Self-Reported Metal Allergy and Early Outcomes After Total Knee Arthroplasty
Bibliographic record
Abstract
The impact of self-reported metal allergy (SRMA) in total knee arthroplasty (TKA) remains controversial. In the absence of objective tests, SRMA is often used as a screening tool for implant selection. The objective of this study was to determine the effect of SRMA on early outcomes after TKA. Between 2010 and 2014, 168 patients with SRMA underwent TKA; 150 (89%) received nickel-free implants, and 18 (11%) received cobalt-chrome implants that contained nickel. Mean age was 67 years, and 95% were female. A cohort of 858 TKA patients (mean age, 68 years) without SRMA matched by sex served as the control group. Outcomes included Knee Society Score (function [KSS-F] and knee [KSS-K]), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, knee flexion, further surgery, and complications. No differences were seen in KSS-F and KSS-K between patients with and without SRMA. The mean WOMAC pain scores were 89.1 for patients with SRMA and 85.2 for patients without SRMA (P=.030). Stiffness and physical function scores were similar. Knee flexion was similar. No differences were found between nickel-free and cobalt-chrome SRMA groups. Patients with SRMA and those without demonstrated similar early functional outcomes. Patients with SRMA who received standard cobalt-chrome implants had no significant difference in functional outcomes compared with patients with nickel-free implants. Better identifiers of patients at risk for adverse events due to implant material are needed. [Orthopedics. 2019; 42(6):330-334.].
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".