Bibliographic record
Abstract
Purpose: This study compared the clinical and radiological results using navigation assisted minimally invasive (NA-MIS) and conventional (CON) techniques in forty-two patients, who underwent bilateral TKA with a minimum follow-up of one-year. Materials and Methods: The clinical evaluations were performed using ROM, HSS, and Western Ontario and McMaster University (WOMAC) scores at 3, 6 and 9 months, and 1 year after surgery. The patients' subjective preferences and radiological indices, including the mechanical axis and coronal inclinations of the prostheses, were compared at 1 year after surgery. Results: The NA-MIS TKA showed better HSS and WOMAC total scores than CON TKA up to six months. However, these differences were not significant 1 year after surgery. The ROM and other WOMAC scores were comparable in both groups at all times. More patients preferred the NA-MIS side to the CON side. The radiological results showed similar mean values between the two surgical groups, even though the NA-MIS group contained fewer outliers than the CON group. Conclusion: Navigation assisted minimal invasive TKA is associated with better clinical results up to 6 months after surgery and shows fewer outlier results. However, the mean values in leg alignment were similar to those of conventional TKA.
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 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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".