Cardiac output monitoring: Technology and choice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The accurate quantification of cardiac output (CO) is given vital importance in modern medical practice, especially in high-risk surgical and critically ill patients. CO monitoring together with perioperative protocols to guide intravenous fluid therapy and inotropic support with the aim of improving CO and oxygen delivery has shown to improve perioperative outcomes in high-risk surgical patients. Understanding of the underlying principles of CO measuring devices helps in knowing the limitations of their use and allows more effective and safer utilization. At present, no single CO monitoring device can meet all the clinical requirements considering the limitations of diverse CO monitoring techniques. The evidence for the minimally invasive CO monitoring is conflicting; however, different CO monitoring devices may be used during the clinical course of patients as an integrated approach based on their invasiveness and the need for additional hemodynamic data. These devices add numerical trend information for anesthesiologists and intensivists to use in determining the most appropriate management of their patients and at present, do not completely prohibit but do increasingly limit the use of the pulmonary artery catheter.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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