Delay in Renal Replacement Therapy Initiation in Critically Ill Patients With AKI: A Secondary Analysis of the STARRT-AKI Trial
Bibliographic record
Abstract
Background: The STARRT-AKI trial demonstrated that earlier initiation of renal-replacement therapy (RRT) does not lead to improved outcomes as compared to a strategy of watchful waiting until a conventional indication arises. However, in patients with persistent acute kidney injury (AKI), the safety of prolonged delay in RRT initiation is unclear. We hypothesized that protracted delays in RRT initiation would be associated with excess mortality. Our objective was to determine the association between relative delay to RRT initiation and outcomes among patients randomized to the standard-strategy in STARRT-AKI. Methods: We conducted a post-hoc secondary analysis of the standard-strategy group in STARRT-AKI. The exposure was time from randomization to RRT initiation, in quartiles. The primary outcome was all-cause mortality at 90 days after randomization. The association between time to RRT initiation and the outcomes were described as adjusted odds ratios (aOR) or adjusted mean differences (aMD), as appropriate. Results: There were 1462 patients in the standard-strategy group, of whom 903 (62%) received RRT. Median time (IQR) to RRT initiation was 12.1 (8.3-13.8), 24.5 (21.8-26.5), 46.8 (35.2-52.1), and 96.1 (76.7-139.2) hours across quartiles 1 through 4, respectively. Compared to patients in quartile 1, longer delay to RRT initiation was associated with lower 90-day mortality in quartiles 3 and 4 (aOR [95% CI] 0.52 [0.35-0.77] and 0.63 [0.42-0.94], respectively). There were no significant differences in RRT dependence, number of RRT-free or hospitalization-free days at 90 days. Patients in quartile 4 had longer durations of ICU and hospital stay (aMD [95% CI] 8.26 [5.77-10.74] and 12.42 [7.59-17.25] days, respectively), relative to quartile 1. Conclusions: Among patients with persistent AKI, delay in RRT initiation was not associated with excess mortality, however, was associated with longer durations of ICU and hospital stay. Funding: Government Support - Non-U.S.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".