Evidence map›Paper›PMID 42292191›Full record

ArticleFrontiers in medicine2026

Surgeon decision-making and implant selection in primary total knee arthroplasty: association of training, experience, and robotic-assisted surgical innovation with implant selection.

Ali Ibrahim Alhefzi, Abdullah Raizah, Shaker Hassan S Alshehri, Fareed F Alfaya, Ghada Mohamed Koura, Ahmed Mohamed Elshiwi, Ajay Prashad Gautam, Saleh M Kardm, Ravi Shankar Reddy

Abstract read
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Article in Frontiers in medicine, 2026. 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

What it found

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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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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

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0 citing papers in PubMed.

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4 · The record

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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

9 authors.

Ali Ibrahim AlhefziDepartment of Orthopedic Surgery, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Abdullah RaizahDepartment of Orthopedic Surgery, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Shaker Hassan S AlshehriDepartment of Orthopedic Surgery, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Fareed F AlfayaDepartment of Orthopedic Surgery, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Ghada Mohamed KouraDepartment of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.
Ahmed Mohamed ElshiwiDepartment of Physical Therapy, Saudi German Hospital, Aseer, Saudi Arabia.
Ajay Prashad GautamDepartment of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.
Saleh M KardmDepartment of Surgery, College of Medicine, Najran University, Najran, Saudi Arabia.
Ravi Shankar ReddyDepartment of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Implant selection in primary total knee arthroplasty (TKA) remains a critical yet variable aspect of surgical decision-making, associated with both patient characteristics and surgeon-related factors. With the increasing integration of surgical innovations such as robotic-assisted techniques, understanding contemporary determinants of implant choice has become essential. This study aimed to evaluate implant selection patterns and identify independent factors associated with the use of cruciate-retaining (CR) vs. posterior-stabilized (PS) implants in a modern clinical setting. This study was designed as a retrospective observational analytical study, with data analyzed within a cross-sectional framework. Methods: A cross-sectional study was conducted on 280 patients undergoing primary TKA at a high-volume tertiary care center between May 2024 and April 2025. Data on patient demographics, clinical characteristics, and implant-related variables were collected. Surgeon-level factors, including fellowship training, years in practice, and use of robotic or navigation systems, were also analyzed. Multivariate logistic regression was performed to identify independent factors associated with the CR implant selection. Results: CR implants were used in 60.0% of cases, whereas PS implants were used in 40.0% ( Conclusion: Implant selection in primary TKA is influenced by a combination of surgeon training and experience, patient characteristics, and the adoption of surgical technologies such as robotic assistance. These findings highlight the impact of surgical innovation on decision-making in modern arthroplasty practice and underscore the need for standardized, evidence-based approaches to reduce variability in implant selection.

Indexed as

arthroplastykneeprosthesis designreplacementrobotic surgical procedures

Identifiers

PMID42292191
PMCPMC13259782

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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.