Quality and performance of machine learning versus logistic regression for predicting IVIG resistance in Kawasaki disease: a PROBAST+AI systematic comparison
Abstract
Background: This study aimed to systematically compare the predictive performance and methodological quality of logistic regression (LR) and machine learning (ML) models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) using the PROBAST + AI framework.
Methods: We searched PubMed, Embase, and Web of Science to identify studies on prediction models for IVIG resistance in KD published between January 1, 2006, and July 31, 2025. We assessed methodological rigour, risk of bias, and applicability using PROBAST + AI. A meta-analysis was performed using random-effects models with logit-transformed area under the receiver operating characteristic curve (AUC) values. Subgroup, sensitivity, and publication bias analyses were additionally conducted.
Results: We identified 52 eligible studies (40 LR and 12 ML). In external validation, pooled AUCs were similar between ML and LR models (0.76 [95% CI 0.64-0.86] vs. 0.75 [95% CI 0.68-0.81]). In internal validation, ML showed a slightly higher pooled AUC than LR (0.86 [95% CI 0.78-0.92] vs. 0.76 [95% CI 0.72-0.79]), although no statistically significant differences were observed. All studies were judged to be at high risk of bias, mainly due to retrospective single-centre designs, inadequate handling of missing data and continuous predictors, and poor reporting of calibration and clinical utility. No study reported sample size calculations.
Conclusions: Given the limited external validation and substantial…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Biportal endoscopic versus microscopic lumbar decompressive laminectomy in patients with spinal stenosis: A randomized controlled trial
- A whey protein-based multi-ingredient nutritional supplement stimulates gains in lean body mass and strength in healthy older men: A randomized controlled trial
- Supplement-based nutritional strategies to tackle frailty: A multifactorial, double-blind, randomized placebo-controlled trial
- A randomized, double-blind, placebo-controlled, proof-of-concept trial of creatine monohydrate as adjunctive treatment for bipolar depression
- Creatine supplementation (3 g/day) and bone health in older women: a 2-year, randomized, placebo-controlled trial
- A Multi-Ingredient Nutritional Supplement in Combination With Resistance Exercise and High-Intensity Interval Training Improves Cognitive Function and Increases N-3 Index in Healthy Older Men: A Randomized Controlled Trial
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.