Endocarditis protésica por Propionibacterium acnes
Bibliographic record
Abstract
Se presenta el caso de un varón de 76 años con endocarditis precoz sobre una bioprótesis aórtica por Propionibacterium acnes. El diagnóstico se estableció con base en el cuadro clínico de fiebre y escalofríos, los hallazgos ecocardiográficos de vegetaciones y absceso periprotésico y el hemocultivo positivo. El paciente fue reintervenido, resecando la bioprótesis y administrando antibióticos durante seis semanas. La evolución postoperatoria fue satisfactoria. Nueve años después de la intervención, el sujeto se encuentra asintomático y sin signos de recidiva. Se comentan algunos aspectos relacionados con la patogenia, el diagnóstico y el tratamiento de esta enfermedad. We report the case of a 76-year-old male patient who presented with early prosthetic aortic valve endocarditis due to Propionibacterium acnes. Diagnosis was established based on clinical picture of high temperature and positive blood cultures associated with echocardiographic findings of prosthetic valve vegetations and perivalvular abscess. Patient underwent redo sternotomy and re-replacement of the aortic valve bioprosthesis. He received a full course of antibiotics for six weeks and his postoperative course was uneventful. After follow-up for nine years, the patient has remained asymptomatic without any signs of recurrence. Some aspects related to the pathogenesis, diagnosis and treatment of this condition are discussed.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".