Nepalese Kidney Transplant Recipient in a Follow up Clinic: Related and Unrelated Living Donor
Bibliographic record
Abstract
A cohort retrospective study was conducted on all follow up kidney transplant recipients at Transplant Follow up Clinic from June 16, 2003 to July 15, 2008. The main objective of this study was to find out the demographic pattern of the kidney transplant recipients and type of donors. Among 452 recipients, the transplantation were done in India (449), Germany (2) and in the USA (1) with male to female ratio of 3:1. Kidney donors were unrelated 315 (69.69%), related 134 (29.43%) and some did not disclose 4 (0.88%). Most of the kidney transplantation (93.75%) were done in 45 different hospitals in India and about three quarters (71.7%) of them were operated in the private hospitals in various states of India; only 2 (4.16%) in Germany and 1 (2.08%) in USA. Newar was the largest population 142 (31.4%) and second largest group was Mangol 124 (27.4.4%) that comprised of Gurung, Rai, Magar, Tamang etc. Brahmins were the third largest population 91 (20.1%). In this study the youngest recipients was 14 years and the oldest was of 75 years. The mean age was 41 (SD 13.84). This study showed that 35 (7.7%) died, 8 (1.7%) reported rejection and underwent re-transplantation and 238 patient have lost follow up till early 2008. Kidney transplantation should be promoted as it is cheaper compared to dialysis in the long run. This study found that unrelated kidney donors have outnumbered the related donors in Nepalese kidney transplant recipients which emphasize the importance of unambiguous documentation and also a provision of lawful action against the middle-men if found involved in an illegal kidney related activities in Nepal. Organ transplantation is an important integral part of human health and should be regularize and promote lawfully to protect humans from trafficking for kidney, possible kidnapping, killing and stealing.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| 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 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".