Evidence map›Paper›PMID 39619703›Full record

ArticleArthroplasty today2024

Impact of Leg Position on Measurements Used to Detect Femoral Component Subsidence in THA.

Elizabeth S Kaji, Austin F Grove, Eva Lehtonen, Kellen L Mulford, Pouria Rouzrokh, Charles P Hannon, Michael J Taunton, Cody C Wyles

Abstract read
In one paragraph

Article in Arthroplasty today, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Elizabeth S KajiOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Austin F GroveOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Eva LehtonenMayo Clinic Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Kellen L MulfordOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Pouria RouzrokhOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Charles P HannonMayo Clinic Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Michael J TauntonOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Cody C WylesOrthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A fully automated artificial intelligence-based tool was developed to detect and quantify femoral component subsidence between serial radiographs. However, it did not account for measurement errors due to leg position differences, such as rotation or flexion, between comparative radiographs. If there are small differences in rotation or flexion of the leg between comparative radiographs, the impact on subsidence measurement is unclear. Methods: Twenty-five primary total hip arthroplasty procedures were performed by 3 fellowship-trained arthroplasty surgeons using a direct anterior approach. A Hana table allowed precise changes in femur position. Final fluoroscopic images were collected with rotational and flexion changes applied to the femur without moving the C-arm. Subsidence values were manually measured and compared across different positions. Results: Variations in greater trochanter to tip of the stem measurements between the neutral position and rotations were minimal, measuring <1 mm on an absolute scale and <1% on a relative scale. These differences decreased as the femur was rotated from an external rotation of 20° to an internal rotation of 20°. Notable variances exceeding 5 mm were observed in the 10° flexion position compared to neutral. Conclusions: Minor changes (20° or less) in leg rotation between serial radiographs are unlikely to significantly affect the greater trochanter to tip of the stem measurement, whereas flexion is highly impactful. These findings suggest that the fully automated artificial intelligence-based tool for detecting and quantifying femoral component subsidence is robust against rotational variations but may be susceptible to significant measurement errors if there are considerable changes in leg flexion between comparative radiographs.

Indexed as

Artificial intelligenceAutomatic calculatorProsthesis looseningRadiographic measurementsSubsidenceTotal hip arthroplasty

Identifiers

PMID39619703
PMCPMC11605327

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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.