Prosthetic vascular graft infection and prosthetic joint infection caused by Pseudomonas stutzeri
Bibliographic record
Abstract
Pseudomonas stutzeri is infrequently isolated from clinical specimens, and if isolated, more likely represents colonization or contamination rather than infection. Despite this, there are dozens of case reports which describe clinically significant P. stutzeri infections at variable sites. A 69-year-old man had a P. stutzeri infection of a prosthetic vascular graft infection, which he received in Panama City. He was successfully treated with a single antipseudomonal agent for 6 weeks and the removal of the infected vascular graft. A 70-year-old man had a P. stutzeri infection of a prosthetic joint, which was successfully treated with a single anti-pseudomonal agent for 6 weeks. There is only one other documented case of a prosthetic vascular graft infection secondary to P. stutzeri . There are 5 documented cases of P. stutzeri prosthetic joint infections. The previous cases were treated with antibiotics and variably, source control with the removal of prosthetic material. Most cases of P. stutzeri infection are due to exposure in health care settings. Immunocompromised states such as HIV or hematological and solid tumor malignancies are risk factors for P. stutzeri infection. Infections caused by P. stutzeri are far less frequent and less fatal than those caused by P. aeruginosa. The etiology of a P. stutzeri infection could be exposure to soil and water, but also contaminated material in the health care setting or an immunocompromised state. Iatrogenic infections that are secondary to health care tourism are a potential cause of fever in the returned traveler.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".