Estudio de la infección "Clostridium difficile": incidencia, epidemiología, características clínicas, factores de riesgo de gravedad y recurrencia
Bibliographic record
Abstract
Clostridium difficile causes a broad range of diseases in humans, from mild colitis to pseudomembranous colitis and disease refractory to treatment, fulminant and fatal. It is an infection whose frequency, seriousness and related morbidity and mortality have increased in recent years [1-4]. Nowadays it is regarded as an emerging public health problem, and prevention and monitoring are particularly recommended. In recent years, different authors have described a change in its epidemiology, which affects not only the populations traditionally involved, but also children and patients from the community [2, 5]. Moreover, the Spanish situation has proven to be different, in terms of the ribotypes present, to other countries in Europe, Canada and the USA. Thus, the performance of an in-depth study in this type of patients in Spain, as well as the source of the acquisition of Clostridium difficile infection (CDI), is of major relevance. The main predisposing factor to acquiring CDI is the use of antibiotics in the previous 8 weeks (90% cases in some series), even with a single prophylactic dose. Other risk factors are a previous stay in health-care centers, particularly hospitals, being old and immunodepression, including transplantations and HIV [6]. The severity of CDI has been associated both with host factors and microorganism-specific factors...
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".