Comparative rheology of low‐ and iso‐osmolarity contrast agents at different temperatures
Bibliographic record
Abstract
BACKGROUND: Several contrast media (CM) are used for diagnostic angiography and coronary percutaneous interventions. Catheter miniaturization allows performance of most diagnostic studies using 4-5 F catheters and interventions using 5-6 F catheters. As a result of catheter lumen downsizing and viscosity of CM, the operators are sometimes required to forcefully inject to produce adequate images. METHODS AND RESULTS: The aim of the study is to perform a comparative rheology analysis between three different commonly used CM: iso-osmolar, nonionic iodixanol, Visipaque, (GE Healthcare); low-osmolar, nonionic ioversol, Optiray; and low-osmolar, ionic ioxaglate, Hexabrix, (Tyco Healthcare, US). The viscosity was experimentally assessed for temperature varying from 14 to 40 degrees C. To reproduce clinical use, an experimental set-up was used and the pressure developed to inject CM was evaluated at different temperatures and compared between the three CM. All three agents demonstrated a nonlinear inverse relationship between temperature and viscosity. At 14 degrees C iodixanol showed a twofold increase in viscosity compared with ioversol and ioxaglate. At 40 degrees C, the difference was reduced to 27%. At room temperature (20 degrees C), the difference in pressure needed to inject CM was 10% between iodixanol and ioxaglate and 6% between iodixanol and ioversol. As the temperatures increased, the differences in pressure became less important, becoming negligible (1%) at 37 degrees C. CONCLUSION: The viscosity of the iso-osmolar nonionic contrast agent iodixanol showed a stronger dependence on temperature compared with ioversol and ioxaglate. The impact of differences in viscosity and pressure to inject between CM were minimized at 37 degrees C. This emphasizes the importance of temperature control when using current low-osmolar CM and iso-osmolar CM with smaller sized catheters.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".