High C-reactive protein to lymphocyte ratio predicts mortality outcomes of patients with severe fever with thrombocytopenia syndrome: A multicenter study in China.

Severe fever with thrombocytopenia syndrome (SFTS) is a life-threatening infectious disease caused by the SFTS virus (SFTSV). This study aimed to evaluate the predictive power of C-reactive protein to lymphocyte ratio (CLR) and establish an early-warning model for SFTS mortality. We retrospectively analyzed hospitalized SFTS patients in six clinical centers from May 2011 to 2022. The efficacy of CLR prediction was evaluated by the receiver operating characteristic (ROC) analysis. A nomogram was established and validated. Eight hundred and eighty-two SFTS patients (median age 64 years, 48.5% male) were enrolled in this study, with a mortality rate of 17.8%. The area under the ROC curve (AUC) of CLR was 0.878 (95% confidence interval [CI]: 0.850-0.903, p < 0.001), which demonstrates high predictive strength. The least absolute shrinkage and selection operator regression selected seven potential predictors. Multivariate logistic regression analysis determined three independent risk factors, including CLR, to construct the nomogram. The performance of the nomogram displayed excellent discrimination and calibration, with significant net benefits in clinical uses. CLR is a brand-new predictor for SFTS mortality. The nomogram based on CLR can serve as a convenient tool for physicians to identify critical SFTS cases in clinical practice.

Diagnostic value of Procalcitonin, C-reactive protein-to-lymphocyte ratio (CLR), C-reactive protein and neutrophil-to-lymphocyte ratio (NLR) for predicting patients with Bacteraemia in the intensive care unit.

BACKGROUND: To explore the diagnostic value of procalcitonin (PCT), C-reactive protein-to-lymphocyte ratio (CLR), C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR) for predicting patients with bacteremia in the intensive care unit (ICU). METHODS: This case-control study included 359 patients with suspected bacteremia were divided into a bacteremia group (n = 152) and a control group (n = 207) from September 2018 to April 2023. Patient data were collected using a laboratory information system (LIS). ROC curves for PCT, CLR, CRP, and NLR in predicting patients with bacteremia. RESULTS: For PCT, CLR, CRP and NLR to predict patients with bacteremia in the ICU, the AUCs were 0.991(95%CI: 0.974-0.998), 0.960(95%CI: 0.935-0.978), 0.955(95%CI: 0.928-0.974), and 0.898(95%CI:0.862-0.927), respectively; the optimal thresholds were 0.248 ng/mL, 47.52 mg/109, 48.32 mg/L, and 6.51, respectively; the sensitivities were 95.4(95%CI: 90.7-98.1), 88.2(95%CI: 81.9-92.8), 87.5(95%CI: 81.2-92.3), and 86.8(95%CI:80.4-91.8), respectively; and the specificities were 95.7(95%CI: 91.9-98.0), 90.8(95%CI: 86.0-94.4), 90.3(95%CI: 85.5-94.0), and 85.0(95%CI:79.4-89.6), respectively. The sensitivities of PCT, CLR, CRP and NLR for predicting bacteremia due to E. coli infection are as high as over 90%, the specificity of PCT is 100, and the sensitivity of NLR is 100. The sensitivity of CRP for predicting bacteremia due to non-Enterobacer infection is 100. CONCLUSIONS: Compared with those in the control group, PCT, CLR, CRP and NLR were significantly greater in the bacteremia group. The PCT, CLR, CRP, and NLR can all predict the occurrence of bacteremia. The PCT had the highest sensitivity and specificity in predicting bacteremia in ICU patients.

Assessing the Predictive Utility of the C-Reactive Protein-to-Lymphocyte Ratio for Mortality in Isolated Traumatic Brain Injury: A Single-Center Retrospective Analysis.

