Serial lung and IVC ultrasound in the assessment of congestive heart failure
Bibliographic record
Abstract
BACKGROUND: Management of congestive heart failure (CHF) is dependent on clinical assessments of volume status, which are subjective and imprecise. Point-of-care ultrasound (POCUS) is useful in the diagnosis of CHF, but how POCUS findings correlate with therapy remains unknown. This study aimed to determine whether the changes in clinical evaluation of CHF with treatment are mirrored with changes in the number of B lines on lung ultrasound (LUS) and inferior vena cava (IVC) size. In this prospective observational study, investigators performed serial clinical and ultrasound assessments within 24 h of admission (T1), day 1 in hospital (T2) and within 24 h of discharge (T3). Clinical assessments included an evaluation of the jugular venous distension (JVD), hepatojugular reflux (HJR), pulmonary rales and a clinical congestion score was calculated. Ultrasound assessment included the IVC size and collapsibility, and the number of B lines in an 8-point scan. RESULTS: Fifty consecutive patients were recruited with a mean age of 71.2 years (SD 12.7). Mean clinical congestion score on admission was 5.6 (SD 1.4) and declined significantly over time to 1.3 (0.91), as did the JVP, HJR and pulmonary rales. No significant changes were found in the IVC size between T1 [1.9 (0.65)] and T3 [2.0 (0.50)] or in the IVC collapsibility index [T1 0.3 (0.19) versus T3 0.25 (0.16)]. The mean number of B lines decreased from 11 (6.1) at T1 to 8.3 (5.5) at T3, although this decrease did not reach statistical significance. Spearman correlation between JVP and HJR versus IVC collapsibility and total B lines did not yield significant results. CONCLUSIONS: Clinical exam findings correlate over time during the management of CHF, whereas LUS and IVC results did not. The number of B lines did decrease with therapy, but did not reach statistical significance likely because the sampled population was small and had only mild heart failure. Further studies are warranted to further explore the use of lung ultrasound in this patient population.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".