Selection and Receipt of Kidney Replacement in Critically Ill Older Patients with AKI
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Older patients in the intensive care unit are at greater risk of AKI; however, use of kidney replacement therapy in this population is poorly characterized. We describe the triggers and outcomes associated with kidney replacement therapy in older patients with AKI in the intensive care unit. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Our study was a prospective cohort study in 16 Canadian hospitals from September 2013 to November 2015. Patients were ≥65 years old, were critically ill, and had severe AKI; exclusion criteria were urgent kidney replacement therapy for a toxin and ESKD. We recorded triggers for kidney replacement therapy (primary exposure), reasons for not receiving kidney replacement therapy, 90-day mortality (primary outcome), and kidney recovery. RESULTS: =66). Ninety-day mortality was similar in patients who did and did not receive kidney replacement therapy (50% versus 51%; adjusted hazard ratio, 0.78; 95% confidence interval, 0.58 to 1.06); however, decisions to offer kidney replacement therapy varied significantly by patient mix, acuity, and perceived benefit. There were no differences in health-related quality of life or rehospitalization among survivors. CONCLUSIONS: Most older, critically ill patients with severe AKI were perceived as candidates for kidney replacement therapy, and approximately one half received therapy. Both willingness to offer kidney replacement therapy and reasons for not starting showed heterogeneity due to a range in patient-specific factors and clinician perceptions of benefit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".