Exploring the diagnostic value of eosinophil-to-lymphocyte ratio to differentiate Kawasaki disease from other febrile diseases based on clinical prediction model

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.

EMR Combined with CRB-65 Superior to CURB-65 in Predicting Mortality in Patients with Community-Acquired Pneumonia

Background

Data about eosinophil-to-lymphocyte ratio (ELR) and eosinophil-to-monocyte ratio (EMR) in patients with community-acquired pneumonia (CAP) are rare. We aimed to evaluate the role of EMR and ELR in predicting disease severity and mortality in patients with CAP.

Methods

A total of 454 patients (76 with severe CAP (SCAP), 378 with non-SCAP) were enrolled from November 18, 2020, and November 21, 2021. Laboratory examination on day 1 after admission was measured. The ELR and EMR values were calculated for patients. Propensity score matching (PSM) was performed to balance potential confounding factors. Binary logistic regression model was fitted to identify the potential risk factors for disease severity and Cox proportional hazards regression model analysis for mortality in CAP. Receiver operating characteristic (ROC) analysis was performed to distinguish disease severity and mortality.

Results

EMR and ELR at admission were significantly lower in SCAP patients than in non-SCAP patients (P<0.001). EMR < 0.018 ([OR] = 12.104, 95% CI: 4.970-29.479), neutrophil (NEU) ([OR]=1.098, 95% CI:1.005-1.199), and age ([OR]=1.091, 95% CI:1.054-1.130) were independent risk factors for disease severity of CAP. EMR < 0.032 ([HR] = 5.816, 95% CI: 1.704-9.848) was an independent predictor of in-hospital mortality. Combining EMR or ELR with CRB-65 improved the overall accuracy of disease severity prediction (AUC from 0.894 to 0.937), the same as CURB-65. The area under the curve of EMR (AUC=0.704; 95% CI: 0.582-0.827) to predict in-hospital mortality was higher than that of CURB-65 (AUC=0.619; 95% CI: 0.484-0.754). Otherwise, EMR combined with CRB-65 (AUC=0.721; 95% CI: 0.592-0.851) had significantly higher diagnostic accuracy for in-hospital mortality than that of CURB-65 alone.

Conclusion

EMR combined with CRB-65 was superior to CURB-65 in predicting mortality in patients with CAP. This new combination was simpler and easier to obtain for physicians in clinics or admission, and it was more convenient for early recognition of patients with poor prognoses.

Values of prognostic nutritional index for predicting Kawasaki disease: a systematic review and meta-analysis

Objective

This systematic review and meta-analysis aimed to evaluate the relationship between the prognostic nutritional index (PNI) and intravenous immunoglobulin (IVIG) resistance and coronary artery lesion (CAL) in Kawasaki disease (KD).

Methods

The relevant literature was searched on PubMed, Embase, Cochrane Library, Web of Science, and Google Scholar up to August 5, 2023. A pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under curve (AUC) were calculated to assess the predicted values of PNI in KD patients with IVIG resistance and CAL.

Results

A total of 8 articles containing 10 studies involving 7,047 participants were included. The pooled results revealed a pooled sensitivity of 0.44 (0.25-0.65), a pooled specificity of 0.87 (0.73-0.94), a pooled PLR of 3.4 (2.0-5.9), a pooled NLR of 0.65 (0.48-0.87), a pooled DOR of 5.26 (2.76-10.02), and a pooled AUC of 0.75 (0.71-0.78) in the diagnosis of KD with CAL. The pooled results suggested that a pooled sensitivity was 0.69 (0.60-0.77), specificity was 0.76 (0.69-0.82), PLR was 2.9 (2.1-4.1), NLR was 0.40 (0.29-0.56), DOR was 7.27 (3.89-13.59), and AUC was 0.79 (0.75-0.82) in the diagnosis of KD with IVIG resistance. The combined results revealed the pooled sensitivity was 0.63 (0.58-0.67), specificity was 0.82 (0.80-0.83), PLR was 3.09 (1.06-8.98), NLR was 0.38 (0.07-2.02), DOR was 8.23 (0.81-83.16) in differentiating KD from febrile patients. These findings demonstrated low sensitivity and relatively high specificity of PNI for KD, KD-CAL, and IVIG-resistant KD.

Conclusion

In conclusion, this study was the first systematic review and meta-analysis of the diagnostic value of PNI in KD with IVIG resistance and CAL. The results suggested that PNI could be used as biomarkers for distinguish KD, KD with CAL, and KD with IVIG resistance.