Serum Galactomannan: A Predictor of Poor Outcomes in Peritoneal Dialysis Patients With Fungal Peritonitis
Bibliographic record
Abstract
Introduction: The potential value of serum galactomannan index (GMI) in monitoring treatment response in patients with fungal peritonitis who are receiving peritoneal dialysis (PD) was assessed in the present study. Methods: The study included all Thailand fungal PD-related infectious complications surveillance (MycoPDICS) DATA study participants who had timely PD catheter removal and availability of both baseline and ≥2 subsequent serum GMI measurements after starting antifungal therapy (if available). Serum GMI was assessed by direct double-sandwich enzyme-linked immunosorbent assay with reference to positive and negative control samples. Comparisons of categorical variables among groups were analyzed by Fisher's exact test for categorical data and the Wilcoxon rank-sum test for continuous variables. Mortality outcomes were analyzed by survival analyses using Kaplan-Meier curves with Log-rank test. Results: Seventy-six (46%) of 166 participants from 21 PD centers between 2018 and 2022 were included. The median age was 58 (50-65) years, and a half of the patients (50%) had type II diabetes. Nineteen (25%) and 57 (75%) episodes were caused by yeast and mold, respectively. Death occurred in 11 (14%) patients at 3 months, and no differences were observed in demographics, laboratories, treatment characteristics, or in baseline serum GMI between those who died and those who survived. Serum GMI progressively declined over the follow-up period after the completion of treatment. Patients who died had significantly higher posttreatment serum GMI levels and were more likely to have positive GMI after treatment. Conclusion: Serum GMI is an excellent biomarker for risk stratification and treatment response monitoring in patients on PD with fungal peritonitis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".