PrOgnosis in Pulmonary Embolism (PoPE): 30-Day mortality risk score based on five admission parameters.

INTRODUCTION AND OBJECTIVE: Several scoring systems have been developed for risk stratification in patients with acute pulmonary embolism (PE). The Pulmonary Embolism Severity Index (PESI) and its simplified version (sPESI) are among the most used, however the high number of variables hinder its application. Our aim was to derive an easy-to-perform score based on simple parameters obtained at admission to predict 30-day mortality in acute PE patients. METHODS: Retrospective study in 1115 patients with acute PE from two institutions (derivation cohort n=835, validation cohort n=280). The primary endpoint was all-cause mortality at 30 days. Statistically and clinically relevant variables were selected for multivariable Cox regression analysis. We derived and validated a multivariable risk score model and compared to other established scores. RESULTS: The primary endpoint occurred in 207 patients (18.6%). Our model included five variables weighted as follows: modified shock index ≥1.1 (hazard ratio [HR] 2.57, 1.68-3.92, p<0.001), active cancer (HR 2.27, 1.45-3.56, p<0.001), altered mental state (HR 3.82, 2.50-5.83, p<0.001), serum lactate concentration ≥2.50 mmol/L (HR 5.01, 3.25-7.72, p<0.001), and age ≥80 years (HR 1.95, 1.26-3.03, p=0.003). The prognostic ability was superior to other scores (area under curve [AUC] 0.83 [0.79-0.87] vs 0.72 [0.67-0.79] in PESI and 0.70 [0.62-0.75] in sPESI, p<0.001) and its performance in the validation cohort was deemed good (73 events in 280 patients, 26.1%, AUC=0.76, 0.71-0.82, p<0.0001) and superior to other scores (p<0.05). CONCLUSIONS: The PoPE score (https://tinyurl.com/ybsnka8s) is an easy tool with superior performance to predict early mortality in patients admitted for PE with non-high-risk PE.

The value of multiparametric prediction scores in heart failure varies with the type of follow-up after discharge: a comparative analysis.

AIMS: Multiple prediction score models have been validated to predict major adverse events in patients with heart failure. However, these scores do not include variables related to the type of follow-up. This study aimed to evaluate the impact of a protocol-based follow-up programme of patients with heart failure regarding scores accuracy for predicting hospitalizations and mortality occurring during the first year after hospital discharge. METHODS AND RESULTS: Data from two heart failure populations were collected: one composed of patients included in a protocol-based follow-up programme after an index hospitalization for acute heart failure and a second one-the control group-composed of patients not included in a multidisciplinary HF management programme after discharge. For each patient, the risk of hospitalization and/or mortality within a period of 12 months after discharge was calculated using four different scores: BCN Bio-HF Calculator, COACH Risk Engine, MAGGIC Risk Calculator, and Seattle Heart Failure Model. The accuracy of each score was established using the area under the receiver operating characteristic curve (AUC), calibration graphs, and discordance calculation. AUC comparison was established by the DeLong method. The protocol-based follow-up programme group included 56 patients, and the control group, 106 patients, with no significant differences between groups (median age: 67 years vs. 68.4 years; male sex: 58% vs. 55%; median ejection fraction: 28.2% vs. 30.5%; functional class II: 60.7% vs. 56.2%, I: 30.4% vs. 31.9%; P = not significant). Hospitalization and mortality rates were significantly lower in the protocol-based follow-up programme group (21.4% vs. 54.7%; P < 0.001 and 5.4% vs. 17.9%; P < 0.001, respectively). When applied to the control group, COACH Risk Engine and BCN Bio-HF Calculator had, respectively, good (AUC: 0.835) and reasonable (AUC: 0.712) accuracy to predict hospitalization. There was a significant reduction of COACH Risk Engine accuracy (AUC: 0.572; P = 0.011) and a non-significant accuracy reduction of BCN Bio-HF Calculator (AUC: 0.536; P = 0.1) when applied to the protocol-based follow-up programme group. All scores showed good accuracy to predict 1 year mortality (AUC: 0.863, 0.87, 0.818, and 0.82, respectively) when applied to the control group. However, when applied to the protocol-based follow-up programme group, a significant predictive accuracy reduction of COACH Risk Engine, BCN Bio-HF Calculator, and MAGGIC Risk Calculator (AUC: 0.366, 0.642, and 0.277, P < 0.001, 0.002, and <0.001, respectively) was observed. Seattle Heart Failure Model had non-significant reduction in its acuity (AUC: 0.597; P = 0.24). CONCLUSIONS: The accuracy of the aforementioned scores to predict major events in patients with heart failure is significantly reduced when they are applied to patients included in a multidisciplinary heart failure management programme.

