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Cited by 11Total Knee Arthroplasty OutcomesKnee injuries and reconstruction techniquesProsthetics and Rehabilitation Robotics

Imageless robotic total knee arthroplasty determines similar coronal plane alignment of the knee (CPAK) parameters to long leg radiographs

Open access
Edelstein, Adam I., Orsi, Alexander D., Plaskos, Christopher, Coffey, Simon, Suleiman, Linda I.·2024·Arthroplasty
DOI 10.1186/s42836-024-00231-9PMC PMC10909262
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Abstract

Background: The coronal plane alignment of the knee (CPAK) classification was first developed using long leg radiographs (LLR) and has since been reported using image-based and imageless robotic total knee arthroplasty (TKA) systems. However, the correspondence between imageless robotics and LLR-derived CPAK parameters has yet to be investigated. This study therefore examined the differences in CPAK parameters determined with LLR and imageless robotic navigation using either generic or optimized cartilage wear assumptions. Methods: Medial proximal tibial angle (MPTA) and lateral distal femoral angle (LDFA) were determined from the intraoperative registration data of 61 imageless robotic TKAs using either a generic 2 mm literature-based wear assumption (Nav lit) or an optimized wear assumption (Nav opt) found using an error minimization algorithm. MPTA and LDFA were also measured from preoperative LLR by two observers and intraclass correlation coefficients (ICCs) were calculated. MPTA, LDFA, joint line obliquity (JLO), and arithmetic hip-knee-ankle angle (aHKA) were compared between the robotic and the average LLR measurements over the two observers. Results: ICCs between observers for LLR were over 0.95 for MPTA, LDFA, JLO, and aHKA, indicating excellent agreement. Mean CPAK differences were not significant between LLR and Nav lit (all differences within 0.6°, P > 0.1) or Nav opt (all within 0.1°, P > 0.83). Mean absolute errors (MAE) between LLR and Nav lit were: LDFA = 1.4°, MPTA = 2.0°, JLO = 2.1°, and aHKA = 2.7°. Compared to LLR, the generic wear classified 88% and the optimized wear classified 94% of knees within one CPAK group. Bland–Altman comparisons reported good agreement for LLR vs. Nav lit and Nav opt, with > 95% and > 91.8% of measurements within the limits of agreement across all CPAK parameters, respectively. Conclusions: Imageless robotic navigation data can be used to calculate CPAK parameters for arthritic knees undergoing TKA with good agreement to LLR. Generic wear assumptions determined MPTA and LDFA with MAE within 2° and optimizing wear assumptions showed negligible improvement.

AI snapshot

Written from the paper’s full text.

TL;DR

Imageless robotic TKA navigation data can calculate CPAK parameters for arthritic knees with good agreement to long leg radiographs when cartilage wear is corrected. Generic 2 mm wear assumptions performed well, and optimizing wear assumptions produced only negligible improvement.

Key findings

  • LLR interobserver agreement was excellent: ICCs > 0.95 for MPTA, LDFA, JLO, and aHKA, with MAEs of 0.7°, 0.5°, 0.8°, and 1.0°, respectively; 73% of patients were in the same CPAK group and 97% within one group between observers.
  • Navlit vs. LLRmean showed no significant mean differences (all within 0.6°, P > 0.1), with MAEs of LDFA = 1.4°, MPTA = 2.0°, JLO = 2.1°, and aHKA = 2.7°; 41% were in the same CPAK group and 88% within one group, with > 95% of measurements within Bland–Altman limits of agreement.
  • Navopt vs. LLRmean also showed no significant mean differences (all within 0.1°, P > 0.83), with MAEs of LDFA = 1.3°, MPTA = 1.9°, JLO = 2.2°, and aHKA = 2.5°; 49% were in the same CPAK group and 94% within one group, with > 91.8% within limits of agreement.
  • BMI sub-analysis found no significant differences between BMI groups (P > 0.17); with Navlit, valgus knees had higher LDFA MAE than varus and neutral knees (2.3° vs. 1.4° and 0.9°, P = 0.02 and P < 0.002) and higher aHKA MAE than varus knees (4.2° vs. 2.2°, P = 0.008).