Introduction: Early identification of high-risk traumatic brain injury (TBI) patients is crucial for optimizing treatment strategies and improving outcomes. The C-reactive protein-to-lymphocyte ratio (CLR) reflects systemic immunology and inflammation function and serves as a new biomarker for patient stratification. This study aimed to assess the predictive value of the CLR for mortality in patients with isolated moderate to severe TBI. Methods: A retrospective analysis of trauma registry data from 2009 to 2022 was conducted, including 1641 adult patients with isolated moderate to severe TBI. Patient demographics, the CLR, injury characteristics, and outcomes were compared between deceased and surviving patients. Univariate and multivariate analyses were performed to identify mortality risk factors. The optimal CLR cut-off value for predicting mortality was determined using receiver operating characteristic (ROC) curve analysis. Results: The CLR was significantly higher in deceased patients compared to survivors (60.1 vs. 33.9, p < 0.001). The optimal CLR cut-off value for predicting mortality was 54.5, with a sensitivity of 0.328 and a specificity of 0.812. The area under the ROC curve was 0.566, indicating poor discriminative ability. In the multivariate analysis, the CLR was not a significant independent predictor of mortality (OR 1.03, p = 0.051). After propensity score matching to attenuate the difference in baseline characteristics, including sex, age, comorbidities, conscious level, and injury severity, the high-CLR group (CLR ≥ 54.5) did not have significantly higher mortality compared to the low-CLR group (CLR < 54.5). Conclusion: While the CLR was associated with mortality in TBI patients, it demonstrated poor discriminative ability as a standalone predictor. The association between a high CLR and worse outcomes may be primarily due to other baseline patient and injury characteristics, rather than the CLR itself.

Exploring the diagnostic value of CLR and CPR in differentiating Kawasaki disease from other infectious diseases based on clinical predictive modeling.

Background: Kawasaki disease (KD) is an important cause of acquired heart disease in children and adolescents worldwide. KD and infectious diseases can be easily confused when the clinical presentation is inadequate or atypical, leading to misdiagnosis or underdiagnosis of KD. In turn, misdiagnosis or underdiagnosis of KD can lead to delayed use of intravenous immunoglobulin (IVIG), increasing the risk of drug resistance and coronary artery lesions (CAL). Objectives: The purpose of this study was to develop a predictive model for identifying KD and infectious diseases in children in the hope of helping pediatricians develop timely and accurate treatment plans. Methods: The data Patients diagnosed with KD from January 2018 to July 2022 in Shenzhen Longgang District Maternity & Child Healthcare Hospital, and children diagnosed with infectious diseases in the same period will be included in this study as controls. We collected demographic information, clinical presentation, and laboratory data on KD before receiving IVIG treatment. All statistical analyses were performed using R-4.2.1 (https://www.rproject.org/). Logistic regression and Least Absolute Shrinkage with Selection Operator (LASSO) regression analyses were used to build predictive models. Calibration curves and C-index were used to validate the accuracy of the prediction models. Results: A total of 1,377 children were enrolled in this study, 187 patients with KD were included in the KD group and 1,190 children with infectious diseases were included in the infected group. We identified 15 variables as independent risk factors for KD by LASSO analysis. Then by logistic regression we identified 7 variables for the construction of nomogram including white blood cell (WBC), Monocyte (MO), erythrocyte sedimentation rate (ESR), alanine transaminase (ALT), albumin (ALB), C-reactive protein to procalcitonin ratio (CPR) and C-reactive protein to lymphocyte ratio (CLR). The calibration curve and C-index of 0.969 (95% confidence interval: 0.960-0.978) validated the model accuracy. Conclusion: Our predictive model can be used to discriminate KD from infectious diseases. Using this predictive model, it may be possible to provide an early determination of the use of IVIG and the application of antibiotics as soon as possible.

CLR (C-Reactive Protein to Lymphocyte Ratio) Served as a Promising Predictive Biomarker for Cerebral Vasospasm in Aneurysmal Subarachnoid Hemorrhage (aSAH): A Retrospective Cohort Study.

