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Record W4396639689 · doi:10.21474/ijar01/18559

RESULTS OF ROBOTIC ASSISTED VS CONVENTIONAL TOTAL KNEE ARTHROPLASTY AT 1 YR FOLLOW UP

2024· article· en· W4396639689 on OpenAlexaboutno aff
Devashish Chhutani, Abhinav Vatsa, Mohammed Sohail Siddique

Bibliographic record

VenueInternational Journal of Advanced Research · 2024
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisPhysical therapyQuality of life (healthcare)Radiological weaponVisual analogue scaleObservational studyProsthesisRandomized controlled trialArthroplastyOrthopedic surgeryRepeated measures designPatient satisfactionKnee replacementSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Background: Osteoarthritis (OA) of the knee is a prevalent condition among older individuals, causing significant discomfort and impairments in quality of life. Conventional total knee arthroplasty (COTKA) is a common treatment, but issues such as inadequate soft tissue balance and prosthesis misalignment can impact outcomes. Robotic-assisted total knee arthroplasty (RATKA) has emerged as a potential solution, offering enhanced precision in prosthesis placement. While observational studies suggest benefits, comprehensive reviews of randomized controlled trials (RCTs) are lacking. This study aims to fill this gap by evaluating the clinical, functional, and radiological outcomes of RATKA compared to COTKA in adult patients with primary knee OA. Methods: This prospective study was conducted at a specialized orthopedic center, involving patients diagnosed with symptomatic knee OA eligible for total knee replacement (TKR). Patients were allocated to either conventional TKR (Group A) or robotic-assisted TKR (Group B). Outcome measures included Visual Analog Scale (VAS) for pain, Knee Society Score (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), patient satisfaction, and quality of life assessments. Radiological outcomes were assessed using standardized radiographs. Statistical analyses included descriptive statistics, group comparisons, and repeated measures analysis of variance (ANOVA). Results: Baseline characteristics showed similar distributions between Group A (n=30) and Group B (n=30). Clinical outcomes demonstrated significant improvements over time in both groups, with Group B consistently outperforming Group A across all measures. Notably, Group B exhibited lower pain scores (VAS), higher functional scores (KSS), lower disability scores (WOMAC), higher patient satisfaction, and better quality of life assessments. Radiological outcomes also favored Group B, with improved mechanical axis deviation and component positioning. Conclusion: Robotic-assisted TKR demonstrated superior clinical, functional, and radiological outcomes compared to conventional TKR in patients with knee OA. These findings support the growing body of evidence favoring the use of robotic technology in TKR procedures, particularly for optimizing implant placement and alignment. Future research should focus on cost-effectiveness and long-term outcomes to further inform clinical practice and enhance patient care.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.049
GPT teacher head0.390
Teacher spread0.341 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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