Methods

  • Retrospective review of 62 robotic TKA procedures performed February 2021–November 2022; one severe valgus deformity with marked bone loss was excluded, leaving 61 imageless robotic TKAs using the OMNIBotics system. Patients had end-stage osteoarthritis (Kellgren–Lawrence grade ≥ 3), mean age 70 ± 9 years, mean BMI 32 ± 7 kg/m², 63% female, preoperative coronal deformity 3° ± 6° varus (range 16° valgus to 17° varus), and flexion contracture 4° ± 7°.
  • MPTA and LDFA were measured from preoperative LLR by two observers and calculated from intraoperative imageless robotic registration data using either a generic 2 mm literature-based wear assumption (Navlit) or an optimized wear assumption (Navopt) found by minimizing RMSE relative to LLRmean. JLO was MPTA + LDFA and aHKA was MPTA − LDFA; CPAK groups were assigned per MacDessi et al.
  • Analyses included Kolmogorov–Smirnov normality tests, two-way mixed-effects ICCs, Welch t-tests, F-tests, Bland–Altman plots, and sub-analyses by BMI and preoperative coronal alignment, using R version 4.1.0; the study was powered to detect a 1° mean difference and required a minimum of 53 participants.

Limitations

  • The paper states that imageless navigation accuracy depends on registration quality; Navopt wear assumptions were optimized to this cohort and may not generalize; the deformity range was 16° valgus to 17° varus, so accuracy may differ for more severe deformities or bone wear; valgus knees had higher MAE, possibly indicating less predictable wear; the sample of 61 patients was relatively small and may not represent all CPAK phenotypes; and the study lacked clinical outcomes data.
  • The text also makes evident that this was a single-surgeon, single-imageless-system retrospective study, and the authors state that further study directly comparing CT-based and imageless navigation-based CPAK assessments is warranted.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s42836-024-00231-9

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

21 of 46 cited sources checked · 9 supported · 0 flagged · accuracy not yet measured

  • Interpretationcitation

    The accuracy of imageless navigation data for aHKA was comparable, if not better, than previous reports for aHKA using CT-based imaging with robotics and intraoperative stressed measures.

    “The accuracy of imageless navigation data for aHKA was comparable, if not better, than previous reports for aHKA using CT-based imaging with robotics and intraoperative stressed measures, which demonstrated standard deviations of 5.3° and 4.2°, respectively [16].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [16] Tarassoli P, Wood JA, Chen DB, Griffiths-Jones W, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle and stressed hip-knee-ankle angle: equivalent methods for estimating constitutional lower limb alignment in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022;30(9):2980–90. source
  • Findingown data

    Compared to long leg radiographs, the optimized wear assumption (Navopt) classified 94% of knees within one CPAK group.

    “Compared to LLR, the generic wear classified 88% and the optimized wear classified 94% of knees within one CPAK group.”
    • Also stated in: § Navopt vs. LLRmean · plain
      “49% and 94% of patients were within the same and within one CPAK group, respectively when comparing Navopt and LLRmean.”
    Quote in the paperSubstantial claim
  • Findingown data

    No CPAK parameters were significantly different between the two long leg radiograph observers for means or variance tests.

    “No CPAK parameters were significantly different between LLR observers for both means and variance tests.”
    Quote in the paperSubstantial claim
  • Findingnone given

    Interobserver agreement for MPTA and LDFA measurements from long leg radiographs was very strong.

    “The interobserver agreement for MPTA and LDFA measurements from long leg radiographs was very strong, which supports use of long leg radiographs as the gold standard reference for this analysis.”
    Quote in the paperSubstantial claim
  • Findingown data

    Bland-Altman comparisons showed that more than 95% of measurements were within the limits of agreement for LLR vs Navlit across all CPAK parameters.

    “Bland–Altman comparisons reported good agreement for LLR vs. Navlit and Navopt, with > 95% and > 91.8% of measurements within the limits of agreement across all CPAK parameters, respectively.”
    • Also stated in: § Navopt vs. LLRmean · plain
      “Bland-Altman comparisons yielded > 95% of measurements within the 2 SD limit of agreement for LLR1 vs. LLR2 and LLRmean vs. Navlit, and > 91.8% for LLR vs. Navopt, indicating good agreement between all measurement methods [31, 32]”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [31] Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135–60. source
    • cites [32] Myles PS, Cui J. Using the Bland-Altman method to measure agreement with repeated measures. Br J Anaesth. 2007;99(3):309–11. source
  • Classified as probably not a substantial claim. 29
  • May combine two claims. 14
  • The quote only partly states this claim. 1

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Tarassoli et al. found no significant differences between radiograph-based aHKA, CT-based aHKA, or stressed HKA.

    “They found no significant differences between radiograph-based aHKA, CT-based aHKA, or stressed HKA.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [16] Tarassoli P, Wood JA, Chen DB, Griffiths-Jones W, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle and stressed hip-knee-ankle angle: equivalent methods for estimating constitutional lower limb alignment in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022;30(9):2980–90. source

  • Classified as probably not a substantial claim.

    Premisecitation

    Tarassoli et al. reported standard deviations for CT-based HKA and stressed HKA, in comparison to radiograph-based aHKA, of 5.3° and 4.2°, respectively.

