Neutrophil-to-lymphocyte ratio as a predictive marker for severe pediatric sepsis

The relationship of COVID-19 severity with laboratory findings and neutrophil-to-lymphocyte ratio in patients admitted to a large teaching hospital in Iran: A cross-sectional study

Background and Aims

COVID-19 patients might be admitted to the hospital based on their clinical manifestations or to the intensive care unit (ICU) due to the severity of their symptoms or critical situation. Our main objective was to investigate clinical and demographic factors influencing COVID-19 patients' admission to the ICU and length of stay (LOS) using extracted data from the hospital information systems in Iran.

Methods

The data of hospitalized patients with confirmed COVID-19 were retrieved from the health information system of Imam Khomeini Hospital Complex, Tehran, Iran between March 2020 and February 2022. The primary outcome was the ICU admission, and the secondary outcome was the LOS. The correlation analysis between laboratory findings and demographic data with ICU admission and LOS was done using SPSS 21.0, and p < 0.05 was considered significant.

Results

Of all the 4156 patients, 2391 (57.5%) were male and the mean age was 58.69 ± 8.19 years. Of these, 9.5% of patients were admitted to ICU at any time point during their hospital stay. Age and laboratory variables such as neutrophil-to-lymphocyte ratio (NLR), ALT (U/L), albumin (g/dL), plasma glucose (mg/dL), ferritin levels (ng/mL), and phosphorous levels (mg/dL) shown the significant relationship with ICU admission. Also, being a smoker and having hypoxemia had a significant relationship with longer stays in the hospital. In this study, we validated a cut-off value of 4.819 for NLR, calculated at hospitalization, as a useful predictor of disease progression and occurrence of serious clinical outcomes, such as ICU admission.

Conclusion

The study examined various clinical factors associated with ICU admission in COVID-19 patients. The findings suggest that certain factors can increase the risk of ICU admission and influence the length of hospital stay which should be focused in future studies.

The prognostic value of the combined neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-platelet ratio (NPR) in sepsis

Sepsis is a severe disease characterized by high mortality rates. Our aim was to develop an early prognostic indicator of adverse outcomes in sepsis, utilizing easily accessible routine blood tests. A retrospective analysis of sepsis patients from the MIMIC-IV database was conducted. We performed univariate and multivariate regression analyses to identify independent risk factors associated with in-hospital mortality within 28 days. Logistic regression was utilized to combine the neutrophil-to-lymphocyte ratio (NLR) and the neutrophil-to-platelet ratio (NPR) into a composite score, denoted as NLR_NPR. We used ROC curves to compare the prognostic performance of the models and Kaplan-Meier survival curves to assess the 28 day survival rate. Subgroup analysis was performed to evaluate the applicability of NLR_NPR in different subpopulations based on specific characteristics. This study included a total of 1263 sepsis patients, of whom 179 died within 28 days of hospitalization, while 1084 survived beyond 28 days. Multivariate regression analysis identified age, respiratory rate, neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-platelet ratio (NPR), hypertension, and sequential organ failure assessment (SOFA) score as independent risk factors for 28 day mortality in septic patients (P < 0.05). Additionally, in the prediction model based on blood cell-related parameters, the combined NLR_NPR score exhibited the highest predictive value for 28 day mortality (AUC = 0.6666), followed by NLR (AUC = 0.6456) and NPR (AUC = 0.6284). Importantly, the performance of the NLR_NPR score was superior to that of the commonly used SOFA score (AUC = 0.5613). Subgroup analysis showed that NLR_NPR remained an independent risk factor for 28 day in-hospital mortality in the subgroups of age, respiratory rate, and SOFA, although not in the hypertension subgroup. The combined use of NLR and NPR from routine blood tests represents a readily available and reliable predictive marker for 28 day mortality in sepsis patients. These results imply that clinicians should prioritize patients with higher NLR_NPR scores for closer monitoring to reduce mortality rates.

