scholarly journals Neutrophil-Lymphocyte Ratio as a Potential Biomarker for Delirium in the Intensive Care Unit

2021 ◽  
Vol 12 ◽  
Author(s):  
Chai Lee Seo ◽  
Jin Young Park ◽  
Jaesub Park ◽  
Hesun Erin Kim ◽  
Jaehwa Cho ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Early Detection ◽  
Inflammatory Markers ◽  
Inflammatory Marker ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Icu Admission ◽  
Potential Biomarker ◽  
Significant Difference

Background: Recognition and early detection of delirium in the intensive care unit (ICU) is essential to improve ICU outcomes. To date, neutrophil-lymphocyte ratio (NLR), one of inflammatory markers, has been proposed as a potential biomarker for brain disorders related to neuroinflammation. This study aimed to investigate whether NLR could be utilized in early detection of delirium in the ICU.Methods: Of 10,144 patients who admitted to the ICU, 1,112 delirium patients (DE) were included in the current study. To compare among inflammatory markers, NLR, C-reactive protein (CRP), and white blood cell (WBC) counts were obtained: the mean NLR, CRP levels, and WBC counts between the initial day of ICU admission and the day of initial delirium onset within DE were examined. The inflammatory marker of 1,272 non-delirium patients (ND) were also comparatively measured as a supplement. Further comparisons included a subgroup analysis based on delirium subtypes (non-hypoactive vs. hypoactive) or admission types (elective vs. emergent).Results: The NLR and CRP levels in DE increased on the day of delirium onset compared to the initial admission day. ND also showed increased CRP levels on the sixth day (the closest day to average delirium onset day among DE) of ICU admission compared to baseline, while NLR in ND did not show significant difference over time. In further analyses, the CRP level of the non-hypoactive group was more increased than that of the hypoactive group during the delirium onset. NLR, however, was more significantly increased in patients with elective admission than in those with emergent admission.Conclusion: Elevation of NLR was more closely linked to the onset of delirium compared to other inflammatory markers, indicating that NLR may play a role in early detection of delirium.

scholarly journals Correlation of Platelet-Lymphocyte Ratio (PLR) as 28-Days Sepsis Mortality Predictor in Intensive Care Unit of RSMH Palembang

2021 ◽  
Vol 1 (2) ◽  
pp. 43-62
Author(s):  
Tiara Santi Rizal ◽  
Fredi Heru Irwanto ◽  
Rizal Zainal ◽  
Mgs Irsan Saleh
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Inflammatory Response ◽  
Sensitivity And Specificity ◽  
Inflammatory Marker ◽  
Sepsis Mortality ◽  
Roc Curve Analysis ◽  
Lymphocyte Ratio ◽  
Morbidity Score ◽  
Anti Inflammatory

Introduction. Inflammatory and anti-inflammatory response are important in pathophysiology and mortality of sepsis. Platelet as first line inflammatory marker was found increasing during early phase of infection. Decrease in lymphocyte was caused by disrupted balance between inflammatory and anti-inflammatory response. Platelet-to- lymphocyte ratio (PLR) is a cheap and accessible biomarker of sepsis mortality. This study aims to find the sensitivity and specificity of PLR as mortality predictor of sepsis in 28 days. Methods. This observational analytic study with retrospective cohort design was conducted to 91 sepsis patients in intensive care unit of Dr. Mohammad Hoesin Palembang Central Hospital between January and December 2019. Samples were secondarily collected from medical record during June-July 2020. Data was analyzed using chi-square test, cog regression test, and ROC curve analysis. Results. The result found 50 patients (54,9%) died in 28 days. Morbidity score (Charlson) was the only statistically significant mortality parameter (p=0,009). The study reported PLR cut-off point of >272,22. The sensitivity and specificity of PLR as 28-days sepsis mortality predictor are 84% and 80,49% respectively. Conclusion. PLR is alternatively reliable mortality predictor in sepsis patient, accounted to its relatively high sensitivity and specificity.

scholarly journals The Predictive Role of Neutrophil to Lymphocyte Ratio and Platelet to Lymphocyte Ratio on Intensive Care Unit Admission and Mortality of COVID-19 Patients in Iran

2021 ◽  
Author(s):  
Peiman Foroughi ◽  
Mojtaba Varshochi ◽  
Mehdi Hassanpour ◽  
Meisam Amini ◽  
Behnam Amini ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Risk Factor ◽  
Intensive Care ◽  
Independent Risk Factor ◽  
Multivariate Logistic Regression Analysis ◽  
Neutrophil To Lymphocyte Ratio ◽  
Platelet To Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Icu Admission ◽  
Inflammatory Index

