Reduced myocardial blood flow reserve in kidney transplant candidates may hamper risk stratification
Bibliographic record
Abstract
BACKGROUND: Rb-positron emission tomography-computed tomography can measure myocardial blood flow (MBF), the response to vasodilator stress can be verified rendering the results of the scan more reliable. METHODS: We reviewed the MBF response to dipyridamole infusion in 328 patients with end-stage kidney disease (ESKD) prior to transplant (188 hemodialysis-HD, 120 peritoneal dialysis-PD, and 20 pre-dialysis patients-CKD5) and in 100 controls with normal kidney function. A stress/rest MBF ratio ≥ 2 was considered an adequate response to dipyridamole. Coronary artery calcium (CAC) was measured on CT. RESULTS: Inadequate MBF response was seen in 36%-HD, 21%-PD, 45%-CKD5 vs. 23%-controls (p = 0.006). Univariable predictors of poor MBF response in ESKD patients were age, diabetes mellitus, and CAC (all p < 0.03) while serum hemoglobin was borderline significant (p = 0.052). Multivariable predictors of a poor MBF response were age (p = 0.002) and lower serum hemoglobin (p = 0.014). Ischemia was identified in 8% of ESKD patients and 24% of controls (p < 0.001). CONCLUSIONS: ESKD patients are less likely to respond appropriately to vasodilator stress compared to patients with normal renal function and had a lower incidence of ischemia despite a high pre-test probability of disease. Physicians performing vasodilator stress without MBF measurement should be aware of the high probability of a false negative response.
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.
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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".