Caution when using publicly available datasets
Bibliographic record
Abstract
We read, with interest, the paper by Maenosono et al. entitled, “Recipient Sex and Estradiol Levels Affect Transplant Outcomes in an Age-Specific Fashion.”1 We commend the authors on their efforts to deepen understanding of the mechanisms underlying the age-dependent sex differences in graft survival that have been observed in humans. We were surprised to see the analysis of differences in graft survival by recipient sex among patients recorded in the Scientific Registry of Transplant Recipients (SRTR) presented as a novel finding. Our group previously identified important donor sex-dependent and age-dependent differences in graft failure risk between male and female kidney transplant recipients using the SRTR data; this study, entitled “Association of Sex with Risk of Kidney Graft Failure Differs by Age,” was published in 2017.2 Not surprisingly, the findings of Maenosono et al., showing higher graft failure rates in young women than men but lower graft failure rates in older women than men, confirm our published findings in a very similar SRTR cohort. This replication should remind researchers and reviewers alike of the importance of a thorough review of existing literature, especially when analyzing publicly available datasets. The accompanying animal studies aimed at determining the contribution of estradiol to the observed sex differences in graft failure risk are novel and begin to answer some of the questions regarding mechanisms underlying observed sex differences in graft survival. However, additional questions remain. For example, the authors emphasize the differences in graft survival between young and old female mice, but do not discuss differences in graft survival between young and old male mice. We and others have demonstrated higher graft failure rates in late adolescent and early young adult than older kidney, liver, and heart transplant recipients.3-5 The association between age and graft failure rate does not differ by recipient sex.5 The experiments of Maenosono et al. suggest that higher estradiol levels during peak reproductive years may be at least partly responsible for the higher graft failure rates observed in younger than older female recipients. This is an important observation. Given that the higher graft failure rates in young (vs. older) human transplant recipients are generally attributed to poorer adherence to immunosuppressive medications, important observations such as these provide evidence that non-behavioral factors may also contribute. Similar animal studies assessing differences in graft survival and in immune profiles by age in males are encouraged. More studies examining sex differences in graft outcomes and identifying mechanisms for these differences are needed. A comprehensive review of existing literature is encouraged to effectively target appropriate avenues of inquiry. The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of 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 | 0.091 | 0.400 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.026 | 0.033 |
| Insufficient payload (model declined to judge) | 0.015 | 0.017 |
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".