    “Standard deviations for CT-based HKA and stressed HKA, in comparison to radiograph-based aHKA, were 5.3° and 4.2°, respectively.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [16] Tarassoli P, Wood JA, Chen DB, Griffiths-Jones W, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle and stressed hip-knee-ankle angle: equivalent methods for estimating constitutional lower limb alignment in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022;30(9):2980–90. source

  • Classified as probably not a substantial claim.

    Premisecitation

    In large cohorts of non-arthritic knees undergoing MRI, cartilage thickness has been reported to be in the 1.5-2.0 mm range.

    “In large cohorts of non-arthritic knees undergoing MRI, cartilage thickness has been reported to be in the 1.5–2.0 mm range [36, 37].”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [36] Frobell RB, Nevitt MC, Hudelmaier M, Wirth W, Wyman BT, Benichou O, et al. Femorotibial subchondral bone area and regional cartilage thickness: a cross-sectional description in healthy reference cases and various radiographic stages of osteoarthritis in 1,003 knees from the Osteoarthritis Initiative. Arthritis Care Res (Hoboken). 2010;62(11):1612–23. source
    • cites [37] Li H, Hosseini A, Li JS, Gill TJT, Li G. Quantitative magnetic resonance imaging (MRI) morphological analysis of knee cartilage in healthy and anterior cruciate ligament-injured knees. Knee Surg Sports Traumatol Arthrosc. 2012;20(8):1496–502. source

      The Results (page unavailable) report mean total knee cartilage thickness of 1.9–2.0 mm in the intact control and ACL-injured knees, broadly consistent with the cited range. But the Materials and methods describe only 22 participants, and the Discussion explicitly calls the sample small; this paper does not support the claim that its measurements came from a large cohort. (LLM, conf=0.89)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Some methods based on CT or MRI use proprietary algorithms that may not be accessible to all surgeons.

    “Some of the methods based on CT or MRI use proprietary algorithms that may not be accessible to all surgeons [14–17].”
    Quote in the paperNot a substantial claim2 of 4 sources checked
    • cites [14] Kim KK, Howell SM, Won YY. Kinematically aligned total knee arthroplasty with patient-specific instrument. Yonsei Med J. 2020;61(3):201–9. source

      The Preoperative Planning sections describe CT- and MRI-based patient-specific instruments and the use of image-processing software, but do not say that any methods use proprietary algorithms or that those algorithms are inaccessible to surgeons. Searches for proprietary algorithms and software access found no passage addressing that point. (LLM, conf=0.73)

      Experimental — accuracy not yet measured
    • cites [15] Calliess T, Bauer K, Stukenborg-Colsman C, Windhagen H, Budde S, Ettinger M. PSI kinematic versus non-PSI mechanical alignment in total knee arthroplasty: a prospective, randomized study. Knee Surg Sports Traumatol Arthrosc. 2017;25(6):1743–8. source
    • cites [16] Tarassoli P, Wood JA, Chen DB, Griffiths-Jones W, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle and stressed hip-knee-ankle angle: equivalent methods for estimating constitutional lower limb alignment in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022;30(9):2980–90. source

      The Methods (Radiographic technique; Computed tomographic and robotic analysis for CT-aHKA; page not provided) describe a CT-based method using Mako software, with a product specialist determining anatomical landmarks. The paper does not state that the software uses proprietary algorithms, that surgeons may lack access to them, or that this applies to MRI-based methods. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
    • cites [17] Tarassoli P, Corban LE, Wood JA, Sergis A, Chen DB, MacDessi SJ. Long leg radiographs underestimate the degree of constitutional varus limb alignment and joint line obliquity in comparison with computed tomography: a radiographic study. Knee Surg Sports Traumatol Arthrosc. 2023;31(11):4755–65. source

  • Classified as probably not a substantial claim.

    Premisecitation

    The CPAK classification defines nine native knee phenotypes based on a 3 × 3 grid organized by aHKA (varus, neutral, valgus) and JLO (apex distal, neutral, and apex proximal).

    “CPAK was developed using measurements made on long leg radiographs (LLR) and defines nine native knee phenotypes that can be targeted in a personalized TKA, based on a 3 × 3 grid organized by aHKA (varus, neutral, valgus) and JLO (apex distal, neutral, and apex proximal) [11].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [11] MacDessi SJ, Griffiths-Jones W, Harris IA, Bellemans J, Chen DB. Coronal Plane Alignment of the Knee (CPAK) classification. Bone Joint J. 2021;103–3(2):329–37. source

  • Classified as probably not a substantial claim.

    Premisecitation

    The arithmetic hip-knee-ankle angle (aHKA) provides information on the constitutional alignment of the lower limb irrespective of cartilage loss.

