Preoperative Urine Alpha 1 Microglobulin Levels Are Associated with AKI and Mortality After Cardiac Surgery
Bibliographic record
Abstract
Background: Higher urine alpha-1 microglobulin (a1m) levels are a marker of proximal tubule dysfunction and may improve CKD assessment and risk stratification. We hypothesized that a1m levels would be associated with adverse outcomes after cardiac surgery. Methods: In 1464 adults undergoing cardiac surgery (CABG and/or valve) and prospectively enrolled in the multicenter TRIBE-AKI study, we measured urine a1m pre-and post-operatively. Outcomes were post-operative AKI during index hospitalization (AKIN stage ≥1) and all-cause mortality (median follow-up (IQR) 6.7 (4.0, 7.9) years). Urine a1m was analyzed as a continuous (log2) predictor in multivariable analyses adjusting for demographics, surgery characteristics, comorbidities, baseline eGFR, urine albumin, and urine creatinine. Results: There were 230 AKI events and 459 deaths. Higher pre-operative a1m was independently associated with AKI (aOR=1.36, 95% CI 1.14-1.62) and all-cause mortality (aHR=1.19, 95% CI 1.06-1.33) (see table). We observed a significant interaction (p=0.01), whereby a1m had a stronger association with mortality in the subset without CHF (aHR=1.29, 95% CI 1.12-1.47) than among those with CHF (aHR=1.06, 95% CI 0.85-1.32). However, post-operative changes in a1m were not associated with AKI or mortality risk. Conclusions: Even after adjusting for baseline kidney function and comorbidities, pre-operative a1m was associated with post-operative AKI and all-cause mortality. Funding: Other NIH Support - NHLBI; study also supported by supported by NIH grant RO1HL085757 (CRP) to fund the TRIBE-AKI Consortium. - AKIa All-cause mortalityb Pre-operative uα1m aOR (95% CI) aHR (95% CI) per doubling 1.36 (1.14, 1.62) 1.19 (1.06, 1.33) Tertile 1 1.00 (reference) 1.00 (reference) Tertile 2 0.64 (0.43, 0.95) 0.93 (0.71, 1.22) Tertile 3 1.17 (0.78, 1.76) 1.40 (1.07, 1.84) aAdjusted for age, sex, race, cardiopulmonary bypass time >120 minutes, nonelective surgery, CABG vs. valve replacement, diabetes, hypertension, congestive heart failure, myocardial infarction, baseline eGFR, urine albumin, urine creatinine, site.bAdjusted for age, sex, race, cardiopulmonary bypass time >120 minutes, nonelective surgery, diabetes, hypertension, congestive heart failure, myocardial infarction, smoking, BMI, AKI/dialysis during index hospitalization, baseline eGFR, urine albumin, urine creatinine, site.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".