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Multimodal Digital Biomarker Prediction of Acute Clinical Deterioration (FUSION-72)

9 septembre 2026 mis à jour par: Truway Health, Inc.

Multimodal Physiologic Signal Fusion for 72-Hour Prediction of Acute Clinical Deterioration

Rather than relying on a single abnormal vital sign, the study will examine how multiple physiologic signals change together over time and whether changes in the relationships among these signals provide useful information about impending clinical deterioration. Individual participant physiologic patterns may be characterized longitudinally to account for differences between individuals and changes within the same individual over time.

The primary objective is to evaluate the predictive accuracy of multimodal digital biomarkers for protocol-defined acute clinical deterioration occurring within 72 hours. The study is observational and does not assign participants to an investigational treatment.

Aperçu de l'étude

Statut

Inscription sur invitation

Les conditions

Intervention / Traitement

Description détaillée

FUSION-72 (Multimodal Physiologic Signal Fusion for 72-Hour Prediction of Acute Clinical Deterioration) is a prospective, longitudinal, observational study designed to investigate multimodal digital biomarkers associated with acute clinical deterioration. The central scientific premise is that clinically meaningful deterioration may be preceded not only by an abnormal value in an individual physiologic parameter, but also by coordinated or discordant changes occurring across multiple physiologic, behavioral, and symptom domains.

The study will collect longitudinal data from multiple digital and physiologic sources, which may include wearable electrocardiography (ECG), photoplethysmography (PPG), peripheral oxygen saturation (SpO2), temperature, gait and activity characteristics, sleep measures, voice characteristics, cough characteristics, and participant-reported symptoms.

These multimodal measurements will be temporally aligned and analyzed to characterize changes within individual participants and relationships among physiologic, behavioral, acoustic, and symptom-derived signals. Analyses will evaluate whether multimodal signal fusion provides additional predictive information beyond individual digital biomarker streams or conventional single-parameter measurements.

The primary objective is to evaluate the predictive accuracy of a prespecified multimodal digital biomarker model for protocol-defined acute clinical deterioration occurring within a subsequent 72-hour prediction window. Secondary objectives include evaluation of time-dependent predictive performance, lead time to detection, incremental predictive value of multimodal signal relationships, model calibration, and robustness of predictive performance across prespecified participant and clinical subgroups.

The study is observational. No investigational treatment is assigned, and participation does not direct, replace, or require modification of usual clinical care or medical management.

Type d'étude

Observationnel

Inscription (Estimé)

10000

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Lieux d'étude

  • États-Unis
    • New York
      • New York, New York, États-Unis, 10016
        • Truway Health, Inc.

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

  • Adulte
  • Adulte plus âgé

Accepte les volontaires sains

Non

Méthode d'échantillonnage

Échantillon non probabiliste

Population étudiée

FUSION-72 will enroll an adult longitudinal cohort for prospective evaluation of multimodal digital biomarkers associated with acute clinical deterioration. Participants will undergo protocol-specified collection of wearable and remote digital measurements, including ECG, PPG, oxygen saturation, temperature, gait, sleep, voice, cough, and participant-reported symptoms. The study is designed to evaluate temporal and cross-signal relationships and their ability to predict protocol-defined clinical deterioration within 72 hours.

La description

Inclusion Criteria:

  • Adults aged 18 through 90 years at enrollment.
  • Able to provide informed consent, or have a legally authorized representative provide consent when permitted by the applicable protocol and regulations.
  • Able and willing to participate in prospective longitudinal digital biomarker monitoring.
  • Able to use, or permit application of, study-authorized wearable or remote-monitoring technologies.
  • Able and willing to provide protocol-specified physiologic, behavioral, acoustic, and symptom data.
  • Expected to have sufficient follow-up to permit evaluation of the 72-hour prediction endpoint.
  • Willing to comply with study procedures and data-collection requirements.

Exclusion Criteria:

  • Inability to provide informed consent or otherwise participate through an approved consent process.
  • Clinical or technical circumstances that prevent reliable collection of the required multimodal digital biomarker data.
  • Inability or unwillingness to comply with study monitoring procedures.
  • Enrollment in another study that, in the investigator's judgment, would materially interfere with FUSION-72 data collection or endpoint assessment.
  • Any circumstance that, in the investigator's judgment, would make participation inappropriate or compromise the integrity of the study.

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

Cohortes et interventions

Groupe / Cohorte
Intervention / Traitement
FUSION-72 Prospective Multimodal Monitoring Cohort
Participants enrolled in a prospective longitudinal observational cohort undergoing multimodal digital biomarker monitoring. Participants will contribute wearable and digital measurements including electrocardiography (ECG), photoplethysmography (PPG), oxygen saturation, temperature, gait, sleep, voice, cough, and participant-reported symptoms. Data will be analyzed longitudinally to characterize temporal changes and relationships among physiologic and behavioral signals and to evaluate prediction of protocol-defined acute clinical deterioration within 72 hours. No investigational treatment or therapeutic intervention is assigned by the study.
Autre: Multimodal Digital Biomarker Monitoring
Prospective collection and analysis of multimodal digital biomarkers derived from wearable and remote-monitoring technologies, including ECG, PPG, oxygen saturation, temperature, gait, sleep, voice, cough, and participant-reported symptom data. The monitoring is observational and does not direct or replace clinical care, does not assign treatment, and does not require modification of participants' usual medical management. Multimodal signals will be temporally aligned and evaluated for changes in inter-signal relationships associated with protocol-defined clinical deterioration occurring within the subsequent 72-hour prediction window.