Potential biomarkers used for risk estimation of pediatric sepsis-associated organ dysfunction and immune dysregulation

Pediatric sepsis is a serious issue globally and is a significant cause of illness and death among infants and children. Refractory septic shock and multiple organ dysfunction syndrome are the primary causes of mortality in children with sepsis. However, there is incomplete understanding of mechanistic insight of sepsis associated organ dysfunction. Biomarkers present during the body's response to infection-related inflammation can be used for screening, diagnosis, risk stratification/prognostication, and/or guidance in treatment decision-making. Research on biomarkers in children with sepsis can provide information about the risk of poor outcomes and sepsis-related organ dysfunction. This review focuses on clinically used biomarkers associated with immune dysregulation and organ dysfunction in pediatric sepsis, which could be useful for developing precision medicine strategies in pediatric sepsis management in the future. IMPACT: Sepsis is a complex syndrome with diverse clinical presentations, where organ dysfunction is a key factor in morbidity and mortality. Early detection of organ complications is vital in sepsis management, and potential biomarkers offer promise for precision medicine in pediatric cases. Well-designed studies are needed to identify phase-specific biomarkers and improve outcomes through more precise management.

Predictive Value of Inflammatory Markers NLR, PLR, APRI, SII, and Liver Function Tests in Systemic Inflammatory Response Syndrome Detection in Full-Term Newborns

Systemic Inflammatory Response Syndrome (SIRS) is associated with significant morbidity and mortality in full-term newborns. This study aimed to evaluate the predictive value of the Neutrophil-to-Lymphocyte Ratio (NLR), Derived Neutrophil-to-Lymphocyte Ratio (dNLR), Platelet-to-Lymphocyte Ratio (PLR), Neutrophil, Lymphocyte, and Platelet Ratio (NLPR), AST-to-Platelet Ratio Index (APRI), and Systemic Immune-Inflammation Index (SII) in identifying the risk for SIRS development in full-term newborns. Conducted between January 2023 and January 2024, this observational cohort study compared full-term newborns diagnosed with SIRS with newborns without SIRS, measuring the inflammatory markers within the first day of life and three days post-birth. The study included 229 newborns, 81 with SIRS and 148 controls without SIRS. Statistically significant differences were observed in NLR (3.81 vs. 2.20, p < 0.0001), PLR (68.12 vs. 52.30, p < 0.0001), and liver enzymes (AST 40.96 U/L vs. 31.58 U/L, ALT 34.66 U/L vs. 22.46 U/L, both p < 0.0001) between the groups. The NLPR demonstrated substantial diagnostic value, with a sensitivity of 78.36% and specificity of 83.52% at 72 h (p < 0.0001). Regression analysis highlighted that the NLPR and SII were strongly predictive of SIRS, with the NLPR showing over three-times higher SIRS risk (HR 3.29, p < 0.0001) and SII indicating nearly 3.5 times the risk (HR 3.47, p < 0.0001). The NLPR, APRI, and SII showed similar prediction values to CRP levels measured on the first and third days of life (HR 3.16). Inflammatory markers like NLR, PLR, and systemic indices such as NLPR and SII, alongside liver function tests, are significant predictors of SIRS in full-term newborns. These findings support the integration of these markers into routine neonatal care, allowing for early identification and potentially improved management of newborns at risk for SIRS, thereby enhancing clinical outcomes.

Exploring systemic inflammation in children with chronic kidney disease: correlates of interleukin 6

BACKGROUND

Systemic inflammation (SI) is linked to chronic kidney disease (CKD) progression and multiple complications. Data regarding SI biomarkers in pediatric patients are scarce. This case-control and cross-sectional study investigates the correlation of neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), total iron binding capacity (TIBC) and serum albumin to serum interleukin-6 (IL-6).

METHODS

NLR and PLR were measured in 53 patients (median age: 12.9 years), including 17 on dialysis and 36 with a median glomerular filtration rate of 39 ml/min/1.73m2, and in 25 age and sex-matched healthy controls. Iron profile, serum albumin and IL-6 were measured in the patient group. IL-6 levels > 3rd quartile were classified as high.

RESULTS

Patients presented higher NLR and PLR and particularly those on dialysis (p < 0.001 and p = 0.001). We observed a significant correlation between natural logarithm (ln) of IL-6 (lnIL-6) and NLR (rs = 0.344, p = 0.014), serum albumin (rs = -0.350, p = 0.011) and TIBC (rs = -0.345, p = 0.012) after adjustment for CKD stage, while the correlation between lnIL-6 and PLR was not significant (rs = 0.206, p = 0.151). Combination of NLR, serum albumin and TIBC predicted high IL-6 (13 patients) with an AUC of 0.771 (95% CI 0.608-0.943). Pairing of NLR ≥ 1.7 and TIBC ≤ 300 μg/dL exhibited the highest sensitivity (76.9%), while incorporating serum albumin ≤ 3.8 g/dL along with them achieved the highest specificity (95%) for detecting high IL-6 levels.

