The high incidence of severe chronic kidney disease after intestinal transplantation and its impact on patient and graft survival
Bibliographic record
Abstract
Introduction Using data from the Scientific Registry of Transplant Recipients (SRTR), cumulative incidence, risk factors for, and impact on survival of severe chronic kidney disease (CKD) in intestinal transplantation (ITx) recipients were assessed. Methods First-time adult ITx recipients transplanted in the United States between January 1, 1990 and December 31, 2012 were included. Severe CKD after ITx was defined as: glomerular filtration rate (GFR) <30 mL/min/1.73 m2, chronic hemodialysis initiation, or kidney transplantation (KTx). Survival analysis and extended Cox model were conducted. Results The cumulative incidence of severe CKD 1, 5, and 10 years after ITx was 3.2%, 25.1%, and 54.1%, respectively. The following characteristics were significantly associated with severe CKD: female gender (HR 1.34), older age (HR 1.38/10 year increment), catheter-related sepsis (HR 1.58), steroid maintenance immunosuppression (HR 1.50), graft failure (HR 1.76), ACR (HR 1.64), prolonged requirement for IV fluids (HR 2.12) or TPN (HR 1.94), and diabetes (HR 1.54). Individuals with higher GFR at the time of ITx (HR 0.92 for each 10 mL/min/1.73 m2 increment), and those receiving induction therapies (HR 0.47) or tacrolimus (HR 0.52) showed lower hazards of severe CKD. In adjusted analysis, severe CKD was associated with a significantly higher hazard of death (HR 6.20). Conclusions The incidence of CKD after ITx is extremely high and its development drastically limits post-transplant survival.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".