Faculty Opinions recommendation of Epidemiology of invasive candidiasis: a persistent public health problem.
Bibliographic record
Abstract
Invasive candidiasis (IC) is a leading cause of mycosis-associated mortality in the United States. We examined data from the National Center for Health Statistics and reviewed recent literature in order to update the epidemiology of IC. IC-associated mortality has remained stable, at approximately 0.4 deaths per 100,000 population, since 1997, while mortality associated with invasive aspergillosis has continued to decline. Candida albicans remains the predominant cause of IC, accounting for over half of all cases, but Candida glabrata has emerged as the second most common cause of IC in the United States, and several less common Candida species may be emerging, some of which can exhibit resistance to triazoles and/or amphotericin B. Crude and attributable rates of mortality due to IC remain unacceptably high and unchanged for the past 2 decades. Nonpharmacologic preventive strategies should be emphasized, including hand hygiene; appropriate use, placement, and care of central venous catheters; and prudent use of antimicrobial therapy. Given that delays in appropriate antifungal therapy are associated with increased mortality, improved use of early empirical, preemptive, and prophylactic therapies should also help reduce IC-associated mortality. Several studies have now identified important variables that can be used to predict risk of IC and to help guide preventive strategies such as antifungal prophylaxis and early empirical therapy. However, improved non-culture-based diagnostics are needed to expand the potential for preemptive (or early directed) therapy. Further research to improve diagnostic, preventive, and therapeutic strategies is necessary to reduce the considerable morbidity and mortality associated with IC. PMID: 17223626
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 | 0.003 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.342 | 0.255 |
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".