Benefit of continuous renal replacement therapy in subgroups of acutely ill patients: a retrospective analysis
Bibliographic record
Abstract
AIMS: Acute renal failure in the intensive care setting is common and impacts on patient's outcome. Continuous hemodialysis or hemofiltration offers theoretical benefit for patients with acute renal failure, but the clinical benefit has not been demonstrated in randomized trials. ICU patients with acute renal failure are a heterogeneous population and we hypothesize that patients with increased illness severity would benefit from continuous renal replacement therapy. METHODS: From a comprehensive ICU database, we identified patients with acute renal failure exposed to continuous or intermittent renal replacement therapy. We a priori identified a subgroup of patients with multiple organ dysfunction syndrome, then used survival analysis to assess the effect of dialysis modality in the overall acute renal failure population and in the subgroup with increased illness severity. RESULTS: We identified 66 patients treated with intermittent and 36 patients treated with continuous renal replacement therapy. Patients with severe illness were preferentially selected for treatment with continuous dialysis (p = 0.01). Overall, there was no significant difference in survival between patients treated with intermittent or continuous dialysis. The relative risk of in-hospital mortality was significantly decreased in patients with multiple organ dysfunction syndrome (relative risk = 0.42+/-0.22, p = 0.027) treated with continuous therapy as compared with intermittent therapy. Among the survivors, continuous dialysis did not appear to hasten the return of renal function. CONCLUSIONS: This retrospective study suggests that continuous dialysis may be beneficial in a subgroup of ICU patients with multiple organ dysfunction syndrome or severe sepsis. Further randomized trials of dialysis modality should, if possible, concentrate on this population.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".