<i>Yokenella regensburgei</i>infection in an immunocompetent individual after trauma following a fall from a personal conveyance
Bibliographic record
Abstract
Background: Yokenella regensburgei infections have been documented in several immunocompromised individuals with numerous associated risk factors including soft tissue infections, organ transplants, and metabolic disorders. Our report presents a rare case of Y. regensburgei infection in an immunocompetent individual. Methods: In September 2020, a 38-year-old man who was otherwise healthy fell from a personal conveyance causing a puncture of his elbow. Two months later, he was admitted to the hospital with a chronic draining wound on his left arm with no fever (36.7°C) and stable vital signs. The patient underwent white blood cell (WBC) imaging, and single-photon emission computed tomography (SPECT/CT) to rule out osteomyelitis. Incision and drainage were performed, and the collected fluid was sent to a microbiology lab for culture diagnosis. Subsequently, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) analysis and antimicrobial susceptibility testing were performed. Results: A WBC image and SPECT/CT test showed an increase in WBC uptake and activity in the subcutaneous tissue of the left arm. The culture diagnosis identified the isolate as Y. regensburgei and the patient received 2 weeks of sulfamethoxazole 800 mg and trimethoprim 160 mg orally twice daily based on the results of the antimicrobial susceptibility testing. He demonstrated clinical improvements shown through wound healing and reduced pain. Conclusion: This report supports the potential of Y. regensburgei to act as an opportunistic pathogen even in hosts with no prior underlying diseases or conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".