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Neonatal Neurological Observation With Video AI (NeoNOVA)

1. juni 2026 opdateret af: Artemis AI Labs
NeoNOVA is a multi-site, prospective, single-arm, silent observational study to determine: among (Population) infants admitted to newborn services during their inpatient hospital stay, whether (Intervention) continuous bedside non-contact high definition video running real-time AI analysis of anatomic landmarks and movement, (Comparison) compared against human-labeled video frames and standardized clinical exams, will (Outcome) accurately localize infant anatomic landmarks (primary objective; outcome median position error in pixels) and demonstrate a statistically significant association between a video-derived movement index and clinical measures of patient neurological exams (secondary objective; outcomes N-PASS and modified Sarnat exams).

Studieoversigt

Status

Ikke rekrutterer endnu

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

Over 1.3 million infants are admitted to Neonatal Intensive Care Units (NICUs) in OECD countries every year. All NICU infants undergo cardiorespiratory monitoring allowing for expedient hemodynamic management. However, there is no analogous clinical decision support for neurologic monitoring, despite neurologic injury having the highest impact on long-term neurodevelopmental outcome. Neonatal encephalopathy (NE) is a leading cause of neurodevelopmental impairment (NDI) and death, occurring in 3 per 1000 live births; inadequate pain control and sedation is a leading risk factor for many complications in the NICU including unplanned extubation (UE), occurring at rates 1-5 UEs per 100 intubation days. Currently, neurologic changes such as NE, pain control, and sedation are primarily assessed by physical examination. However, this approach is deeply flawed since physical examination is performed at set time intervals, is highly subjective, and may not discern subtle or subacute changes.

To fill this critical gap in neonatal care, we developed and validated NeoPose, a low-cost, non-invasive, computer vision digital health tool to continuously monitor infants using real time video streams. NeoPose uses Pose Artificial Intelligence (AI) for an explainable approach to measure, quantify, and analyze infant movement. From the vectorized movement, we can accurately confirm the presence of encephalopathy and quantify the degree of sedation. Our explainable AI platform enables continuous neuromonitoring with AI-driven alerts, suspicious event replay, movement comparisons, and training on a vast dataset of normal and abnormal infant movements far beyond what any provider could witness.

The Neonatal Neurological Observation with Video AI (NeoNOVA) study is a multi-site, prospective, single-arm, pragmatic, silent observational study to evaluate the performance of NeoPose and AI-derived insights in real world settings. NeoNOVA will deploy a bedside video monitoring system (ArtemisAI Platform) that continuously, passively video records the subject from enrollment to discharge. The study will prospectively validate the AI system's tracking accuracy against ground-truth human-labeled video frames (primary objective; outcome median position error in pixels), will evaluate the association between a video-derived movement index and standardized bedside assessments of encephalopathy, pain, and sedation (secondary objective; outcomes N-PASS and modified Sarnat scales), and will support hypothesis-generating research on novel video prediction algorithms for outcomes like sepsis and need for respiratory support (tertiary objective). The study operates in "silent mode," where AI outputs are not shown to the patient's clinical team. Findings are intended to support a structured clinical evidence generation plan for a Software as a Medical Device (SaMD) designed for continuous, non-contact neurological monitoring in the NICU.

Undersøgelsestype

Observationel

Tilmelding (Anslået)

200

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Undersøgelse Kontakt Backup

Studiesteder

  • Forenede Stater
    • New York
      • New York, New York, Forenede Stater, 10029
      • New York, New York, Forenede Stater, 10065
        • Weill Cornell Medicine / NewYork-Presbyterian Hospital
        • Kontakt:
        • Ledende efterforsker:
          • Sushma Krishna, MD

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Barn
  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ja

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

Neonates of any sex, gestational age, demographic background, or health status admitted to newborn services, including the NICU, at a participating hospital. No diagnosis-specific criteria apply. Consent is provided by at least one parent or legally authorized representative aged 18 or older. Sites will make reasonable efforts to enroll a demographically diverse sample reflective of their local NICU populations, supporting prespecified subgroup analyses of AI performance consistency across gestational age, race/ethnicity, sex, and clinical condition. The first five participants at each site are excluded from primary and secondary endpoint analyses and serve as a technology familiarization cohort.

Beskrivelse

Inclusion Criteria:

  • Signed and dated informed consent from at least one parent or legally authorized representative (LAR) who is at least 18 years old.
  • Parent/LAR expresses willingness to comply with study procedures for the duration of the infant's hospital stay.
  • Infant of any sex (including intersex/undetermined) admitted to newborn services (including the NICU) at a participating hospital.