CONCLUSION

Both NLR and PLR levels increase in CKD, especially in patients on chronic dialysis. NLR, rather than PLR, along with TIBC and serum albumin, are associated with IL-6 in pediatric CKD.

Prognostic Nutritional Index Enhances the Discriminatory Ability of Procalcitonin for Predicting Pediatric Sepsis

Objective. Improving diagnostic ability of pediatric sepsis is of great significance for reducing the mortality of sepsis. This study explored the discriminatory capacity of nutritional index (PNI) in pediatric sepsis. Methods. We retrospectively enrolled 134 children with suspected sepsis and collected their clinical and laboratory data. Receiver operating characteristic curves (ROC), decision curve analysis (DCA) and net reclassification improvement (NRI) were performed to compare the predictive significance of the PNI, procalcitonin (PCT) and their combination. Results. Among 134 patients, 65 children were diagnosed with sepsis and 69 children with non-sepsis. PCT and PNI were independently associated with pediatric sepsis. PCT was superior to PNI to predict pediatric sepsis. The model based on PCT + PNI improved the predictive capacity than them alone, as demonstrated by ROC, DCA and NRI, respectively. Conclusion. PNI was independently associated with pediatric sepsis, and addition of PNI could improve the capacity of PCT to predict pediatric sepsis.

The landscape of immune dysregulation in pediatric sepsis at a single-cell resolution

Recognizing immune dysregulation as a hallmark of sepsis pathophysiology, leukocytes have attracted major attention of investigation. While adult and pediatric sepsis are clinically distinct, their immunological delineation remains limited. Breakthrough of single cell technologies facilitated the characterization of immune signatures. We tackled to delineate immunological profiles of pediatric sepsis at a single-cell level by analyzing blood samples from six septic children, at both acute and recovery phases, and four healthy children. 16 single-cell transcriptomic datasets (96,156 cells) were analyzed and compared to adult sepsis dataset. We showed a unique shift in neutrophil subpopulations and functions between acute and recovery phases, along with examining the regulatory role of resistin. Neutrophil signatures were comparable between adult and pediatric sepsis. Innate-like CD4 T cells were predominantly and uniquely observed in acute phase of pediatric sepsis. Our study provides a thorough and comprehensive understanding of immune dysregulation in pediatric sepsis.

The Neutrophil-to-Lymphocyte Ratio (NLR) Can Predict Sepsis's Presence and Severity in Malnourished Infants-A Single Center Experience

Sepsis represents one of the leading causes of death in newborns and infants, and prompt diagnosis is essential for achieving favorable outcomes. Regarding malnourished children with concurrent infection, most studies have focused, besides blood culture, on C-reactive protein and procalcitonin. Because malnutrition has a deleterious effect on cellular immune competence, the present study characterized the acute-phase response, including hematological indices, in response to sepsis. Among the examined laboratory biomarkers, procalcitonin and neutrophil-to-lymphocyte ratio were the most accurate discriminators between sepsis patients and those with bacterial infection. Moreover, these two parameters showed a gradual increase between sepsis, severe sepsis, and septic shock patients (p < 0.001). Subgroup analysis of the sepsis group revealed positive correlations of NLR with prolonged ICU stay (<0.001), acute organ dysfunction (0.038), mechanical ventilation (<0.001), and fatality (<0.001). In summary, our results suggest that the neutrophil-to-lymphocyte ratio can be used as an auxiliary diagnostic index in discriminating the presence and severity of bacterial sepsis in malnourished infants.

Predicting Clinical Deterioration and Mortality at Differing Stages During Hospitalization: A Systematic Review of Risk Prediction Models in Children in Low- and Middle-Income Countries

OBJECTIVE

To determine which risk prediction model best predicts clinical deterioration in children at different stages of hospital admission in low- and middle-income countries.

METHODS

For this systematic review, Embase and MEDLINE databases were searched, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The key search terms were "development or validation study with risk-prediction model" AND "deterioration or mortality" AND "age 0-18 years" AND "hospital-setting: emergency department (ED), pediatric ward (PW), or pediatric intensive care unit (PICU)" AND "low- and middle-income countries." The Prediction Model Risk of Bias Assessment Tool was used by two independent authors. Forest plots were used to plot area under the curve according to hospital setting. Risk prediction models used in two or more studies were included in a meta-analysis.

