MP197EARLY MORTALITY ON CONTINUOUS RENAL REPLACEMENT THERAPY (CRRT): THE PRAIRIE CRRT STUDY
Bibliographic record
Abstract
Introduction and Aims: Patients with acute kidney injury (AKI) requiring Renal Replacement Therapy (RRT) have an increased short-term and long-term risk of mortality. In most North American ICUs, these patients require continuous renal replacement therapy (CRRT). CRRT is resource intensive and the natural history of patients requiring CRRT in the ICU is poorly understood. Methods: We conducted a prospective cohort study of patients undergoing CRRT for AKI in three ICU’s of the Regina Qu’Appelle Health Region (RQHR). We collected data on demographic, laboratory and clinical measures and followed patients from admission to the ICU to 9 months post discharge in the community. Results: Of the 2634 patients admitted to the ICUs in the study period (April 2013 to September 2014), (2201/2634) 83.6% had no AKI. 269 or 10.2% had stage III AKI. 106/269 (40%) were started on CRRT. Of those on CRRT, 66/106 died in ICU whilst on CRRT. 17/66 (26%) died within 24 hours of initiating therapy. Patients who died within 24 hours had a higher FiO2 (0.8 ± 0.2 vs. 0.6 ±0.2, p: 0.011); higher epinephrine (32.0 ± 29.9 vs. 6.5 ± 9.3, p: 0.005); higher norepinephrine levels (39.4 ± 23.5 vs. 19.6 ± 14.2, p:0. 005); lower pH (7.1 ± 0.2 vs. 7.3 ± 0.1, p: 0.005) when compared to those who survived the first 24 hours of admission.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".