Kynurenine and depressive symptoms in a poststroke population
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Depression is a commonly occurring and persistent sequel of stroke affecting approximately 29% of patients. An immunological hypothesis has been put forward, and synthesis of kynurenine from tryptophan has been proposed to link inflammatory activity with neurotoxicity and neurotransmitter dysfunction. This study assessed the relationship between peripheral blood kynurenine and poststroke depressive symptoms. PATIENTS AND METHODS: This was a multisite cross-sectional observational cohort study of patients with ischemic stroke. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression (CES-D) scale and divided into high, medium, and low depressive symptom tertiles. Concentrations of kynurenine and tryptophan were assayed from fasting serum samples, and the kynurenine/tryptophan ratio was compared between tertiles. Serum cytokine concentrations were assayed in a subgroup of patients, and the ratio of proinflammatory (IL-6, IL-18, IFNγ, TNF, IL-1β) to anti-inflammatory (IL-10) cytokines compared. NLM IDENTIFIER: NCT00254020. RESULTS: In these patients (n=86, 52.3% male, mean age 71.7±14.2 years), there were no differences in kynurenine/tryptophan ratios between CES-D scale tertiles (F 2,76=0.04, P=0.96) controlling for relevant covariates. For cytokines (n=53), serum IL-1β concentrations (F 2,52=3.55, P=0.037) and serum ratios of IL-18/IL-10 (F 2,52=3.30, P=0.046), IFNγ/IL-10 (F 2,52=4.02, P=0.025), and IL-1β/IL-10 (F 2,52=4.34, P=0.019) were elevated in the middle CES-D tertile. Post hoc analyses suggested that serum ratios of IL-18/IL-10 (ρ=0.28, P=0.04), and IL-1β/IL-10 (ρ=0.43, P=0.001), as well as IL-1β (ρ=0.29, P=0.04), were significantly associated with fatigue. CONCLUSION: Peripheral kynurenine/tryptophan ratios were not associated with depressive symptoms in a poststroke population. However, in exploratory analyses a proinflammatory bias was identified specifically in patients with mild depressive symptoms and associated with poststroke fatigue, suggesting an avenue for future research.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".