Objective: Although ventilator-associated pneumonia (VAP) is a major cause of nosocomial infection, its role in the prognosis of patients remains undefined. The objective of this study was to evaluate the impact of VAP on the clinical evolution of patients. Methods: This was a prospective cohort study involving 233 patients on mechanical ventilation (VAP group, n = 64; control group, n = 169). Primary outcomes were time on mechanical ventilation (TMV), time in ICU (TICU), overall length of hospital stay (LHS) and in-ICU mortality. Secondary outcomes were in-hospital mortality, microbiological profile, prior use of antibiotics and risk factors for VAP acquisition. Results: Control and VAP group outcomes were, respectively, as follows: median TMV (days), 9 (interquartile range [IQR]: 5-15) and 23 (IQR: 15-37; p < 0.0001); median TICU (days), 12 (IQR: 8-21) and 27 (IQR: 17-42; p < 0.0001); median LHS (days), 33 (IQR: 18-64) and 46 (IQR: 25-90; p = 0.05); and in-ICU mortality, 38% (95% CI: 31-45) and 55% (95% CI: 42-67; p = 0.02). VAP was a predictor of in-ICU mortality (OR = 3.40; 95% CI: 1.54-7.48). TMV (OR = 2.27; 95% CI: 1.05-4.87) and prior use of antibiotics (OR = 1.07; 95% CI: 1.04-1.10) were risk factors for VAP. VAP did not affect in-hospital mortality. Acinetobacter spp. was the most common isolate (28%). Inappropriate empirical antibiotic therapy was administered in 48% of cases. Conclusions: In this study, there was a high incidence of infection with resistant bacteria and inappropriate initial antibiotic therapy. Long TMV and prior use of antibiotics are risk factors for VAP.Keywords: Pneumonia, ventilator-associated; Cross infection; Intensive care units; Hospital mortality; Risk factors. ResumoObjetivo: Apesar de representar uma das principais causas de infecção nosocomial, o papel da pneumonia associada à ventilação mecânica (PAVM) no prognóstico ainda permanece indefinido. O objetivo deste estudo foi avaliar o impacto dessa doença na evolução clínica dos pacientes. Métodos: Estabeleceu-se uma coorte prospectiva de 233 pacientes sob ventilação mecânica (grupo PAV, n = 64; grupo controle, n = 169). Os desfechos primários foram tempo de ventilação mecânica (TVM), tempo de permanência na UTI (TUTI), tempo de permanência hospitalar (TH) e mortalidade na UTI. Os desfechos secundários foram mortalidade hospitalar, perfil microbiológico, uso prévio de antibióticos e fatores de risco para PAVM. Resultados: Os desfechos dos grupos controle e PAVM foram, respectivamente, os seguintes: mediana do TVM (dias), 9 (intervalo interquartílico [II]: 5-15) e 23 (II: 15-37; p < 0,0001); mediana do TUTI (dias), 12 (II: 8-21) e 27 (II: 17-42; p < 0,0001); mediana do TH (dias), 33 (II: 18-64) e 46 (II: 25-90; p = 0,02); e mortalidade na UTI, 38% (IC95%: 31-45) e 55% (IC95%: 42-67; p = 0,02). A PAVM foi um preditor de mortalidade na UTI (OR = 3,40; IC95%: 1,78). O TVM (OR = 2,27; IC95%: 1,05-4,87) e o uso prévio de antibióticos (OR = 1,07; IC95%: 1,04-1,10) foram fatores de risco para PAVM. A PAVM não afetou a morta...

Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p &lt; 0.001), lower SBP (p = 0,035) and need of inotropes (p &lt; 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p &lt; 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p &lt; 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p &lt; 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p &lt; 0.001, CI 0.971-0.988), higher urea (OR 1.01, p &lt; 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p &lt; 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p &lt; 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

Funding Acknowledgements Type of funding sources: None. Introduction Patients (pts) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF as predictor of in-hospital M (IHM), post discharge early M [1-month mortality (1mM)] and 1-month readmission (1mRA), in our center population, using real-life data. Methods Based on a single-center retrospective study, data collected from pts admitted in the Cardiology department with AHF between 2010 and 2017. Pts without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used non-parametric tests, logistic regression analysis and ROC curve analysis. Results We included 300 pts admitted with AHF. Mean age was 67.4 ± 12.6 years old and 72.7% were male. 37.7% had previous history of revascularization procedures, 66.9% had hypertension, 41% were diabetic and 38% had dyslipidaemia. Mean heart rate was 95.5 ± 27.5bpm, mean systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, mean urea level at admission was 68.8 ± 40.7mg/dL, mean sodium was 137.6 ± 4.7mmol/L, mean glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. Mean ACTION-ICU score was 10.4 ± 2.3. Inotropes’ usage was necessary in 32.7% of the pts, 11.3% of the pts needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the pts were readmitted 1 month after discharge. Older age (p &lt; 0.001), lower SBP (p = 0,035), presenting in KKC 4 (p &lt; 0.001, OR 8.13) and need of inotropes (p &lt; 0.001) were predictors of IHM in our population. Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p &lt; 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the studied variables were predictive of need of IV. LVEF (OR 0.924, p &lt; 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p &lt; 0.001, CI 0.971-0.988), higher urea (OR 1.01, p &lt; 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors inotropes’ usage. ACTION-ICU was able to predict IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed ACTION-ICU performs well when predicting IHM (Area under curve (AUC) 0.729, confidence interval (CI) 0.59-0.87), inotropes’ usage (AUC 0.619, CI 0.54-0.70) and 1mM (AUC 0.705, CI 0.58-0.84). Conclusion In our population, ACTION-ICU score was able to predict IHM, 1mM and inotropes’s usage.

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