Pulmonary artery elastance as a predictor of hospital mortality in heart failure cardiogenic shock.

AIMS: The initial bundle of cares strongly affects haemodynamics and outcomes in acute decompensated heart failure cardiogenic shock (ADHF-CS). We sought to characterize whether 24 h haemodynamic profiling provides superior prognostic information as compared with admission assessment and which haemodynamic parameters best predict in-hospital death. METHODS AND RESULTS: All patients with ADHF-CS and with available admission and 24 h invasive haemodynamic assessment from two academic institutions were considered for this study. The primary endpoint was in-hospital death. Regression analyses were run to identify relevant predictors of study outcome. We included 127 ADHF-CS patients [65 (inter-quartile range 52-72) years, 25.2% female]. Overall, in-hospital mortality occurred in 26.8%. Non-survivors were older, with greater CS severity. Among admission variables, age [odds ratio (OR) = 1.06; 95% confidence interval (CI): 1.02-1.11; Padj = 0.005] and CPIRAP (OR = 0.62 for 0.1 increment; 95% CI: 0.39-0.95; Padj = 0.034) were found significantly associated with in-hospital death. Among 24 h haemodynamic univariate predictors of in-hospital death, pulmonary elastance (PaE) was the strongest (area under the curve of 0.77; 95% CI: 0.68-0.86). PaE (OR = 5.98; 95% CI: 2.29-17.48; Padj < 0.001), pulmonary artery pulsatility index (PAPi, OR = 0.77; 95% CI: 0.62-0.92; Padj = 0.013) and age (OR = 1.06; 95% CI: 1.02-1.11; Padj = 0.010) were independently associated with in-hospital death. Best cut-off for PaE was 0.85 mmHg/mL and for PAPi was 2.95; cohort phenotyping based on these PaE and PAPi thresholds further increased in-hospital death risk stratification; patients with 24 h high PaE and low PAPi exhibited the highest in-hospital mortality (56.2%). CONCLUSIONS: Pulmonary artery elastance has been found to be the most powerful 24 h haemodynamic predictor of in-hospital death in patients with ADHF-CS. Age, 24 h PaE, and PAPi are independently associated with hospital mortality. PaE captures right ventriclar (RV) afterload mismatch and PAPi provides a metric of RV adaptation, thus their combination generates four distinct haemodynamic phenotypes, enhancing in-hospital death risk stratification.

Extracellular volume fraction (ECV) derived from pre-operative computed tomography predicts prognosis in patients undergoing transcatheter aortic valve implantation (TAVI).

AIMS: Transcatheter aortic valve implantation (TAVI) is the treatment of choice for high-risk patients with severe aortic stenosis (AS). A portion of TAVI recipients has no long-term clinical benefit, and myocardial fibrosis may contribute to unfavourable outcomes. We aimed to assess the prognostic value of an interstitial fibrosis marker, extracellular volume fraction (ECV), measured at planning computed tomography (CT) before TAVI. METHODS AND RESULTS: From October 2020 to July 2021, 159 consecutive patients undergoing TAVI planning CT were prospectively enroled. ECV was calculated as the ratio of myocardium and blood pool differential attenuations before and 5 min after contrast administration, pondered for haematocrit. A composite endpoint including heart failure hospitalization (HFH) and death was collected by telehealth or in-person follow-up visits in the 113 patients constituting the final study population. Cox proportional hazards model was used to assess association between ECV and the composite endpoint.Median follow-up was 13 (11-15) months. The composite endpoint occurred in 23/113 (20%) patients. These patients had lower aortic valve mean pressure gradient [39 (29-48) vs. 46 (40-54) mmHg, P = 0.002] and left ventricular and right ventricular ejection fraction [51 (37-69) vs. 66 (54-74)%, P = 0.014; 45 (31-53) vs. 49 (44-55)%, P = 0.010] and higher ECV [31.5 (26.9-34.3) vs. 27.8 (25.3-30.2)%, P = 0.006]. At multivariable Cox analysis, ECV higher than 31.3% was associated to increased risk of death or HFH at follow-up (hazard ratio = 5.92, 95% confidence interval 2.37-14.75, P < 0.001). CONCLUSION: In this prospective observational cohort study, ECV measured at TAVI planning CT predicts the composite endpoint (HFH or death) in high-risk severe AS patients.

A comprehensive and easy-to-use ECG algorithm to predict the coronary occlusion site in ST-segment elevation myocardial infarction.