Background: Subarachnoid hemorrhage is a devastating disease. Even after state-of-the-art treatment patients suffer from complications, including cerebral vasospasm (CVS), delayed cerebral ischemia (DCI), and chronic hydrocephalus (CH) following aneurysmal subarachnoid hemorrhage (aSAH). The aim of our study is to identify the predictive value of the C-reactive protein to lymphocyte ratio (CLR) for neurological functional outcome and complications after aSAH. Methods: We retrospectively analyzed a total of 166 aSAH patients who met the inclusion criteria enrolled in our study. Multivariate logistic regression analyses were performed to evaluate the independent risk factors. The predictive value of different models was compared by calculating the areas under the receiver operating characteristic (ROC) curve. Results: On-admission levels of CLR in patients with poor outcomes (6 months mRS 3-6), CVS, DCI, and CH were significantly higher than those in patients with good outcomes (6 months mRS 0-2), non-CVS, non-DCI, and non-CH. Multivariate logistic regression analysis revealed that admission CLR was independently associated with CVS (OR [95% CI] 2.116 [1.507-2.971]; p < 0.001), and DCI (OR [95% CI] 1.594 [1.220-2.084]; p = 0.001). In ROC analysis, the area under the curve (AUC) of CLR for poor outcomes (6 months mRS 3-6), CVS, DCI, and CH prediction were (AUC [95% CI] 0.639 [0.555-0.724]; p = 0.002), (AUC [95% CI] 0.834 [0.767-0.901]; p < 0.001), (AUC [95% CI] 0.679 [0.581-0.777]; p < 0.001), and (AUC [95% CI] 0.628 [0.543-0.713]; p = 0.005) revealing that admission CLR had a favorable predictive value for CVS after aSAH. The sensitivity and specificity of admission CLR for CVS prediction were 77.1% and 75.4%. On-admission CLR of 0.757 mg × 10-6 was identified as the best cutoff threshold to discriminate between CVS and non-CVS (CVS: CLR < 0.757 mg × 10-6 11/100 [11.0%] vs. CLR ≥ 0.757 mg × 10-6 37/66 [56.1%]; p < 0.001). Conclusions: High levels of on-admission CLR serve as an independent risk factor for CVS and DCI after aSAH. Admission CLR is an easy-to-quantify laboratory parameter that efficiently predicts the CVS after aSAH, which can provide some guidance for clinicians to evaluate for possible progression and treatment strategies in patients with aSAH.

Association of Three Novel Inflammatory Markers: Lymphocyte to HDL-C Ratio, High-Sensitivity C-Reactive Protein to HDL-C Ratio and High-Sensitivity C-Reactive Protein to Lymphocyte Ratio With Metabolic Syndrome.

OBJECTIVE: We aimed to compare the association of three novel inflammatory indicators with metabolic syndrome (MetS) among Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort participants. METHODS: According to the International Diabetes Federation (IDF) criteria, the cohort participants were divided into the MetS(+) and MetS(-) groups. The lymphocyte to high-density lipoprotein cholesterol (HDL-C) ratio (LHR), high-sensitivity C-reactive protein (hs-CRP) to HDL-C ratio (HCHR) and hs-CRP to lymphocyte ratio (HCLR) were calculated and were compared between the groups. Binary logistic regression (LR) analysis was performed to find the association of the indices with the presence of MetS among men and women. Receiver-operating characteristic (ROC) curve analysis was used to establish cut-off values in predicting MetS for men and women. p-Values <0.05 were considered as statistically significant. RESULTS: Among a total of 8890 participants (5500 MetS(-) and 3390 MetS(+)), LHR, HCHR and HCLR were significantly higher in the MetS(+) group than in MetS(-) group (p < 0.001). In LR analysis, after adjusting for multiple cofounders, LHR remained an independent factor for the presence of MetS among men (OR: 1.254; 95% CI: 1.202-1.308; p < 0.001) and women (OR: 1.393; 95% CI: 1.340-1.448; p < 0.001). HCHR also remained an independent factor for the presence of MetS only in women (OR: 1.058; 95% CI: 1.043-1.073; p < 0.001). ROC curve analysis showed that LHR had the higher AUC for predicting MetS in both men (AUC: 0.627; 95% CI: 0.611-0.643; p < 0.001) and women (AUC: 0.683; 95% CI: 0.670, 0.696; p < 0.001). CONCLUSION: This suggests that among both genders, the LHR as an inexpensive and easy-to-access marker has a better diagnostic performance and could be a promising alternative to the traditional expensive inflammatory markers such as hs-CRP for the evaluation of inflammation in patients with MetS.

Can C-Reactive Protein-Lymphocyte Ratio Be Used as a Screening Tool to Confirm the Diagnosis of Periprosthetic Joint Infection?

Background: This study aimed to investigate whether periprosthetic joint infection (PJI) can be predicted by the C-reactive protein-to-lymphocyte ratio (CLR), whether this ratio increases the accuracy of PJI diagnosis, and whether it is more sensitive than other blood values and ratios. Methods: The patients were divided into two groups: the septic revision (SR) group and the aseptic revision (AR) group. In cases of septic revision, the diagnosis of PJI was made based on the criteria proposed by the European Bone and Joint Infection Society (EBJIS). The groups were compared in terms of age, sex, body mass index, comorbidity, and preoperative laboratory results. The sensitivity, specificity, and diagnostic performance of the values and ratios were analyzed and compared. Results: The receiver operating characteristic (ROC) analysis for the CLR gave a diagnostic value of 15.52, which provided a sensitivity of 91.1% and a specificity of 64.2% for PJI. The CLR gave lower specificity and higher sensitivity compared to the erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) values. The ROC analysis showed that the CLR had a similar area under the curve (AUC) with the ESR and CRP (0.808). The CLR had a higher specificity than other ratios (platelet volume ratio, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio) and a higher value of the AUC. In the multivariate analysis, the CLR (hazard ratio, 1.088; 95% confidence interval, 1.063-1.113; p < 0.001) was found to be a significant risk factor. As CLR increased by one unit, the risk of PJI increased by 1.088 times, and it was statistically significant (p < 0.001). Conclusions: The findings of this study suggest that CLR can serve as a valuable screening tool for diagnosing PJI. CLR demonstrated higher sensitivity in predicting PJI compared to ESR and CRP, and it exhibited greater specificity than other infection markers.

