Subclinical Congestion Evaluated by Point of Care Ultrasound (POCUS) at Discharge Predicts Readmission in Patients with Acute Heart Failure: Prognostic Cohort Study
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Bibliographic record
Abstract
Background: Heart failure (HF) is a complex entity that increases the risk of adverse outcomes. Point of care ultrasound (POCUS) allows easy lung and systemic venous congestion identification. Using ultrasound to detect sub-clinical congestion at discharge may help predict readmissions and mortality. Outcomes: The primary outcome was to address 30-day rehospitalization, and as a secondary outcome we investigated readmission and mortality in patients with residual congestion assessed with POCUS. Methods: A prospective prognostic cohort study was conducted at a tertiary-level institution in Colombia. Patients with acute decompensated heart failure (ADHF) at discharge were evaluated using POCUS through lung ultrasound (LUS), portal vein pulsatility (PVP), and a composite assessment of residual congestion. Inclusion criteria were ADHF, over 18 years old, with a “warm-wet” clinical profile. POCUS was performed using an ultraportable device using LUS and PVP. Statistical analysis used logistic regression models to estimate the association between ultrasound congestion and outcomes. Results: A total of 100 patients were included. The population was mostly female, with a median age of 78 years; 59% were hypertensive, and 39% had type 2 diabetes. Median NT-ProBNP was 3878 pg/ml. At discharge, 55% of patient had an inferior vena cava (IVC) over 2 cm, 54% had interstitial syndrome, and 41% had PVP >30%. Regarding 30-day readmission, we found an odds ratio (OR) 7.22 (95% CI 2.7-19.3) for interstitial syndrome; for PVP >30%, an OR 24.61 (95% CI 7.7-78.1) and an OR 13.19 (95% CI 2.7-62.6) for composite of residual congestion. Conclusion: Patients with ADHF and sub-clinical congestion, evidenced in LUS and PVP, were more likely to have readmission within 30 days of discharge. These findings should be confirmed with clinical trials to assess the effectiveness of a POCUS-guided treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it