Search

Venoarterial extracorporeal membrane oxygenation (VA ECMO) is a form of temporary mechanical circulatory support and simultaneous extracorporeal gas exchange for acute cardiorespiratory failure, including refractory cardiogenic shock (CS) and cardiac arrest (CA). Few studies have assessed predictors of successful weaning (SW) from VA ECMO. This systematic review and meta-analysis aimed to identify a multiparameter strategy associated with SW from VA ECMO. PubMed and the Cochrane Library and the International Clinical Trials Registry Platform were searched. Studies reporting adult patients with CS or CA treated with VA ECMO published from the year 2000 onwards were included. Primary outcomes were hemodynamic, laboratory, and echocardiography parameters associated with a VA ECMO SW. A total of 11 studies (n=653) were included in this review. Pooled VA ECMO SW was 45% (95%CI: 39–50%, I2 7%) and in-hospital mortality rate was 46.6% (95%CI: 33–60%; I2 36%). In the SW group, pulse pressure [MD 12.7 (95%CI: 7.3–18) I2 = 0%] and mean blood pressure [MD 20.15 (95%CI: 13.8–26.4 I2 = 0) were higher. They also had lower values of creatinine [MD –0.59 (95%CI: –0.9 to –0.2) I2 = 7%], lactate [MD –3.1 (95%CI: –5.4 to –0.7) I2 = 89%], and creatine kinase [–2779.5 (95%CI: –5387 to –171) I2 = 38%]. And higher left and right ventricular ejection fraction, MD 17.9% (95%CI: –0.2–36.2) I2 = 91%, and MD 15.9% (95%CI 11.9–20) I2 = 0%, respectively. Different hemodynamic, laboratory, and echocardiographic parameters were associated with successful device removal. This systematic review demonstrated the relationship of multiparametric assessment on VA ECMO SW. [ABSTRACT FROM AUTHOR]

Background and Aims: Atrial fibrillation frequently occurs in the postoperative period of cardiac surgery, associated with an increase in morbidity and mortality. The scores POAF, CHA2DS2-VASc and HATCH demonstrated a validated ability to predict atrial fibrillation after cardiac surgery (AFCS). The objective is to develop and validate a risk score to predict AFCS from the combination of the variables with highest predictive value of POAF, CHA2DS2-VASc and HATCH models.Methods: We conducted a single-center cohort study, performing a retrospective analysis of prospectively collected data. The study included consecutive patients undergoing cardiac surgery in 2010-2016. The primary outcome was the development of new-onset AFCS. The variables of the POAF, CHA2DS2-VASc and HATCH scores were evaluated in a multivariate regression model to determine the predictive impact. Those variables that were independently associated with AFCS were included in the final model.Results: A total of 3113 patients underwent cardiac surgery, of which 21% presented AFCS. The variables included in the new score COM-AF were: age (≥75: 2 points, 65-74: 1 point), heart failure (2 points), female sex (1 point), hypertension (1 point), diabetes (1 point), previous stroke (2 points). For the prediction of AFCS, COM-AF presented an AUC of 0.78 (95% CI 0.76-0.80), the rest of the scores presented lower discrimination ability (P < 0.001): CHA2DS2-VASc AUC 0.76 (95% CI 0.74-0.78), POAF 0.71 (95% CI 0.69-0.73) and HATCH 0.70 (95% CI: 0, 67-0.72). Multivariable analysis demonstrated that COM-AF score was an independent predictor of AFCS: OR 1,91 (IC 95% 1,63-2,23).Conclusion: From the combination of variables with higher predictive value included in the POAF, CHA2DS2-VASc, and HATCH scores, a new risk model system called COM-AF was created to predict AFCS, presenting a greater predictive ability than the original ones. Being necessary future prospective validations. [ABSTRACT FROM AUTHOR]

