Pediatric neurology · 2026
Deciphering the Breathless Future: A Novel Approach to Predicting Respiratory Failure in Children With Guillain-Barré Syndrome.
СтатьяНазвание и аннотация: Перевод в очереди
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Yu Zhiwei, Luo Hanyu, Li Yuhang, Ma Jiannan, Yang Han, Zhang Qing, Wang Juan, Cheng Min, Hong Siqi, Jiang Li
Аннотация
BACKGROUND: The applicability and utility of clinical predictive models for respiratory failure in the pediatric Guillain-Barré syndrome (GBS) and Asian population are significantly constrained. Therefore, we aim to develop and validate a clinical prediction model to predict respiratory failure risk in pediatric GBS patients in China, alongside the economic immunological biomarkers in decision-making, and evaluate the Erasmus GBS Respiratory Insufficiency Score (EGRIS)-Kids score's efficacy.
METHODS: The retrospective study originated from our pediatric GBS cohort at Children's Hospital of Chongqing Medical University during 2014-2022. We utilized logistic regression to identify predictors and construct a nomogram and web-based dynamic nomogram. The net reclassification index and integrated discriminant improvement index were used to compare models after incorporating new indices, with bootstrapping validation.
RESULTS: Our study included 175 children, among which 23 (13%) patients have developed respiratory insufficiency. Variables included in our score were: age (odds ratio [OR] 1.23), bulbar palsy (OR 23.17), bilateral hip flexion (OR 0.75), and platelet-to-lymphocyte ratio (PLR; OR 2.47). The area under the receiver operating characteristic curve of the nomogram was 0.899 (95% confidence interval 0.839-0.960). The calibration plots showed an adequate consistency between the reported and predicted occurrence. The EGRIS-Kids model yielded an area under the receiver operating characteristic curve of 0.849 (95% confidence interval 0.754-0.944) in our cohort and the incorporation of PLR exhibited an incremental value of 12.51% (P = 0.03).
CONCLUSIONS: We performed the first external validation of the EGRIS-Kids score in Chinese children with GBS. Furthermore, we developed a new predictive model incorporating the PLR, which shows promise and additional value but requires further external validation.
METHODS: The retrospective study originated from our pediatric GBS cohort at Children's Hospital of Chongqing Medical University during 2014-2022. We utilized logistic regression to identify predictors and construct a nomogram and web-based dynamic nomogram. The net reclassification index and integrated discriminant improvement index were used to compare models after incorporating new indices, with bootstrapping validation.
RESULTS: Our study included 175 children, among which 23 (13%) patients have developed respiratory insufficiency. Variables included in our score were: age (odds ratio [OR] 1.23), bulbar palsy (OR 23.17), bilateral hip flexion (OR 0.75), and platelet-to-lymphocyte ratio (PLR; OR 2.47). The area under the receiver operating characteristic curve of the nomogram was 0.899 (95% confidence interval 0.839-0.960). The calibration plots showed an adequate consistency between the reported and predicted occurrence. The EGRIS-Kids model yielded an area under the receiver operating characteristic curve of 0.849 (95% confidence interval 0.754-0.944) in our cohort and the incorporation of PLR exhibited an incremental value of 12.51% (P = 0.03).
CONCLUSIONS: We performed the first external validation of the EGRIS-Kids score in Chinese children with GBS. Furthermore, we developed a new predictive model incorporating the PLR, which shows promise and additional value but requires further external validation.