Outcome among patients with acute renal failure needing continuous renal replacement therapy: A single center study
Bibliographic record
Abstract
Outcome of acute renal failure (ARF) and use of continuous renal replacement therapy (CRRT) have shown a consistently high mortality. (1) Evaluate the short-term patient survival. (2) Evaluate dialysis-free survival. (3) Evaluate risk factors associated with overall survival and the continued need for intermittent dialysis. We identified adults (>/=18 years) needing CRRT, treated in the critical care units of Froedtert Medical and Lutheran Hospital from January 1, 2003 till December 31, 2005. Patients were divided into two major groups needing CRRT, end stage renal disease (ESRD) (chronic dialysis) and non-ESRD with ARF. Continuous renal replacement therapy was performed with an average of 2 L replacement fluid exchanges/h. Sigma stat software was used for analysis. Comparison was done for noncontinuous variables by chi-square and t test for categorical and continuous variables, respectively. A total of 110 (ESRD 24/non-ESRD 86) patients received CRRT during study period. Over all in-hospital mortality among non-ESRD patients was 63% vs. 46% for ESRD. Among non-ESRD patients who survived, 47% needed intermittent hemodialysis on intensive care unit discharge and 28% continued to need hemodialysis at last follow-up. Among non-ESRD patients alive at discharge, those who were dialysis dependent on last follow-up were older (64.5) than those who did not require dialysis on last follow-up (58.4) P=0.347. Non-ESRD patients who died were in the hospital for an average of 17.5 days compared with 29 days for those who were discharged from the hospital. Patients with ARF needing CRRT have high in-hospital mortality. A significant percentage of patients remained dialysis dependant on last follow-up.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".