Hemodialysis catheter infection with unusual presentation and grave outcome
Bibliographic record
Abstract
Bacteremia from central venous catheter (CVC) infection causes morbidity and mortality in patients on hemodialysis (HD). Diagnosis of the infection can be difficult and may require special imaging. A 70-year-old man with diabetic nephropathy was on HD for 11 months through a permanent CVC. Because of symptomatic osteoporosis, he had kyphoplasty in three lumbar vertebrae (L2, L3, L4) 6 months after starting HD. Severe back pain persisted after kyphoplasty. Throughout the HD period, the exit site of the CVC had a clean appearance, there was no fever, and blood leukocyte counts were normal. During the 11th month of HD, he complained of subjective fever at home. Blood count revealed normal leukocyte count with neutrophilic predominance and blood cultures grew methicillin-resistant Staphylococcus aureus (MRSA). Echocardiogram revealed no heart valve vegetations, but irregular thickening of the CVC wall. Fluorodeoxyglucose positron-emission tomography-computed tomography (FDG-PET-CT) revealed severe inflammation of the CVC wall and a picture consistent with osteomyelitis and severe destruction of the body of the 11th thoracic vertebra. He was treated with intravenous vancomycin and removal of the CVC, the wall of which was grossly inflamed and grew in culture MRSA. Three weeks later, he discontinued HD because of persistent severe back pain. CVC infection with bacteremia and remote infectious foci having grave sequelae can develop in HD patients with paucity of clinical manifestations. FDG-PET-CT is a useful imaging tool in establishing the presence and extent of both the CVC infection and remote metastatic infectious foci.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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 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".