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Record W4406716805 · doi:10.1097/corr.0000000000003356

Kinematic Alignment Does Not Result in Clinically Important Improvements After TKA Compared With Mechanical Alignment: A Meta-analysis of Randomized Trials

2025· review· en· W4406716805 on OpenAlexaff
Nicholas Nucci, Moyukh Chakrabarti, Zachary DeVries, Seper Ekhtiari, Sebastian Tomescu, Raman Mundi

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2025
Typereview
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsUniversity of TorontoMcMaster UniversityUniversity of Ottawa
Fundersnot available
KeywordsMedicineKinematicsMeta-analysisRandomized controlled trialMEDLINEOxford knee scoreMinimal clinically important differencePhysical medicine and rehabilitationPhysical therapySurgeryOsteoarthritisInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is debate as to whether kinematic TKA or mechanical alignment TKA is superior. Recent systematic reviews have suggested that kinematically aligned TKAs may be the preferred option. However, the observed differences in alignment favoring kinematic alignment may not improve outcomes (performance or durability) in ways that patients can perceive, and likewise, statistical differences in outcome scores sometimes observed in clinical trials may be too small for patients to notice. Minimum clinically important differences (MCIDs) are changes that are deemed meaningful to the patient. A meta-analysis of randomized trials that frames results on this topic in terms of MCIDs may therefore be informative to surgeons and their patients. QUESTIONS/PURPOSES: (1) Does kinematic alignment for TKA insertion improve patient-reported outcome measures (PROMs) by clinically important margins (for example, 5 points of 48 on the adjusted Oxford Knee Score [OKS] or 13.7 points of 100 on the Forgotten Joint Score [FJS]) compared with mechanical alignment? (2) Does kinematic alignment for TKA insertion improve ROM by a clinically important margin (defined as 3.8° to 6.4° in flexion) compared with mechanical alignment? METHODS: A systematic review of Medline and Embase databases was performed from inception to January 29, 2023, the date of search. We identified RCTs comparing mechanical alignment TKA with kinematic alignment TKA. All English-language RCTs comparing PROMs data in kinematic versus mechanical alignment TKAs performed in patients 18 years or older were included. Studies that were not in English, involved overlapping reports of the same trial, and/or utilized nonrandomized controlled trial methodology were excluded. Conference abstracts or study protocols, pilot studies, and review articles were also excluded. Two reviewers screened abstracts, full-text, and extracted data and assessed included studies for risk of bias using the Cochrane Risk of Bias tool, version 2. Twelve randomized controlled trials (RCTs) were identified, which included 1033 patients with a mean age of 68 years (range 40 to 94) from eight countries who were undergoing primary TKA. Six studies were determined to be low risk of bias, with the remaining six studies determined to be of moderate-to-high risk of bias. As a result, we would expect that the included studies might overestimate the benefit of the newer approach. Outcomes included ROM and PROMs. Where feasible, pooled analysis was completed. PROMs data were extracted from nine pooled studies, with a randomized n = 443 in the kinematic alignment group and n = 435 in the mechanical alignment group. ROM data were extracted from six pooled studies, with randomized n = 248 in the kinematic alignment group and n = 243 in the mechanical alignment group. PROMS were converted to common scales where possible. Multiple versions of the OKS exist; therefore, OKS scores were converted if needed to a 0 to 48 Oxford scale, in which higher scores represent better clinical outcomes. WOMAC scores were converted to OKS using previously reported techniques. The OKS and converted WOMAC scores were represented as "functional scores" in our data set because of their conversion. An MCID of 5 was utilized as previously documented for the OKS. Heterogeneity was assessed using the I 2 statistic, and for an I 2 of > 25%, random-effects models were utilized. RESULTS: In nine pooled studies, we found no clinically important difference between the kinematic and mechanical alignment groups in terms of our generated functional score (mean difference 3 of possible 48 [95% confidence interval (CI) 0.81 to 4.54]; p = 0.005). The functional score included OKS and WOMAC scores converted to OKS. The difference did not exceed the MCID for the OKS. In three pooled studies, we found no difference between the kinematic and mechanical alignment groups in terms of FJS at 1 to 2 years (mean difference 4 of possible 200 [95% CI -1.77 to 9.08]; p = 0.19). In three pooled studies, we found no difference between the kinematic and mechanical alignment groups in terms of EuroQol 5-domain instrument VAS score at 1 to 2 years (mean difference 0.2 of possible 100 [95% CI -3.17 to 3.61]; p = 0.90). We found no clinically meaningful difference between kinematic TKA and mechanical alignment TKA for ROM (extension mean difference 0.1° [95% CI -1.08 to 1.34]; p = 0.83, and flexion mean difference 3° [95% CI 0.5 to 5.61]; p = 0.02). CONCLUSION: This meta-analysis found no clinically important benefit favoring kinematic over mechanical alignment in TKA based on the available RCTs. Because patients cannot perceive advantages to kinematic alignment, and because it adds costs, time (if using advanced technologies), and potential risks to the patient that are associated with novelty, it should not be widely adopted in practice until or unless such advantages have been shown in well-designed RCTs. 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)0.027
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.066
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.044
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.224
GPT teacher head0.495
Teacher spread0.271 · 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 designMeta-analysis
Domainnot available
GenreReview

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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Citations14
Published2025
Admission routes1
Has abstractyes

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