C-Reactive Protein-to-Albumin Ratio (CAR) and C-Reactive Protein-to-Lymphocyte Ratio (CLR) are Valuable Inflammatory Biomarker Combination for the Accurate Prediction of Periprosthetic Joint Infection.

Background: Periprosthetic joint infection (PJI) is a catastrophic complication after total joint arthroplasty (TJA). Timely and accurate diagnosis is important for the management of PJI. Currently, many biomarkers are available for the diagnosis of PJI, but which inflammatory biomarker combination has the best diagnostic value has not been reported. Materials and Methods: We retrospectively analyzed 244 patients who underwent revision knee or hip arthroplasty in our institution. They were divided into two groups: 87 in the PJI group and 157 in the aseptic failure (AF) group. The preoperative C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), CRP-to-albumin ratio (CAR), CRP-to-lymphocyte ratio (CLR), neutrophil-to-albumin ratio (NAR) and platelet-to-albumin ratio (PAR) were determined and compared between the two groups. Receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to assess the diagnostic value of all biomarkers, and the optimal cut-off value, positive predictive value (PPV) and negative predictive value (NPV) were further calculated by the Youden index. Results: The NLR, PLR, CAR, CLR, NAR and PAR of the PJI group were significantly higher than those of the AF group (P<0.001). According to the ROC and AUC results, the diagnostic value of CAR and CLR was considered excellent with AUCs of 0.931 and 0.935, respectively. The diagnostic value of NAR (0.739) and PAR (0.785) were fair, the diagnostic value of NLR (0.694) was poor, and PLR (0.535) had no diagnostic ability. Subgroup analysis showed no significant differences in combined inflammatory biomarkers between the two groups. Conclusion: CAR and CLR are valuable combined inflammatory biomarkers for diagnosing PJI, while other markers were of limited value for the diagnosis of PJI.

C-reactive protein to lymphocyte ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 patients.

Objective: The aim of the present study is to assess the utility of C-reactive protein to Lymphocyte Ratio (CLR) in predicting short-term clinical outcomes of patients infected by SARS-CoV-2 BA.2.2. Methods: This retrospective study was performed on 1,219 patients with laboratory-confirmed SARS-CoV-2 BA.2.2 to determine the association of CLR with short-term clinical outcomes. Independent Chi square test, Rank sum test, and binary logistic regression analysis were performed to calculate mean differences and adjusted odds ratios (aORs) with their 95% CI, respectively. Results: Over 8% of patients admitted due to SARS-CoV-2 BA.2.2. were critically ill. The best cut-off value of CLR was 21.25 in the ROC with a sensitivity of 72.3% and a specificity of 86%. After adjusting age, gender, and comorbidities, binary logistic regression analysis showed that elevated CLR was an independent risk factor for poor short-term clinical outcomes of COVID-19 patients. Conclusion: C-reactive protein to Lymphocyte Ratio is a significant predictive factor for poor short-term clinical outcomes of SARS-CoV-2 BA.2.2 inflicted patients.

Corrigendum: Clinical value and prognosis of C reactive protein to lymphocyte ratio in severe aneurysmal subarachnoid hemorrhage.

[This corrects the article DOI: 10.3389/fneur.2022.868764.].

C-reactive protein-to-lymphocyte ratio is a reliable marker in patients with COVID-19 infection: the CLEAR COVID study.

