Perioperative oxidative stress predicts subsequent pain-related outcomes in the 6 months after total knee arthroplasty
Bibliographic record
Abstract
ABSTRACT: Total knee arthroplasty (TKA) is effective for pain reduction in most patients, but 15% or more report unsatisfactory long-term pain outcomes. We tested whether oxidative stress (OS) related to extended tourniquet application during TKA and subsequent ischemic reperfusion (IR) contributed to adverse post-TKA pain outcomes. Blood samples were obtained in 91 patients with osteoarthritis (63% female) undergoing TKA before tourniquet placement (T1), 45 minutes after tourniquet inflation (T2), and 15 minutes after tourniquet removal (T3). Plasma levels of F 2 -isoprostanes and isofurans, the most specific measures of in vivo OS, were quantified. Pain intensity and function were assessed at baseline and again at 6 weeks and 6 months after TKA. Results indicated that higher Combined OS (F 2 -isoprostanes + isofurans/2) at T1 baseline and larger increases in Combined OS from T1 to T2 were associated with higher baseline-corrected past 24-hour worst and average pain intensity (numeric rating scale) and higher past week McGill Pain Questionnaire-2 total scores at 6-month follow-up ( P 's < 0.05). Increases in Combined OS from T1 to T3, which should most directly capture OS and IR injury related to tourniquet use, were not associated with short-term or long-term post-TKA pain outcomes. Longer ischemia duration was unexpectedly associated with lower baseline-corrected pain intensity at 6-month follow-up. Combined OS was not linked to functional outcomes at either follow-up. Elevated perioperative OS seems to exert small but significant adverse effects on long-term post-TKA pain outcomes, although this OS seems unrelated to IR injury associated with extended tourniquet use.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".