Renal recovery following acute kidney injury
Bibliographic record
Abstract
PURPOSE OF REVIEW: Renal recovery after acute kidney injury (AKI) is an important outcome, most commonly defined as dialysis independence at hospital discharge. This review focuses on the epidemiology of renal recovery after AKI and provides a framework for determining the relationship of a lack of renal recovery and subsequent outcomes including the development of chronic kidney disease. RECENT FINDINGS: The majority of studies addressing renal recovery includes only critically ill patients requiring dialysis and considers renal recovery as dialysis independency at hospital discharge. However, a significant proportion of AKI patients are not in the ICU, are not dialyzed, and may require alternate definitions for assessing renal recovery. There is emerging evidence that an AKI episode can lead to chronic kidney disease and can accelerate the progression to end stage renal disease. Patients that survive after AKI present a higher long-term mortality risk, especially those with partial renal recovery. SUMMARY: Patients with incomplete renal recovery after AKI are underrepresented in most epidemiologic studies and the precise effect on the incidence and prevalence of end stage renal disease population has yet to be determined. A standardized definition for renal recovery is needed and the influence of an AKI episode on long-term outcomes needs to be better evaluated.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".