Intra-abdominal <i>Candida</i> spp infection in acute abdomen in a quality assurance (QA)-certified academic setting
Bibliographic record
Abstract
Aims To evaluate the contribution of light microscopy to detecting Candida spp infection in patients with complicated intra-abdominal infections (IAIs) admitted for acute abdomen to a quality assurance (QA)-certified surgical emergency ward. Methods We conducted a retrospective study (2008–2012) of 809 abdominal intraoperative or biopsy tissue specimens obtained from patients admitted with acute abdomen and microbiological samples positive for Candida spp. Demographic data, mortality, comorbidities, specimen type, microscopy results, special histological staining performed, antimicrobial therapy were collected and analysed. Any comments at the multidisciplinary team meeting was recorded in minutes of and approved. Results Sixty-six patients with complicated IAIs due to Candida spp were identified (39 male, 27 female, mean±SD age 75±20 years). Candida albicans was isolated in 35 cases and Candida non-albicans spp in 31 cases. Candida spp were isolated from blood in 50% of all selected microbiological specimens. Patients were stratified according to Candida spp (albicans vs non-albicans) , underlying cancer disease and no previous antimicrobial administration, and a positive correlation with C. albicans isolation was found (p=0.009 and p=0.048, respectively). Out of 41 cases with microscopic evaluation, we identified yeast forms, pseudohyphae or both, indicative of Candida spp, in 23. Identification of Candida spp in histological specimens was higher in C. albicans cases than in C. non-albicans cases (73% vs 37.5%). Microscopy allowed prompt treatment of all patients. Conclusions Light microscopy still has great diagnostic significance, being a solid QA step. It provides rapid information and clues in patients who may harbour impaired defence mechanisms, concurrent chronic conditions and/or cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".