    “The arithmetic hip-knee-ankle angle (aHKA) [10], providing information on the constitutional alignment of the lower limb irrespective of cartilage loss, and the joint line obliquity (JLO) together comprise the coronal plane alignment of the knee (CPAK) classification [11].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [10] Griffiths-Jones W, Chen DB, Harris IA, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle (aHKA): An algorithm for estimating constitutional lower limb alignment in the arthritic patient population. Bone Jt Open. 2021;2(5):351–8. source
    • The authors state this as an assumption: Use of aHKA to predict constitutional alignment assumes that the distal femur and proximal tibia joint surfaces in the native knee are parallel.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    There are several available methods for identifying native coronal plane morphology, including generic cartilage wear assumptions, use of long leg radiographs, or methods based on advanced imaging.

    “There are several available methods for identifying native coronal plane morphology, including generic cartilage wear assumptions, use of long leg radiographs, or methods based on advanced imaging [12–15].”
    Quote in the paperNot a substantial claim3 of 4 sources checked
    • cites [12] Howell SM. Use the right looking glass when you do Caliper-verified Kinematically Aligned TKA! Arthroplast Today. 2022;15:139–40. source

      In the main text (page unavailable), Howell describes restoring prearthritic joint lines using a 2 mm allowance for complete cartilage loss and intraoperative caliper measurements. That supports the cartilage-wear element, but the paper does not describe long-leg radiographs or advanced imaging as methods for identifying native coronal morphology; it says this KA approach does not rely on a preoperative radiographic image. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
    • cites [13] de Winnock Grave P, Luyckx T, Claeys K, Tampere T, Kellens J, Muller J, et al. Higher satisfaction after total knee arthroplasty using restricted inverse kinematic alignment compared to adjusted mechanical alignment. Knee Surg Sports Traumatol Arthrosc. 2022;30(2):488–99. source

      The Surgical technique section (page unavailable) describes preoperative CT used to create a subject-specific knee model, supporting the advanced-imaging example. The iKA section describes restoring pre-arthritic alignment while accounting for bony wear. Neither section establishes generic cartilage-wear assumptions or long-leg radiographs as methods for identifying native morphology; the full-leg radiograph shown is postoperative. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
    • cites [14] Kim KK, Howell SM, Won YY. Kinematically aligned total knee arthroplasty with patient-specific instrument. Yonsei Med J. 2020;61(3):201–9. source

      The Preoperative Planning section (Reconstruction of 3D model; page not provided) describes CT-based 3D modelling and discusses MRI as another imaging option, supporting the advanced-imaging part of the claim. Our copy does not describe generic cartilage-wear assumptions or long-leg radiographs as methods for identifying native coronal-plane morphology. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [15] Calliess T, Bauer K, Stukenborg-Colsman C, Windhagen H, Budde S, Ettinger M. PSI kinematic versus non-PSI mechanical alignment in total knee arthroplasty: a prospective, randomized study. Knee Surg Sports Traumatol Arthrosc. 2017;25(6):1743–8. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationown data

    The degree of wear is less predictable in valgus than varus deformities.

    “which may indicate that the degree of wear is less predictable in valgus than varus deformities [39].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [39] Khury F, Oltmanns M, Unseld T, Fuchs M, Reichel H, Faschingbauer M. Which knee phenotypes exhibit the strongest correlation with cartilage degeneration? Clin Orthop Relat Res. 2023. https://doi.org/10.1097/CORR.0000000000002831. Epub ahead of print. source

      The Discussion of Key Findings reports an atypical association between a valgus-containing knee phenotype and medial cartilage loss, supporting the suggestion that wear does not always follow the expected pattern. It does not compare how predictable the degree of wear is in valgus versus varus deformities; its findings chiefly concern the location of cartilage loss. Page numbers were not available in our copy. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Kinematic alignment and related approaches aim to recreate native knee morphology by removing the amount of bone and cartilage that will be exactly replaced by the implant, with the intent of restoring natural kinematics and joint laxities.

    “Kinematic alignment and related approaches aim to recreate native knee morphology by removing the amount of bone and cartilage that will be exactly replaced by the implant, with the intent of restoring natural kinematics and joint laxities [6, 7].”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [6] Howell SM, Roth JD, Hull ML. Kinematic alignment in total knee arthroplasty definition, history, principle, surgical technique, and results of an alignment option for TKA. Arthropaedia. 2014;1:44–53.

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [7] de Winnock Grave P, Kellens J, Luyckx T, Tampere T, Lacaze F, Claeys K. Inverse kinematic alignment for total knee arthroplasty. Orthop Traumatol Surg Res. 2022;108(5):103305. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Macdessi et al. found a 1.3° greater mean difference between measurements for knees with coronal deformities >8° using the LLR method.

