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Record W3173123412 · doi:10.5152/j.aott.2021.20160

Comparison of outcomes between gap balancing and measured resection techniques for total knee arthroplasty: A prospective, randomized, controlled trial

2021· article· en· W3173123412 on OpenAlexaboutno aff
Ye Zhang, Yu Zhang, Jian-Ning Sun, Lun An, Xiangyang Chen, Shuo Feng

Bibliographic record

VenueActa Orthopaedica et Traumatologica Turcica · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCondyleWOMACRadiographyTotal knee arthroplastyOsteoarthritisValgusProspective cohort studyRandomized controlled trialOrthodonticsSurgeryNuclear medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to compare the effect of Gap Balancing (GB) versus Measured Resection (MR) techniques on the early clinical and radiological results of Total Knee Arthroplasty (TKA). METHODS: In this prospective study, 99 patients (99 knees) who underwent unilateral TKA between March 2018 and January 2019 were randomly allocated to one of two groups: The GP group, TKA with GB technique (19 male, 31 female; mean age = 55.9 ±16.5) and the MR group, TKA with MR technique (19 male, 30 female; mean age = 54.2 ± 18.7). Patients in both groups were comparable in terms of the demographic and clinical data. The angle of cutting block to PCA and Cutting Thickness of the Medial and Lateral Condyle (CTMC, CTLC) were intraoperatively measured. In radiographic analysis, Preoperative Mechanical Femorotibial Angle (Pre-mFTA), Postoperative Mechanical Femorotibial Angle (Post-mFTA), and joint line changes were examined. Femoral component Rotation Angle (FCRA) was also measured by computed tomography. In gait analysis, the spatiotemporal parameters (walking speed, step length, and single support time) and kinematics parameters (flexion angle, extension angle, and transversal rotation) were collected at 12 months postoperatively. Furthermore, Western Ontario and McMaster Universities Arthritis Index (WOMAC) were performed at 12 months after surgery. RESULTS: CTMC and CTLC were both significantly higher in GB group than in the MR group (9.8±2.0 mm vs 8.5 ± 1.2 mm; 7.9 ± 1.8mm vs 6.8 ± 1.4mm; P = 0.001, P = 0.002, respectively). Angle of cutting block to PCA was statistically lower in GB group than in the MR group (1.7 ± 1.5° vs 3.1 ± 0.5 °; P < 0.001). FCRA is greater in the GB group compared to the MR group, but the difference did not reach statistical significance (1.2 ± 2.8 ° vs 0.7 ± 2.0 °; P > 0.05). Although post-mFTA significantly improved compared with pre-mFTA in both groups, no significant difference was observed in the changes of post-mFTA between the two groups (0.9 ± 1.7° vs 0.3 ± 1.8°, P > 0.05). No significant differences were determined between the two groups in spatiotemporal gait parameters including walking speed, step length, and single support time. The sagittal max knee flexion range was significantly larger in the GB group than in the MR group (49.27 ± 5.24 ° vs 45.99 ± 8.21 °, P < 0.05). The flexion range did not reach the level of the control group. There was no significant difference between the two groups in WOMAC at 12 months follow-up (P > 0.05). CONCLUSION: Evidence from this study has revealed GB and MR techniques have both little effect on early clinical results of TKA. Nonetheless, GB technique can provide better knee flexion in the early postoperative gait status compared with MR technique. LEVEL OF EVIDENCE: Level I, Therapeutic Study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.336
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations8
Published2021
Admission routes1
Has abstractyes

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