Abstract Since the outbreak of COVID-19 several studies conducted to identify predictive factors which are associated with prognosis of COVID-19. In this study we aimed to determine whether the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) could help the clinicians to predict intensive care unit (ICU) admission and mortality of COVID-19 patients. This retrospective cohort study involved examining the medical records of 311 Iranian COVID-19 patients from 22 July 2020 to 22 August 2020. All characteristic data and laboratory results were recorded. The receiver operating characteristic (ROC) curve was used to identify the predictive value of studied parameters for ICU admission and death. Comparison of data revealed that some factors were jointly higher in non-survivors and ICU admitted patients than survivors and non-ICU admitted patients, such as: age, hemoglobin (HB), NLR, derived neutrophil-to-lymphocyte ratio (dNLR), PLR, systemic inflammatory index (SII), lactate dehydrogenase (LDH), Respiratory diseases, ischemic heart disease (IHD). Multivariate logistic regression analysis showed that only hypertension (OR 3.18, P=0.02) is an independent risk factor of death in COVID-19 patients, and also PLR (OR 1.02, P=0.05), hypertension (OR 4.00, P=0.002) and IHD (OR 5.15, P=0.008) were independent risk factor of ICU admission in COVID-19 patients. This study revealed that the NLR, PLR, platelet-to-white blood Cell ratio (PWR), dNLR and SII are valuable factors for predicting ICU admission and mortality of COVID-19 patients.

scholarly journals The Effects of Neutrophil-Lymphocyte Ratio, Platelet-Lymphocyte Ratio and Prognostic Markers in Determining the Mortality in Patients Diagnosed With Pneumonia in Intensive Care

2021 ◽  
Author(s):  
Ömer Faruk Altaş ◽  
Mehmet Kızılkaya
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Mortality Risk ◽  
Demographic Data ◽  
Apache Ii ◽  
Prognostic Scores ◽  
Characteristic Analysis ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Point Increase

Objective: In this study, we aimed to reveal the level of predicting mortality of the Neutrophil/Lymphocyte (NLR) and Platelet/Lymphocyte Ratios (TLR) calculated in patients hospitalized with the diagnosis of pneumonia in the intensive care unit when compared with other prognostic scores. Method: The hospital records of 112 patients who were admitted to the intensive care unit between January 2015 and January 2018 and met the inclusion criteria were retrospectively reviewed. The patients’ demographic data, the NLR and PLR levels, and the APACHE II (Acute Physiology and Chronic Health Evaluation II) and SOFA (Sequential Organ Failure Assessment) scores were calculated from the patient files. Results: Of the 112 patients examined, 70 were males. The risk analysis showed that the male gender had 2.7 times higher risk of mortality. The NLR, PLR, APACHE II, and SOFA values were found statistically significant in predicting mortality (p<0.001). An evaluation of the risk ratios demonstrated that each one point increase in the NLR increased the mortality risk by 5%, and each one point increase in the SOFA score increased the mortality risk by 13% (p<0.05). In the ROC (receiver operating characteristic) analysis, the NLR assessment proved to be the most powerful, most specific, and sensitive test. The cut-off values were 11.3 for the NLR, 227 for the PLR, 29.8 for the APACHE II scores, and 5.5 for the SOFA scores. Conclusion: We believe that NLR and PLR are strong and independent predictors of mortality that can be easily and cost-effectively tested.

scholarly journals Neutrophil-lymphocyte ratio in the early diagnosis of sepsis in an intensive care unit: a case-control study

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Eduarda Cristina Martins ◽  
Lilian da Fe Silveira ◽  
Karin Viegas ◽  
Andrea Diez Beck ◽  
Geferson Fioravantti Júnior ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Early Diagnosis ◽  
Case Control Study ◽  
Case Control ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Control Study

scholarly journals The Correlation of Platelet Lymphocyte Ratio (PLR) as 28 Days Sepsis Mortality Predictor in Intensive Care Unit RSMH Palembang

2020 ◽  
Vol 1 (2) ◽  
pp. 42-62
Author(s):  
Tiara Shanty
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Inflammatory Response ◽  
Sensitivity And Specificity ◽  
Inflammatory Marker ◽  
Sepsis Mortality ◽  
Roc Curve Analysis ◽  
Lymphocyte Ratio ◽  
Morbidity Score ◽  
Anti Inflammatory