    “In a matched-pairs study comparing aHKA in the osteoarthritic knee to mechanical HKA in the contralateral healthy knee, Macdessi et al. found a 1.3° greater mean difference between measurements for knees with coronal deformities > 8° using the LLR method [38].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [38] MacDessi SJ, Griffiths-Jones W, Harris IA, Bellemans J, Chen DB. The arithmetic HKA (aHKA) predicts the constitutional alignment of the arthritic knee compared to the normal contralateral knee: a matched-pairs radiographic study. Bone Jt Open. 2020;1(7):339–45. source

  • Classified as probably not a substantial claim.

    Premisecitation

    CPAK was developed using measurements made on long leg radiographs.

    “CPAK was developed using measurements made on long leg radiographs (LLR) and defines nine native knee phenotypes that can be targeted in a personalized TKA, based on a 3 × 3 grid organized by aHKA (varus, neutral, valgus) and JLO (apex distal, neutral, and apex proximal) [11].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [11] MacDessi SJ, Griffiths-Jones W, Harris IA, Bellemans J, Chen DB. Coronal Plane Alignment of the Knee (CPAK) classification. Bone Joint J. 2021;103–3(2):329–37. source

  • Classified as probably not a substantial claim.

    Premisecitation

    The ability of CT-based robotics to define constitutional alignment and CPAK has been established.

    “The ability of CT-based robotics to define constitutional alignment and CPAK has been established [16–18], yet it remains unknown if imageless intraoperative robotic data can accurately describe CPAK parameters [19–23].”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [16] Tarassoli P, Wood JA, Chen DB, Griffiths-Jones W, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle and stressed hip-knee-ankle angle: equivalent methods for estimating constitutional lower limb alignment in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022;30(9):2980–90. source

      The Methods describe using CT-based Mako robotic planning to calculate aHKA, and the Discussion reports high agreement between CT-derived and radiographic measurements of constitutional alignment (page numbers unavailable). The paper does not establish that CT-based robotics can define CPAK; CPAK appears in the cited references, but no CPAK classification is evaluated here. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [17] Tarassoli P, Corban LE, Wood JA, Sergis A, Chen DB, MacDessi SJ. Long leg radiographs underestimate the degree of constitutional varus limb alignment and joint line obliquity in comparison with computed tomography: a radiographic study. Knee Surg Sports Traumatol Arthrosc. 2023;31(11):4755–65. source
    • cites [18] Gieroba TJ, Marasco S, Babazadeh S, Di Bella C, van Bavel D. Arithmetic hip knee angle measurement on long leg radiograph versus computed tomography-inter-observer and intra-observer reliability. Arthroplasty. 2023;5(1):35. source

      The Conclusion (page unavailable) reports that CT measurements of MPTA, LDFA, and aHKA are more reproducible than long-leg radiograph measurements and correlate well with them, supporting CT assessment of alignment using scans obtained for robotic planning. But the Discussion (page unavailable) does not establish that CT-based robotics itself defines CPAK: it describes CPAK as incorporating aHKA and joint-line obliquity, and says CT-based aHKA measurement may be integrated into robotic planning software in the future. (LLM, conf=0.87)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Study design and conductcitation

    A 1° difference was determined clinically sufficient to power the study, and similar patient numbers have been used in other studies comparing LLR to CT for CPAK.

    “However, a 1° difference was determined clinically sufficient to power our study and similar patient numbers have been used in other studies comparing LLR to CT for CPAK [16, 18].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [16] Tarassoli P, Wood JA, Chen DB, Griffiths-Jones W, Bellemans J, MacDessi SJ. Arithmetic hip-knee-ankle angle and stressed hip-knee-ankle angle: equivalent methods for estimating constitutional lower limb alignment in kinematically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2022;30(9):2980–90. source

      The Methods (Study group; Study design, pages unavailable) report 76 patients and 88 knees and compare measurements from long-leg radiographs with CT, supporting the citation as an example of a similarly sized study. The paper compares arithmetic hip-knee-ankle angles, however, rather than explicitly comparing CPAK classifications. The citing authors’ 1° threshold concerns their own study; this source used a 1.5° equivalence margin (Methods, Sample size calculation). (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [18] Gieroba TJ, Marasco S, Babazadeh S, Di Bella C, van Bavel D. Arithmetic hip knee angle measurement on long leg radiograph versus computed tomography-inter-observer and intra-observer reliability. Arthroplasty. 2023;5(1):35. source

      The source’s Results report 68 patients, with 64 CT scans and 68 LLRs assessed, supporting its use as an example of a similarly sized LLR–CT comparison. Its Introduction specifies that the comparison concerned aHKA measurements, not CPAK classification. The 1° threshold and power calculation refer to the citing authors’ own study, not this source. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Premisecitation

    The arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) together comprise the coronal plane alignment of the knee (CPAK) classification.

