A combination of left ventricular outflow tract velocity time integral and lung ultrasound to predict mortality in ST elevation myocardial infarction.
Guilherme Pinheiro MachadoGuilherme Heiden TeloGustavo Neves de AraujoJoao Pedro da Rosa BarbatoAndre AmonAntônia MartinsMarina NassifWagner AzevedoAnderson Donelli da SilveiraFernando Luis ScolariAlan PagnoncelliSandro Cadaval GoncalvesAlexander G TruesdellRodrigo WainsteinMarco WainsteinPublished in: Internal and emergency medicine (2024)
Development of ventricular failure and pulmonary edema is associated with a worse prognosis in ST-elevation myocardial infarction (STEMI). We aimed to evaluate the prognostic ability of a novel classification combining lung ultrasound (LUS) and left ventricular outflow tract (LVOT) velocity time integral (VTI) in patients with STEMI. LUS and LVOT-VTI were performed within 24 h of admission in STEMI patients. A LUS combined with LVOT-VTI (LUV) classification was developed based on LUS with < or ≥ 3 positive zone scans, combined with LVOT-VTI > or ≤ 14. Patients were classified as A (< 3zones/ > 14 cm VTI), B (≥ 3zones/ > 14 cm VTI), C (< 3zones/ ≤ 14 cm VTI) and D (≥ 3zones/ ≤ 14 cm VTI). Primary outcome was occurrence of in-hospital mortality. Development of cardiogenic shock (CS) within 24 h was also assessed. A total of 308 patients were included. Overall in-hospital mortality was 8.8%, while mortality for LUV A, B, C, and D was 0%, 3%, 12%, and 45%, respectively. The area under the curve (AUC) for predicting in-hospital mortality was 0.915. Moreover, after exclusion of patients admitted in Killip IV, at each increasing degree of LUV, a higher proportion of patients developed CS within 24 h: LUV A = 0.0%, LUV B 5%, LUV C = 12.5% and LUV D = 30.8% (p < 0.0001). The AUC for predicting CS was 0.908 (p < 0.001). In a cohort of STEMI patients, LUV provided to be an excellent method for prediction of in-hospital mortality and development of CS. LUV classification is a fast, non-invasive and very user-friendly ultrasonographic evaluation method to stratify the risk of mortality and CS.
Keyphrases
- st elevation myocardial infarction
- end stage renal disease
- ejection fraction
- left ventricular
- newly diagnosed
- percutaneous coronary intervention
- chronic kidney disease
- peritoneal dialysis
- type diabetes
- machine learning
- heart failure
- cardiovascular disease
- aortic stenosis
- coronary artery disease
- st segment elevation myocardial infarction
- ultrasound guided