Assessing the Outcome of Adult Kidney Transplantation from a Deceased Expanded Criteria Donor: A Descriptive Study
Bibliographic record
Abstract
Background End-stage renal disease (ESRD) creates a great burden on the quality of life. Patients after kidney transplantation have been reported to have a greater quality of life and better outcomes health outcomes. Therefore, it is important to optimize the best method of following well-constructed criteria such as the expanded criteria donor (ECD) to reduce the chances of rejection rate and deaths post-transplantation particularly in elderly patients in conjunction with the kidney profile donor index (KDPI). Methods This is a retrospective descriptive study of all patients who received kidney transplantation from a deceased donor from the ECD as well as ECD with donation after cardiac death (DCD) at St. Joseph Health Care Hospital over a 24 month time period from January 2017 to January 2019. All adult recipients from standard criteria donor (SCD) and living donors were excluded from the study. Results The study included 60 patients with 36 (60%) from the ECD and 24 (40%) were from the ECD/DCD group. The most common cause of ESRD among recipients was diabetes mellitus (DM) involving 23 (38.3%) of the patients. The creatinine outcome was the highest in the ECD/DCD group at one month (211 ± 71) and the lowest creatinine recorded was also in the ECD/DCD at 12 months (160 ± 78). Lastly, only four patients died in 12 months and only six recipients reported graft loss over 12 months. Conclusion Descriptive data of the included ECD/DCD showed increase trend in survivability of the recipients when used among the elderly, giving us more insight on the benefits of ECD/DCD transplantation.
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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 | 0.002 |
| 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".