Comparison of risk scores for predicting intravenous immunoglobulin resistance in Taiwanese patients with Kawasaki disease

Huang, Chi-Nan; Wu, Fuli; Chang, Ya-Mei; Huang, Hsin-Chung; Lin, Min; Wang, Jou‐Kou; Wu, Mei‐Hwan

doi:10.1016/j.jfma.2020.12.010

Cited by 10 publications

(10 citation statements)

References 29 publications

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“…As shown, there was a strong co‐citation relationship between “kobayashi t, 2006, circulation,” 20 “egami k, 2006, j pediatr us,” 21 and “sano t, 2007, eur j pediatr.” 22 Egami, Kobayashi, and Sano scoring systems are used to predict IVIG resistance and are the basis of research in this field. However, due to differences in race and population regions, the effectiveness of these scoring models still needs to be verified 23 …”

Section: Resultsmentioning

confidence: 99%

“…However, due to differences in race and population regions, the effectiveness of these scoring models still needs to be verified. 23 …”

Section: Resultsmentioning

confidence: 99%

“…However, due to differences in race and population regions, the effectiveness of these scoring models still needs to be verified. 23 At the same time, the references were clustered in CiteSpace according to similarity between them and divided into 42 clusters according to the log-likelihood rate algorithm. The Q-value was 0.7156 and S-value 0.8888, indicating that the clustering results were reliable.…”

Section: Analysis Of Referencesmentioning

confidence: 99%

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Knowledge framework of intravenous immunoglobulin resistance in the field of Kawasaki disease: A bibliometric analysis (1997−2023)

Zhang,

Huang,

et al. 2024

Immunity Inflam & Disease

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BackgroundKawasaki disease (KD) is an autoimmune disease with cardiovascular disease as its main complication, mainly affecting children under 5 years old. KD treatment has made tremendous progress in recent years, but intravenous immunoglobulin (IVIG) resistance remains a major dilemma. Bibliometric analysis had not been used previously to summarize and analyze publications related to IVIG resistance in KD. This study aimed to provide an overview of the knowledge framework and research hotspots in this field through bibliometrics, and provide references for future basic and clinical research.MethodsThrough bibliometric analysis of relevant literature published on the Web of Science Core Collection (WoSCC) database between 1997 and 2023, we investigated the cooccurrence and collaboration relationships among countries, institutions, journals, and authors and summarized key research topics and hotspots.ResultsFollowing screening, a total of 364 publications were downloaded, comprising 328 articles and 36 reviews. The number of articles on IVIG resistance increased year on year and the top three most productive countries were China, Japan, and the United States. Frontiers in Pediatrics had the most published articles, and the Journal of Pediatrics had the most citations. IVIG resistance had been studied by 1889 authors, of whom Kuo Ho Chang had published the most papers.ConclusionResearch in the field was focused on risk factors, therapy (atorvastatin, tumor necrosis factor‐alpha inhibitors), pathogenesis (gene expression), and similar diseases (multisystem inflammatory syndrome in children, MIS‐C). “Treatment,” “risk factor,” and “prediction” were important keywords, providing a valuable reference for scholars studying this field. We suggest that, in the future, more active international collaborations are carried out to study the pathogenesis of IVIG insensitivity, using high‐throughput sequencing technology. We also recommend that machine learning techniques are applied to explore the predictive variables of IVIG resistance.

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Section: Resultsmentioning

confidence: 99%

“…However, due to differences in race and population regions, the effectiveness of these scoring models still needs to be verified. 23 …”

Section: Resultsmentioning

confidence: 99%

Section: Analysis Of Referencesmentioning

confidence: 99%

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Knowledge framework of intravenous immunoglobulin resistance in the field of Kawasaki disease: A bibliometric analysis (1997−2023)

Zhang,

Huang,

et al. 2024

Immunity Inflam & Disease

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“…While results from China diverse. Huang, et.al [23] retrospectively analyzed 84 KD patients in Taiwan, China reported a sensitivity and speci city of the Kobayashi score of 37.5% and 86.8% respectively. Song, et.al [24] conducted a study of 1163 KD patients in Beijing, China reported a sensitivity and speci city of the Kobayashi score of 16% and 85% respectively, meaning that most IVIG resistance KD children would be missed in a similar population.…”