OBJECTIVE: COVID-19 infection is characterized with elevation of inflammatory markers in bloodstream. A novel inflammatory marker, C-reactive protein (CRP)-to-lymphocyte ratio (CLR), is suggested to be associated with inflammation. We aimed to compare the CLR values of the deceased COVID-19 patients to the CLR of survived subjects. MATERIALS AND METHODS: The patients with COVID-19 whom presented to outpatient or inpatient clinics of AbantIzzet Baysal University Hospital were enrolled to the present retrospective study. Subjects were grouped as either deceased or survived. CLR values of the groups were compared. RESULTS: Study cohort was consisted of 568 subjects in deceased and 4753 patients in survived group. Median CLR of the deceased and survived groups were 90 (0.2-1679)% and 11 (0.2-1062)%, respectively (p < 0.001). The sensitivity (75%) and specificity (70%) of CLR (> 23.4% level) in detecting mortality were higher than those of CRP and ferritin (AUC 0.80, p < 0.001, 95% CI 0.78-0.82). CONCLUSION: We suggest that elevated CLR levels in COVID-19 patients on admission should alert physicians for poor outcome.

OBJETIVO: La infección por Covid-19 se caracteriza por elevación de marcadores inflamatorios en el torrente sanguíneo. Se sugiere que un nuevo marcador inflamatorio, la proporción de C-reactive protein (CRP) a linfocitos (CLR), está asociado con la inflamación. Nuestro objetivo fue comparar los valores de CLR de los pacientes fallecidos con Covid-19 con el CLR de los sujetos sobrevivientes. MATERIALES Y MÉTODOS: Los pacientes con Covid-19 que se presentaron en clínicas ambulatorias o de hospitalización del Hospital Universitario Abant Izzet Baysal se inscribieron en el presente estudio retrospectivo. Los sujetos se agruparon como fallecidos o sobrevivientes. Se compararon los valores de CLR de los grupos. RESULTADOS: La cohorte del estudio estuvo compuesta por 568 sujetos en el grupo fallecido y 4753 pacientes en el grupo sobreviviente. La mediana de CLR de los grupos fallecidos y sobrevivientes fue 90 (0.2-1679)% y 11 (0.2-1062)%, respectivamente (p < 0.001). La sensibilidad (75%) y la especificidad (70%) de CLR (nivel > 23.4%) en la detección de mortalidad fueron superiores a las de CRP y ferritina (AUC 0.80, p < 0.001, IC 95%: 0,78-0.82). CONCLUSIÓN: Sugerimos que los niveles elevados de CLR en pacientes con Covid-19 al ingreso deberían alertar a los médicos sobre un resultado deficiente.

Clinical Value and Prognosis of C Reactive Protein to Lymphocyte Ratio in Severe Aneurysmal Subarachnoid Hemorrhage.

Objective: To investigate the relationship between CLR and disease severity and clinical prognosis of aSAH. Methods: The authors retrospectively analyzed the clinical data of 221 patients with aSAH, who were admitted to the intensive care unit from January 2017 to December 2020. The indicators of inflammatory factors in the first blood routine examination within 48 h of bleeding were obtained. The prognosis was evaluated by mRS score at discharge, mRS>2 was a poor outcome. Through the receiver operating characteristic (ROC) curve, the area under the curve was calculated and the predicted values of inflammatory factors (CLR, CRP, WBC, and neutrophils) were compared. Univariate and multivariable logistic regression analyses were used to evaluate the relationship between CLR and the clinical prognosis of patients. ROC curve analysis was performed to determine the optimal cut-off threshold, sensitivity, and specificity of CLR in predicting prognosis at admission. Results: According to the mRS score at discharge, 139 (62.90%) patients were classified with poor outcomes (mRS>2). The inflammatory factor with the best predictive value was CLR, which had an optimal cut-off threshold of 10.81 and an area under the ROC curve of 0.840 (95%CI.788-0.892, P < 0.001). Multivariable Logistic regression analysis showed that the Modified Fisher grade, Hunt-Hess grade, and CLR at admission were independent risk factors for poor outcomes of patients with aSAH (P < 0.05). According to Hunt-Hess grade, patients were divided into a mild group (Hunt-Hess ≤ 3) and a severe group (Hunt-Hess > 3), and the CLR value was significantly higher in severe patients with aSAH than in mild patients. The optimal cut-off threshold of CLR in the severe group was 6.87, and the area under the ROC curve was 0.838 (95% CI.752-0.925, P < 0.001). Conclusions: The CLR value at the admission of patients with aSAH was significantly associated with Hunt-Hess grade, The higher Hunt-Hess grade, the higher the CL R-value, and the worse the prognosis. Early CLR value can be considered as a feasible biomarker to predict the clinical prognosis of patients with aSAH.