18F-FDG PET/CT as a central tool in the shift from chronic Q fever to Coxiella burnetii persistent focalized infection
Bibliographic record
Abstract
Because Q fever is mostly diagnosed serologically, localizing a persistent focus of Coxiella burnetii infection can be challenging. F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) could be an interesting tool in this context.We performed a retrospective study on patients diagnosed with C burnetii infection, who had undergone F-FDG PET/CT between 2009 and 2015. When positive F-FDG PET/CT results were obtained, we tried to determine if it changed the previous diagnosis by discovering or confirming a suspected focus of C burnetii infection.One hundred sixty-seven patients benefited from F-FDG PET/CT. The most frequent clinical subgroup before F-FDG PET/CT was patients with no identified focus of infection, despite high IgG1 serological titers (34%). For 59% (n = 99) of patients, a hypermetabolic focus was identified. For 62 patients (62.6%), the positive F-FDG PET/CT allowed the diagnosis to be changed. For 24 of them, (38.7%), a previously unsuspected focus of infection was discovered. Forty-two (42%) positive patients had more than 1 hypermetabolic focus. We observed 21 valvular foci, 34 vascular foci, and a high proportion of osteoarticular localizations (n = 21). We also observed lymphadenitis (n = 27), bone marrow hypermetabolism (n = 11), and 9 pulmonary localizations.We confirmed thatF-FDG PET/CT is a central tool in the diagnosis of C burnetii focalized persistent infection. We proposed new diagnostic scores for 2 main clinical entities identified using F-FDG PET/CT: osteoarticular persistent infections and lymphadenitis.
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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 | 0.000 | 0.001 |
| 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) | 0.008 | 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; both teacher heads agree on what is shown here.
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".