a laboratory statistic that can indicate bacterial infection. Aim: To measure NLCR in patients with sepsis and compare the NLCR in patient with culture positive and culture negative sepsis. Materials and Methods: This single-centre, cross-sectional study was conducted in the Department of General Medicine at R.L. Jalappa Hospital (Sri Devaraj URS Medical College), Kolar, Karnataka, India, from October 2021 to December 2021. A total of 120 patients above 18 years of age with sepsis, diagnosed as per the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3), were included in the study. Participants were evaluated for sepsis and septic shock (society of critical care medicine conference definitions) the principles of initial resuscitation (fluid therapy, vasopressors, inotropic support), and infection issues (source identification and control, appropriate antibiotic therapy) were followed regularly and the outcome studied. Neutrophil count, lymphocyte count, and calculation of NLCR were done at the time of admission. The correlation studies of NLCR in culture-positive and culturenegative was done and compared. Data was analysed by using coGuide software (version 1.03). Results: The mean age of patients was 58.98±17.78 years, ranged from 20 to 96 years, 47 (39.17%) were male and 73 (60.83%) were female, majority 93 (77.50%) out of 120 patients had fever. Majority 78 (65%) had type 2 diabetes mellitus. Neutrophilto-Lymphocyte ratio (NLR) was 10±1.67, ranging from 7.40 to 14.50. The area under the ROC curve was 0.522. There was no statistically significant relationship between the NLCR and culture report (p-value=0.216). The NLCR had poor predictive validity in predicting culture positive, as indicated by the area under the curve {0.522 (95% CI: 0.417 to 0.626, p-value= 0.988)}. Conclusion: NLCR can be considered as predictor for the initiation of treatment of patients with sepsis.

Assessment of Surrogate Markers/Indices of Systemic Inflammation Among COVID-19 Patients with and Without Comorbid Conditions

Background: As widely reported, comorbid conditions are a significant risk for severe COVID-19 infection which is characterized by heightened adverse consequences. Since cytokine-induced inflammatory processes define COVID-19 severity, this study was aimed to evaluate the burden of COVID-19-induced inflammatory episodes, assessed using surrogate markers/indices of inflammation, among COVID-19 patients with and without comorbid conditions in Nigeria. Methods: This was a retrospective analysis of data obtained from treatment-naive real-time polymerase chain reaction (RT-PCR) confirmed COVID-19 patients at the Eleme COVID-19 treatment center in Port Harcourt within the southern region of Nigeria. All relevant data was acquired from case notes, medical review charts, nurses’ charts, and laboratory records by trained research assistants using data acquisition templates. All the data acquired were analyzed and compared between the COVID-19 patients with and without comorbid conditions using standard descriptive and comparative statistical tools. Results: Among those studied (n=604), 31.8% (n=192) had at least one pre-existing comorbid condition while 68.2% (n=412) had no comorbid conditions before COVID-19 diagnosis/subsequent presentation. The comorbid positive subgroup were mostly males and had higher mean age, BMI, body temperature, SBP, DBP, and higher proportions of elderly patients, high-risk occupational status (health workers) and social behavior (cigarette smoking), obesity, severe disease, and worse disease outcome, but lower oxygen saturation compared to the comorbid negative subjects at presentation. Additionally, the comorbid positive subjects also had higher mean levels of blood urea, creatinine, pro-calcitonin, CRP, ferritin, Glasgow prognostic scores, fibrinogen, D-Dimer, and the fibrinogen-albumin ratio, total white cell counts, isolated neutrophil counts, neutrophil-lymphocyte count ratio, and the platelet-lymphocyte count ratio but lower levels of potassium, albumin, isolated lymphocyte count and isolated platelet count compared to the comorbid negative subjects (p<0.05). The inflammatory markers/indices were significantly associated with obesity, age ≥65 years, hypertension, past/current cigarette smoking, diabetes, and cardiovascular disease. Conclusion: Comorbidities are significantly associated with amplified systemic inflammatory markers and indices among COVID-19 subjects. This may indicate the pathophysiologic link between various comorbidities and the COVID-19 severity among Nigerians. However, further studies are recommended to substantiate the findings of the current study.

Correlation between neutrophil lymphocyte count ratio and outcomes of severe traumatic head injury

Background: Raised peripheral neutrophil lymphocyte ratio is associated with poorer outcomes in conditions such as severe brain injury, ICH, cardiovascular conditions, cancer.Methods: Retrospective analysis of 96 severe Traumatic Brain injury data treated at our institute over a period of 1 year. The patients were followed up for a period of at least 1 month. The primary outcome of the study was 1 month GOS and the various variables which may be associated with the poor GOS at 1 month follow up. Model based analysis was done for NLCR &lt;24 hrs at 48 hrs and GCS at the time of presentation and discriminative ability of the models were studied by the Area under the curve.Results: Univariate analysis were done of 96 patients of severe traumatic brain injury for various variables such as age, sex, mode of head injury, type of head injury, presenting GCS and NLCR at 24 hrs and 48 hrs to that of GOS at 1 month follow up. Initial GCS &lt;7 (p=0.0138) with AUC=0.6689 and peak NLCR (&lt;24 hr) of &gt; 9.6 (AUC=0.931) with a p value of &lt;0.001 with sensitivity of 100% and specificity of 79.27% and peak NLCR (48 hrs) of &gt;12.4 (AUC= 0.973) with a p value of &lt;0.001 with sensitivity of 100% and specificity of 89.02% were associated with unfavourable outcome.Conclusions: High NLCR and initial poor GCS are independent unfavourable prognostic factors in 1 month GOS following severe traumatic head injury.

