Evidence map›Paper›PMID 41452403›Full record

ArticleJournal of robotic surgery2025

Computed tomography versus long-leg radiography for CPAK-based coronal alignment assessment in total knee arthroplasty: a prospective evaluation.

Anoop Jhurani, Sanchay Lavaniya, Gaurav Ardawatia, Piyush Agarwal, Abhishek Dwivedi, Mudit Srivastava

Erratum issuedAbstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Anoop JhuraniDepartment of Robotic Joint Replacement Surgery Unit, Fortis Escorts Hospital, Jaipur, Rajasthan, India. anoopjhurani@gmail.com.
Sanchay LavaniyaDepartment of Robotic Joint Replacement Surgery Unit, Fortis Escorts Hospital, Jaipur, Rajasthan, India.
Gaurav ArdawatiaDepartment of Robotic Joint Replacement Surgery Unit, Fortis Escorts Hospital, Jaipur, Rajasthan, India.
Piyush AgarwalDepartment of Robotic Joint Replacement Surgery Unit, Fortis Escorts Hospital, Jaipur, Rajasthan, India.
Abhishek DwivediDepartment of Robotic Joint Replacement Surgery Unit, Fortis Escorts Hospital, Jaipur, Rajasthan, India.
Mudit SrivastavaDepartment of Clinical Research, Fortis Escorts Hospital, Jaipur, Rajasthan, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate assessment of coronal alignment is essential for total knee arthroplasty (TKA) planning. The Coronal Plane Alignment of the Knee (CPAK) classification integrates mechanical alignment and joint line obliquity into nine phenotypes, but its reliability depends on measurement accuracy. This study aimed to compare the accuracy and reliability of CPAK classification and coronal alignment parameters obtained from computed tomography (CT) and long-leg standing radiographs. A prospective comparative study was conducted on 100 patients undergoing primary TKA for degenerative arthritis. Each patient underwent standardized long-leg standing radiographs and full-limb CT scans using MAKO robotic planning software. Measurements included the arithmetic hip-knee-ankle (aHKA) angle, lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), and joint line obliquity (JLO). CPAK classification was determined from aHKA and JLO values. Two independent observers recorded all parameters. Inter-modality differences were analyzed using paired t-tests, and reliability was assessed using intraclass correlation coefficients (ICC) and Cohen's kappa. A total of 100 patients were analyzed, with complete datasets for 86 patients. CT consistently produced different values for HKA, LDFA, and MPTA compared with radiographs (p < 0.001), while aHKA, JLO and CPAK classifications showed no significant difference. Both modalities demonstrated excellent interobserver reliability (ICC > 0.88) and near-perfect CPAK agreement (κ = 0.86-0.88) measurement without altering overall CPAK phenotype classification. CT-based measurements provide greater precision and reproducibility for coronal alignment parameters compared with radiographs. However, CPAK classification remains largely consistent between modalities, validating its robustness across imaging techniques. CT offers precise value for preoperative planning, particularly in robotic-assisted workflows or complex deformities, while radiographs remain adequate for routine phenotyping. Level II - Prospective comparative study.

Indexed as

Arthroplasty, Replacement, KneeKnee JointOsteoarthritis, KneeRadiographyRobotic Surgical ProceduresTomography, X-Ray ComputedAgedAged, 80 and overFemaleHumansMaleMiddle AgedProspective StudiesReproducibility of ResultsComputed tomographyCoronal alignmentCPAK classificationLong-leg radiographReliabilityRobotic-assisted surgeryTotal knee arthroplasty

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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.