Listeria spondylodiscitis: an uncommon etiology of a common condition; a case report
Bibliographic record
Abstract
BACKGROUND: Listeriosis is a severe food-borne infection caused by the Gram-positive rod, Listeria monocytogenes. Despite the low incidence (3-8 cases per million), Listeriosis has a case fatality rate of 20-30% as it occurs predominantly in immunocompromised individuals at extremes of age, diabetics and pregnant women. Listeriosis classically presents as a febrile gastroenteritis, isolated bacteremia, meningitis, or maternal-fetal infections. Focal bone and joint infection are rare and primarily involve orthopedic implant devices. Here, we present the first case of Listeria-associated spondylodiscitis. CASE PRESENTATION: A 79-year-old male presents with acute-on-chronic back pain in the absence of risk factors or exposures, aside from age. On radiological imaging, spondylodiscitis of L3-L4 was diagnosed. Subsequently, a CT-guided biopsy was performed to aid in confirming microbiological aetiology. Listeria monocytogenes was grown in culture and patient received appropriate antibacterial therapy. CONCLUSION: The case highlights the utility of image-guided tissue sampling in aiding diagnosis and management in patients with vertebral osteomyelitis. It also encourages consideration of uncommon organisms such as Listeria as an etiology of vertebral osteomyelitis, even in the absence of prosthetic implants.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".