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Record W4414239748 · doi:10.1002/ksa.70034

No difference in PROMs between kinematic and mechanical alignment in TKA: An umbrella review with secondary meta‐analysis and GRADE assessment

2025· article· en· W4414239748 on OpenAlexaboutno aff
Johannes Stöve, Daniel Schrednitzki, Katharina Ortwig, Michael T. Hirschmann, Andreas M. Halder

Bibliographic record

VenueKnee Surgery Sports Traumatology Arthroscopy · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsKinematicsOrthopedic surgeryBiomechanicsMinimal clinically important differenceSignificant difference

Abstract

fetched live from OpenAlex

PURPOSE: To identify, synthesise and critically appraise the findings of meta-analyses that compare patient-reported outcome measures (PROMs) between unrestricted kinematic alignment and mechanical alignment in total knee arthroplasty (TKA). It was hypothesised that some meta-analyses inaccurately combine PROMs from unrestricted and restricted kinematic alignment techniques. METHODS: Two authors independently screened articles based on inclusion and exclusion criteria and assessed the methodological quality based on the 16 domains of A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2). Effect sizes of difference in PROMs were tabulated for each meta-analysis. Studies included in the meta-analyses were assessed to determine if they were on true unrestricted kinematic alignment. A secondary meta-analysis excluded studies on restricted kinematic alignment techniques, to recalculate pooled estimates (mean difference (MD) with their 95% confidence interval (CI)) of the Knee Society Score (KSS), Oxford Knee Score (OKS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Forgotten Joint Score (FJS). The quality of evidence was assessed using the GRADE. RESULTS: There were 15 meta-analyses pooling data from 39 clinical studies eligible for data extraction. None fulfilled all seven critical AMSTAR-2 domains. Some reported kinematic alignment yielded superior KSS (Function, n = 9; Knee, n = 6: Combined, n = 8), OKS (n = 7), WOMAC (n = 8) and FJS (n = 1). The secondary meta-analysis included only studies on unrestricted kinematic alignment and results at the latest follow-up, for which the mean and standard deviations were reported and revealed no difference in KSS, OKS, WOMAC or FJS between kinematic and mechanical alignment. GRADE analysis revealed 'very low' quality of evidence for KSS, WOMAC and FJS, while it was 'low' quality for OKS. CONCLUSION: Current evidence suggests no difference in PROMs between kinematic and mechanical alignment in TKA. Meta-analyses that report the contrary often need more rigour as they pool studies on various kinematic alignment techniques or represent the same cohort at different times. Orthopaedic societies should promote using objective outcome measures to evaluate and compare alignment techniques. REGISTRATION: Systematic review protocol registration (Prospero: CRD42023434713). LEVEL OF EVIDENCE: Level III.

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)0.073
metaresearch head score (Gemma)0.164
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 score0.073
Threshold uncertainty score0.387

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.164
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0280.058
Bibliometrics0.0130.010
Science and technology studies0.0010.002
Scholarly communication0.0080.004
Open science0.0040.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.326
Teacher spread0.293 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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