A novel nomogram model for differentiating Kawasaki disease from sepsis

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.

A machine learning model for distinguishing Kawasaki disease from sepsis

KD is an acute systemic vasculitis that most commonly affects children under 5 years old. Sepsis is a systemic inflammatory response syndrome caused by infection. The main clinical manifestations of both are fever, and laboratory tests include elevated WBC count, C-reactive protein, and procalcitonin. However, the two treatments are very different. Therefore, it is necessary to establish a dynamic nomogram based on clinical data to help clinicians make timely diagnoses and decision-making. In this study, we analyzed 299 KD patients and 309 sepsis patients. We collected patients' age, sex, height, weight, BMI, and 33 biological parameters of a routine blood test. After dividing the patients into a training set and validation set, the least absolute shrinkage and selection operator method, support vector machine and receiver operating characteristic curve were used to select significant factors and construct the nomogram. The performance of the nomogram was evaluated by discrimination and calibration. The decision curve analysis was used to assess the clinical usefulness of the nomogram. This nomogram shows that height, WBC, monocyte, eosinophil, lymphocyte to monocyte count ratio (LMR), PA, GGT and platelet are independent predictors of the KD diagnostic model. The c-index of the nomogram in the training set and validation is 0.926 and 0.878, which describes good discrimination. The nomogram is well calibrated. The decision curve analysis showed that the nomogram has better clinical application value and decision-making assistance ability. The nomogram has good performance of distinguishing KD from sepsis and is helpful for clinical pediatricians to make early clinical decisions.

Clinical characteristics and outcomes of children with Kawasaki disease combined with sepsis in the pediatric intensive care unit

Background

Kawasaki disease (KD) is a vascular inflammatory disease with unknown pathogenesis. There are few studies on KD combined with sepsis worldwide.

Purpose

To provide valuable data regarding clinical characteristics and outcomes related to pediatric patients with KD combined with sepsis in pediatric intensive care unit (PICU).

Methods

We retrospectively analyzed the clinical data of 44 pediatric patients admitted in PICU at Hunan Children's Hospital with KD combined with sepsis between January 2018 and July 2021.

Results

Of the 44 pediatric patients (mean age, 28.18 ± 24.28 months), 29 were males and 15 were female. We further divided the 44 patients into two groups: KD combined with severe sepsis (n=19) and KD combined with non-severe sepsis (n=25). There were no significant between-group differences in leukocyte, C-reactive protein, and erythrocyte sedimentation rate. Interleukin-6, interleukin-2, interleukin-4 and procalcitonin in KD with severe sepsis group were significantly higher than those in KD with non-severe sepsis group. And the percentage of suppressor T lymphocyte and natural killer cell in severe sepsis group were significantly higher than those in non-severe group, while the CD4⁺/CD8⁺ T lymphocyte ratio was significantly lower in KD with severe sepsis group than in KD with non-severe sepsis group. All 44 children survived and were successfully treated after intravenous immune globulin (IVIG) combined with antibiotics.

Conclusion

Children who develop with KD combined with sepsis have different degrees of inflammatory response and cellular immunosuppression, and the degree of inflammatory response and cellular immunosuppression is significantly correlated with the severity of the disease.

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

Kawasaki disease (KD) is a febrile disease that affects children under 5 years of age and leads to serious cardiovascular complications such as coronary artery disease. The development of markers that can predict early is important to reduce the under- and misdiagnosis of KD. The aim of this research was to develop a diagnostic predictive model to differentiate Kawasaki disease (KD) from other febrile diseases using eosinophil-to-lymphocyte ratio (ELR) and other biomarkers. We recruited a total of 190 children with KD and 1604 children with other febrile diseases. We retrospectively collected clinical information from the children, which included laboratory data on the day of admission, such as white blood cells (WBC), hemoglobin (HGB), calcitoninogen (PCT), hypersensitive c-reactive protein (CRP), snake prognostic nutritional index (PNI), peripheral blood neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and ELR. We performed analyses using univariate analysis, multivariate logistic regression, and column line plots, and evaluated the diagnostic parameters of the predictive models. ELR was significantly increased in patients with KD. After multivariate logistic regression, WBC, HGB, CRP, NLR, ELR and PNI were finally included as indicators for constructing the prediction model. The ROC curve analysis suggested that the C-index of the diagnostic prediction model was 0.921. The calibration curve showed good diagnostic performance of the columnar graph model. The cut-off value of ELR alone for KD was 0.04, the area under the ROC curve was 0.809. Kids with KD show highly expressive level of ELR compared to children with febrile disease, which can be used to diagnose KD, and column line graphs constructed together with other indicators can help pediatricians to identify KD more effectively from febrile children.

The Role of Procalcitonin for Predicting Kawasaki Disease

Some studies have estimated the diagnostic value of procalcitonin (PCT) for Kawasaki disease (KD), but the results are not always consistent. The aim of this study was to ascertain the diagnostic value of PCT for KD. Relevant and eligible articles assessing the diagnostic significance of PCT in KD were systematically searched from PubMed as well as the CNKI databases (last update: October 31, 2020), followed by bivariate models to evaluate the overall diagnostic significance of PCT in KD. This systematic review and meta-analysis included four articles. The overall diagnostic specificity and sensitivity were 0.78 (95% CI: 0.74-0.82) and 0.73 (95% CI: 0.69-0.76), respectively. The area under the summary receiver operating characteristic (sROC) curve (AUC) was 0.82. The negative likelihood ratio (NLR) and positive likelihood ratio (PLR) values for PCT were 0.34 and 3.23, respectively. By analyzing the accessible articles, we showed PCT is not a particularly useful test for KD diagnosis.