RESULTS

We screened 9486 articles and selected 78 publications, including 67 unique predictive models comprising 1.5 million children. The best performing models individually were signs of inflammation in children that can kill (SICK) (ED), pediatric early warning signs resource limited settings (PEWS-RL) (PW), and Pediatric Index of Mortality (PIM) 3 as well as pediatric sequential organ failure assessment (pSOFA) (PICU). Best performing models after meta-analysis were SICK (ED), pSOFA and Pediatric Early Death Index for Africa (PEDIA)-immediate score (PW), and pediatric logistic organ dysfunction (PELOD) (PICU). There was a high risk of bias in all studies.

CONCLUSIONS

We identified risk prediction models that best estimate deterioration, although these risk prediction models are not routinely used in low- and middle-income countries. Future studies should focus on large scale external validation with strict methodological criteria of multiple risk prediction models as well as study the barriers in the way of implementation.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews: Prospero ID: CRD42021210489.

Changes and Rate of Change in Neutrophil-Lymphocyte Ratio (∆NLR) as an Early Prognostic Marker for the Severity of Outcomes in Patients With COVID-19 and Its Applicability in Other Viral and Bacterial Diseases

INTRODUCTION

COVID-19 is a global pandemic that has spread rapidly and resulted in numerous deaths worldwide. Many inflammatory markers such as neutrophil-lymphocyte ratio (NLR), D-dimer, serum ferritin, C-reactive protein (CRP), and interleukin-6 (IL-6) were used for the diagnosis and prognosis of COVID-19.

METHODS

We have proposed using Delta NLR (0-48 hours) (∆NLR) as an early diagnostic marker for COVID-19 and other inflammatory disorders. We have created a prediction model based on six variables: overall severity, death, shifting to the ICU, length of stay, oxygen requirement, and ventilator support. Prediction models help us prepare for future pandemics through early diagnosis and management.

RESULTS

A total of 1,865 patient records were retrieved from the database. The final sample available for analysis was 461. Change in NLR or ∆NLR was significant for all the models (except for length of stay) created by logistic regression.

CONCLUSION

An independent predictor of the poor prognosis of COVID-19 is the severity of the disease in the initial one or two days. ∆NLR is a unique marker, and its scope of use in other disorders' prognoses must be further researched. The prediction models also help us in decision-making strategies and also prepare us for future pandemics.

Establishment and evaluation of a prediction model for acute gastrointestinal injury in patients with prolonged disorder of consciousness

Objective

To establish a prediction model for acute gastrointestinal injury (AGI) in patients with prolonged disorder of consciousness (pDOC) and to evaluate and apply the prediction model. 

Methods

The clinical data of 165 patients with pDOC admitted to the hyperbaric oxygen department from January 2021 to December 2021 were retrospectively reviewed, and the patients were divided into an AGI group (n = 91) and an N-AGI group (n = 74) according to whether AGI occurred. A prediction model was built by fitting multiple independent influencing factors through logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the model, the Hosmer–Lemeshow (H–L) test was used to evaluate the goodness-of-fit of the model, and the ROC curve and calibration curve were drawn to evaluate the predictive performance. A nomogram was plotted to visualize the prediction model.

Results

According to the multivariate logistic regression analysis results, the prediction model was finally constructed with the CRS-R score, DAO, PCT, ALB, and I-FABP, and a nomogram was generated. The area under the ROC curve (AUC) of the prediction model was 0.931, the sensitivity was 83.5%, and the specificity was 93.2%. The data were divided into 5 groups for the H–L test (χ² = 2.54, P = 0.468 > 0.05) and into 10 groups for the H–L test (χ² = 9.98, P = 0.267 > 0.05). A calibration curve was drawn based on the test results, indicating that the prediction model has a good goodness-of-fit and good prediction stability.

Conclusion

The prediction model for AGI in pDOC patients constructed in this study can be used in clinical practice and is helpful to predict the occurrence of AGI in pDOC patients.

Prognostic value of neutrophils to lymphocytes and platelets ratio for 28-day mortality in patients with acute respiratory distress syndrome: a retrospective study

Background

Acute respiratory distress syndrome (ARDS) is a rapidly progressive and fatal respiratory failure disease that often occurs in critically ill patients. Since ARDS is associated with immune dysregulation and coagulation abnormalities, it is necessary to identify an appropriate predictor that can accurately predict ARDS mortality based on its pathophysiology. Therefore, this study aimed to evaluate the clinical value of neutrophils to lymphocytes and platelets ratio (N/LPR) in predicting 28-day mortality in ARDS patients.

