A Simplified Approach to Extravascular Lung Water Assessment Using Point-of-Care Ultrasound in Patients with End-Stage Chronic Renal Failure Undergoing Hemodialysis
Bibliographic record
Abstract
BACKGROUND: Fluid overload leading to pulmonary congestion is an important issue in patients undergoing hemodialysis. This study aimed to determine if a simplified method of extravascular lung water assessment using ultrasound provided clinically relevant information. METHODS: This prospective study recruited 47 patients from a single hemodialysis center. Pulmonary ultrasound was performed before and after 2 hemodialysis sessions in 28 regions on the thorax. The B-line score was defined as the percentage regions where B-lines were present. RESULTS: When B-lines were detected before hemodialysis, a significant relationship was found between fluid removal and the change in B-line score. Patients with a B-line score of ≥21.4% (4th quartile) after the second hemodialysis session were more likely to be hospitalized for pulmonary edema or acute coronary syndrome. CONCLUSIONS: A simplified pulmonary assessment using ultrasound provides relevant information about pulmonary congestion in hemodialysis patients and identifies patients at risk of hospitalization for heart-related problems.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".