Population-based Survivorship of Computer-navigated Versus Conventional Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: The goal of computer navigation in total knee arthroplasty (TKA) is to improve the accuracy of alignment. However, the relationship between this technology and implant longevity has not been established. The purpose of this study was to analyze survivorship of computer-navigated TKAs compared with traditionally instrumented TKAs. METHODS: The PearlDiver Medicare database was used to identify patients who underwent a primary TKA using conventional instrumentation versus computer navigation between 2005 and 2014. Conventional and computer-navigated cohorts were matched by age, sex, year of procedure, comorbidities, and geographic region. Kaplan-Meier curves were generated to estimate survivorship with aseptic mechanical complications, periprosthetic joint infection, and all-cause revision as end points. RESULTS: During the study period, 75,709 patients who underwent a computer-navigated TKA were identified and matched to a cohort of 75,676 conventional TKA patients from a cohort of 1,607,803 conventional TKA patients. No difference existed in survival between conventional instrumentation (94.7%) and navigated TKAs (95.1%, P = 0.06) at 5 years. A modest decrease was found in revisions secondary to mechanical complications associated with navigation (96.1%) compared with conventional instrumentation (95.7%, P = 0.02) at 5 years. No differences in revision rates because of periprosthetic joint infection were observed (97.9% versus 97.9% event-free survival, P = 0.30). In a subgroup of Medicare patients younger than 65 years of age, use of computer navigation was associated with a decrease in all-cause revision (91.4% versus 89.6% event free survival, P = 0.01) and revision secondary to mechanical complications (89.6% versus 87.8% event-free survival, P = 0.01) at 5 years. DISCUSSION: Among Medicare patients, no notable difference existed in TKA survival associated with the use of computer navigation at the 5-year follow-up. Use of computer navigation was associated with a slight decrease in revisions secondary to mechanical failure. Although improved survivorship was associated with patients younger than 65 years of age who had a navigated TKA, generalizability of these findings is limited given the unique characteristics of this Medicare subpopulation.
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 | 0.001 | 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".