Efficacy of micafungin in invasive candidiasis caused by common <i>Candida</i> species with special emphasis on non‐<i>albicans Candida</i> species
Bibliographic record
Abstract
The incidence of invasive candidiasis caused by non-albicans Candida (NAC) spp. is increasing. The aim of this analysis was to evaluate the efficacy of micafungin, caspofungin and liposomal amphotericin B in patients with invasive candidiasis and candidaemia caused by different Candida spp. This post hoc analysis used data obtained from two randomised phase III trials was conducted to evaluate the efficacy and safety of micafungin vs. caspofungin and micafungin vs. liposomal amphotericin B. Treatment success, clinical response, mycological response and mortality were evaluated in patients infected with C. albicans and NAC spp. Treatment success rates in patients with either C. albicans or NAC infections were similar. Outcomes were similar for micafungin, caspofungin and liposomal amphotericin B. Candida albicans was the most prevalent pathogen recovered (41.0%), followed by C. tropicalis (17.9%), C. parapsilosis (14.4%), C. glabrata (10.4%), multiple Candida spp. (7.3%) and C. krusei (3.2%). Age, primary diagnosis (i.e. candidaemia or invasive candidiasis), previous corticosteroid therapy and Acute Physiology and Chronic Health Evaluation II score were identified as potential predictors of treatment success and mortality. Micafungin, caspofungin and liposomal amphotericin B exhibit favourable treatment response rates that are comparable for patients infected with different Candida spp.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".