Association between B-cell activating factor and future depressive symptoms in hemodialysis patients
Bibliographic record
Abstract
OBJECTIVE: B-cell activating factor (BAFF) and a proliferation-inducing ligand (APRIL) are cytokines that play critical roles in the maturation, homeostasis, and differentiation of B-cells. Both cytokines have also been associated with mental disorders. The link between inflammation and depression is well-established. Patients undergoing hemodialysis who also experience depressive symptoms exhibit a state of immune dysfunction. We hypothesized that BAFF and APRIL levels would influence future depressive symptoms in hemodialysis patients. METHODS: We enrolled 72 hemodialysis patients without baseline depressive symptoms. Depressive symptoms were assessed annually for 2 years using the Beck Depression Inventory-II. The participants were measured for plasma BAFF, APRIL, and tumor necrosis factor-a levels. To evaluate the impact of these levels on the development of depressive symptoms, we performed Cox regression and Kaplan-Meier analysis. RESULTS: Depressive symptoms were observed in 31 (43.1%) patients. In both univariate and multivariate Cox regression analyses, a 1 SD increase in BAFF was significantly associated with an increased risk of future depressive symptoms, with hazard ratios of 1.44 (95%CI 1.03-2.00) and 1.70 (95%CI 1.04-2.78), respectively. Higher BAFF groups had a significantly greater incidence of depressive symptoms over 2 years (p = 0.048). CONCLUSION: Elevated plasma BAFF levels were significantly associated with the development of depressive symptoms in hemodialysis patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".