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ER-VISION-AI Study (ER-VISION-AI)

21 luglio 2026 aggiornato da: Ewha Womans University Mokdong Hospital

Multimodal Visual Language Model-Assisted Diagnostic Strategy in the Emergency Department: A Prospective Multicenter Randomized Controlled Trial (ER-VISION-AI Study)

Prospective, multicenter, randomized, open-label, blinded-endpoint (PROBE-like) clinical trial evaluating whether physician-supervised Generative Pre-trained Transformer (GPT)-assisted multimodal diagnostic support improves diagnostic concordance in emergency department patients presenting with acute cardiopulmonary symptoms.

Panoramica dello studio

Stato

Non ancora reclutamento

Condizioni

Intervento / Trattamento

Tipo di studio

Interventistico

Iscrizione (Stimato)

1000

Fase

  • Non applicabile

Contatti e Sedi

Questa sezione fornisce i recapiti di coloro che conducono lo studio e informazioni su dove viene condotto lo studio.

Contatto studio

Luoghi di studio

  • Corea del Sud
      • Seoul, Corea del Sud, 07804
        • Ewha Womans University Mokdong Hospital
        • Contatto:

Criteri di partecipazione

I ricercatori cercano persone che corrispondano a una certa descrizione, chiamata criteri di ammissibilità. Alcuni esempi di questi criteri sono le condizioni generali di salute di una persona o trattamenti precedenti.

Criteri di ammissibilità

Età idonea allo studio

  • Adulto
  • Adulto più anziano

Accetta volontari sani

No

Descrizione

Inclusion Criteria:

  • Age ≥18 years
  • Presentation to a participating emergency department with acute cardiopulmonary symptoms, including chest pain, dyspnea, palpitations, syncope, dizziness, or fever accompanied by cardiopulmonary symptoms
  • Performance of both a standard 12-lead electrocardiogram and chest radiography during the initial emergency department evaluation
  • Availability of initial clinical assessment, vital signs, laboratory findings, and all mandatory clinical information required for the multimodal AI workflow
  • Expected emergency department observation or hospital admission for at least 24 hours
  • Ability and willingness to provide written informed consent

Exclusion Criteria:

  • Inability or refusal to provide written informed consent
  • Requirement for immediate life-saving intervention that precludes completion of the study workflow
  • Death before completion of the initial emergency department diagnostic assessment
  • Electrocardiographic quality insufficient for reliable physician or Artificial intelligence (AI) interpretation
  • Chest radiographic quality insufficient for reliable physician or Artificial intelligence (AI) interpretation
  • Cardiac pacing rhythm
  • Missing mandatory clinical information required for the multimodal Artificial intelligence (AI) workflow
  • Previous enrollment in the ER-VISION-AI trial
  • Inability to establish a blinded adjudicated reference diagnosis

Piano di studio

Questa sezione fornisce i dettagli del piano di studio, compreso il modo in cui lo studio è progettato e ciò che lo studio sta misurando.

Come è strutturato lo studio?

Dettagli di progettazione

  • Scopo principale: Diagnostico
  • Assegnazione: Randomizzato
  • Modello interventistico: Assegnazione parallela
  • Mascheramento: Nessuno (etichetta aperta)

Armi e interventi

Gruppo di partecipanti / Arm
Intervento / Trattamento
Sperimentale: GPT-assisted multimodal visual language model (VLM) diagnostic strategy
Participants receive physician-supervised Generative Pre-trained Transformer (GPT)-assisted multimodal diagnostic support integrating electrocardiography, chest radiography, structured clinical information, laboratory findings, vital signs, and relevant medical history. Treating physicians remain responsible for all diagnostic and therapeutic decisions.
Test diagnostico: Generative Pre-trained Transformer (GPT)-assisted multimodal visual language model (VLM) diagnostic support
A Generative Pre-trained Transformer (GPT)-based multimodal visual language model integrates electrocardiograms, chest radiographs, structured clinical information, laboratory findings, vital signs, and relevant clinical history to generate diagnostic suggestions and differential diagnoses for physician-supervised clinical decision support.
Comparatore attivo: Conventional physician-guided diagnostic strategy
Participants undergo standard emergency department diagnostic evaluation according to routine clinical practice without Generative Pre-trained Transformer (GPT)-assisted diagnostic support.
Test diagnostico: Conventional emergency department diagnostic evaluation
Routine emergency department diagnostic evaluation performed according to standard clinical practice without AI-assisted diagnostic support.

Cosa sta misurando lo studio?

Misure di risultato primarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Diagnostic concordance between the final emergency department diagnosis and the blinded adjudicated reference diagnosis established at hospital discharge.
Lasso di tempo: During the index hospitalization, up to hospital discharge (average 3 days)
Diagnostic concordance between the treating physician's final emergency department diagnosis and the blinded adjudicated reference diagnosis based on the prespecified principal diagnostic category.
During the index hospitalization, up to hospital discharge (average 3 days)

