Serum Ammonia Screening and Donor Mollicutes Detection for Hyperammonemia Syndrome Post–Lung Transplantation: A Prospective Observational Study
Bibliographic record
Abstract
BACKGROUND: Hyperammonemia syndrome (HS) is a rare but potentially fatal complication of lung transplantation (LT). Optimal screening methods are unknown. Here we investigated serum ammonia screening (SAS) for HS and compared it with polymerase chain reaction (PCR) for Mollicutes (Urease-producing bacteria). METHODS: All LT recipients from July 2019 to February 2020 and October 2021 to November 2022 with available donor bronchial wash samples from the LT biobank were included. Mollicutes PCR was performed using 2 commercially available kits. Daily ammonia serum levels were measured for the first 14 days. Recipients were prospectively followed for HS for 30 days post-LT. HS was defined by new neurological symptoms and the presence of elevated serum ammonia (>1 × >70 µmol/L). RESULTS: Of 241 LT recipients, 5 (2%) developed HS within the first month post-LT. Median time to HS was 8 (interquartile range, 5-10) days. All HS was diagnosed within the first 14 days post-LT, while daily SAS was in place. Ammonia was confirmed elevated (>1 × >70 µmol/L) in 4% (9/241) during follow-up; however, outside of HS, 4 were found to be related to liver disease. Donor and recipient Mollicutes PCR was positive in 8% (19/241) and 1% (1/72), respectively, at transplant. Donor Mollicutes PCR, in contrast to recipient Mollicutes PCR, was associated with HS but only in 2 of the 5 HS cases. No HS patient died within 90 days post-LT. CONCLUSIONS: HS was a rare complication in our LT cohort. Daily post-LT SAS might add to early HS diagnosis and treatment and is potentially associated with improved outcome. Donor screening with Mollicutes PCR has limited predictive value for HS post-LT.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".