BACKGROUND: Several electrocardiogram (ECG) criteria have been proposed to predict the location of the culprit occlusion in specific subsets of patients presenting with ST-segment elevation myocardial infarction (STEMI). The aim of this study was to develop, through an independent validation of currently available criteria, a comprehensive and easy-to-use ECG algorithm, and to test its diagnostic performance in real-world clinical practice. METHODS: We analyzed ECG and angiographic data from 419 consecutive STEMI patients submitted to primary percutaneous coronary intervention over a one-year period, dividing the overall population into derivation (314 patients) and validation (105 patients) cohorts. In the derivation cohort, we tested >60 previously published ECG criteria, using the decision-tree analysis to develop the algorithm that would best predict the infarct-related artery (IRA) and its occlusion level. We further assessed the new algorithm diagnostic performance in the validation cohort. RESULTS: In the derivation cohort, the algorithm correctly predicted the IRA in 88% of cases and both the IRA and its occlusion level (proximal vs mid-distal) in 71% of cases. When applied to the validation cohort, the algorithm resulted in 88% and 67% diagnostic accuracies, respectively. In a real-world comparative test, the algorithm performed significantly better than expert physicians in identifying the site of the culprit occlusion (P = .026 vs best cardiologist and P < .001 vs best emergency medicine doctor). CONCLUSIONS: Derived from an extensive literature review, this comprehensive and easy-to-use ECG algorithm can accurately predict the IRA and its occlusion level in all-comers STEMI patients.

A simplified echocardiographic formula to estimate cardiac index in the intensive care unit.

BACKGROUND AND AIM: Measurement of cardiac index (CI) is crucial in the hemodynamic assessment of critically ill patients in the intensive care unit (ICU). The most reliable trans-thoracic echocardiography (TTE) technique for CI estimation is the left ventricular outflow tract (LVOT) Doppler method that requires, among other parameters, the LVOT cross-sectional area (CSA) measurement. However, inherent and practical disadvantages, mostly related to the ICU setting, hamper LVOT-CSA assessment. In this study, we aimed to validate a simplified formula, leveraging on LVOT-velocity time integral (VTI) and heart rate (HR) only, for non-invasive estimation of CI in ICU patients. METHODS AND RESULTS: We prospectively enrolled 50 consecutive patients admitted to our ICU requiring pulmonary artery catheterization (PAC) over a one-year period. For each patient we measured the CI by PAC (CIPAC) and TTE. The latter was obtained both with the "traditional formula" (traditional CITTE), requiring LVOT-CSA assessment, and our new "simplified formula" (simplified CITTE). The correlation between the simplified CITTE and CIPAC was strong (r = 0.81) and resulted significantly greater than the traditional CITTE and CIPAC correlation (r = 0.70; p < 0.05 for Pearson r coefficients comparison). Both TTE-based CI showed an acceptable agreement (+0.19 ± 0.48 L/min/m2 for simplified CITTE and - 0.18 ± 0.58 L/min/m2 for traditional CITTE) with the reference CIPAC. CONCLUSION: In this study, we validated a practical approach, leveraging on TTE LVOT-VTI and HR only, for non-invasive estimation of CI in ICU patients.

Lung Ultrasound in COVID-19 A Role Beyond the Acute Phase?

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is a viral illness caused by severe acute respiratory syndrome coronavirus 2. With the increasing number of improved and discharged patients with COVID-19, the definition of an adequate follow-up strategy is needed. The purpose of this study was to assess whether lung ultrasound (LUS) is an effective indicator of subclinical residual lung damage in patients with COVID-19 who meet discharge criteria. METHODS: We prospectively enrolled 70 consecutive patients with COVID-19 who had a prolonged hospitalization with inpatient rehabilitation between April 6 and May 22, 2020. All of the patients underwent an LUS evaluation at discharge. Data of patients with more severe disease during the acute phase (ie, required ventilatory support) were compared to those of patients with milder disease. RESULTS: Among the 70 patients with COVID-19 (22 women and 48 men; mean age ± SD, 68 ± 13 years), the LUS score before discharge was still frankly pathologic and higher in patients who had more severe disease during the acute phase compared to patients with milder disease (median [interquartile range], 8.0 [5.5-13.5] versus 2.0 [1.0-7.0]; P < .001), even when both categories met internationally defined discharge criteria. CONCLUSIONS: Lung ultrasound can identify the persistence of subclinical residual lung damage in patients with severe COVID-19 even if they meet discharge criteria. Considering the low cost, easy application, and lack of radiation exposure, LUS seems the ideal tool to be adopted in outpatient and primary care settings for the follow-up of patients with COVID-19.