Estimation of left ventricular stroke volume by impedance cardiography: its relation to the aortic reservoir
Bibliographic record
Abstract
New Findings What is the central question of this study? Thoracic impedance has been used to calculate left ventricular stroke volume for decades, while its theoretical basis remains controversial and the parameters generated have not been related satisfactorily to the haemodynamic events. What is the main finding and what is its importance? We provide mechanistic explanations for the following: (i) why the upstroke of the change in thoracic impedance (Δ Z ) waveform is constantly delayed with respect to that of the central aortic pressure; (ii) why the contour of the Δ Z waveform is ‘blunted’ compared with that of the central aortic pressure; (iii) what mechanism is related to the ‘second bump’ of the Δ Z waveform in early diastole (the ‘O‐wave’); and (iv) the mechanism that is likely to be associated with the decreasing Δ Z waveform in later diastole. Impedance cardiography is a non‐invasive technique used to estimate left ventricular (LV) stroke volume (SV) using the change in thoracic impedance (Δ Z ). It remains controversial, partly because impedance cardiographic parameters have not been successfully related to haemodynamic events. We hypothesized that the change in Δ Z may be proportional to the variation in thoracic (primarily aortic) blood volumes. Nine anaesthetized and ventilated dogs were divided into the following two groups: the ‘aortic volume group’ ( n = 5), in which aortic and IVC (inferior vena caval) dimensions were measured ultrasonically; and the ‘reservoir volume group’, in which aortic and IVC reservoir volumes were calculated using the reservoir–wave model. Measurements were made in control conditions, in the presence of nitroprusside and methoxamine and after volume loading. In both the aortic volume group and the reservoir volume group, the maximal rate of increase in Δ Z [(d Z /d t ) max ] strongly correlated with the maximal rate of change in aortic/reservoir blood volume ( R 2 = 0.85 and 0.95, respectively), which in turn was proportional to the LV SV. The LV and IVC contributions to Δ Z were small in control conditions (∼5 and 1%, respectively), but the LV contribution increased slightly (to 7%) with administration of methoxamine and after volume loading (to 10%). It is concluded that the change in thoracic impedance (Δ Z ) during the cardiac cycle is proportional to the change in aortic reservoir (i.e. Windkessel) volume, which provides a mechanistic explanation for previously demonstrated good correlations with standard measures of cardiac output.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".