Urinary NGAL levels before and after coronary angiography: a complex story
Bibliographic record
Abstract
BACKGROUND: We describe urinary neutrophil gelatinase-associated lipocalin (uNGAL) values in association with clinical characteristics and urinary parameters in adults undergoing coronary angiography. METHODS: This is an observational study of consecutive patients who underwent elective coronary angiography during a 4-month period in a large urban tertiary care hospital. RESULTS: One hundred and thirteen patients were enrolled, and 100 had sufficient data to be included in the analyses. A large range of preprocedural uNGAL levels were observed (range 1-269 ng/mg Cr). Median preprocedural uNGAL was 8 ng/mg Cr. Age (P = 0.009), serum creatinine (P = 0.077) and albumin excretion (P = 0.009) were significant predictors of baseline uNGAL. Half the cohort demonstrated an increase and half a decrease in the absolute values of uNGAL after angiography, irrespective of preprocedural levels. CONCLUSIONS: We observed variable, but relatively low absolute levels of uNGAL prior to angiography in this 'cardiac' cohort. Only age, serum creatinine and albumin excretion could explain some of this variability. When designing studies of at-risk individuals where uNGAL may be used as a marker for acute kidney injury, this variability should be taken into account.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".