The link between pulmonary hypertension and adverse renal transplant outcome may be renal venous hypertension
Bibliographic record
Abstract
Sir, The recent retrospective study by Goyal et al.[1] outlining the relationship between delayed graft function and pulmonary hypertension in patients undergoing renal transplantation addresses a number of potential responsible mechanisms for this relationship. For example, they suggest that haemodynamic instability (i.e. systemic hypotension) or deleterious circulating vasoactive substances can lead to poor perfusion and ischaemia of the transplanted kidney. Indeed, episodes of hypotension are not uncommon in the perioperative setting and patients with delayed graft functioning are also known to have higher levels of circulating endothelin-1, a potent vasoconstrictor that can lead to renal ischaemic injury,[2] in addition to pulmonary hypertension itself.[3] However, an often under-recognised means by which kidney function can be impaired is through poor renal blood flow due to elevation in renal venous pressure that can result from pulmonary hypertension-associated right ventricular (RV) dysfunction. Elevations in the right atrial (RA) pressures can be reflected in the inferior vena cava and renal vein that can result in a reduction in overall renal perfusion pressure (i.e., arterial pressure–venous pressure).[4] This likely explains the benefit to the acute treatment of RV dysfunction with pulmonary vasodilators and other inotropic agents that can reduce the RA pressure and improve renal function.[5] Hence, although the circulating vasoactive substances that can lead to pulmonary hypertension could theoretically result in renal vasoconstriction, the main problem may not be the arterial flow to the kidney but rather the venous outflow from the kidney, which can similarly cause an ischaemic injury due to low transmural organ blood flow. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".