Use of Erythrocyte Sedimentation Rate and C-Reactive Protein Level to Diagnose Infection Before Revision Total Knee Arthroplasty
Bibliographic record
Abstract
Background: Despite the widespread use of several diagnostic tests, there is still no perfect test for the diagnosis of infection at the site of a total knee arthroplasty. The purpose of this study was to evaluate the diagnostic test characteristics of the erythrocyte sedimentation rate and C-reactive protein level for the assessment of infection in patients presenting for revision total knee arthroplasty. Methods: One hundred and fifty-one knees in 145 patients presenting for revision total knee arthroplasty were evaluated prospectively for the presence of infection with measurement of the erythrocyte sedimentation rate and the C-reactive protein level. The characteristics of these tests were assessed with use of two different techniques: first, receiver-operating-characteristic curve analysis was performed to determine the optimal positivity criterion for the diagnostic test, and, second, previously accepted criteria for establishing positivity of the tests were used. Results: A diagnosis of infection was established for forty-five of the 151 knees that underwent revision total knee arthroplasty. The receiver-operating-characteristic curves indicated that the optimal positivity criterion was 22.5 mm/hr for the erythrocyte sedimentation rate and 13.5 mg/L for the C-reactive protein level. Both the erythrocyte sedimentation rate (sensitivity, 0.93; specificity, 0.83; positive likelihood ratio, 5.81; accuracy, 0.86) and the C-reactive protein level (sensitivity, 0.91; specificity, 0.86; positive likelihood ratio, 6.89; accuracy, 0.88) have excellent diagnostic test performance. Conclusions: The erythrocyte sedimentation rate and the C-reactive protein level provide excellent diagnostic test information for establishing the presence or absence of infection prior to surgical intervention in patients with pain at the site of a knee arthroplasty. Level of Evidence: Diagnostic Level I. See Instructions to Authors for a complete description of levels of evidence.
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 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 | 0.000 |
| 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 | 0.000 | 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".