Methods

From July 2018 to October 2021, the medical records of ARDS patients were retrospective reviewed. Neutrophil count, lymphocyte count, and platelet count were collected, and the neutrophil-to-lymphocyte ratio (NLR) and N/LPR were calculated. Multivariate logistic regression analyses were performed to identify independent predictors of 28-day mortality in ARDS. Receiver operating characteristic (ROC) curve with the area under curve (AUC) was used to evaluate optimal cut-off values for 28-day mortality in ARDS. Kaplan–Meier analysis was used to estimate the 28-day survival probabilities stratified by optimal cut-off values of N/LPR and NLR.

Results

A total of 136 ARDS patients were included in this study and were further divided into survivors (n = 69) and non-survivors (n = 67) groups according to their survival status on day 28. There were no significant differences between the two groups in age, sex, history of smoking and drinking, comorbidities, and reasons of admission (P > 0.05). Non-survivors had significantly higher neutrophil counts, NLR and N/LPR and had significantly lower platelet counts than survivors (P < 0.05). Multivariate regression analysis revealed that N/LPR, NLR and platelet counts were independent predictors for 28-day mortality in ARDS (P < 0.05). The ROC analyses showed that N/LPR with optimal cut-off value of 10.57 (sensitivity: 74.6%; specificity: 72.5%) is a more reliable predictor for 28-day mortality in ARDS than NLR and platelet count (AUC: 0.785 vs. 0.679 vs. 0.326). Further subgroup analysis confirmed that ARDS patients with N/LPR < 10.57 had significantly lower 28-day mortality than patients with N/LPR ≥ 10.57 (P < 0.001). Kaplan–Meier analysis also confirmed that ARDS patients with N/LPR < 10.57 had significantly longer survival.

Conclusion

N/LPR is an independent risk factor associated with 28-day mortality in ARDS patients and shows better performance in predicting mortality rate than NLR.

Predictive Value of Procalcitonin and Neutrophil-to-Lymphocyte Ratio Variations for Bloodstream Infection with Septic Shock

BACKGROUND Little is known of neutrophil-to-lymphocyte ratio (NLR) variations in septic shock. Hence, the predictive value of procalcitonin (PCT) and NLR variations for septic shock in bloodstream infection were explored. MATERIAL AND METHODS We analyzed 146 patients with bloodstream infection admitted to the Intensive Care Unit (ICU) of the First Affiliated Hospital of Anhui Medical University from October 2016 to May 2020. PCT and NLR were evaluated at 0 and 48 h after admission, and their variations (ΔPCT and DNLR) were calculated. The patients were divided into a shock group (n=80) and a non-shock group (n=66) and a gram-positive cocci group (n=69) and a gram-negative bacilli group (n=77). The predictive value of ΔPCT and DNLR was compared among groups. RESULTS AUROC of NLR0h (0.756) higher than PCT0h (0.743).DPCT (0.561 vs 0.301) and ΔNLR (0.609 vs 0.361) were significantly higher in the shock group than in the non-shock group (P<0.05). No significant difference was seen in DPCT and DNLR in the gram-positive cocci infection group. However, the gram-negative bacilli infection group showed a significant difference in ΔPCT (0.606 vs 0.312) and ΔNLR (0.872 vs 0.508) between the shock and non-shock groups (P<0.05). ΔPCT+ΔNLR showed the best area under the curve (0.937), with a high sensitivity (78.80%) and specificity (90.80%), for predicting septic shock. CONCLUSIONS The prediction efficiency of initial NLR is higher than that of PCT. ΔPCT+ΔNLR best predicted septic shock in patients with bloodstream infections, with better accuracy for gram-negative infections.

Value of CRP, PCT, and NLR in Prediction of Severity and Prognosis of Patients With Bloodstream Infections and Sepsis

Objective

To investigate the value of C-reactive protein (CRP), procalcitonin (PCT), and neutrophil to lymphocyte ratio (NLR) in assessing the severity of disease in patients with bloodstream infection and sepsis, and to analyze the relationship between the levels of three inflammatory factors and the prognosis of patients.

