DOI 10.1007/s00415-026-14046-y
Gold Coast criteria for ALS diagnosis: individual participant data meta-analysis.
Аннотация
BACKGROUND
To evaluate the diagnostic accuracy of the Gold Coast criteria (GCC) and compare their performance with the revised El Escorial (rEEC) and Awaji criteria in patients with suspected amyotrophic lateral sclerosis (ALS).
METHODS
Embase, MEDLINE, and Scopus were searched for English-language studies published between January 1, 2020, and August 11, 2025. Eligible studies assessed the diagnostic accuracy of GCC compared with rEEC and Awaji criteria in suspected ALS. Authors were invited to contribute individual participant data. Data were checked, harmonised, and recoded. A one-stage individual-participant data meta-analysis, adjusted for age and sex, was performed. Diagnostic performance was assessed using pooled sensitivity, specificity, and area under the receiver operating characteristic curve. Risk of bias was assessed using QUADAS-2 and QUADAS-C, and certainty of evidence using GRADE for diagnostic test accuracy. The study was registered with PROSPERO, CRD420251123597.
RESULTS
Individual participant data were available for 3007 participants from five international studies. GCC demonstrated higher sensitivity than rEEC and Awaji criteria: 0.96 (95% confidence interval [CI] 0.93-0.98) versus 0.87 (95% CI 0.78-0.92) and 0.87 (95% CI 0.78-0.93), respectively. Certainty of evidence for sensitivity was moderate at pre-test probabilities of 50% and 75%, and low at 25%. Specificity was numerically lower for GCC at 0.68 (95% CI 0.53-0.81) compared with rEEC at 0.73 (95% CI 0.59-0.83) and the Awaji criteria at 0.72 (95% CI 0.57-0.83). The certainty of evidence for specificity was rated as very low across all assessed pre-test probabilities (25%, 50%, and 75%).
CONCLUSIONS
GCC provide a sensitive framework for suspected ALS and may support earlier diagnosis in specialist settings. Specificity was imprecise and heterogeneous, supporting use with mimic exclusion and longitudinal reassessment.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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