Comparison of arterial pressure cardiac output monitoring with transpulmonary thermodilution in septic patients.
Bibliographic record
Abstract
BACKGROUND: The measurement of cardiac output in critically ill patients is complicated by rapid pathophysiological changes. The aim of this study was to compare the recently developed Arterial Pressure Cardiac Output algorithm (APCO) with transpulmonary thermodilution (TDCO). Clinical and hemodynamic parameters were tested for their impact on the measurements. MATERIAL/METHODS: Twenty septic patients were examined. Cardiac output measurements were performed simultaneously on 3 consecutive days. The data were evaluated using regression analysis and the Bland Altman approach. RESULTS: Bland Altman analysis presented a bias of 0.72 L/min and limits of agreement of 2.16 to 3.61 L/min for TDCO vs. APCO. Statistically significant covariables in the regression analysis were systemic vascular resistance (p<0.001), mean arterial pressure (p<0.001), cardiac function index (p=0.01), global end-diastolic index (p=0.02) and stroke volume index (p=0.005). Multiple linear regression analysis showed the residual percentage error decreased from 49.1% to 21.5%. CONCLUSIONS: The APCO algorithm provides a broad range of hemodynamic measurements with a minimally invasive approach and simple access to the patient's hemodynamic state. However, an underestimation at high cardiac output and an overestimation at low cardiac output relative to transpulmonary thermodilution were observed in septic patients. Therefore, the APCO algorithm in its current state cannot be substituted for transpulmonary thermodilution.
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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".