Copyright of Revista Argentina de Cardiología is the property of Sociedad Argentina de Cardiologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction: High leuko-glycaemic index (LGI) (> 2000) has been associated with poor prognosis in many critical care settings. However, there is no evidence of LGI's prognostic value in the postoperative period of coronary artery bypass grafting (CABG). This study aims to analyze the prognostic value of LGI in the postoperative period of CABG. Methods: Single-center retrospective analysis of prospectively collected data was performed. Consecutive adult patients undergoing CABG between 2007 and 2019 were included. Blood glucose levels and white blood cells count were evaluated in the immediate postoperative period. LGI was calculated by multiplying both values and dividing them by 1,000 and analyzed in quartiles. Receiver operating characteristic curve was used to determine the best cutoff value. The primary combined endpoint was in-hospital mortality, low cardiac output (LCO), or acute kidney injury (AKI). Secondary endpoints included in-hospital death, AKI, atrial fibrillation, and LCO. Results: The study evaluated 3,813 patients undergoing CABG (88.5% male, 89.8% off-pump surgery, aged 64.6 years [standard deviation 9.6]). The median of LGI was 2,035. Presence of primary endpoint significantly increased per LGI quartile (9.2%, 9.7%, 11.8%, and 15%; P<0.001). High LGI was associated with increased occurrence of in-hospital mortality, LCO, AKI, and atrial fibrillation. The best prognostic cutoff value for primary endpoint was 2,000. In a multivariate logistic regression model, high LGI was independently associated with in-hospital death, LCO, or AKI. Conclusion: High LGI was an independent predictor of inhospital mortality, LCO, or AKI in postoperative period of CABG. It was also associated with higher in-hospital death. [ABSTRACT FROM AUTHOR]

Copyright of Medicina (Buenos Aires) is the property of Medicina (Buenos Aires) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction; Postoperative atrial fibrillation (POAFib) occurs in 20 to 40% of patients following cardiac surgery, and is associated with an increased perioperative morbidity and mortality. We aimed to develop and validate a simple clinical risk model for the prediction of POAFib after cardiac surgery. Methods; An analytical single center retrospective cohort study was conducted, including consecutive patients undergoing cardiac surgery between 2004 and 2017 with POAFib. To create the predictive risk score, a logistic regression model was performed using a random sample of 75% of the population. Coefficients of the model were then converted to a numerical risk score, and three groups were defined: low risk (≤1 point), intermediate risk (2-5 points) and high risk (≥6 points). The score was validated using the remaining 25% of the patients. Discrimination was evaluated through the area under the curve (AUC) ROC, and calibration using the Hosmer-Lemeshow (HL) test, calibration plots, and ratio of expected and observed events (E/O). Results; Six thousand five hundred nine patients underwent cardiac surgery: 52% coronary artery bypass grafting (CABG), 20% valve surgery, 14% combined (CABG and valve surgery) and 12% other. New-onset AF occurred in 1222 patients (18.77%). In the multivariate analysis, age, use of cardiopulmonary bypass pump, severe reduction in left ventricular ejection fraction (LVEF), chronic renal disease and heart failure were independent risk factors for POAFib, while the use of statins was a protective factor. The NOPAF score was calculated by adding points for each independent risk predictor. In the derivation cohort, the AUC was 0.71 (CI95% 0.69-0.72), and in the validation cohort the model also showed good discrimination (AUC 0.67 IC 0.64-0.70) and excellent calibration (HL P = 0.24). The E/O ratio was 1 (CI 95%: 0.89-1.12). According to the risk category, POAFib occurred in 5% of low; 11% of intermediate and 27.7% of high risk patients in the derivation cohort (P <0.001), and 5.7%; 12.6%; and 23.6% in the validation cohort respectively (P <0.001) Conclusion: From a large hospitalized population, we developed and validated a simple risk score named NOPAF, based on clinical variables that accurately stratifies the risk of POAFib. This score may help to identify high-risk patients prior to cardiac surgery, in order to strengthen postoperative atrial fibrillation prophylaxis. [ABSTRACT FROM AUTHOR]

