N-terminal pro–B-type natriuretic peptide and pulmonary echography are predictors of acute heart failure needing early mechanical ventilation in acute coronary syndrome
Bibliographic record
Abstract
AIM: The aim of this study was to determine the best clinical predictors of acute heart failure needing mechanical ventilation (MV) in the first 48 h of evolution of patients admitted because of acute coronary syndrome (ACS). METHODS: We analyzed a cohort of patients admitted for ACS between February 2017 and February 2018. A pulmonary ultrasound was performed on admission and was considered positive (PE+) when there were three or more B-lines in two quadrants or more of each hemithorax. It was compared with N-terminal pro-B-type natriuretic peptide (NT-proBNP), peak troponin T-us value GRACE (Global Registry of Acute Coronary Events), CRUSADE (Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the American College of Cardiology and American Heart Association guidelines - Bleeding Score), CACS (Canada Acute Coronary Syndrome risk score), and HAMIOT (Heart Failure after Acute Myocardial Infarction with Optimal Treatment score) scores, shock index, ejection fraction, chest X-ray, and Killip class at admission as predictors of MV in the first 48 h of admission. RESULTS: A total of 119 patients were included: 54.6% with ST elevation and 45.4% without ST elevation. Twelve patients (10.1%) required MV in the first 48 h of evolution. The sensitivity of PE+ was 100% (73.5-100%), specificity 91.6% (84.6-96.1%), and area under the curve was 0.96 (0.93-0.96). The sensitivity of an NT-proBNP value more than 3647 was 88.9% (51.9-99.7%), specificity 92.1% (84.5-96.8%), and area under the curve was 0.905 (0.793-1). The κ statistic between both predictors was 0.579. All the other scores were significantly worse than PE + . CONCLUSION: Lung ultrasound and a high NT-proBNP (3647 ng/L in our series) on admission are the best predictors of acute heart failure needing MV in the first 48 h of ACS. The agreement between both tests was only moderate.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".