S. Redline

Common data element (CDE) and AI-Enabled approaches for clinical data Management: Workshop proceedings from the NIH INCLUDE Project.

OBJECTIVE To evaluate challenges in managing multisite, longitudinal, and multisystem clinical data for Down syndrome (DS) research and identify approaches to improve standardization and reuse. METHODS This report summarizes the outcomes and lessons learned from a NIH workshop convened by the INCLUDE Project to align and modernize clinical data management (CDM) practices using common data elements (CDEs) and artificial intelligence (AI)-enabled tools. RESULTS (1) consensus that shared CDEs, ontologies, and consistent data models are foundational for cross-study harmonization and interoperability; (2) identification of complementary electronic health record strategies, including standards-based exchange and research data models to support scalable extraction and analysis; (3) recognition that AI-enabled methods, including natural language processing with human review, can accelerate abstraction of information from clinical narratives and support data harmonization across heterogeneous sources; and (4) prioritization of governance needs for privacy protection, transparency, bias mitigation, and ongoing oversight when applying AI to sensitive health data. CONCLUSION The major conclusion is that combining standardized CDE-driven design with appropriately governed AI-enabled workflows can reduce manual burden, improve data quality, and enable integrated multimodal research, with lessons that are not only applicable the INCLUDE Project but also to other complex clinical research programs.

Nirmatrelvir-ritonavir targeting viral persistence in post-COVID-19 condition (long COVID) in the USA (RECOVER-VITAL): a randomised, double-blind, placebo-controlled, phase 2 trial.

BACKGROUND Post-acute sequelae of SARS-CoV-2 infection, more commonly known as long COVID, has emerged as a major health problem. The pathogenesis of long COVID is unknown, but among the leading hypotheses is viral persistence. We aimed to investigate whether the use of the SARS-CoV-2 antiviral nirmatrelvir-ritonavir improved long COVID symptoms. METHODS We conducted a double-blind, placebo-controlled, randomised trial involving adults who had developed persistent symptoms (≥12 weeks) associated with three major symptom phenotypes (cognitive, autonomic, or exercise) after acute SARS-CoV-2 infection at 69 US sites. Participants were eligible if they were 18 years or older and had a previous suspected, probable, or confirmed SARS-CoV-2 infection, as defined by the Pan American Health Organization. Eligible participants were also required to have either at least two moderate symptoms from the same phenotype or one severe phenotype-associated symptom, as identified with the Cluster Targeted COVID-19 Symptom Questions. Participants were randomly allocated in a double-blind manner in a 1:1:1 ratio using permuted blocks of size 30 to receive either 15 days of active intervention followed by 10 days of placebo (300 mg nirmatrelvir-100 mg ritonavir twice daily, then 100 mg ritonavir-placebo); 25 days of active intervention (300 mg nirmatrelvir-100 mg ritonavir twice daily); or 25 days of placebo-ritonavir (100 mg ritonavir-placebo). A clinically significant change in patient-reported outcomes at day 90 comprised the primary endpoint: Patient-Reported Outcomes Measurement Information System Cognitive Function Short Form 8a, Orthostatic Hypotension Questionnaire question 1, and a modified version of the DePaul Symptom Questionnaire Post-Exertional Malaise short form. Secondary outcomes were phenotype-specific performance measures. The study was registered at ClinicalTrials.gov (NCT05595369) and is complete. FINDINGS Between July 27, 2023, and Sept 6, 2024, 1207 individuals were screened. Of these, 964 were randomly allocated and 959 participants, excluding four participants who were later found ineligible and one who did not initiate treatment, were enrolled in the three phenotypes: 332 to cognitive, 334 to autonomic, and 332 to exercise. In the 959 participants in the mITT population, 643 (67%) self-reported as female, 314 (33%) were male, and two participants had a sex of unknown or undifferentiated; 750 (78%) were White; and 108 (11%) were Hispanic, Latino, or Spanish. The median age was 49 years (IQR 38-59). No statistically significant benefits were observed for any phenotype for primary endpoints. For the cognitive phenotype, adjusted differences compared to placebo were 3·2% (95% CI -10·4 to 16·8, p=0·65) for the 25-day regimen and -2·2% (-15·5 to 11·1, p=0·74) for the 15-day regimen. For the autonomic phenotype, adjusted differences were -6·4% (-18·5 to 5·7, p=0·30) for the 25-day regimen compared to placebo and -0·1% (-12·5 to 12·3, p=0·99) for the 15-day regimen compared to placebo. For exercise, adjusted differences were -7·8% (-19·5 to 3·8, p=0·19) for the 25-day regimen compared to placebo and 0·9% (-11·4 to 13·2, p=0·88) for the 15-day regimen compared to placebo. There were no differences in secondary endpoints, and no safety signals were observed; there were no deaths, and 52 serious adverse events occurred in 42 (4%) of 963 participants over the course of the study. INTERPRETATION Nirmatrelvir-ritonavir for 15 days or 25 days showed no evidence of benefit in long COVID in any of the three phenotypes studied. These findings suggest additional approaches to measuring the symptom burden and treating Long COVID are needed. FUNDING National Institutes of Health.

Cross-sectional and Longitudinal Relationships Between Multi-Dimensional Sleep Composites and Cognition in Multi-Ethnic Study of Atherosclerosis (MESA).