Metabolomics Signature for Non‐Responders to Total Joint Replacement Surgery in Primary Osteoarthritis Patients: The Newfoundland Osteoarthritis Study
Bibliographic record
Abstract
ABSTRACT Although total joint replacement (TJR) surgery is considered as the most effective treatment for advanced osteoarthritis (OA) patients, up to one‐third of patients reported unfavorable long‐term post‐operative pain outcomes. We aimed to identify metabolic biomarkers to predict non‐responders to TJR using a metabolomics approach. TJR patients were recruited and followed‐up at least 1‐year post‐surgery; TJR outcomes were assessed by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function subscales. Targeted metabolomic profiling was performed on plasma samples collected pre‐surgery and pairwise metabolite ratios, as proxies for enzymatic reactions, were calculated. Association tests were performed between each metabolite ratio and non‐responders. The metabolome‐wide significance was defined as p < 2 × 10−5. A total of 461 TJR patients due to primary OA were included in the analysis. Fifteen percent of patients were classified as pain non‐responders; 16% were classified as function non‐responders. Lower baseline WOMAC pain and function scores were significantly associated with pain and function non‐responders, respectively (both p < 0.03). Two metabolite ratios were significantly associated with pain non‐responders; acetylcarnitine (C2) to phosphatidylcholine acyl‐alkyl C40:1 (PC ae C40:1) was five times higher in pain non‐responders whereas phosphatidylcholine diacyl C36:4 (PC aa C36:4) to isoleucine was twenty one times lower in pain non‐responders than responders (all p ≤ 1.93 × 10−5). One metabolite ratio, glutamine to isoleucine, was significantly lower in function non‐responders than responders (eight times lower; p = 1.08 × 10−5). Three metabolite ratios (C2 to PC ae C40:1, PC aa C36:4, and glutamine to isoleucine) related to inflammation and muscle breakdown could be considered as novel plasma markers for predicting non‐responders to TJR and warrant further investigation. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 38:793‐802, 2020
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".