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Record W4399527176 · doi:10.1002/jeo2.12054

Limitations of the knee society score in kinematically aligned total knee arthroplasty

2024· article· en· W4399527176 on OpenAlexaboutno aff
Alexandra Leica, Manuel‐Paul Sava, Zainab‐Aqeel Khan, Rolf Hügli, Michael T. Hirschmann

Bibliographic record

VenueJournal of Experimental Orthopaedics · 2024
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineChecklistSystematic reviewPhysical therapyRadiological weaponOxford knee scoreCritical appraisalMEDLINEValgusArthroplastyEvidence-based medicineOrthopedic surgeryRandomized controlled trialTotal knee arthroplastySurgeryOsteoarthritisAlternative medicinePsychology

Abstract

fetched live from OpenAlex

Purpose: The Knee Society Scoring System (KSS) is a frequently used outcome score which quantifies functional patients' outcomes before and after total knee arthroplasty (TKA). Several problems arise when trying to implement KSS for obtaining postoperative outcomes after more personalised aligned TKAs. Scoring for valgus femorotibial angle (FTA) intervals outside moderate ranges is often poorly explained, the specific version of KSS used for outcome collection is frequently unclear and the exact measuring methods are typically not described in the literature. The aims of this systematic review were to investigate the latest user practice, the application of KSS and its limitations after kinematically aligned (KA) TKA. Methods: A systematic literature search following PRISMA guidelines was conducted on PubMed, Embase, Medline and Scopus to identify potentially relevant articles for this review, published from the beginning of January 2013 until the end of January 2023. Broad Mesh terms such as 'kinematic alignment', 'total knee arthroplasty' and 'knee society score' were used for building search strategy in each database accordingly. Articles reporting postoperative values of the objective surgeon-assessed KSS after KA TKA or KA and mechanically aligned TKA were included. For assessing included randomised control trials (RCTs), an Agency for Healthcare Research and Quality's design-specific scale for assessing RCTs was used. The non-RCTs were assessed by using the Joanna Briggs Institute Critical Appraisal Tool. The Ottawa-Newcastle Score system was also used. Studies were additionally evaluated for their radiological methodology by using a five-question checklist (Radiological Assessment Qualit criteria). Results: The initial search identified 167 studies, of which 129 were considered for screening. Ten studies reporting outcomes after KA TKA did not use the objective surgeon-assessed part of KSS for clinical outcome measurement, and 30 studies reporting outcomes after KA TKA did not use KSS at all for clinical and/or functional outcomes. From the 10 included studies, only six have used the latest KSS score (2011), the rest using its 1989 variant; and out of these six studies, only two presented values of the FTA, which is needed for calculating the KSS's 'alignment' subcomponent, the rest presenting hip-knee-ankle angle (HKA) values. Additionally, when converting these HKA values to FTA intervals, the authors of this systematic review found that KA TKA FTA intervals display limits, which tend to be outside the 'well-scored' KSS anatomical alignment interval. Conclusion: The inconsistent and nonstandardised use of the surgeon-assessed KSS across studies reviewed compromises assessment reliability and patient outcome scores. To enhance precision and comparability, it is crucial to standardise the KSS application, incorporating personalised alignment strategies for more accurate patient evaluations. 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)0.093
metaresearch head score (Gemma)0.239
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0930.239
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0090.012
Science and technology studies0.0010.003
Scholarly communication0.0060.004
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.286
Teacher spread0.249 · 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 designObservational
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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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