Comparison of Tc-99m-labelled antileukocyte fragment Fab′ and Tc-99m-HMPAO leukocyte scintigraphy in the diagnosis of bone and joint infections: a prospective study
Bibliographic record
Abstract
Between January and July 1998, we conducted a prospective study to compare Tc-99m-labelled antigranulocyte monoclonal antibody fragment Fab' (LEUKOSCAN) scintigraphy versus Tc-99m-hexamethylpropyleneamine oxime (Tc-99m-HMPAO)-labelled leukocyte scintigraphy (HMPAO-LS) for the diagnosis of unselected patients with bone and joint infection. Twenty-three patients (16 men and 7 women; mean age, 67 years) with suspected bone infection were explored successively with bone scintigraphy, HMPAO-LS and LEUKOSCAN scintigraphy. Thirty-two foci were studied (diabetic foot = 11, prosthetic material = 8, joint disease = 4, others = diagnosed in 18 cases, eight on the basis of bacteriological and histological examination of surgical or puncture specimens, with or without radiographic signs, and 10 on the basis of clinical course and radiographic findings. Overall sensitivity, specificity and accuracy were 86%, 72% and 78%, respectively, for LEUKOSCAN scintigraphy (12 true positives (TP), 13 true negatives (TN), 5 false positives (FP), 2 false negatives (FN)), 93%, 100% and 96%, respectively, for HMPAO-LS (13TP, 18TN, 0FP, 1FN), and 100%, 17% and 53.3%, respectively, for bone scintigraphy. In this small series, LEUKOSCAN scintigraphy was found to be less specific for the diagnosis of osteomyelitis than HMPAO-LS. In addition, the interpretation of LEUKOSCAN scintigraphy is more difficult than HMPAO-LS for the diagnosis of bone infection in the diabetic foot, and would appear to be less discriminating for differentiating soft tissue infection from osteitis in the case of plantar perforating ulcers.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".