Misure di risultato secondarie

Misura del risultato
Misura Descrizione
Lasso di tempo
Diagnostic concordance after Generative Pre-trained Transformer (GPT)-assisted diagnostic support
Lasso di tempo: During the index emergency department visit (average 6 hours)
Diagnostic concordance between the physician's final emergency department diagnosis after Generative Pre-trained Transformer (GPT)-assisted multimodal diagnostic support and the blinded adjudicated reference diagnosis in participants assigned to the intervention group.
During the index emergency department visit (average 6 hours)
Time from emergency department presentation to final diagnosis
Lasso di tempo: During the index emergency department visit (average 6 hours)
Time required from emergency department presentation until establishment of the physician's final emergency department diagnosis.
During the index emergency department visit (average 6 hours)
Diagnostic reclassification after Generative Pre-trained Transformer (GPT)-assisted evaluation
Lasso di tempo: During the index emergency department visit (average 6 hours)
Frequency of changes between the physician's initial working diagnosis and the final emergency department diagnosis after review of Generative Pre-trained Transformer (GPT)-generated diagnostic recommendations.
During the index emergency department visit (average 6 hours)
Physician diagnostic confidence
Lasso di tempo: During the index emergency department visit (average 6 hours)
Physician-reported diagnostic confidence recorded before and after Generative Pre-trained Transformer (GPT)-assisted diagnostic support using the prespecified study assessment scale.
During the index emergency department visit (average 6 hours)
Physician acceptance of Generative Pre-trained Transformer (GPT)-generated diagnostic recommendations
Lasso di tempo: During the index emergency department visit (average 6 hours)
Frequency of physician acceptance, modification, or rejection of Generative Pre-trained Transformer (GPT)-generated diagnostic recommendations in the intervention group.
During the index emergency department visit (average 6 hours)
Emergency department disposition accuracy
Lasso di tempo: Up to hospital discharge (average 3 days)
Accuracy of emergency department disposition decisions, including discharge, hospital admission, or intensive care unit admission, compared with the adjudicated reference diagnosis.
Up to hospital discharge (average 3 days)
Emergency department length of stay
Lasso di tempo: Up to hospital discharge (average 3 days)
Length of stay in the emergency department measured from patient presentation until emergency department discharge or hospital admission.
Up to hospital discharge (average 3 days)
Hospital length of stay
Lasso di tempo: Up to hospital discharge (average 3 days)
Total duration of hospitalization from admission until hospital discharge.
Up to hospital discharge (average 3 days)
In-hospital mortality
Lasso di tempo: Up to hospital discharge (average 3 days)
All-cause mortality occurring during the index hospitalization.
Up to hospital discharge (average 3 days)
30-day all-cause mortality
Lasso di tempo: 30 days
All-cause mortality occurring within 30 days after the index emergency department visit.
30 days
30-day emergency department revisit
Lasso di tempo: 30 days
Revisit to any emergency department for any cause within 30 days after the index emergency department visit.
30 days
30-day hospital readmission
Lasso di tempo: 30 days
Hospital readmission for any cause within 30 days after discharge from the index hospitalization.
30 days

Collaboratori e investigatori

Qui è dove troverai le persone e le organizzazioni coinvolte in questo studio.

Sponsor

Ewha Womans University Mokdong Hospital

Collaboratori

Ewha Womans University Seoul Hospital

Pubblicazioni e link utili

La persona responsabile dell'inserimento delle informazioni sullo studio fornisce volontariamente queste pubblicazioni. Questi possono riguardare qualsiasi cosa relativa allo studio.

Pubblicazioni generali

Studiare le date dei record

Queste date tengono traccia dell'avanzamento della registrazione dello studio e dell'invio dei risultati di sintesi a ClinicalTrials.gov. I record degli studi e i risultati riportati vengono esaminati dalla National Library of Medicine (NLM) per assicurarsi che soddisfino specifici standard di controllo della qualità prima di essere pubblicati sul sito Web pubblico.

Studia le date principali

Inizio studio (Stimato)

1 gennaio 2027

Completamento primario (Stimato)

31 dicembre 2028

Completamento dello studio (Stimato)

31 dicembre 2029

Date di iscrizione allo studio

Primo inviato

18 luglio 2026

Primo inviato che soddisfa i criteri di controllo qualità

21 luglio 2026

Primo Inserito (Effettivo)

27 luglio 2026

Aggiornamenti dei record di studio

Ultimo aggiornamento pubblicato (Effettivo)

27 luglio 2026

Ultimo aggiornamento inviato che soddisfa i criteri QC

21 luglio 2026

Ultimo verificato

1 luglio 2026

Maggiori informazioni

Termini relativi a questo studio

Parole chiave

Termini MeSH pertinenti aggiuntivi

Altri numeri di identificazione dello studio

  • ER-VISION-AI study

Piano per i dati dei singoli partecipanti (IPD)

Hai intenzione di condividere i dati dei singoli partecipanti (IPD)?

INDECISO

Descrizione del piano IPD

The investigators have not yet determined whether de-identified individual participant data (IPD), including the analyzable dataset and supporting documentation, will be shared with researchers outside the study team. A final decision will be made after completion of the study, taking into consideration institutional policies, participant privacy, ethical requirements, and applicable regulations.

Informazioni su farmaci e dispositivi, documenti di studio

Studia un prodotto farmaceutico regolamentato dalla FDA degli Stati Uniti

No

Studia un dispositivo regolamentato dalla FDA degli Stati Uniti

No

Queste informazioni sono state recuperate direttamente dal sito web clinicaltrials.gov senza alcuna modifica. In caso di richieste di modifica, rimozione o aggiornamento dei dettagli dello studio, contattare register@clinicaltrials.gov. Non appena verrà implementata una modifica su clinicaltrials.gov, questa verrà aggiornata automaticamente anche sul nostro sito web .

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