Preoperative gait patterns and BMI are associated with tibial component migration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: There is no standard for patient triage in total knee arthroplasty (TKA) based on joint functional characteristics. This is largely due to the lack of objective postoperative measurement of success in TKA in terms of function and longevity, and the lack of knowledge of preoperative metrics that influence outcome. We examined the association between the preoperative mechanical environment of the patients knee joint during gait and the post-TKA stability of the tibial component as measured with radiostereometric analysis (RSA). METHODS: 37 subjects were recruited out of a larger randomized RSA trial. 3-dimensional gait analysis was performed in the preoperative week. Longitudinal RSA data were gathered postoperatively at 6 months and 1 year. RESULTS: We found a statistically significant association between the pattern of the knee adduction moment during gait preoperatively and the total migration of the implant at 6 months postoperatively. A substantial proportion of the variability in the total postoperative tibial component migration (R(2) = 0.45) was explained by a combination of implant type, preoperative knee joint loading patterns during gait, and body mass index at 6 months postoperatively. The relationships did not remain statistically significant at 1 year postoperatively. INTERPRETATION: Our findings support the hypothesis that preoperative functional characteristics of patients, and particularly joint loading patterns during activities of daily living, are important for outcome in TKA. This represents a first step in the development of predictive models of objective TKA outcome based on preoperative patient characteristics, which may lead to better treatment strategies. ClinicalTrials.gov (NCT00405379).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it