Association of Age, Frailty, and Strategy for Initiation of Kidney Replacement Therapy: A Post Hoc Analysis of the STARRT-AKI Trial
Bibliographic record
Abstract
Background: Acute kidney injury (AKI) is a significant public health issue, and its incidence continues to rise. Older age is associated with a high risk of AKI and mortality, which often poses a clinical dilemma particularly with the implementation of invasive management such as renal-replacement therapy (RRT). The aim of this study is to assess the association of age and frailty with clinical outcomes in patients with severe AKI, according to accelerated and standard RRT initiation strategies in the STARRT-AKI trial. Methods: This was a secondary analysis of an international randomized trial. Older age was defined as ≥65 years. Frailty was assessed using the clinical frailty scale (CFS) score and defined as a score ≥5. The primary outcome was all-cause mortality at 90 days. Secondary outcomes included RRT dependence and RRT-free days at 90 days. We used logistic and linear regression and interaction testing to explore the impact of age and frailty on clinical outcomes. Results: Of 2927 patients randomized in the STARRT-AKI trial, 1616 (55.2%) were aged ≥ 65 years (median [IQR] 73.9 [69.4 - 78.9]). Older patients had greater comorbid cardiovascular and chronic kidney disease, were more likely to be surgical admissions and to receive vasopressors at baseline. Older patients had higher 90-day mortality (50.4% vs. 35.6%, adjusted-OR, 1.81 [1.53 to 2.13], p<0.001). There was no significant difference in RRT dependence at 90 days between older and younger patients (8.7% vs. 7.8%, adjusted-OR, 1.21 [0.82 to 1.79], p=0.325). Patients with frailty had higher mortality; but no difference in RRT dependence at 90-days. There was no significant interaction between age and CFS score in relation to mortality, RRT dependence at 90 days, and other secondary outcomes. There was no significant difference in the proportion of patients who received RRT in the standard-strategy stratified by age groups (adjusted-OR, 0.85 [0.67 to 1.08], p=0.180). Conclusion: In this secondary analysis of the STARRT-AKI trial, older and frail patients had higher mortality at 90 days; however, there was no difference in RRT dependence. Mortality and RRT dependence were not modified by RRT initiation strategy in older or frail patients.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".