    “The arithmetic hip-knee-ankle angle (aHKA) [10], providing information on the constitutional alignment of the lower limb irrespective of cartilage loss, and the joint line obliquity (JLO) together comprise the coronal plane alignment of the knee (CPAK) classification [11].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [11] MacDessi SJ, Griffiths-Jones W, Harris IA, Bellemans J, Chen DB. Coronal Plane Alignment of the Knee (CPAK) classification. Bone Joint J. 2021;103–3(2):329–37. source

  • Classified as probably not a substantial claim.

    Premisecitation

    It remains unknown if imageless intraoperative robotic data can accurately describe CPAK parameters.

    “The ability of CT-based robotics to define constitutional alignment and CPAK has been established [16–18], yet it remains unknown if imageless intraoperative robotic data can accurately describe CPAK parameters [19–23].”
    Quote in the paperSubstantial claim1 of 5 sources checked
    • cites [19] Jenny JY, Baldairon F, Hirschmann MT. Functional knee phenotypes of OA patients undergoing total knee arthroplasty are significantly more varus or valgus than in a non-OA control group. Knee Surg Sports Traumatol Arthrosc. 2022;30(8):2609–16. source
    • cites [20] Jenny JY, Baldairon F. The coronal plane alignment of the knee classification does not correlate with the functional knee phenotype classification. Knee Surg Sports Traumatol Arthrosc. 2023;31(9):3906–11. source
    • cites [21] Jenny JY, Baldairon F. The coronal alignment technique impacts deviation from native knee anatomy after total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2023;31(4):1427–32. source
    • cites [22] Kim R, Wakelin EA, Plaskos C, Gupta S, Putman S. Variation in knee balance as a function of hip-knee-ankle angle and joint line obliquity in robotic assisted total knee arthroplasty. Int Orthop. 2023;47(2):479–84. source
    • cites [23] Orsi AD, Wakelin E, Plaskos C, McMahon S, Coffey S. Restricted inverse kinematic alignment better restores the native joint line orientation while achieving similar balance, laxity, and arithmetic Hip-Knee-Ankle angle to gap balancing total knee arthroplasty. Arthroplast Today. 2023;19:101090. source

      The Methods (Data analysis; page unavailable) say native CPAK was calculated from navigation-system landmarks with a wear correction. The Discussion (page unavailable) identifies the lack of X-ray imaging to calculate native CPAK as a limitation. This supports uncertainty about the accuracy of this study’s estimates, but does not establish the broader claim that the accuracy of imageless intraoperative robotic data for CPAK parameters remains unknown. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    Between long leg radiograph observers, 73% of patients were within the same CPAK group and 97% were within one CPAK group.

    “73% and 97% of patients were within the same and within one CPAK group, respectively, between observers.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Interobserver intraclass correlation coefficients for long leg radiograph measurements of MPTA, LDFA, JLO, and aHKA were greater than 0.95, indicating excellent agreement.

    “ICCs between observers for LLR were over 0.95 for MPTA, LDFA, JLO, and aHKA, indicating excellent agreement.”
    • Also stated in: § LLR1 vs. LLR2 · plain
      “Between LLR observers, all CPAK parameters had highly reliable ICCs (> 0.95), with RMSE below 1.2° (Table 2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Mean absolute errors between long leg radiographs and Navlit were LDFA = 1.4°, MPTA = 2.0°, JLO = 2.1°, and aHKA = 2.7°.

    “Mean absolute errors (MAE) between LLR and Navlit were: LDFA = 1.4°, MPTA = 2.0°, JLO = 2.1°, and aHKA = 2.7°.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Mean CPAK parameter differences between long leg radiographs and the literature-based navigation wear assumption (Navlit) were not significant, with all differences within 0.6° (P > 0.1).

    “Mean CPAK differences were not significant between LLR and Navlit (all differences within 0.6°, P > 0.1)”
    • Also stated in: § Navlit vs. LLRmean · plain
      “There were no significant differences observed when comparing CPAK parameters between Navlit and LLRmean for both means and variance tests. Differences in mean values between Navlit and LLRmean were within 0.6° for all CPAK parameters, with standard deviations below 3.4°.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Our optimized wear assumption predicted less wear on the lateral side on both the tibia and femur for valgus deformities.

    “Our optimized wear assumption predicted less wear on the lateral side on both the tibia and femur for valgus deformities.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Mean CPAK parameter differences between long leg radiographs and the optimized navigation wear assumption (Navopt) were not significant, with all differences within 0.1° (P > 0.83).

