Increased urinary excretion of kynurenic acid is associated with non-recovery from acute kidney injury in critically ill patients
Bibliographic record
Abstract
BACKGROUND: Acute kidney injury (AKI) is often observed in critically ill patients and is associated with high morbidity and mortality. Non-recovery from AKI has a negative impact on the prognosis of affected patients and early risk stratification seems key to improve clinical outcomes. We analyzed metabolites of a conserved key inflammatory pathway (i.e. tryptophan degradation pathway) in serial urine samples of patients with AKI. METHODS: One hundred twelve ICU patients with AKI were included in a prospective observational analysis. After exclusion criteria, 92 patients were eligible for analysis. Serial urine samples were collected and tryptophan levels including key tryptophan metabolites were measured using tandem mass spectrometry. RESULTS: Sixty-seven patients recovered in the first 7 days of AKI (early recovery, ER) whereas n = 25 had late-/non-recovery (LNR). Urinary concentrations of tryptophan, kynurenine, 3-OH anthranillic acid, serotonine, and kynurenine/tryptophan were significantly lower in LNR patients. In contrast, creatinine normalized excretion of kynurenic acid (KynA) was substantially increased in LNR patients (7.59 ± 6.81 vs. 3.19 ± 3.44 (ER) μmol/mmol, p < 0.005). High urinary KynA excretion was associated with higher RIFLE class, longer AKI duration, increased need for RRT, and 30-day mortality. Logistic regression revealed KynA as the single most important predictor of renal recovery on days 1 and 2 of AKI. CONCLUSIONS: Increased urinary levels of kynurenic acid, a key inflammatory metabolite of the tryprophan degradation pathway, are associated with adverse renal and clinical outcomes in critically ill patients with AKI. Urinary KynA may serve as an early risk stratificator in respective patients with AKI.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".