Albuminuria post–liver transplant is a predictor of kidney disease progression and mortality
Bibliographic record
Abstract
BACKGROUND: Albuminuria is a marker of chronic kidney disease (CKD) associated with an increased risk of end-stage kidney disease (ESKD) and mortality in the general population, but it is uncertain whether the same association exists in liver transplant (LT) recipients. This study examined the association between albuminuria and kidney failure and mortality in LT recipients. METHODS: Retrospective cohort study of 294 adults who received a LT between January 1, 1989, and December 31, 2011, in British Columbia, Canada. Cox multivariable regression was used to determine the association between ACR and a primary combined outcome of mortality, doubling of serum creatinine, or ESKD; and a secondary outcome of a decrease in estimated glomerular filtration rate (eGFR) ≥30%. RESULTS: At baseline, mean eGFR was 67 (SD 20.9) mL/min/1.73 m 2 , and 10% had severe albuminuria (ACR >30 mg/mmol). The primary outcome occurred in 20.4% (60) of patients and was associated with ACR >30 mg/mmol (HR 2.77, 95% CI 1.28–6.04; P = 0.01). A decline in eGFR ≥30% occurred in 21.8% (64) of patients, and was associated with ACR >30 mg/mmol (HR 4.77, 95% CI 2.31–9.86; P < 0.0001). CONCLUSIONS: Severe albuminuria (ACR >30 mg/mmol) was associated with an increased risk of loss of kidney function and mortality after LT. Prospective studies are needed to determine if specific interventions directed at reducing albuminuria can improve long-term outcomes in LT recipients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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 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".