Predictors of post‐hospitalization recovery of renal function among patients with acute kidney injury requiring dialysis
Bibliographic record
Abstract
INTRODUCTION: Acute kidney injury (AKI) requiring dialysis complicates 1% of all hospital admissions, and up to 30% of survivors will still require dialysis at hospital discharge. There is a paucity of data to describe the postdischarge outcomes or to guide evidence-based dialysis management of this vulnerable population. METHODS: Single-center, retrospective analysis of 100 consecutive patients with AKI who survived to hospital discharge and required outpatient dialysis. Data collection included baseline characteristics, hospitalization characteristics, and outpatient dialysis treatment variables. Primary outcome was dialysis independence 90 days after discharge. FINDINGS: Overall, 43% of patients recovered adequate renal function to discontinue dialysis, with the majority recovering within 30 days post discharge. Worse baseline renal function was associated with lower likelihood of renal recovery. In the first week postdischarge, patients with subsequent nonrecovery of renal function had greater net fluid removal (5.3 vs. 4.1 L, P = 0.037), higher ultrafiltration rates (6.0 vs. 4.7 mL/kg/h, P = 0.041) and more frequent intradialytic hypotension (24.6% vs. 9.3% with 3 or more episodes, P = 0.049) compared to patients that later recovered. DISCUSSION: A significant proportion of AKI survivors will recover renal function following discharge. Outpatient intradialytic factors may influence subsequent renal function recovery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".