SP45 Impedance Cardiography: Novel Technology to Measure Haemodynamics in Cardiovascular Populations
Bibliographic record
Abstract
Purpose: Impedance cardiography (ICG) is non-invasive technology to measure heart rate (HR), stroke volume (SV), cardiac output (CO), preejection period (PEP), left ventricular ejection time (LVET), and myocardial contractility. Simultaneous measurement of blood pressure (BP) permits the derivation of systemic vascular resistance (SVR). The aim of this review was to evaluate the evidence of the clinical application of ICG in cardiovascular populations. Methods: Studies were reviewed that used ICG to measure haemodynamics in hypertension, coronary artery disease (CAD), coronary artery bypass grafting (CABG), and cerebral stroke (CVA). The Cochrane Library, MEDLINE, and CINAHL were searched using the terms thoracic impedance, impedance technology, ambulatory impedance cardiography, bio-electrical impedance, blood pressure, SVR, ischaemia, acute coronary syndrome, hypertension, and CVA. The search was limited to studies published in English between 1998 and 2008 and studies were excluded that examined pharmacological treatment or persons with heart failure. Results: Nine studies used ICG in 854 adults. Three studies examined the reliability and validity of ICG in CAD, CVA, and CABG populations. ICG measures such as HR (r =0.97), PEP (r =0.90), and SVR (r =0.98) were highly repeatable. Six studies reported hemodyanmics in hypertensive individuals. Compared to non-hypertensive individuals, persons with hypertension exhibited higher BP, higher SVR and decreased cardiac index (CI). Compared to hypertensives managed by BP alone, ICG-guided antihypertensive treatment resulted in significant reductions in systolic and diastolic BP and superior BP control.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".