FO068KIDNEY FAILURE AFTER AKI AMONG PEOPLE UNDER NEPHROLOGY CLINIC CARE: A PROVINCEWIDE COHORT STUDY
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Poor outcomes after acute kidney injury (AKI) have been well described for hospital cohorts, but not for those already receiving nephrology clinic care. Nevertheless, this is where discussions about future kidney failure risk commonly occur. We assessed whether AKI was independently associated with kidney failure and death (competing risk) in this setting. We then evaluated the widely used five year Kidney Failure Risk Equation (KFRE5yr), and developed refitted models with and without AKI as an additional predictor. METHODS: The study involved people receiving nephrology clinic care in British Columbia 2003-2009 (population 4.5 million), followed to 2016. Predictors were KDIGO AKI during the previous two years, age, sex, proteinuria, eGFR and renal diagnosis. Cox models estimated cause-specific hazard ratios (HR) (AKI vs no AKI) for kidney failure and death, stratified by eGFR (</≥30 ml/min/1.73m2). The published KFRE5yr was compared with refitted prediction models without and with AKI. A KFRE5yr risk threshold ≥3% has been suggested to triage entry into nephrology clinics. We used decision curve analysis to evaluate this threshold among people in clinics with eGFR ≥30. RESULTS: Of 7491 people, 995 had AKI and 6496 had no AKI in the previous two years. Those with AKI had increased subsequent kidney failure (33.1% vs 26.3%) but also increased death (23.8% vs 16.8%) (p-values <0.001), irrespective of age (figure 1), eGFR and renal diagnosis. After adjusting for confounders, AKI was still associated with kidney failure for those with eGFR ≥30 (HR 1.43 [1.13-1.81]), but no longer for those with eGFR <30 (HR 1.05 [0.91-1.21]) (table). For those with eGFR ≥30, KFRE5yr gave inferior predictions of 5 year kidney failure risk than refitted models without or with AKI (respective C statistics 0.701, 0.715 and 0.716). Using decision curve analysis, KFRE5yr at any risk threshold <10% was inferior to “treating all” patients in the clinic (figure 2). Refitted models were superior but AKI made no difference. CONCLUSIONS: AKI is associated with increased kidney failure among people under nephrology clinic care, but does not incrementally improve risk predictions because of a substantial competing risk of death. While KFRE5yr may help triage referrals to nephrology clinics, for people already in clinic with eGFR ≥30, it may not help guide safe discharge from follow-up. FO068 Table Independent association of AKI with subsequent kidney failure and death (cause-specific Cox models)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".