Utility of 18 F‐FDG PET/CT scan to diagnose the etiology of fever of unknown origin in patients on dialysis
Bibliographic record
Abstract
INTRODUCTION: Studies on fever of unknown origin (FUO) in patients of chronic kidney disease and end stage renal disease patients on dialysis were not many. In this study, we used 18 F-FDG PET/CT scan whole body survey for detection of hidden infection, in patients on dialysis, labelled as FUO. METHODS: In this retrospective study, 20 patients of end stage renal disease on dialysis were investigated for the cause of FUO using 18F-FDG PET/CT scan. All these patients satisfied the definition of FUO as defined by Petersdorf and Beeson. Any focal abnormal site of increased FDG concentration detected by PET/CT, either a solitary or multiple lesions was documented and at least one of the detected abnormal sites of radio tracer concentration was further examined for histopathology. FINDINGS: All patients were on renal replacement therapy. Of these, 18 were on hemodialysis and two were on peritoneal dialysis. 18F-FDG PET/CT scan showed metabolically active lesions in 15 patients and metabolically quiescent in five patients. After 18F-FDG PET/CT scan all, but one patient had a change in treatment for fever. Anti-tuberculous treatment was given in 15 patients, antibiotics in four patients and anti-malaria treatment in one patient. DISCUSSION: The present study is first study of 18F-FDG PET/CT scan in patients of end stage renal disease on dialysis with FUO. The study showed that the 18 F FDG PET/CT scan may present an opportunity to attain the diagnosis in end stage renal disease patients on dialysis with FUO.
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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 | 0.004 |
| 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) | 0.002 | 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".