Infection Prevention and Control Guideline for Cystic Fibrosis: 2013 Update
Bibliographic record
Abstract
The 2013 Infection Prevention and Control (IP&C) Guideline for Cystic Fibrosis (CF) was commissioned by the CF Foundation as an update of the 2003 Infection Control Guideline for CF. During the past decade, new knowledge and new challenges provided the following rationale to develop updated IP&C strategies for this unique population: 1. The need to integrate relevant recommendations from evidence-based guidelines published since 2003 into IP&C practices for CF . These included guidelines from the Centers for Disease Control and Prevention (CDC)/Healthcare Infection Control Practices Advisory Committee (HICPAC), the World Health Organization (WHO), and key professional societies, including the Infectious Diseases Society of America (IDSA) and the Society for Healthcare Epidemiology of America (SHEA). During the past decade, new evidence has led to a renewed emphasis on source containment of potential pathogens and the role played by the contaminated healthcare environment in the transmission of infectious agents. Furthermore, an increased understanding of the importance of the application of implementation science, monitoring adherence, and feedback principles has been shown to increase the effectiveness of IP&C guideline recommendations. 2. Experience with emerging pathogens in the non-CF population has expanded our understanding of droplet transmission of respiratory pathogens and can inform IP&C strategies for CF . These pathogens include severe acute respiratory syndrome coronavirus and the 2009 influenza A H1N1. Lessons learned about preventing transmission of methicillin-resistant Staphylococcus aureus (MRSA) and multidrug-resistant gram-negative pathogens in non-CF patient populations also can inform IP&C strategies for CF.
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 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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 0.012 |
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".