Long-term renal function after burn-related acute kidney injury with continuous renal replacement therapy
Bibliographic record
Abstract
Acute kidney injury (AKI) is a common complication of severe burn injury and is associated with significant morbidity and mortality. Continuous Renal Replacement Therapy (CRRT) is the preferred treatment for stage 3 AKI due to severe burn. This retrospective cohort study at a single institution aimed to examine the long-term renal outcomes after discharge of burn survivors who underwent CRRT during their ICU stay between 2012-2021 due to burn-related AKI, hypothesizing a return to baseline renal function in the long term. Among the 31 patients meeting inclusion criteria, 22 survived their burn injuries, resulting in a 29 % mortality rate. No significant disparities were observed in demographics, comorbidities, burn characteristics, or critical care interventions between survivors and non-survivors. Serum creatinine and eGFR values normalized for 91 % of patients at discharge. Impressively, 91 % of survivors demonstrated a return to baseline renal function during long-term (>3 years) follow-up. Furthermore, only 18 % underwent dialysis after discharge, primarily within the first year. Cumulative mortality rates were 18.2 %, 22.7 %, and 31.8 % at 1, 3, and > 3 years after discharge, respectively. Causes of death were primarily non-renal. These results suggest that burn-related AKI with CRRT results in lower rates of conversion to ongoing renal dysfunction compared to general ICU cohorts. Despite limitations, this study contributes vital insights into the underexplored issue of long-term outcomes after dicharge in this patient 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".