Introduction. Inflammatory and anti-inflammatory response are important in pathophysiology and mortality of sepsis. Platelet as first line inflammatory marker was found increasing during early phase of infection. Decrease in lymphocyte was caused by disrupted balance between inflammatory and anti-inflammatory response. Platelet-to-lymphocyte ratio (PLR) is a cheap and accessible biomarker of sepsis mortality. This study aims to find the sensitivity and specificity of PLR as mortality predictor of sepsis in 28 days. Method. This observational analytic study with retrospective cohort design was conducted to 91 sepsis patients in intensive care unit of Dr. Mohammad Hoesin Palembang Central Hospital between January and December 2019. Samples were secondarily collected from medical record during June-July 2020. Data was analyzed using chi-square test, cog regression test, and ROC curve analysis. Results. The result found 50 patients (54,9%) died in 28 days. Morbidity score (Charlson) was the only statistically significant mortality parameter (p=0,009). The study reported PLR cut-off point of >272,22. The sensitivity and specificity of PLR as 28-days sepsis mortality predictor are 84% and 80,49% respectively. Conclusion. PLR is alternatively reliable mortality predictor in sepsis patient, accounted to its relatively high sensitivity and specificity.

scholarly journals Lactate Clearance as a Predictive Marker of Mortality in Adult Intensive Care Unit

2020 ◽  
Vol 5 (2) ◽  
pp. 32-38
Author(s):  
Shirish Raj Joshi ◽  
Renu Gurung ◽  
Subhash Prasad Acharya ◽  
Bashu Dev Parajuli ◽  
Navindra Raj Bista
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Blood Lactate ◽  
Lactate Concentration ◽  
Blood Lactate Concentration ◽  
Lactate Clearance ◽  
Icu Mortality ◽  
Adult Intensive Care Unit ◽  
Icu Admission ◽  
Significant Difference

Introduction: Lactate clearance has been widely investigated. Serial lactate concentrations can be used to examine disease severity and predict mortality in the intensive care unit. We investigated the diagnostic accuracy of lactate concentration and lactate clearance in predicting mortality in critically ill patients during the first 24 hours in Intensive Care Unit (ICU).Methods: It was a Prospective, observational study conducted in ICU. Sixty eight consecutive patients having blood lactate level >2 mmol/L were included irrespective of disease and postoperative status. We measured blood lactate concentration at ICU admission(H0), at six hours(H6), 12 hours(H12), and 24 hours(H24). Lactate clearance was measured for H0-H6, H0-H12 and H0-H24 time period.Results: ICU mortality was 33.8%. Lactate clearance was 15.80 ± 17.21% in survivors and 1.73±11% in non survivors for the H0-H6 (p = 0.001) and remained higher in survivors than in non survivors over the study period of 24 hours; 17.97±15 vs. -2.04±19.84% for H0-H12 and 27.40 ± 11.41% vs. -14.83 ± 26.84% for the H0-H24 period (p < 0.001 for each studied period). There was significant difference in lactate concentration (static) between survivors and non survivors during the course of initial 24 hours. The best predictor of ICU mortality was lactate clearance for the H0-H24 period (AUC =0.89; 95% CI 0.78-1.01). Logistic regression found that H0-H24 lactate clearance was independently correlated to a survival status (p = 0.005, OR = 0.922 and 95% CI 0.871-0.976).Conclusion: Blood lactate concentration and lactate clearance are both predictive for mortality during initial 24 hours of ICU admission.

scholarly journals Postoperative Inflammatory Marker Surveillance in Colorectal Peritoneal Carcinomatosis

2021 ◽  
Author(s):  
Sasinthiran Thiagarajan ◽  
Joey Wee-Shan Tan ◽  
Siqin Zhou ◽  
Qiu Xuan Tan ◽  
Josephine Hendrikson ◽  
...  
Keyword(s):  
Peritoneal Carcinomatosis ◽  
Inflammatory Markers ◽  
Inflammatory Marker ◽  
Prognostic Significance ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Cox Proportional Hazard ◽  
Kaplan Meier ◽  
Clinicopathologic Parameters ◽  
Cox Proportional Hazard Regression

Abstract Background The prognostic significance of inflammatory markers in solid cancers is well-established, albeit with considerable heterogeneity. This study sought to investigate the postoperative inflammatory marker trend in peritoneal carcinomatosis (PC), with a focus on colorectal PC (CPC), and to propose optimal surveillance periods and cutoffs. Methods Data were collected from a prospectively maintained database of PC patients treated at the authors’ institution from April 2001 to March 2019. The platelet–lymphocyte ratio (PLR), the neutrophil–lymphocyte ratio (NLR), and the lymphocyte–monocyte ratio (LMR) were collected preoperatively and on postoperative days 0, 1 to 3, 4 to 7, 8 to 21, 22 to 56, and 57 to 90 as averages. Optimal surveillance periods and cutoffs for each marker were determined by maximally selected rank statistics. The Kaplan–Meier method and Cox proportional hazard regression models were used to investigate the association of inflammatory markers with 1-year overall survival (OS) and recurrence-free survival (RFS) using clinicopathologic parameters. Results The postoperative inflammatory marker trend and levels did not differ between the patients with and those without hyperthermic intraperitoneal chemotherapy (HIPEC). Low postoperative LMR (days 4–7), high postoperative NLR (days 8–21), and high postoperative PLR (days 22–56) were optimal for prognosticating poor 1-year OS, whereas high postoperative PLR and NLR (days 57–90) and low postoperative LMR (days 8–21) were associated with poor 1-year RFS. A composite score of these three markers was prognostic for OS in CPC. Conclusions The reported cutoffs should be validated in a larger population of CPC patients. Future studies should account for the inflammatory response profile when selecting appropriate surveillance periods.

scholarly journals Is the Neutrophil/Lymphocyte Ratio a Marker of Mortality in ARDS Patients Followed in Pulmonary Intensive Care Unit?

