Bibliographic record
Abstract
PURPOSE OF REVIEW: Describe the contemporary assessment of cardiac hemodynamics using a comprehensive echo-Doppler examination in the heart failure (HF) patient. RECENT FINDINGS: Cardiac flow and filling pressures, on both the left and right sides of the heart, are fundamental to the accurate assessment of the HF patient. Accurate assessment of left ventricular (LV) and right ventricular (RV) systolic and diastolic function is necessary to establish, or exclude, HF as a cause or component of dyspnea in a given patient and to help determine causes of hemodynamic instability in HF patients. Variables such as spectral Doppler (mitral and tricuspid inflow, pulmonary and hepatic venous flow, and pulmonary valve regurgitation signal), tissue Doppler imaging, and speckle tracking, applied to the left and right heart, can help to accurately estimate cardiac hemodynamics. SUMMARY: A comprehensive echocardiogram with Doppler can provide an accurate assessment of left and right heart hemodynamics that is fundamental to the assessment and management of the HF patient.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".