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Documenting Trofinetide Treatment Phenotypes in Rett Syndrome with a Dual-LLM Consensus Pipeline

Daniel Palacios, Guantong Qi, Mikael Guzman Karlsson, Shawntel K. David, Mohammed Sameeruddin, Bernhard Suter, Zhandong Liu, Davut Pehli̇van, Hu Chen · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.22062 · cited by 0 works (OpenAlex) · open-access PDF

Korean

의도적 인 대안은 오히려 논의 외부입니다 : Trofinetide는 2023 년에 최초의 Rett 증후군 치료로 승인 된 정규 심사 증후군 모니터링을 제공합니다. 차트 검토가 임상 집중적이기 때문에 확장 가능한 실제 모니터링이 부족합니다. 우리는 텍사스 어린이 병원 (LLM)에서 지속적인 trofinetide 노출을 가진 108 명의 환자로부터 26763 개의 노트를 개발했습니다. 파이프 라인 필터는 키워드에 따라 18 개의 치료 반응 현형을 추출하고, 합의가 필요한 4 개의 LLM, 13 개의 Rett 임상 특징 및 약물 거부 매트릭스를 집합합니다. 건축물 및 메서드 방향은 설계되었습니다. 설계 및 냉동

Machine translation (Meta M2M100); the English original follows.

Abstract

Objective: Trofinetide, approved in 2023 as the first Rett syndrome treatment, lacks scalable real-world monitoring because chart review is labor-intensive. We developed a dual large language model (LLM) consensus pipeline to extract 18 treatment-response phenotypes, comprising 4 adverse effects, 13 Rett clinical features, and medication refusal, from clinical notes. Materials and Methods: We analyzed 26,763 notes from 108 patients with confirmed sustained trofinetide exposure at Texas Children's Hospital. The pipeline filters notes by keyword, classifies each through two LLMs requiring consensus, and aggregates a patient-by-timepoint matrix. Architecture and prompt were selected on a diarrhea development set, then frozen and applied to the other 17 phenotypes with the phenotype definition substituted, as an out-of-sample test. The reported prompt comparison scores 183 expert-labeled cells. Results: A prompt requiring diarrhea to be active and severe performed best (84.2 $\pm$ 0.0% accuracy; F1 = 0.674), 47 percentage points above regular-expression matching ($p < 0.0001$). Expert reviewers judged six of the pipeline's calls per phenotype, three positive and three negative, and agreed with 90.2% (92/102). The 13 Rett clinical features are manifestations of the disorder itself rather than adverse effects of trofinetide. Gross and fine motor impairment, language/communication, and stereotypy were documented present in 92-100% of patients at every visit. Discussion: In-context LLM extraction captured multi-domain treatment responses. The outcome is documented presence at each visit, not a direction-of-change judgment. Conclusion: Coupling in-context LLM reasoning with a consensus architecture offers a scalable alternative to keyword and regular-expression extraction for real-world evidence, adapting to new phenotypes and medications through configuration alone.

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Topics: Rett syndrome, Medicine, Pipeline (software), Dysarthria, Adverse effect, Diarrhea

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