Overcoming barriers and expanding opportunities in liver transplantation in Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Liver transplantation (LT) is the only curative treatment for end-stage liver disease. Although Mexico has made important strides in surgical capacity and institutional development, the country continues to report one of the lowest LT rates in Latin America. Multiple challenges remain, including inequitable access to care, limited organ donation, and structural inefficiencies in allocation systems. To review the current status of LT in Mexico, describe historical trends, highlight significant barriers to progress, and discuss potential opportunities for program expansion. We conducted a narrative review incorporating data from the National Transplant Center (Centro Nacional de Trasplantes in Spanish), relevant peer-reviewed literature, and global benchmarks. The analysis focused on trends in liver transplant volume, donor types, etiology shifts, institutional disparities, and the impact of the coronavirus disease 2019 (COVID-19) pandemic. LT activity in Mexico increased from 25 transplants in 1999 to 297 in 2023. However, over 68% of transplants are concentrated in Mexico City, and only eight centers perform more than ten LTs per year. Deceased donors account for most grafts, while living donor transplants remain rare and mostly limited to private institutions. The national waiting list functions primarily as a registry rather than a priority-based allocation system. The COVID-19 pandemic further disrupted transplant programs, particularly in the public sector. Innovative approaches such as donation after circulatory death, hepatitis C virus-positive donor utilization, and advanced perfusion technologies are currently unavailable or underutilized in Mexico. Mexico's LT system faces geographic, regulatory, and resource-related limitations. To improve outcomes and ensure equitable access, strategic reforms focused on donor expansion, centralized allocation, perfusion technologies, and standardization of care are urgently needed.
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.
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 | 0.001 | 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 it