Prognostic Significance of Severe Vitamin D Deficiency in Patients with Primary Sclerosing Cholangitis
Bibliographic record
Abstract
Vitamin D deficiency has been linked with adverse events in various liver diseases. The present study aimed to recognize the association between severe vitamin D deficiency and disease progression, hepatobiliary malignancies, liver-related mortality, and the need for liver transplantation in primary sclerosing cholangitis (PSC). Patients with a diagnosis of PSC (n = 354), followed by the autoimmune liver disease clinic at the University of Alberta, were included. Patients with vitamin D levels < 25 nmol/L were defined as severely deficient. Univariate and multivariate analyses were conducted using the Cox proportional hazards regression models. The mean vitamin D level was 59 ± 2 nmol/L, and 63 patients (18%) had a severe vitamin D deficiency. Patients with a severe vitamin D deficiency were 2.5 times more likely to experience hepatobiliary malignancies (HR 2.55, 95% CI, 1.02–6.40, p = 0.046). A severe vitamin D deficiency at diagnosis (HR 1.82, 95% CI, 1.05–3.15, p = 0.03) and persistent deficiencies over time (HR 2.26, 95% CI, 1.17–4.37, p = 0.02) were independently associated with a higher risk of poor clinical liver outcomes. A severe vitamin D deficiency at diagnosis and persistent deficiency at longitudinal assessments were associated with liver-related mortality or the need for liver transplantation.
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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 | 0.000 | 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 | 0.000 | 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".