Blood metal ion levels are not a useful test for adverse reactions to metal debris
Bibliographic record
Abstract
OBJECTIVES: Alarm over the reported high failure rates for metal-on-metal (MoM) hip implants as well as their potential for locally aggressive Adverse Reactions to Metal Debris (ARMDs) has prompted government agencies, internationally, to recommend the monitoring of patients with MoM hip implants. Some have advised that a blood ion level >7 µg/L indicates potential for ARMDs. We report a systematic review and meta-analysis of the performance of metal ion testing for ARMDs. METHODS: We searched MEDLINE and EMBASE to identify articles from which it was possible to reconstruct a 2 × 2 table. Two readers independently reviewed all articles and extracted data using explicit criteria. We computed a summary receiver operating curve using a Bayesian random-effects hierarchical model. RESULTS: Our literature search returned 575 unique articles; only six met inclusion criteria defined a priori. The discriminative capacity of ion tests was homogeneous across studies but that there was substantial cut-point heterogeneity. Our best estimate of the "true" area under curve (AUC) for metal ion testing is 0.615, with a 95% credible interval of 0.480 to 0.735, thus we can state that the probability that metal ion testing is actually clinically useful with an AUC ≥ 0.75 is 1.7%. CONCLUSION: Metal ion levels are not useful as a screening test for identifying high risk patients because ion testing will either lead to a large burden of false positive patients, or otherwise marginally modify the pre-test probability. With the availability of more accurate non-invasive tests, we did not find any evidence for using blood ion levels to diagnose symptomatic patients.Cite this article: M. Pahuta, J. M. Smolders, J. L. van Susante, J. Peck, P. R. Kim, P. E. Beaule. Blood metal ion levels are not a useful test for adverse reactions to metal debris: a systematic review and meta-analysis. Bone Joint Res 2016;5:379-386. DOI: 10.1302/2046-3758.59.BJR-2016-0027.R1.
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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 | 0.060 | 0.200 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".