Objectives: Veno-arterial Extracorporeal membrane oxygenation (VA ECMO) is a salvage intervention in patients with cardiogenic shock (CS), and cardiac arrest (CA) refractory to standard therapies. The design of ECMO Teams has achieved the standardization of processes, although its impact on survival and prognosis is unknown., Objective: We aimed to analyze whether the creation of an ECMO Team has modified the prognosis of patients undergoing VA ECMO for refractory CS or CA., Materials and Methods: . We conducted a single-center retrospective cohort study. Patients with refractory CS or CA who underwent VA ECMO were divided in two consecutive periods: from 2014 to April 2019 (pre-ECMO T) and from May 2019 to December 2022 (Post ECMO T). The main outcomes were survival on ECMO, in-hospital survival, complications, and annual ECMO volume., Results: Eighty-three patients were included (36 pre-ECMO T and 47 post-ECMO T). The mean age was 53 +/-13 years. The most common reason for device indication was different: postcardiotomy shock (47.2%) pre-ECMO T and refractory cardiogenic shock (29.7%) post-ECMO T. The rate of extracorporeal cardiopulmonary resuscitation was 14.5%. The median duration of VA ECMO was longer after ECMO team implementation: 8 days (IQR 5-12.5) vs. five days (IQR 2-9, p=0.04). Global in-hospital survival was 45.8% (38.9% pre-ECMO T vs. 51.1% post-ECMO T; p=0.37), and the survival rate from VA ECMO was 60.2% (55.6% pre-ECMO T vs 63.8% post-ECMO T; p= 0.50). The volume of VA ECMO implantation was significantly higher in the post-ECMO team period (13.2 +/3.5 per year vs. 6.5 +/-3.5 per year, p: 0.02). The rate of complications was similar in both groups., Conclusions: After the implementation of an ECMO team, there was no statistical difference in the survival rate of patients treated with VA ECMO. However, a significant increase in the number of patients supported per year was observed after the implementation of this multidisciplinary team. Post-ECMO T, the most common reason for device indication was cardiogenic shock, with longer run times and a higher rate of extracorporeal cardiopulmonary resuscitation., Competing Interests: Conflictos de interés Ninguno

Adherence to cardiovascular medications following acute coronary syndrome hospitalization is generally poor. The primary outcome was to demonstrate that the use of a digital application for smartphones increases the adherence to pharmacological treatment by 30 % in relation to the group without intervention, in patients with an acute coronary syndrome with or without ST segment elevation. In this unicentric, single blinded, randomized controlled trial with 1:1 allocation we compared the use of a digital application for smartphones and written information as standard of care, for the adherence to pharmacological treatment in 90 patients admitted to the hospital with an acute coronary syndrome. Adherence to medical treatment was measured by Morisky Medication Adherence Scale. A patient is considered to have good adherence when score is perfect (8 points). The follow up period was 90 days after hospital discharge. The mean age of the population was 63 ± 9 and 76% were male. At 90 days, 67.4% (31/46) of patients using the smartphone application were adherent compared with 20.5% (9/44) of patients in the control group (p < 0.001). In patients with acute coronary syndrome, the use of a smartphone application increased the medication adherence compared with the standard of care.

Introduction: Postoperative atrial fibrillation (POAFib) occurs in 20 to 40% of patients following cardiac surgery, and is associated with an increased perioperative morbidity and mortality. We aimed to develop and validate a simple clinical risk model for the prediction of POAFib after cardiac surgery., Methods: An analytical single center retrospective cohort study was conducted, including consecutive patients undergoing cardiac surgery between 2004 and 2017 with POAFib. To create the predictive risk score, a logistic regression model was performed using a random sample of 75% of the population. Coefficients of the model were then converted to a numerical risk score, and three groups were defined: low risk (≤1 point), intermediate risk (2-5 points) and high risk (≥6 points). The score was validated using the remaining 25% of the patients. Discrimination was evaluated through the area under the curve (AUC) ROC, and calibration using the Hosmer-Lemeshow (HL) test, calibration plots, and ratio of expected and observed events (E/O)., Results: Six thousand five hundred nine patients underwent cardiac surgery: 52% coronary artery bypass grafting (CABG), 20% valve surgery, 14% combined (CABG and valve surgery) and 12% other. New-onset AF occurred in 1222 patients (18.77%). In the multivariate analysis, age, use of cardiopulmonary bypass pump, severe reduction in left ventricular ejection fraction (LVEF), chronic renal disease and heart failure were independent risk factors for POAFib, while the use of statins was a protective factor. The NOPAF score was calculated by adding points for each independent risk predictor. In the derivation cohort, the AUC was 0.71 (CI95% 0.69-0.72), and in the validation cohort the model also showed good discrimination (AUC 0.67 IC 0.64-0.70) and excellent calibration (HL P = 0.24). The E/O ratio was 1 (CI 95%: 0.89-1.12). According to the risk category, POAFib occurred in 5% of low; 11% of intermediate and 27.7% of high risk patients in the derivation cohort (P <0.001), and 5.7%; 12.6%; and 23.6% in the validation cohort respectively (P <0.001)., Conclusion: From a large hospitalized population, we developed and validated a simple risk score named NOPAF, based on clinical variables that accurately stratifies the risk of POAFib. This score may help to identify high-risk patients prior to cardiac surgery, in order to strengthen postoperative atrial fibrillation prophylaxis.