    “or Navopt (all within 0.1°, P > 0.83)”
    • Also stated in: § Navopt vs. LLRmean · plain
      “Similarly, there were no significant differences found when comparing CPAK parameters between Navopt and LLRmean for both means and variance tests. Differences in mean values between Navopt and LLRmean were within 0.1° for all CPAK parameters, with standard deviations below 3.1°.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Our standard deviation for aHKA was 3.4° with literature-based cartilage assumptions, decreasing to 3.1° with optimized cartilage assumptions.

    “Our standard deviation was 3.4° with literature-based cartilage assumptions, which decreased to 3.1° with optimized cartilage assumptions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Tarassoli et al. reported that long leg radiographs underestimated proximal tibial varus in comparison to CT-based assessments by 1.3° on average.

    “Tarassoli et al. reported, in a subsequent study, that long leg radiographs underestimated proximal tibial varus in comparison to CT-based assessments by 1.3° on average [17].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [17] Tarassoli P, Corban LE, Wood JA, Sergis A, Chen DB, MacDessi SJ. Long leg radiographs underestimate the degree of constitutional varus limb alignment and joint line obliquity in comparison with computed tomography: a radiographic study. Knee Surg Sports Traumatol Arthrosc. 2023;31(11):4755–65. source

  • Probably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.

    Interpretationreasoning

    The smaller magnitude of lateral wear assumptions in the optimized model is likely explained by proximal tibial landmarking not fully capturing cartilage loss in valgus knees.

    “This likely explains the smaller magnitude of the lateral wear assumptions in the optimized model.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Proximal tibial landmarking that does not fully capture cartilage loss is particularly relevant to the valgus knee, where wear is often posterolateral but the landmark is taken in the mid-coronal plane.

    “Proximal tibial landmarking that does not fully capture the cartilage loss is particularly relevant to the valgus knee, where wear is often posterolateral, but the landmark is taken in the mid-coronal plane.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Over 99% of arthritic knees had less than 1 mm of bone wear.

    “Importantly, they also reported that over 99% of arthritic knees had < 1 mm of bone wear [29].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [29] Nam D, Lin KM, Howell SM, Hull ML. Femoral bone and cartilage wear is predictable at 0 degrees and 90 degrees in the osteoarthritic knee treated with total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2014;22(12):2975–81. source

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    The study lacked clinical outcomes data, and application of CPAK parameters to alignment strategies in TKA requires additional study.

    “Fourth, our study lacked clinical outcomes data, and application of CPAK parameters to alignment strategies in TKA requires additional study.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    A similar phenomenon of increased error with severe deformity may be true for robotic data because bone erosion can alter the landmarks used to determine LDFA and MPTA.

    “A similar phenomenon may be true for robotic data as bone erosion can alter the landmarks used to determine LDFA and MPTA and we therefore recommend exercising caution when selecting landmarks to calculate CPAK parameters for patients with significant deformity and bone wear.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductreasoning

    The study was powered to determine a mean difference of 1° between methods and had a relatively small sample size of 61 patients.

    “Lastly, our study was powered to determine a mean difference of 1° between methods and, as such, had a relatively small sample size of 61 patients.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Personalized approaches have been reported to achieve improved balance, kinematics, and outcomes compared to mechanical alignment.

    “These personalized approaches have been reported to achieve improved balance, kinematics, and outcomes compared to mechanical alignment [8, 9].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [8] Blakeney W, Clement J, Desmeules F, Hagemeister N, Riviere C, Vendittoli PA. Kinematic alignment in total knee arthroplasty better reproduces normal gait than mechanical alignment. Knee Surg Sports Traumatol Arthrosc. 2019;27(5):1410–7. source
    • cites [9] Elbuluk AM, Jerabek SA, Suhardi VJ, Sculco PK, Ast MP, Vigdorchik JM. Head-to-Head comparison of kinematic alignment versus mechanical alignment for total knee arthroplasty. J Arthroplasty. 2022;37(8S):S849–51. source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    It is necessary that an operative modality used to execute a personalized knee replacement can accurately determine the constitutional alignment and joint line obliquity of the knee.

    “It is therefore necessary that an operative modality used to execute a personalized knee replacement can accurately determine the constitutional alignment and joint line obliquity of the knee, such that those parameters can then be targeted for the knee reconstruction.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    The cartilage assumptions used in Navopt were optimized to this cohort of patients and may not be generalized to other patient populations.

    “Second, the cartilage assumptions used in NAVopt were optimized to this cohort of patients and may not be generalized to other patient populations.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Optimal cartilage wear assumptions to be used with imageless navigation data remain undefined.

    “Furthermore, optimal cartilage wear assumptions to be used with imageless navigation data remain undefined.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Results indicate that imageless intraoperative robotic navigation data can be used to determine CPAK parameters for arthritic knees undergoing TKA when correcting for wear, with similar CPAK values to those determined from LLR.

