An Assessment of Clinical and Functional Outcomes in the Patients Undergoing Total Knee Arthroplasty during Postoperative Period
Bibliographic record
Abstract
ABSTRACT Background and objective Patient-reported outcome measures continue to play an important role in assessing the performance and determining the comparative effectiveness of total knee arthroplasty. Patient's satisfaction can be influenced by many factors, such as, residual pain, postoperative functionality, and the presence of postoperative complications and hence we evaluated clinical and functional outcomes following total knee arthroplasty. This study was conducted to bust the myth of postoperative pain and disability following a total knee replacement. Materials and methods A prospective observational cohort study was conducted among the patients who underwent primary total knee arthroplasty in the Department of Orthopaedics in the Sundaram Medical Foundation during the study period of March 2017 and January 2018. A total of 30 cases were included. During their follow-up, patient's outcomes were assessed using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and American Knee Society Scores (AKSS). Data were analyzed using SPSS v.17. Results At the end of 6 months, 76.7% of participants were satisfied with their outcome. Significant improvement was noted in both clinical (p = 0.000) and functional outcome (p = 0.000) of AKSS and total WOMAC scores (p = 0.007) during the follow-up at the sixth month. Also, there was a significant difference in AKSS scores noted with respect to age but other parameters like duration of illness and type of arthritis were not significant. Conclusion The majority of study subjects were satisfied with the clinical and functional outcome based on WOMAC and AKSS, which in turn encouraged them to undergo total knee replacement of the other knee. Clinical significance From our study, we could determine the importance of patient- and clinician-reported outcome measures in predicting the satisfaction of the patient following total knee replacement. Assessment of a patient planned for total knee replacement, with the outcome scores both preoperatively and postoperatively will give us a brief idea on how better the patient will fair following surgery and will also help us in the rehabilitation of the patient accordingly. How to cite this article Venkatesan AS, Jayasankar P, Williams S. An Assessment of Clinical and Functional Outcomes in the Patients Undergoing Total Knee Arthroplasty during Postoperative Period. J Orth Joint Surg 2020;2(2):57–61.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".