Integrating an AI-Driven Hydronephrosis Decision-Making Tool
Integration of a Hydronephrosis AI-Driven Decision-Making Tool Into Clinical Practice: A Clinical Trial
Studieoversigt
Status
Status
Betingelser
Betingelser
Intervention / Behandling
Intervention / Behandling
Undersøgelsestype
Undersøgelsestype
Tilmelding (Anslået)
Tilmelding
Fase
Fase
- Ikke anvendelig
Deltagelseskriterier
Berettigelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
- Barn
Tager imod sunde frivillige
Beskrivelse
Inclusion Criteria:
- Seen for HN in-person in the Pediatric Urology clinic with ultrasound scans taken at SickKids
- New and follow-up patients 0-24 months.
Exclusion Criteria:
- Older than 24m
- Concurrent urinary tract anomalies (duplex configurations; PUV etc.)
- History of renal surgical intervention (post-op patients)
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
- Primært formål: Andet
- Tildeling: N/A
- Interventionel model: Enkelt gruppeopgave
- Maskning: Ingen (Åben etiket)
Antal våben
Våben og indgreb
Deltagergruppe / ArmDeltagergruppe / Arm |
Intervention / BehandlingIntervention / Behandling |
|---|---|
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Eksperimentel: AI Model Intervention Arm
When children with HN are seen in clinic, their ultrasound imaging and history will be provided to an initial clinician who will first formulate a plan of care without access to the AI model as per the standard of care.
After the initial plan is documented and before discussion with the primary provider, the initial clinician will then be granted access to the AI model, where they can input the ultrasound images and receive the model's prediction.
The clinician can choose to modify or maintain their drafted plan based on the model's output.
The clinician's final drafted plan will subsequently be discussed with the blinded final clinical expert (primary provider) who will make the final decision to maintain the standard of care for each patient.
The final clinical expert will be blinded to whether the initial clinician changed their plan or not given the AI model
|
The AI intervention is a deep learning algorithm used to predict obstructive hydronephrosis.
It was developed at SickKids and has recently completed the silent trial phase.
This clinical trial aims to validate the model's clinical integration by assessing its impact on clinician decision-making and care plan recommendations.
To uphold standard care, a blinded clinician will make final decisions.
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Hvad måler undersøgelsen?
Primære resultatmål
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Change in Clinician Management Decisions Following Exposure to the AI Model
Tidsramme: Immediately after AI model exposure during each case review session, through study completion (average of 6 months)
|
The proportion of clinician management decisions revised immediately after exposure to the AI model output.
Management decisions include: (1) discharge, (2) monitor with ultrasound, (3) additional invasive testing, or (4) referral for surgery.
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Immediately after AI model exposure during each case review session, through study completion (average of 6 months)
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Sekundære resultatmål
Sekundære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
|
Agreement Between Clinician Decisions and Expert Reference Decisions Using Cohen's Kappa
Tidsramme: Immediately after clinician review and AI model exposure during each case review session, through study completion (average of 6 months)
|
Agreement between clinician management decisions and the expert reference decision will be assessed before and after AI exposure using Cohen's kappa statistic.
Higher kappa values indicate greater agreement.
|
Immediately after clinician review and AI model exposure during each case review session, through study completion (average of 6 months)
|
|
Proportion of Management Decision Changes Stratified by Clinician Experience Level
Tidsramme: Immediately after AI model exposure during each case review session, through study completion (average of 6 months)
|
The proportion of clinician management decisions revised after AI model exposure will be compared across clinician subgroups, including training level and years of experience.
|
Immediately after AI model exposure during each case review session, through study completion (average of 6 months)
|
Samarbejdspartnere og efterforskere
Sponsor
Sponsor
Datoer for undersøgelser
Studer store datoer
Studiestart (Anslået)
Studiestart
Primær færdiggørelse (Anslået)
Primær færdiggørelse
Studieafslutning (Anslået)
Studieafslutning
Datoer for studieregistrering
Først indsendt
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først indsendt, der opfyldte QC-kriterier
Først opslået (Faktiske)
Først opslået
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
Sidste opdatering sendt
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Yderligere relevante MeSH-vilkår
Andre undersøgelses-id-numre
Andre undersøgelses-id-numre
- 3474
Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter
Studerer et amerikansk FDA-reguleret lægemiddelprodukt
Studerer et amerikansk FDA-reguleret enhedsprodukt
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