An Emerging Marker Predicting The Severity of Covid-19: Neutrophil-Lymphocyte Count Ratio

Objective: To assess the efficacy of neutrophil-lymphocyte count ratio in predicting the severity of covid-19 Materials and Methods: The patients with positive results for COVID-19 were shifted to COVID ITC, CMH, Multan. The clinical histories of confirmed patients of COVID-19 during February 2020 to May 2021 were reviewed. The patients were divided into 4 classes, mild, common, severe, and fatal, according to guidelines of COVID-19 i.e., trial version 7. Data was collected regarding age, sex, smoking history, temperature, epidemiological history, clinical symptoms, and laboratory findings of all included patients including NLCR. Results: The mean NLCR of Mild and Severe Group was 2.77±1.23 and 20.31±4.45, respectively, (p=0.000). (Table. II). The area under the curves of NLCR was larger than neut, suggesting the optimal performance of NLCR with cut-off value 5.89. The sensitivity and specificity of NLCR was 85% and 95%, respectively. (Table. III). Conclusion: It can be concluded that an increase in NLCR levels can indicate that the covid-19 disease is moving towards exacerbation. NLCR can be recommended as a novel and highly sensitive and specific indicator for severity prediction in Covid-19 patients. Keywords: Emerging, Marker, Severity, Covid-19, Neutrophils, Lymphocytes, Ratio

Neutrophil count, lymphocyte count and neutrophil-to-lymphocyte ratio in relation to response to adjunctive dexamethasone treatment in community-acquired pneumonia

BackgroundIt is hypothesised that community-acquired pneumonia (CAP) patients with more severe disease or inflammation might benefit more from adjunctive corticosteroid treatment. Neutrophil count, lymphocyte count and neutrophil-lymphocyte ratio (NLR) have been associated with inflammation and disease severity in CAP. We investigated the interaction between these parameters and adjunctive dexamethasone effects on clinical outcomes in CAP. MethodsWe conducted a post hoc analysis of the randomised placebo-controlled Santeon-CAP trial (n = 401), which showed a positive effect of adjunctive oral dexamethasone on length of stay (LOS) in CAP patients. White blood cell (WBC) count, neutrophil count, NLR (highest tertile vs. lowest two tertiles) and lymphocyte count (lowest tertile vs. highest two tertiles) were examined as potential effect modifiers of treatment with dexamethasone on LOS (primary outcome) and ICU-admission, 30-day mortality and hospital readmission. ResultsWBC differential counts were available for 354 patients. The effect of dexamethasone on LOS was more pronounced in high WBC count, high neutrophil count or high NLR subgroups (difference in median LOS of 2 days versus zero days in the reference subgroups, p for interaction < 0.05). There was no effect modification for the other outcomes. Patients with low WBC and low neutrophil counts did not benefit from dexamethasone, while hospital readmission rate was higher in those treated with dexamethasone (6% vs. 11%). ConclusionsWBC count and/or neutrophil might be easily available biomarkers to guide selection of CAP patients who are more likely to benefit from adjunctive dexamethasone treatment. Future prospective trials are needed to confirm this predictive potential.

The Impact of Neutrophil-Lymphocyte Count Ratio in COVID-19: A Systematic Review and Meta-Analysis.

Background: The neutrophil–lymphocyte count ratio (NLR) has emerged as a potential prognostic tool for different diseases. In the current coronavirus disease (COVID-19) pandemic, the NLR may be a useful tool for risk scarification and the optimal utilization of limited healthcare resources. However, there is no consensus regarding the optimal value of NLR, and the association with disease severity and mortality. Thus, this study aims to systematically analyze the current evidence of the utility of baseline NLR as a predictive tool for mortality, disease severity in COVID-19 patients. Methods: A compendious screening of electronic databases up to June 15, 2021, was done after enlisting the protocol in PROSPERO (CRD42020202659). Studies evaluating the utility of baseline NLR in COVID-19 are included for this review as per the PRISMA statement. Results: We retrieved a total of 13112 and 12986 COVID-19 patients for survivability and severity over 90 studies. The expired and critically sick patients had elevated baseline NLR on admission, in comparison to survivors and noncritical patients. (SMD = 3.82; 95% CI: 2.79-4.85; I2 = 100% and SMD = 1.42; 95% CI: 1.22-1.63; I2 = 95%, respectively). The summary receiver operating curve analysis for mortality (AUC = 0.87; 95% CI: 0.86-0.87; I2 = 94.7%), and severity (AUC = 0.82; 95% CI: 0.80-0.84; I2 = 79.7%) were also suggestive of its significant predictive value. Conclusions: The elevated NLR on admission in COVID-19 patients is associated with poor outcomes.