Clinical, epidemiological, and mycological features of patients with candidemia: Experience in two tertiary referral centers in Iran
Bibliographic record
Abstract
Background and Purpose: Candidemia is a major cause of morbidity and mortality among patients receiving immunosuppressive therapy and those hospitalized with serious underlying diseases. Here, we investigated the epidemiological, clinical, and mycological features of candidemia in Tehran, Iran. Materials and Methods: A prospective observational study of all patients diagnosed with candidemia was performed at two referral teaching hospitals in Tehran, Iran, from February to December 2018. Demographic characteristics, underlying diseases, risk factors, clinical symptoms, and laboratory analyses of candidemic patients with positive culture were mined. Candida isolates were molecularly identified by sequencing of the internal transcribed spacer region (ITS1-5.8S-ITS2). The antifungal susceptibility testing for fluconazole, itraconazole, voriconazole, posaconazole, amphotericin B, caspofungin, micafungin, and anidulafunginagainst the isolates was performed using CLSI broth microdilution reference method (M27-A3). Results: A total of 89 episodes were identified, with an incidence of 2.1 episodes/1000 admissions. The common underling disease were malignancy (46%), renal failure/dialysis (44%), and hypertension (40%). The overall crude mortality was 47%. C. albicans (44%) was the most frequent causative agent, followed by C. glabrata (21%), C. parapsilosis complex (15%), C. tropicalis (11%), and C. lusitaniae (3.5%). All the isolates were susceptible to amphotericin B. The activity of all four azoles was low against non-albicans Candida species, especially C. tropicalis. Conclusion: The increase in non-albicans Candida species with reduced susceptibility to antifungal drugs might be alarming in high-risk patients. Therefore, accurate knowledge of predisposing factors and epidemiological patterns in candidemia are effective steps for managing and decreasing the mortality rate in candidemia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".