Section: Discussionmentioning

confidence: 99%

Comparison of different risk scoring systems for predicting intravenous immunoglobulin resistance in Chinese children with Kawasaki disease

Zeng

Chen

et al. 2023

Preprint

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Objective: This study aims to evaluate the predictive efficacies of 6 established scoring systems for intravenous immunoglobulin (IVIG) resistance to Kawasaki disease (KD) in Chinese children. Methods: We retrospectively analyzed KD patients treated at cardiovascular medical ward in our institution between January 2020 and December 2022. Data were analyzed in 6scoring systems (Egami, Formosa, Harada, Kobayashi, Lan and Yang). Results: We recruited 763 KD patients in our study, including 60 IVIG-resistant cases (7.9%). Our study indicated that IVIG resistance KD patients represent a higher risk of developing coronary arterial lesions (CALs) (P < 0.001). In determining IVIG resistance, the sensitivity and specificity varied among scoring systems (Egami, 33.3% and 87.2%; Formosa, 91.7% and 42.0%; Harada, 76.7% and 42.8%; Kobayashi, 66.7% and 79.2%; Lan, 68.3% and 73.0%; Yang, 65.0% and 76.4%, respectively). Our study discovered that neutrophilic granulocyte percentage (NE%) ≥ 72.3% was an independent risk factor associated with IVIG resistance. Conclusion: The Kobayashi, Lan and Yang scoring systems were shown to be appropriate for determining IVIG resistance in Chinese KD patients. Meanwhile, more consideration should be considered for KD patients with high NE% to reduce IVIG resistance.

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“…Moreover, the prediction models themselves did not work well in different populations or the studies did not perform external population validation. [9][10][11][12][13] The Prediction Model Risk of Bias Assessment Tool (PROBAST) is useful for assessing prediction model studies and critically appraising prediction model studies. 14,15 It includes 20 signal questions across four domains (Participants, Predictors, Outcomes, and Analysis) that can be used to evaluate the risk of bias (ROB) of the prediction models.…”

Section: Introductionmentioning

confidence: 99%

Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST

et al. 2023

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Background The prediction model of intravenous immunoglobulin (IVIG) resistance in Kawasaki disease can calculate the probability of IVIG resistance and provide a basis for clinical decision-making. We aim to assess the quality of these models developed in the children with Kawasaki disease. Methods Studies of prediction models for IVIG-resistant Kawasaki disease were identified through searches in the PubMed, Web of Science, and Embase databases. Two investigators independently performed literature screening, data extraction, quality evaluation, and discrepancies were settled by a statistician. The checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) was used for data extraction, and the prediction models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Results Seventeen studies meeting the selection criteria were included in the qualitative analysis. The top three predictors were neutrophil measurements (peripheral neutrophil count and neutrophil %), serum albumin level, and C-reactive protein (CRP) level. The reported area under the curve (AUC) values for the developed models ranged from 0.672 (95% confidence interval [CI]: 0.631–0.712) to 0.891 (95% CI: 0.837–0.945); The studies showed a high risk of bias (ROB) for modeling techniques, yielding a high overall ROB. Conclusion IVIG resistance models for Kawasaki disease showed high ROB. An emphasis on improving their quality can provide high-quality evidence for clinical practice. Impact statement This study systematically evaluated the risk of bias (ROB) of existing prediction models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease to provide guidance for future model development meeting clinical expectations. This is the first study to systematically evaluate the ROB of IVIG resistance in Kawasaki disease by using PROBAST. ROB may reduce model performance in different populations. Future prediction models should account for this problem, and PROBAST can help improve the methodological quality and applicability of prediction model development.

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Comparison of risk scores for predicting intravenous immunoglobulin resistance in Taiwanese patients with Kawasaki disease

Cited by 10 publications

References 29 publications

Knowledge framework of intravenous immunoglobulin resistance in the field of Kawasaki disease: A bibliometric analysis (1997−2023)

Knowledge framework of intravenous immunoglobulin resistance in the field of Kawasaki disease: A bibliometric analysis (1997−2023)

Comparison of different risk scoring systems for predicting intravenous immunoglobulin resistance in Chinese children with Kawasaki disease

Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST

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