Combination of Hemoglobin-for-Age Z-Score and Plasma Hepcidin Identified as a Novel Predictor for Kawasaki Disease

Kawasaki disease (KD) is a febrile coronary vasculitis that affects younger children and includes complications such as coronary artery aneurysm. KD diagnoses are diagnosed based on clinical presentations, a process that still poses a challenge for front-line physicians. In the current study, we developed a novel predictor using the hemoglobin-for-age z-score (HbZ) and plasma hepcidin to differentiate Kawasaki disease (KD) from febrile children (FC). There were 104 FC and 115 KD subjects (89 typical KD; 26 incomplete KD) for this study, and data were collected on the biological parameters of hemoglobin and plasma hepcidin levels. A receiver operating characteristic curve (auROC), multiple logistics regression, and support vector machine analysis were all adopted to develop our prediction condition. We obtained both predictors, HbZ and plasma hepcidin, for distinguishing KD and FC. The auROC of the multivariate logistic regression of both parameters for FC and KD was 0.959 (95% confidence interval = 0.937–0.981), and the sensitivity and specificity were 85.2% and 95.9%, respectively. Furthermore, the auROC for FC and incomplete KD was 0.981, and the sensitivity and specificity were 92.3% and 95.2%, respectively. We further developed a model of support vector machine (SVM) classification with 83.3% sensitivity and 88.0% specificity in the training set, and the blind cohort performed well (78.4% sensitivity and 100% specificity). All data showed that sensitivity and specificity were 81.7% and 91.3%, respectively, by SVM. Overall, our findings demonstrate a novel predictor using a combination of HbZ and plasma hepcidin with a better discriminatory ability for differentiating from WBC and CRP between children with KD and other FC. Using this predictor can assist front-line physicians to recognize and then provide early treatment for KD.

Near Infrared Spectroscopy Detects Change of Tissue Hemoglobin and Water Levelsin Kawasaki Disease and Coronary Artery Lesions

Background: Kawasaki disease (KD) is a form of systemic vasculitis that mainly affects children under the age of five years old. Limb swelling and redness are among the primary symptoms of KD. Previous studies have reported that wireless optical monitoring systems can identify limb indurations characteristics in patients with KD. Therefore, we conducted this study to monitor the dynamic changes in different stages of KD and the disease outcome of coronary artery lesions (CAL).Methods: KD patients who were admitted for intravenous immunoglobulin (IVIG) treatment and controls with or without fever were enrolled in this study. Near infrared spectroscopy data were collected for KD patients at different stages, including before (within one day before IVIG treatment, KD1) and shortly after IVIG treatment (within three days, KD2), at least 21 days after IVIG (KD3), 6 months later (KD4), 1 year later (KD5), 2 years later (KD6), and 3 years later (KD7).Results: This study included a total of 350 pieces of data, including data from 20 healthy controls, 64 fever controls, 53 KD1, 67 KD2, 58 KD3, 28 KD4, 25 KD5, 15 KD6, and 20 KD7. The relative HbO2 of the KD1 group were significantly lower than those of the healthy group (0.298 ± 0.01 vs. 0.304 ± 0.05, p = 0.028) but no significant differences were found with the fever group. The HbT concentrations of KD1 group showed significantly lower than health group (0.632 ± 0.019 vs. 0.646 ± 0.021, p = 0.001) but no significant difference with fever control. Relative levels of HbO2, HbT and Hb showed significant difference between KD1 and health control while StO2 and H2O showed difference between KD1 and fever control. The relative H2O concentration was significantly higher in KD patients with CAL formation than without (p < 0.005). Conclusion: This report is the first to use near infrared spectroscopy to detect changes in tissue hemoglobin and water levels at different stages of KD in patients and showed that water content was significantly associated with CAL formation. This non-invasive device may benefit physicians by serving for early identification of KD from fever illness.

Clinical implications of procalcitonin in Kawasaki disease: a useful candidate for differentiating from sepsis and evaluating IVIG responsiveness

OBJECTIVE

Kawasaki disease (KD) is an acute systemic vasculitis and suspected to be triggered by several potential infections in which procalcitonin (PCT) experiences an increase to some extent. However, whether PCT can serve as a useful candidate for differentiating KD from sepsis, and even for predicting incomplete KD, intravenous immunoglobulin (IVIG) nonresponsiveness and coronary artery abnormalities (CAAs) remains unclear.

METHODS

A total of 254 Chinese KD children were enrolled and divided into 6 subgroups, including complete KD, incomplete KD, IVIG-responsive KD, IVIG-nonresponsive KD, KD with CAAs and KD without CAAs. Blood samples were collected from all subjects within 24-h pre- and 48-h post-IVIG infusion, respectively. PCT, C-reactive protein, erythrocyte sedimentation rate and blood cell counts were detected. In addition, both 261 children with sepsis and 251 healthy children sex- and age-matched with KD children were enrolled in the same period.

RESULTS

(1) PCT experienced the highest increase in sepsis patients before antibiotic therapy, followed by acute KD patients and the healthy controls. (2) The proportion of KD patients with a PCT concentration below 0.25 ng/ml was 11 folds higher than that of sepsis patients. (3) PCT had a sensitivity of 91.7% and a specificity of 30.3% at a cutoff value of > 0.15 ng/ml to predict IVIG nonresponsiveness, and the proportion of IVIG-nonresponders with a PCT concentration of 0.25-0.50 ng/ml was 2 folds higher than that of IVIG-responders.

CONCLUSIONS

The PCT concentrations below 0.25 ng/ml may be useful for discriminating KD from sepsis, and moreover, the PCT concentrations of 0.25-0.50 ng/ml may be helpful in predicting IVIG nonresponsiveness.