Antecedentes Y Objetivos: El sistema de calificación APACHE II permite predecir la mortalidad intrahospitalaria en terapia intensiva. Sin embargo, no está validado para cirugía cardíaca, ya que no posee buena capacidad diferenciadora. El objetivo es determinar el valor pronóstico de APACHE II en el postoperatorio de procedimientos cardíacos., Materiales Y Métodos: Se analizó en forma retrospectiva la base de cirugía cardíaca. Se incluyó a pacientes intervenidos entre 2017 y 2018, de los cuales se calculó la puntuación APACHE II. Se utilizó curva ROC para determinar el mejor valor de corte. El punto final primario fue mortalidad intrahospitalaria. Como puntos finales secundarios se evaluó la incidencia de bajo gasto cardíaco (BGC), accidente cerebrovascular (ACV), sangrado quirúrgico y necesidad de diálisis. Se realizó un modelo de regresión logístico multivariado para ajustar a las variables de interés., Resultados: Se analizó a 559 pacientes. La media del sistema de calificación APACHE II fue de 9.9 (DE 4). La prevalencia de mortalidad intrahospitalaria global fue de 6.1%. El mejor valor de corte de la calificación para predecir mortalidad fue de 12, con un área bajo la curva ROC de 0.92. Los pacientes con APACHE II ≥ 12 tuvieron significativamente mayor mortalidad, incidencia de BGC, ACV, sangrado quirúrgico y necesidad de diálisis. En un modelo multivariado, el sistema APACHE II se relacionó de modo independiente con mayor tasa de mortalidad intrahospitalaria (OR, 1.14; IC95%, 1.08-1.21; p < 0.0001)., Conclusiones: El sistema de clasificación APACHE II demostró ser un predictor independiente de mortalidad intrahospitalaria en pacientes que cursan el postoperatorio de cirugía cardíaca., Background and Objectives: The APACHE II score allows predicting in-hospital mortality in patients admitted to intensive care units. However, it is not validated for patients undergoing cardiac surgery, since it does not have a good discriminatory capacity in this clinical scenario. The aim of this study is to determine prognostic value of APACHE II score in postoperative of cardiac surgery., Materials and Methods: The study was performed using the cardiac surgery database. Patients undergoing surgery between 2017 and 2018, with APACHE II score calculated at the admission, were included. The ROC curve was used to determine a cut-off value The primary endpoint was in-hospital death. Secondary endpoints included low cardiac output (LCO), stroke, surgical bleeding, and dialysis requirement. A multivariable logistic regression model was developed to adjust to various variables of interest., Results: The study evaluated 559 patients undergoing cardiac surgery. The mean of APACHE II Score was 9.9 (SD 4). The prevalence of in-hospital death was 6.1%. The best prognostic cut-off value for the primary endpoint was 12, with a ROC curve of 0.92. Patients with an APACHE II score greater than or equal to 12 had significantly higher mortality, higher incidence of LCO, stroke, surgical bleeding and dialysis requirement. In a multivariate logistic regression model, the APACHE II score was independently associated with higher in-hospital death (OR, 1.14; 95CI%, 1.08-1.21; p < 0.0001)., Conclusions: The APACHE II Score proved to be an independent predictor of in-hospital death in patients undergoing postoperative cardiac surgery, with a high capacity for discrimination., (Copyright: © 2020 Permanyer.)