Ultrasound Monitoring of RBC Aggregation as a Real-Time Marker of the Inflammatory Response in a Cardiopulmonary Bypass Swine Model*
Bibliographic record
Abstract
OBJECTIVES: In many pathological conditions, including high-risk surgery, the severity of the inflammatory response is related to the patient outcome. However, determining the patient inflammatory state presents difficulties, as markers are obtained intermittently through blood testing with long delay. RBC aggregation is a surrogate marker of inflammation that can be quantified with the ultrasound Structure Factor Size and Attenuation Estimator. The latter is proposed as a real-time inflammation monitoring technique for patient care. DESIGN: Ten swine underwent a 90-minute cardiopulmonary bypass, and surveillance was maintained during 120 minutes in the postbypass period. To promote the inflammatory reaction, lipopolysaccharide was administrated two times prior to surgery in six of those swine (lipopolysaccharide group). During the whole procedure, the Structure Factor Size and Attenuation Estimator cellular imaging method displayed a RBC aggregation index (W) computed from images acquired within the pump circuit and the femoral vein. Interleukin-6, interleukin-10, C-reactive protein, haptoglobin, immunoglobulin G, and fibrinogen concentrations were measured at specific periods. MAIN RESULTS: Compared with controls, the lipopolysaccharide group exhibited higher W within the pump circuit (p < 0.05). In the femoral vein, W was gradually amplified in the lipopolysaccharide group during cardiopulmonary bypass and the postbypass period (p < 0.05), whereas interleukin levels were higher in the lipopolysaccharide group but only at the end of cardiopulmonary bypass and beginning of postbypass (p < 0.05). CONCLUSIONS: Continuous RBC aggregation monitoring can characterize the evolving inflammatory response during and after cardiopulmonary bypass. The Structure Factor Size and Attenuation Estimator is proposed as a real-time noninvasive monitoring technique to anticipate inflammation-related complications during high-risk surgery or critical care situations. Because RBC aggregation promotes vascular resistance and thrombosis, W could also provide early information on vascular disorders in those clinical situations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".