Prediction of Fungal Infection Development and Their Impact on Survival Using the NACSELD Cohort
Bibliographic record
Abstract
OBJECTIVES: Bacterial infections are associated with negative outcomes in cirrhosis but fungal infections are being increasingly recognized. The objective of this study is to define risk factors for fungal infection development and impact on 30-day survival. METHODS: In a large, multi-center cirrhotic inpatient cohort, demographics, cirrhosis details, intensive care unit (ICU), organ failures/acute-on-chronic liver failure (ACLF), and 30-day survival were compared between patients without infections and with bacterial infections alone, with those with fungal infections. Variables associated with fungal infection development were determined using multi-variable regression. Ordinal variables (0=no infection, 1=community-acquired bacterial infection, 2=nosocomial bacterial, and 3=fungal infection) were input into a 30-day survival model. RESULTS: A total of 2,743 patients (1,691 no infection, 918 bacterial, and 134 fungal infections) were included. Patients with fungal infection, all of which were nosocomial, were more likely to be admitted with bacterial infections, on spontaneous bacterial peritonitis prophylaxis, and have diabetes and advanced cirrhosis. Bacterial infection types did not predict risk for fungal infections. Multi-variable analysis showed male gender to be protective, whereas diabetes, longer stay, ICU admission, acute kidney injury (AKI), and admission bacterial infection were associated with fungal infection development (area under the curve (AUC)=0.82). Fungal infections were associated with significantly higher ACLF, inpatient stay, ICU admission, and worse 30-day survival. The case fatality rate was 30% with most fungal infections but >50% for fungemia and fungal peritonitis. On a multi-variable analysis, age, AKI, model for end-stage liver disease, ICU admission, and ordinal infection variables impaired survival (P<0.0001, AUC=0.83). CONCLUSIONS: Fungal infections are associated with a poor 30-day survival in hospitalized cirrhotic patients compared with uninfected patients, and those with bacterial infections. Patients with diabetes, AKI, and those with an admission bacterial infection form a high-risk subgroup.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".