Clinical impact of MultiPoint pacing in responders to cardiac resynchronization therapy.

BACKGROUND: Cardiac resynchronization therapy demonstrated benefits in heart failure. However, only 60-70% are responders and only 22% are super-responders. MultiPoint pacing (MPP) improves structural remodeling, but data in responder patients is scarce. METHODS: A prospective, randomized study of the efficacy of MPP was conducted in patients who were CRT responders after 6 months of bi-ventricular (BiV) therapy. At 6 months, responder patients (LV end-systolic volume [LVESV] reduction ≥15%) were randomized to either continued BiV therapy or to MPP programmed with wide anatomical separation ≥30 mm, and followed until 12 months. Efficacy was determined by 6-12 month changes in LVESV and LV ejection fraction (LVEF). Evaluations of super-responder rate (LVESV reduction ≥30%) and quality of life (NYHA, EQ-5D, MLHFQ) were also performed. RESULTS: From February 2017 to February 2019, 73 CRTs with Quartet LV leads were implanted (42.9% female, 65.7 ± 10.8 years old, 79.5% dilated cardiomyopathy). At 6 months, 74.2% responded to BiV and were randomized to BiV (n = 25) or MPP (n = 24). MPP versus BiV delivered greater LVESV improvement (8.3% decrease in MPP vs. 10.3% increase in BiV patients, p = .047), greater increase in LVEF (7.7% vs. 1.8%, p = .008), and higher 0-12 month super-responder rate (86.4% vs. 56.0%, p = .027). More MPP vs. BiV patients experienced an improvement in NYHA (84.6% vs. 50.0%, p = .047) and EQ-5D (94.4% vs. 54.0%, p = .006). CONCLUSIONS: MPP with wide anatomical spacing in CRT responder patients resulted in improved LV reverse remodeling with higher rates of super-responders, and better quality of life metrics.

Angiotensin-converting enzyme inhibitors and angiotensin-receptor blockers and the risk of COVID-19 infection or severe disease: Systematic review and meta-analysis.

OBJECTIVE: Animal studies suggested that angiotensin-converting enzyme inhibitors (ACEi) and angiotensin-receptor blockers (ARB) facilitate the inoculation of potentially leading to a higher risk of infection and/or disease severity. We aimed to systematically evaluate the risk of COVID-19 infection and the risk of severe COVID-19 disease associated with previous exposure to (ACEi) and/or ARB). METHODS: MEDLINE, CENTRAL, PsycINFO, Web of Science Core Collection were searched in June 2020 for controlled studies. Eligible studies were included and random-effects meta-analyses were performed. The estimates were expressed as odds ratios (OR) and 95% confidence intervals (95%CI). Heterogeneity was assessed with I2 test. The confidence in the pooled evidence was appraised using the GRADE framework. RESULTS: Twenty-seven studies were included in the review. ACEi/ARB exposure did not increase the risk of having a positive test for COVID-19 infection (OR 0.99, 95%CI 0.89-1.11; I2 = 36%; 5 studies, GRADE confidence moderate). The exposure to ACEi/ARB did not increase the risk of all-cause mortality among patients with COVID-19 (OR 0.91, 95%CI 0.74-1.11; I2 = 20%; 17 studies; GRADE confidence low) nor severe/critical COVID-19 disease (OR 0.90, 95%CI 0.74-1.11; I2 = 55%; 17 studies; GRADE confidence very low). Exploratory analyses in studies enrolling hypertensive patients showed a association of ACEi/ARB with a significant decrease of mortality risk. CONCLUSIONS: ACEi/ARB exposure does not seem to increase the risk of having the SARS-CoV-2 infection or developing severe stages of the disease including mortality. The potential benefits observed in mortality of hypertensive patients reassure safety, but robust studies are required to increase the confidence in the results.