Truway Health, Inc.
New York, 10016, United States
NCT Number: NCT07814118
The OMNIPHYS study will investigate whether multimodal ultrasound and other routinely collected clinical and physiologic data can be combined with artificial intelligence to characterize changes in a person's physiologic state over time. The study will examine cardiac, vascular, pulmonary, and systemic physiologic measurements and develop longitudinal models that describe baseline physiology, physiologic perturbation, compensation, deterioration, treatment response, and recovery. The study is observational and will not assign experimental treatments. The goal is to determine whether changes in multimodal physiologic patterns can be identified and characterized earlier and more reliably than conventional single-time-point assessment.
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All sexes
Observational
New York, 10016, United States
OMNIPHYS: A Prospective Multimodal Longitudinal Study of AI-Enabled Physiologic State Modeling and Early Detection of Clinical Deterioration
The OMNIPHYS study is a prospective, longitudinal observational investigation designed to develop and evaluate a multimodal framework for characterizing human physiologic state and physiologic trajectory over time. The study is centered on the hypothesis that clinically meaningful deterioration may be preceded by measurable changes across multiple physiologic domains, including cardiac function, vascular flow, pulmonary findings, systemic venous congestion, and other routinely available clinical measurements.
The study will collect and analyze multimodal data obtained during clinically appropriate assessments. Ultrasound-derived data may include two-dimensional and three-dimensional imaging, color Doppler, spectral Doppler, cardiac motion and functional measurements, vascular flow characteristics, venous findings, and pulmonary ultrasound observations. Additional clinical data may include vital signs, electrocardiographic measurements, oxygen saturation, laboratory results, medication and intervention records, diagnoses, encounters, and other relevant longitudinal clinical observations.
The study will develop a Physiologic State Vector (PSV) representing multidimensional observations of an individual at defined points in time. Rather than treating disease status as a binary outcome, OMNIPHYS will investigate physiologic states and transitions between states.
The prespecified conceptual state framework includes:
S0 - Baseline: stable observed physiologic phenotype.
S1 - Physiologic Perturbation: measurable deviation from an individual's established baseline.
S2 - Compensation: persistent physiologic abnormality without defined acute clinical deterioration.
S3 - Pre-Decompensation: a longitudinal trajectory associated with increasing probability of clinically significant deterioration.
S4 - Acute Decompensation: clinically meaningful physiologic or clinical deterioration.
S5 - Intervention Response: measurable physiologic change following clinical intervention.
S6 - Recovery: movement toward the participant's prior or expected physiologic state.
S7 - Persistent Dysfunction: sustained deviation from baseline following an acute event or intervention.
The principal research construct is therefore:
Physiologic State → Longitudinal Trajectory → State Transition → Clinical Outcome
The primary investigational performance measure will be the Physiologic Transition Detection Time (PTDT), defined as the interval between a prospectively defined algorithmic detection of a clinically meaningful physiologic transition and the corresponding predefined clinical reference event. PTDT will be evaluated as a research endpoint and will not independently direct clinical care unless separately authorized under an applicable clinical protocol.
Secondary analyses will evaluate physiologic-state classification, trajectory prediction, treatment-response characterization, recovery prediction, longitudinal model calibration, uncertainty estimation, human-AI concordance, cross-site performance, cross-device robustness, and model stability over time.
The OMNIPHYS framework is intended to support multiple pathology-specific cohorts while maintaining a common physiologic modeling architecture. Potential cohorts may include heart failure, cardiomyopathy, pulmonary hypertension, valvular disease, myocarditis, pericardial disease, pulmonary edema, acute respiratory distress syndrome, pulmonary embolic disease, venous thrombosis, sepsis-associated cardiac dysfunction, systemic venous congestion, acute kidney injury, and other clinically appropriate conditions.