    “The results from this investigation indicate that imageless intraoperative robotic navigation data can be used to determine CPAK parameters for arthritic knees undergoing TKA when correcting for wear, with similar CPAK values obtained to those determined from LLR.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Use of aHKA to predict constitutional alignment assumes that the distal femur and proximal tibia joint surfaces in the native knee are parallel.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The accuracy in determining CPAK parameters for both radiographic and imageless robotics methods may differ for more severe deformities outside the range of 16° valgus to 17° varus where bone wear may be more pronounced.

    “While the patient population in this study had a large range of coronal deformity from 16° valgus to 17° varus, the accuracy in determining CPAK parameters for both radiographic and imageless robotics methods may differ for more severe deformities outside of this range where bone wear may be more pronounced.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    The optimized wear assumption's prediction of less lateral wear may reflect the landmarking algorithm used with this imageless navigation system.

    “This finding agrees with data from Nam et al., which suggests that there may be less than 2 mm of wear on most valgus knees [29], and also may reflect the landmarking algorithm used with this imageless navigation system.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Accuracy of imageless navigation is dependent upon the quality of registration, and results could be different if appropriate registration is not performed.

    “First, accuracy of imageless navigation is dependent upon the quality of the registration, and results presented here could be different if appropriate registration is not performed.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Personalized alignment strategies that target recreation of native knee joint morphology may limit the need for soft tissue releases and result in more natural kinematics.

    “Personalized alignment strategies that target recreation of native knee joint morphology may limit the need for soft tissue releases and result in more natural kinematics [8, 9, 34, 35].”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [8] Blakeney W, Clement J, Desmeules F, Hagemeister N, Riviere C, Vendittoli PA. Kinematic alignment in total knee arthroplasty better reproduces normal gait than mechanical alignment. Knee Surg Sports Traumatol Arthrosc. 2019;27(5):1410–7. source
    • cites [9] Elbuluk AM, Jerabek SA, Suhardi VJ, Sculco PK, Ast MP, Vigdorchik JM. Head-to-Head comparison of kinematic alignment versus mechanical alignment for total knee arthroplasty. J Arthroplasty. 2022;37(8S):S849–51. source
    • cites [34] Vigdorchik JM, Wakelin EA, Koenig JA, Ponder CE, Plaskos C, DeClaire JH, et al. Impact of component alignment and soft tissue release on 2-year outcomes in total knee arthroplasty. J Arthroplasty. 2022;37(10):2035-40 e5. source
    • cites [35] Niki Y, Nagura T, Nagai K, Kobayashi S, Harato K. Kinematically aligned total knee arthroplasty reduces knee adduction moment more than mechanically aligned total knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2018;26(6):1629–35. source
38 of 38

  • The authors state this as an assumption.

    Use of aHKA to predict constitutional alignment assumes that the distal femur and proximal tibia joint surfaces in the native knee are parallel.

    “Use of aHKA to predict constitutional alignment does assume that the distal femur and proximal tibia joint surfaces in the native knee are parallel.”
1 of 1

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • LDFA mean absolute error differs between the discussion and results

    Minor

    The discussion reports a Navlit LDFA mean absolute error of 1.5°, whereas the abstract and Table 2 report 1.4° for the same comparison.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Howell SM, Roth JD, Hull ML. Kinematic alignment in total knee arthroplasty definition, history, principle, surgical technique, and results of an alignment option for TKA. Arthropaedia. 2014;1:44–53.

Cited by

Sorted by citations

Related

Authors
Edelstein, A. I., Orsi, A. D., Plaskos, C., Coffey, S., & Suleiman, L. I.
Affiliations
  • Northwestern University (US)
  • Nepean Hospital (AU)
Corresponding author
Plaskos, Christopher
ORCID
Venue
Arthroplasty
Publisher
Springer Science and Business Media LLC
Published
2024-03-03
Volume
6
Issue
1
Pages
14-14
ISSN
2524-7948 (ISSN-L)
DOI
10.1186/s42836-024-00231-9
PMC
PMC10909262
OpenAlex
W4392756958
Semantic Scholar
8a54f123384bf1273fcb40b75d6980c9d9790a85
Cited by
11
References
37
Citations by year
2026: 6 · 2025: 5
FWCI
4.19
Type
journal article
Language
en
Open access
Licence
Locations
  • Arthroplasty (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Surgery › Total Knee Arthroplasty Outcomes
  • Health Sciences › Medicine › Surgery › Knee injuries and reconstruction techniques
  • Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
Keywords
total knee arthroplasty, coronal plane alignment of the knee, long-leg radiographs, medial proximal tibial angle, lateral distal femoral angle, joint line obliquity, hip-knee-ankle angle, intraoperative registration, knee osteoarthritis, observer agreement

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-19.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-19.

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Statistics and arithmetic are recomputed, not judged.

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