MRI Features Associated With the Detection of Microbial Pathogens by CT-Guided Biopsy in Septic Spondylodiscitis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess the magnetic resonance imaging (MRI) features associated with microbial pathogen detection by computed tomography (CT)-guided biopsy in patients with suspected septic spondylodiscitis. METHODS: For the last 10-year period, we analyzed the medical records of patients who underwent MRI and CT-guided biopsy for suspected septic spondylodiscitis. Clinical characteristics were recorded. The following MRI features were assessed: edema or contrast enhancement of the intervertebral disc, adjacent vertebrae, epidural and paravertebral space, presence of abscess, and paravertebral edema size. A positive biopsy was defined by pathogen identification on bacterial analysis or the presence of granuloma on histology. Predictors of a positive biopsy were assessed with a logistic regression model. RESULTS: We examined data for 61 patients (34 [56%] male; mean age, 59.9 ± 18.0 years); for 35 patients (57%), CT-guided biopsy was positive for a pathogen. The 4 MRI findings significantly associated with a positive biopsy were epiduritis, greater than 50% vertebral endplate edema, loss of intradiscal cleft, and abscess. The size of paravertebral edema was greater with a positive than negative biopsy (median, 15.9 [interquartile range, 11.3-21.3] vs 7.3 [4.6-12.9] mm; p = 0.004). On multivariable analysis, epiduritis was the only independent predictor of a positive biopsy (adjusted odds ratio, 7.4 [95% confidence interval, 1.7-31.4]; p = 0.006). CONCLUSIONS: Epiduritis and the size of paravertebral edema on MRI are associated with detection of a microbial pathogen in suspected septic spondylodiscitis. For patients without these MRI signs, the need for further investigations such as enriched or prolonged cultures, a second CT-guided biopsy, or even surgical biopsy need to be discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".