Intradialytic Cardiac Magnetic Resonance Imaging to Assess Cardiovascular Responses in a Short-Term Trial of Hemodiafiltration and Hemodialysis
Bibliographic record
Abstract
Hemodynamic stress during hemodialysis (HD) results in recurrent segmental ischemic injury (myocardial stunning) that drives cumulative cardiac damage. We performed a fully comprehensive study of the cardiovascular effect of dialysis sessions using intradialytic cardiac magnetic resonance imaging (MRI) to examine the comparative acute effects of standard HD versus hemodiafiltration (HDF) in stable patients. We randomly allocated 12 patients on HD (ages 32–72 years old) to either HD or HDF. Patients were stabilized on a modality for 2 weeks before undergoing serial cardiac MRI assessment during dialysis. Patients then crossed over to the other modality and were rescanned after 2 weeks. Cardiac MRI measurements included cardiac index, stroke volume index, global and regional contractile function (myocardial strain), coronary artery flow, and myocardial perfusion. Patients had mean±SEM ultrafiltration rates of 3.8±2.9 ml/kg per hour during HD and 4.4±2.5 ml/kg per hour during HDF ( P =0.29), and both modalities provided a similar degree of cooling. All measures of systolic contractile function fell during HD and HDF, with partial recovery after dialysis. All patients experienced some degree of segmental left ventricular dysfunction, with severity proportional to ultrafiltration rate and BP reduction. Myocardial perfusion decreased significantly during HD and HDF. Treatment modality did not influence any of the cardiovascular responses to dialysis. In conclusion, in this randomized, crossover study, there was no significant difference in the cardiovascular response to HDF or HD with cooled dialysate as assessed with intradialytic MRI.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".