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
Predictive Accuracy of Multimodal Digital Biomarker Fusion for Acute Clinical Deterioration Within 72 Hours
Délai: At initiation of each prespecified prediction episode and 72 hours after initiation of each prespecified prediction episode.
Performance of the prespecified multimodal digital biomarker model in predicting protocol-defined acute clinical deterioration during the subsequent 72-hour prediction window. Model performance will be evaluated using the area under the receiver operating characteristic curve (AUROC), with additional assessment of the area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and calibration.
At initiation of each prespecified prediction episode and 72 hours after initiation of each prespecified prediction episode.

Mesures de résultats secondaires

Mesure des résultats
Description de la mesure
Délai
Time-Dependent Predictive Performance of Individual and Combined Digital Biomarkers
Délai: At initiation of each prespecified prediction episode and 72 hours after initiation of each prespecified prediction episode.
Comparison of predictive performance associated with individual and multimodal combinations of electrocardiography (ECG), photoplethysmography (PPG), peripheral oxygen saturation (SpO2), temperature, gait, sleep, voice, cough, and symptom-derived features for prediction of protocol-defined acute clinical deterioration.
At initiation of each prespecified prediction episode and 72 hours after initiation of each prespecified prediction episode.
Lead Time to Detection of Acute Clinical Deterioration
Délai: For each protocol-defined acute clinical deterioration event, during the 72 hours preceding event occurrence and ending at the time of event occurrence.
Time interval, measured in hours, between the earliest prespecified model-generated deterioration signal meeting protocol-defined prediction criteria and occurrence of the corresponding protocol-defined acute clinical deterioration event.
For each protocol-defined acute clinical deterioration event, during the 72 hours preceding event occurrence and ending at the time of event occurrence.
Incremental Predictive Value of Multimodal Signal Relationships
Délai: At initiation of each prespecified prediction episode and 72 hours after initiation of each prespecified prediction episode.
Assessment of whether incorporating prespecified temporal relationships and interactions among multiple physiologic, behavioral, acoustic, and symptom-derived signals improves prediction of protocol-defined acute clinical deterioration compared with models based on individual signal domains or conventional single-parameter measurements.
At initiation of each prespecified prediction episode and 72 hours after initiation of each prespecified prediction episode.
Model Calibration for 72-Hour Clinical Deterioration Risk
Délai: At 72 hours after initiation of each prespecified prediction episode.
Agreement between predicted probabilities of protocol-defined acute clinical deterioration and observed event frequencies within the subsequent 72-hour prediction horizon, assessed using prespecified calibration metrics.
At 72 hours after initiation of each prespecified prediction episode.
Robustness of Multimodal Prediction Across Participant and Clinical Subgroups
Délai: At 72 hours after initiation of each prespecified prediction episode.
Evaluation of predictive performance across prespecified participant and clinical subgroups, including age category, sex, baseline health status, comorbidity burden, care setting, and availability or completeness of individual digital biomarker streams.
At 72 hours after initiation of each prespecified prediction episode.

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Parrainer

Truway Health, Inc.

Les enquêteurs

  • Chercheur principal: Gavin C Solomon, MD, Truway Health, Inc.

Publications et liens utiles

La personne responsable de la saisie des informations sur l'étude fournit volontairement ces publications. Il peut s'agir de tout ce qui concerne l'étude.

Publications générales

Liens utiles

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Réel)

1 septembre 2026

Achèvement primaire (Estimé)

30 septembre 2038

Achèvement de l'étude (Estimé)

31 mars 2039

Dates d'inscription aux études

Première soumission

1 septembre 2026

Première soumission répondant aux critères de contrôle qualité

9 septembre 2026

Première publication (Réel)

14 septembre 2026

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

14 septembre 2026

Dernière mise à jour soumise répondant aux critères de contrôle qualité

9 septembre 2026

Dernière vérification

1 septembre 2026

Plus d'information

Termes liés à cette étude

Mots clés

Termes MeSH pertinents supplémentaires

Autres numéros d'identification d'étude

  • TH-FUSION72-2026-001

Plan pour les données individuelles des participants (IPD)

Prévoyez-vous de partager les données individuelles des participants (DPI) ?

NON

Description du régime IPD

Individual participant data will not be shared with other researchers. Individual-level clinical, imaging, and other participant data will remain under the control of the participating research sites and will not be transferred to external investigators or deposited in a publicly accessible repository. The study may use privacy-preserving federated analysis in which participating sites retain source data locally and transmit only approved, non-identifying computational outputs, such as model parameters, aggregate statistics, or other de-identified results, as permitted by the protocol and applicable IRB requirements. Any sharing of aggregate or de-identified study findings will be conducted in accordance with the approved protocol, participant consent/authorization, applicable law, and institutional data-use policies.

Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

Ces informations ont été extraites directement du site Web clinicaltrials.gov sans aucune modification. Si vous avez des demandes de modification, de suppression ou de mise à jour des détails de votre étude, veuillez contacter register@clinicaltrials.gov. Dès qu'un changement est mis en œuvre sur clinicaltrials.gov, il sera également mis à jour automatiquement sur notre site Web .

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