Evidence map›Paper›PMID 36635747›Full record

ArticleTrials2023

An AI-based patient-specific clinical decision support system for OA patients choosing surgery or not: study protocol for a single-centre, parallel-group, non-inferiority randomised controlled trial.

Nanna Kastrup, Helene H Bjerregaard, Mogens Laursen, Jan B Valentin, Søren P Johnsen, Cathrine E Jensen

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in Trials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04332055 (Measuring the Effect of an ePRO-based Clinical Decision Support System in Knee- and Hip Replacement Surgery), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04332055 nacompletednot on this map

Measuring the Effect of an ePRO-based Clinical Decision Support System in Knee- and Hip Replacement Surgery

TypeinterventionalSponsorNorthern Orthopaedic Division, DenmarkRan2020 to 2022Enrolled223ConditionsDecision Making, Shared, Arthroplasty, Replacement, Knee, Arthroplasty, Replacement, Hip, Osteoarthritis, KneeArmsERVIN
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Nanna KastrupDanish Center for Healthcare Improvements, Aalborg University, Frederik Bajers Vej 5, 9220, Aalborg, Denmark. Nkh@dcm.aau.dk.ORCID http://orcid.org/0000-0003-0554-9994
Helene H BjerregaardThe Danish Clinical Quality Program - National Clinical Registries, Hedeager 3, 8200, Aarhus N, Denmark.
Mogens LaursenOrthopaedic Department, Aalborg University Hospital, Hobrovej 18-22, DK-9000, Aalborg, Denmark.
Jan B ValentinDanish Center for Clinical Health Services Research, Aalborg University, Frederik Bajers Vej 5, 9220, Aalborg, Denmark.
Søren P JohnsenDanish Center for Clinical Health Services Research, Aalborg University, Frederik Bajers Vej 5, 9220, Aalborg, Denmark.
Cathrine E JensenDanish Center for Healthcare Improvements, Aalborg University, Frederik Bajers Vej 5, 9220, Aalborg, Denmark.
Aalborg University · DKAalborg University Hospital · DKDanish National Centre for Social Research · DK

Funding

Danish Ministry of Health No award number is provided with the grant, all correspondence in done by subitting a project description which was approved and the funding was transferred to the research centerHelsefonden 20-B-0008
6 · The paper itself

Abstract

backgroundOsteoarthritis (OA) affects 20% of the adult Danish population, and the financial burden to society amounts to DKK 4.6 billion annually. Research suggests that up to 75% of surgical patients could have postponed an operation and managed with physical training. ERVIN.2 is an artificial intelligence (AI)-based clinical support system that addresses this problem by enhancing patient involvement in decisions concerning surgical knee and hip replacement. However, the clinical outcomes and cost-effectiveness of using such a system are scantily documented.

objectiveThe primary objective is to investigate whether the usual care is non-inferior to ERVIN.2 supported care. The second objective is to determine if ERVIN.2 enhances clinical decision support and whether ERVIN.2 supported care is cost-effective.

methodsThis study used a single-centre, non-inferiority, randomised controlled in a two-arm parallel-group design. The study will be reported in compliance with CONSORT guidelines. The control group receives the usual care. As an add-on, the intervention group have access to baseline scores and predicted Oxford hip/knee scores and HRQoL for both the surgical and the non-surgical trajectory. A cost-utility analysis will be conducted alongside the trial using a hospital perspective, a 1-year time horizon and effects estimated using EQ-5D-3L. Results will be presented as cost per QALY gain. DISCUSSION: This study will bring knowledge about whether ERVIN.2 enhances clinical decision support, clinical effects, and cost-effectiveness of the AI system. The study design will not allow for the blinding of surgeons.

trial registrationClinicalTrials.gov NCT04332055 . Registered on 2 April 2020.

Indexed as

Decision Support Systems, ClinicalOsteoarthritisAdultArtificial IntelligenceCost-Benefit AnalysisEquivalence Trials as TopicHumansKnee JointRandomized Controlled Trials as TopicArtificial intelligenceClinical decision support systemCost-effectivenessMachine learningOsteoarthritisPatient-reported outcomesRandomised controlled trialTotal hip replacementTotal knee replacement

Identifiers

PMID36635747
PMCPMC9837885
OpenAlexW4315780586

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.