Prognosis of acute kidney injury requiring renal replacement therapy in solid organ transplanted patients
Bibliographic record
Abstract
Solid organ transplanted patients represent a complex and multi-morbid population with potential acute illness. They are at high risk not only for chronic renal failure (CRF), but also for acute kidney injury (AKI) and little is known about the overall epidemiology or prognosis. We conducted a retrospective review of all solid organ transplant patients who required emergency renal replacement therapy (RRT) for AKI during a period of 7.5 years. We identified 53 episodes of AKI requiring RRT occurring in 51 transplanted patients, and 58.5% of them were freshly (<48 h) transplanted when admitted in ICU. The majority of episodes were a result of cardio-circulatory or septic events (84%), and a large proportion of the AKI episodes were a result of multifactorial causes (27%). Overall 90 days mortality was 49%, and no difference was detected between kidney and nonkidney transplants. On univariate analysis, the risk factors for death were smoking status [OR = 4.09 (CI 95%: 1.16-14.43); P = 0.028] and sepsis [OR = 4.90 (CI 95%: 1.39-17.31); P = 0.014]. Transplanted patients with AKI are younger, more prone to be diabetic and to have previous chronic renal failure compared with the general ICU population, possibly in part because of their immunosuppressive therapy. Nevertheless, they have the same prognosis.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".