Exclusion Criteria:

  • Parents or LAR unable to provide informed consent or are under the age of 18.
  • Non-viable neonates

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Intervention / Behandling
NICU-Admitted Infants Undergoing Continuous Video Monitoring
Infants admitted to newborn services, including the neonatal intensive care unit (NICU), who meet eligibility criteria and undergo continuous, non-contact bedside video monitoring from enrollment until hospital discharge.
Enhed: Continuous bedside video monitoring with AI anatomic landmark tracking for neurologic monitoring
A non-contact, passive bedside video recording system is mounted adjacent to the infant's crib or incubator. The device continuously captures video data from enrollment to hospital discharge or withdrawal. The device runs AI models to track infant anatomic landmarks and calculate a continuous movement index. The trial runs in "silent mode," where AI outputs are not shown to the patient's clinical team and do not influence care.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
AI Anatomic Landmark Tracking Accuracy
Tidsramme: At study completion, an average of 1 week.
The primary endpoint is analytical performance of the AI pose estimation system, quantified as median position error (in pixels) between AI-predicted and human-labeled anatomic landmark positions extracted from continuous bedside video. Success is defined as median position error less than typical human inter-rater variability.
At study completion, an average of 1 week.

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Movement Index - Encephalopathy measured by modified Sarnat exam
Tidsramme: Through study completion, an average of 1 week.
Association between a video-derived movement index and encephalopathy classification of severity from the modified Sarnat exam score, a bedside neurological exam assessed by trained clinical staff.
Through study completion, an average of 1 week.
Movement Index - N-PASS
Tidsramme: Through study completion, an average of 1 week.
Association between a video-derived movement index and Neonatal Pain, Agitation, and Sedation Scale (N-PASS) score (ordinal outcome), a bedside neurological exam measuring pain/sedation and assessed by trained clinical staff.
Through study completion, an average of 1 week.
Movement Index - Sedative Exposure
Tidsramme: Through study completion, an average of 1 week.
Association between movement index and sedative exposure, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - Chronological Age at Video
Tidsramme: Through study completion, an average of 1 week.
Association between movement index and chronological age at video, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - Gestational age at birth
Tidsramme: Through study completion, an average of 1 week.
Association between the movement index and gestational age at birth, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - Sleep state
Tidsramme: Through study completion, an average of 1 week.
Association between the movement index and sleep state, a routinely collected clinical variable that influences neonatal arousal.
Through study completion, an average of 1 week.
Movement Index - EEG evidence of cerebral dysfunction
Tidsramme: Through study completion, an average of 1 week.
Association between the movement index and, if obtained as part of routine clinical care, EEG evidence of cerebral dysfunction (a biomarker of encephalopathy).
Through study completion, an average of 1 week.

Andre resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
AI Anatomic Landmark Tracking - Post-Menstrual Age at Video
Tidsramme: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) across post-menstrual ages at the time of video recording.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Encephalopathy Status
Tidsramme: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) across encephalopathy statuses.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Caregiver-reported Race/Ethnicity
Tidsramme: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) across caregiver-reported race/ethnicity.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Sex
Tidsramme: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) and sex.
At study completion, an average of 1 week.
AI Anatomic Landmark Tracking - Lighting Conditions
Tidsramme: At study completion, an average of 1 week.
Assess performance of AI anatomic landmark tracking (median position error) and lighting conditions (phototherapy, lights on/off, time of day).
At study completion, an average of 1 week.
Parent and Provider Feedback
Tidsramme: At baseline and study completion (Day 1 - Day 7, on average).
Brief structured surveys administered to parents and clinical providers to assess acceptability, usability, and perceived burden of the bedside video monitoring system. Findings will inform system design refinements and support future bedside adoption and regulatory human factors documentation.
At baseline and study completion (Day 1 - Day 7, on average).

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Artemis AI Labs

Efterforskere

  • Ledende efterforsker: Benjamin Glicksberg, PhD, Icahn School of Medicine at Mount Sinai

Publikationer og nyttige links

Den person, der er ansvarlig for at indtaste oplysninger om undersøgelsen, leverer frivilligt disse publikationer. Disse kan handle om alt relateret til undersøgelsen.

Generelle publikationer

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Anslået)

1. juni 2026

Primær færdiggørelse (Anslået)

31. maj 2027

Studieafslutning (Anslået)

31. maj 2029

Datoer for studieregistrering

Først indsendt

26. maj 2026

Først indsendt, der opfyldte QC-kriterier

1. juni 2026

Først opslået (Faktiske)

5. juni 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

5. juni 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

1. juni 2026

Sidst verificeret

1. juni 2026

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • STUDY-25-01036

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

Aggregate deidentified data and results will be shared. Individual participant video data will not be shared due to PHI concerns.

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

Studerer et amerikansk FDA-reguleret lægemiddelprodukt

Ingen

Studerer et amerikansk FDA-reguleret enhedsprodukt

Ja

produkt fremstillet i og eksporteret fra U.S.A.

Ingen

Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

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