PLASMA CONCENTRATIONS OF HOMOARGININE ARE ASSOCIATED WITH RISK OF TOTAL JOINT REPLACEMENT REVISION SURGERY
Bibliographic record
Abstract
Osteoarthritis (OA) is a highly prevalent joint disorder worldwide, with 1 in 5 Canadians over the age of 60 living with the disease. After all conservative modalities fail, the most effective treatment for OA is total joint arthroplasty (TJA). Over 130,000 hip and knee arthroplasties were performed in Canada during 2018–2019. Thesearthroplasties are expected to last 15–20 years; however, 2–5% of patients require an early prosthetic revision. Metabolomic technology has introduced a novel and effective approach to study disease etiology and treatment pathways at the biochemical level. Existing literature suggests a link exists between Arginine supplementation and surgical infection rates. However, no studies on the metabolomics of TJA revisions have been reported to date. Study participants included 1,086 TJA patients recruited between 2011 and 2017 at two provincial tertiary care hospitals that provide TJA. A subset of this cohort (n=481) had plasma metabolomic data available (630 metabolites and 230 sum and ratios) that was profiled utilizing a method previously published by our group. The majority of these patients underwent TJA due to OA and their revision status was collected through a chart review on the provincial Health Care Information System. Individual metabolite concentrations between revision and non-revision groups were analyzed with the predefined significance level of p?7.9×10-5 to adjust for multiple testing with Bonferroni's method. In the cohort of 481 patients 18 were found to have undergone a revision, giving a revision rate of 3.7% in this group. The mean age was 65 years, mean BMI 33.9 kg/m2, and 57% of these patients were female. These demographic variables were not found to be significantly associated with revision status. Out of the 630 metabolites and 230 sum and ratios, we found that homoarginine (HArg) was significantly lower in patients who required revision surgery (Figure 1). The receiver operator curve (ROC) analysis found an area under the curve (AUC) of 0.76 for HArg to discriminate revision from non-revision patients. We further restricted our analysis to those revision cases due to infection (n=6) and found that the AUC increased to 0.915. When standardizing HArg concentration to Z-score, per SD decrease in HArg was associated with a 4.47 times risk for revision in the entire cohort and a 23.2 times risk for revisions due to infection. Further, we found no associations between arginine, lysine, and revision but the ratio of HArg to the sum of arginine and lysine was significantly associated with revision, suggesting the synthesis of HArg was reduced in revision patients. These findings are limited by sample size but suggest that HArg level is predictive for patients that will subsequently require revision surgery. These findings are intriguing given the role of HArg in NO synthesis and the growing literature that arginine supplementation reduces post-operative infection rates. For any figures or tables, please contact the authors directly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".