Limitations and challenges of EIT-based monitoring of stroke volume and pulmonary artery pressure
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Electrical impedance tomography (EIT) shows potential for radiation-free and noninvasive hemodynamic monitoring. However, many factors degrade the accuracy and repeatability of these measurements. Our goal is to estimate the impact of this variability on the EIT-based monitoring of two important central hemodynamic parameters: stroke volume (SV) and pulmonary artery pressure (PAP). APPROACH: We performed simulations on a 4D ([Formula: see text]) bioimpedance model of a human volunteer to study the influence of four potential confounding factors (electrode belt displacement, electrode detachment, changes in hematocrit and lung air volume) on the performance of EIT-based SV and PAP estimation. Results were used to estimate how these factors affect the EIT measures of either absolute values or relative changes (i.e. trending). MAIN RESULTS: Our findings reveal that the absolute measurement of SV via EIT is very sensitive to electrode belt displacements and lung conductivity changes. Nonetheless, the trending ability of SV EIT might be a promising alternative. The timing-based measurement of PAP is more robust to lung conductivity changes but sensitive to longitudinal belt displacements at severe hypertensive levels and to rotational displacements (independent of the PAP level). SIGNIFICANCE: We identify and quantify the challenges of EIT-based SV and PAP monitoring. Absolute SV via EIT is challenging, but trending is feasible, while both the absolute and trending of PAP via EIT are mostly impaired by belt displacements.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it