Methods

The clinical data of 146 patients with bloodstream infection and sepsis admitted to our intensive care unit (ICU) from October 2016 to May 2020 were retrospectively analyzed. The differences in the levels of inflammatory indicators such as CRP, PCT, and NLR within 24 h in patients with bloodstream infection sepsis with different conditions (critical group, non-critical group) and the correlation between these factors and the condition (acute physiology and chronic health evaluation II, APACHE II score) were analyzed. In addition, the prognosis of all patients within 28 days was counted, and the patients were divided into death and survival groups according to their mortality, and the risk factors affecting their death were analyzed by logistic regression, and the receiver operating characteristic (ROC) curve was used to analyze the value of the relevant indicators in assessing the prognosis of patients.

Results

The levels of NLR, CRP, PCT, total bilirubin (TBIL), glutamic oxaloacetic transaminase (AST), and serum creatinine (Scr) were significantly higher in the critically ill group than in the non-critically ill group, where correlation analysis revealed a positive correlation between CRP, PCT, and NLR and APACHE II scores (P < 0.05). Univariate logistic regression analysis revealed that CRP, PCT, NLR, and APACHE II scores were associated with patient prognosis (P < 0.05). Multi-factor logistic regression analysis found that PCT, NLR, and APACHE II scores were independent risk factors for patient mortality within 28 days (P < 0.05). ROC curve analysis found that PCT and NLR both had an AUC area > 0.7 in predicting patient death within 28 days (P < 0.05).

Conclusion

Inflammatory factors such as NLR, CRP, and PCT have important clinical applications in the assessment of the extent of disease and prognosis of patients with bloodstream infection and sepsis.

Value of the Neutrophil-Lymphocyte Ratio in Predicting COVID-19 Severity: A Meta-analysis

Background

Coronavirus disease 2019 (COVID-19) is highly contagious and continues to spread rapidly. However, there are no simple and timely laboratory techniques to determine the severity of COVID-19. In this meta-analysis, we assessed the potential of the neutrophil-lymphocyte ratio (NLR) as an indicator of severe versus nonsevere COVID-19 cases.

Methods

A search for studies on the NLR in severe and nonsevere COVID-19 cases published from January 1, 2020, to July 1, 2021, was conducted on the PubMed, EMBASE, and Cochrane Library databases. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and area under the curve (AUC) analyses were done on Stata 14.0 and Meta-disc 1.4 to assess the performance of the NLR.

Results

Thirty studies, including 5570 patients, were analyzed. Of these, 1603 and 3967 patients had severe and nonsevere COVID-19, respectively. The overall sensitivity and specificity were 0.82 (95% confidence interval (CI), 0.77-0.87) and 0.77 (95% CI, 0.70-0.83), respectively; positive and negative correlation ratios were 3.6 (95% CI, 2.7-4.7) and 0.23 (95% CI, 0.17-0.30), respectively; DOR was 16 (95% CI, 10-24), and the AUC was 0.87 (95% CI, 0.84-0.90).

Conclusion

The NLR could accurately determine the severity of COVID-19 and can be used to identify patients with severe disease to guide clinical decision-making.

Monocyte Distribution Width, Neutrophil-to-Lymphocyte Ratio, and Platelet-to-Lymphocyte Ratio Improves Early Prediction for Sepsis at the Emergency

(1) Background: Sepsis is a life-threatening condition, and most patients with sepsis first present to the emergency department (ED) where early identification of sepsis is challenging due to the unavailability of an effective diagnostic model. (2) Methods: In this retrospective study, patients aged ≥20 years who presented to the ED of an academic hospital with systemic inflammatory response syndrome (SIRS) were included. The SIRS, sequential organ failure assessment (SOFA), and quick SOFA (qSOFA) scores were obtained for all patients. Routine complete blood cell testing in conjugation with the examination of new inflammatory biomarkers, namely monocyte distribution width (MDW), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), was performed at the ED. Propensity score matching was performed between patients with and without sepsis. Logistic regression was used for constructing models for early sepsis prediction. (3) Results: We included 296 patients with sepsis and 1184 without sepsis. A SIRS score of >2, a SOFA score of >2, and a qSOFA score of >1 showed low sensitivity, moderate specificity, and limited diagnostic accuracy for predicting early sepsis infection (c-statistics of 0.660, 0.576, and 0.536, respectively). MDW > 20, PLR > 9, and PLR > 210 showed higher sensitivity and moderate specificity. When we combined these biomarkers and scoring systems, we observed a significant improvement in diagnostic performance (c-statistics of 0.796 for a SIRS score of >2, 0.761 for a SOFA score of >2, and 0.757 for a qSOFA score of >1); (4) Conclusions: The new biomarkers MDW, NLR, and PLR can be used for the early detection of sepsis in the current sepsis scoring systems.