Evidence map›Paper›PMID 36523643›Full record

ArticleRadiology. Artificial intelligence2022

Patient-specific Hip Arthroplasty Dislocation Risk Calculator: An Explainable Multimodal Machine Learning-based Approach.

Bardia Khosravi, Pouria Rouzrokh, Hilal Maradit Kremers, Dirk R Larson, Quinn J Johnson, Shahriar Faghani, Walter K Kremers, Bradley J Erickson, Rafael J Sierra, Michael J Taunton and 1 more

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In one paragraph

Article in Radiology. Artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  7. Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025
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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

11 authors.

Bardia KhosraviOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID https://orcid.org/0000-0002-8024-339X
Pouria RouzrokhOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID 0000-0003-4664-0751
Hilal Maradit KremersOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID https://orcid.org/0000-0003-3882-602X
Dirk R LarsonOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.
Quinn J JohnsonOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID 0000-0002-6380-7261
Shahriar FaghaniOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID 0000-0003-3275-2971
Walter K KremersOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.
Bradley J EricksonOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID 0000-0001-7926-6095
Rafael J SierraOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.
Michael J TauntonOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID 0000-0002-7636-0489
Cody C WylesOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery (B.K., P.R., H.M.K., D.R.L., Q.J.J., M.J.T., C.C.W.), Radiology Informatics Laboratory, Department of Radiology (B.K., P.R., S.F., B.J.E.), Department of Quantitative Health Sciences (H.M.K., D.R.L., W.K.K.), Alix School of Medicine (Q.J.J.), Department of Orthopedic Surgery (R.J.S., M.J.T., C.C.W.), and Department of Clinical Anatomy (C.C.W.), Mayo Clinic, 200 First St SW, Rochester, MN 55905.ORCID 0000-0002-8629-7567

Funding

Resource CoreP30AR076312 · NIAMS · MAYO CLINIC ROCHESTER · PI Daniel Berry · 2019 to 2026
$5.5M
Precision Orthopedics: Multimodal Data Infrastructure for Personalized Surgical Decisions in Joint ArthroplastyR01AR073147 · NIAMS · MAYO CLINIC ROCHESTER · PI Hilal Maradit Kremers · 2018 to 2026
$3.5M
NIAMS NIH HHS P30 AR076312NIAMS NIH HHS R01 AR073147
6 · The paper itself

Abstract

Purpose: To develop a multimodal machine learning-based pipeline to predict patient-specific risk of dislocation following primary total hip arthroplasty (THA). Materials and Methods: This study retrospectively evaluated 17 073 patients who underwent primary THA between 1998 and 2018. A test set of 1718 patients was held out. A hybrid network of EfficientNet-B4 and Swin-B transformer was developed to classify patients according to 5-year dislocation outcomes from preoperative anteroposterior pelvic radiographs and clinical characteristics (demographics, comorbidities, and surgical characteristics). The most informative imaging features, extracted by the mentioned model, were selected and concatenated with clinical features. A collection of these features was then used to train a multimodal survival XGBoost model to predict the individualized hazard of dislocation within 5 years. C index was used to evaluate the multimodal survival model on the test set and compare it with another clinical-only model trained only on clinical data. Shapley additive explanation values were used for model explanation. Results: The study sample had a median age of 65 years (IQR: 18 years; 52.1% [8889] women) with a 5-year dislocation incidence of 2%. On the holdout test set, the clinical-only model achieved a C index of 0.64 (95% CI: 0.60, 0.68). The addition of imaging features boosted multimodal model performance to a C index of 0.74 (95% CI: 0.69, 0.78; Conclusion: Due to its discrimination ability and explainability, this risk calculator can be a potential powerful dislocation risk stratification and THA planning tool.

Indexed as

Conventional RadiographyConvolutional Neural Network (CNN)Gradient Boosting Machines (GBM)HipOutcomes AnalysisSkeletal-AppendicularSupervised LearningSurgery

Identifiers

PMID36523643
PMCPMC9745445

What OpenQuestion holds

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Registered trials

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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.