A designated research component will investigate federated learning, in which appropriately governed model-development processes may be evaluated across participating institutions without requiring centralized transfer of patient-level datasets. The study will assess whether multimodal physiologic models maintain performance across institutions, ultrasound platforms, acquisition environments, operators, and heterogeneous clinical populations.
The study may additionally investigate a research construct termed the TRUWAY Physiologic Digital Twin, defined as a computational longitudinal representation of observed physiologic measurements and their temporal relationships. This construct is intended for research into trajectory modeling and prediction and does not represent a clinical diagnosis or autonomous clinical decision-making system.
Data interoperability and research infrastructure may incorporate recognized clinical data representations, including DICOM for medical imaging and FHIR-compatible clinical data structures where available and appropriate. Data provenance, version control, quality assurance, model-version tracking, and longitudinal auditability will be incorporated into the research architecture.
The anticipated study horizon is approximately 20 years, from September 2026 through September 2046, permitting investigation of short-term physiologic transitions as well as long-term disease trajectories, recurrence, recovery, persistent dysfunction, technological evolution, and longitudinal model performance.
OMNIPHYS is designed as an observational research protocol. It does not by itself prescribe medical treatment, alter clinical management, or establish that an investigational algorithm is safe or effective for clinical use. Research findings will be evaluated according to the approved protocol, applicable institutional requirements, human-subject protections, data-governance requirements, and prospective statistical analysis plans.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Observational physiologic and imaging data acquisition.
Time frame: Continuous longitudinal assessment from baseline (Year 0) through Year 50; PTDT will be calculated separately for each predefined clinical reference event occurring during the 50-year follow-up period.
Time interval, measured in days, between the first prespecified algorithmic detection of a clinically meaningful physiologic state transition and the corresponding predefined clinical reference event. Transitions may include progression from baseline or compensated physiology to pre-decompensation or acute decompensation. The analysis will evaluate the temporal relationship between multimodal physiologic signals and subsequent clinical events.
Time frame: Baseline (Year 0) through Year 50; physiologic state-classification accuracy will be assessed using all evaluable longitudinal observations and predefined clinical reference events collected during the 50-year follow-up period.
Accuracy of classification of predefined longitudinal physiologic states (S0 Baseline, S1 Physiologic Perturbation, S2 Compensation, S3 Pre-Decompensation, S4 Acute Decompensation, S5 Intervention Response, S6 Recovery, and S7 Persistent Dysfunction) using multimodal clinical, physiologic, and ultrasound-derived data.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Performance of longitudinal models in predicting subsequent physiologic state transitions and clinically meaningful deterioration from prior multimodal physiologic observations.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Time from enrollment or a predefined physiologic assessment to the occurrence of a prespecified clinically meaningful deterioration event, evaluated in relation to longitudinal multimodal physiologic trajectories.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Association between observed clinical interventions and subsequent changes in multimodal physiologic state, including quantitative characterization of physiologic response, non-response, delayed response, and recurrence.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Magnitude and rate of movement from an abnormal or decompensated physiologic state toward a predefined recovery state following a clinical event or intervention.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Discrimination, calibration, sensitivity, specificity, and predictive performance of multimodal artificial-intelligence models for identifying predefined physiologic states and clinically meaningful state transitions.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Performance consistency of physiologic-state models across participating clinical sites, ultrasound systems, transducer configurations, acquisition protocols, patient populations, and other relevant data domains.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Longitudinal assessment of changes in model performance, calibration, data distributions, and physiologic feature distributions over time to characterize temporal robustness and potential model drift.
Time frame: Baseline (Year 0) through Year 50 of longitudinal follow-up.
Agreement between AI-derived physiologic-state classifications and qualified human clinical or imaging assessments using prespecified agreement and concordance measures.
Truway Health, Inc.
Industry
OMNIPHYS: A Prospective Multimodal Longitudinal Study of AI-Enabled Physiologic State Modeling and Early Detection of Clinical Deterioration
Acronym: OMNIPHYS
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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