2019 ◽  
Vol 20 (-1) ◽  
pp. 9-9
Author(s):  
Nazli Deniz Atik ◽  
◽  
Esra Bahcivan ◽  
Pervin Korkmaz Ekren ◽  
Funda Elmas Uysal ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio

scholarly journals Severity and Outcome Detection for the Cancer Patients with COVID-19 Using Machine Learning Models

2021 ◽  
Author(s):  
Akbar Davoodi ◽  
Shaghayegh Haghjooy Javanmard ◽  
Golnaz Vaseghi ◽  
Amirreza Manteghinejad
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Cancer Patients ◽  
Cancer Center ◽  
Support Vector ◽  
Neutrophil Lymphocyte Ratio ◽  
Icu Admission ◽  
Reactive Protein ◽  
Risk Of Death

Abstract Background:The COVID-19 pandemic challenges the healthcare system to provide enough resources to battle the pandemic without jeopardizing routine treatments. As a result, this is important that we can predict the outcomes of patients at the time of admission. This study aims to apply different machine learning (ML) models for predicting Intensive Care Unit (ICU) admission and mortality of Cancer Patients infected with COVID-19.Methods:This study's data were collected from a referral cancer center in Iran. The study included all patients with cancer and a confirmed diagnosis of COVID-19.Different ML prediction algorithms like Logistic Regression (LR), Naïve Bayes (NB), k-Nearest Neighbours (kNN), Random Forest (RF), and Support Vector Machine (SVM) were used. Also, we applied the SelectKBest method to find the most important features for predicting ICU admission and mortality.Results:Three hundred thirty-nine patients enrolled in the study. One hundred fifteen were admitted to the Intensive Care Unit (ICU), and 118 patients died during the hospital admission. The Area Under Curve (AUC) for predicting mortality is 0.61 for LR, 0.74 for NB, 0.61 for kNN, 0.6 for SVM, and 0.79 for RF. The AUC for predicting ICU admission is 0.61 for LR, 0.74 for NB, 0.56 for kNN, 0.55 for SVM, and 0.7 for RF.C-reactive protein (CRP), Aspartate transaminase (AST), and Neutrophil-Lymphocyte Ratio (NLR) also are the most common features in predicting ICU admission and mortality.Conclusion:Our findings show the promise of different AI methods for predicting the risk of death or ICU in cancer patients infected with COVID-19, highlighting the importance of first laboratory results and patients' symptoms.

scholarly journals Designing and Evaluating the Establishment of Admission Criteria for Patients in an Intensive Care Unit: A Descriptive Study in Iran

2021 ◽  
Author(s):  
Fariba Hosseinpour ◽  
Mahyar Sedighi ◽  
Fariba Hashemi ◽  
Sima Rafiei
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Length Of Stay ◽  
Statistical Tests ◽  
P Value ◽  
Admission Criteria ◽  
Total Cost ◽  
Icu Admission ◽  
Study Results ◽  
Significant Difference

Background: A few studies have reviewed and revised ICU admission criteria based on specific circumstances and local conditions. The aim was to develop ICU admission criteria and compare the cost, mortality, and length of stay among identified admission priorities. Methods: This was a cross-sectional study conducted in an intensive care unit of a training hospital in Qazvin, Iran. The study was conducted among 127 patients admitted to ICU from July to September 2019. The data collection tool was a self-designed checklist, which included items regarding patients' clinical data and their billing, type of diagnosis, level of consciousness at the time of hospitalization based on GCS scale or Glasgow Coma Scale, length of stay, and patient status at the time of discharge. Descriptive statistical tests were used to describe study variables, and in order to determine the relationship between study variables, ANOVA and Chi-square test were used. Results: A set of criteria were designed to prioritize patient admissions in ICU. Based on the defined criteria, patients were categorized into four groups based on patient's stability, hemodynamic, and respiration. Study findings revealed that a significant percentage of patients were admitted to the ward while in the second and third priorities of hospitalization (26.8 % and 32.3 %, respectively). There was a statistically significant difference in the four groups in terms of patients' age, total cost, and insurance share of the total cost (P-value < 0.05). Conclusion: Study results emphasize the necessity to classify patients based on defined criteria to efficiently use available resources.

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