Impact of surgeon’s hand and ocular dominance on right and left total knee arthroplasty alignment
Bibliographic record
Abstract
Postoperative alignment is an important modifiable confounder that contributes to the longevity of total knee arthroplasty (TKA). Studies have shown that surgeon’s handedness can affect surgical performance; however, no studies have assessed the effect of surgeon’s hand or ocular dominance on TKA alignment. The purpose of this study was to evaluate the effect of surgeon’s hand and ocular dominance on coronal plane alignment in TKA. We retrospectively evaluated 138 patients who underwent sequential bilateral TKA by the same surgeon, using the Genesis II PS knee (Smith & Nephew, Memphis, TN). We assessed postoperative alignment by measuring and comparing anatomical tibiofemoral angle (TFA) bilaterally on standard postoperative knee radiographs, as well as Knee Society function and pain scores to determine any functional differences. Lastly, we evaluated whether a crossed hand-ocular dominant surgeon had greater accuracy when performing a TKA on the side opposite their hand dominance compared to uncrossed hand-ocular dominant surgeons. All surgeons were right-hand dominant and there was a significantly larger anatomical TFA on left TKAs (mean [SD], 4.6° [2.8°]) compared to right TKAs (3.8° [2.5°]) (P = 0.003). There was no significant difference between right and left Knee Society function (P = 0.09) and pain scores (P = 0.86). When comparing left TKAs, surgeons with uncrossed hand-ocular dominance (4.5°) performed with equal accuracy compared to surgeons with crossed hand-ocular dominance (4.8°) (2-tailed test = 0.597), indicating no effect of ocular dominance. In summary, hand but not ocular dominance was shown to have significant postoperative alignment effects on TKA.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".