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Evaluation of biomarkers and use of echocardiography in survival prognosis post cardio-respiratory arrest
148
Abstracts / Resuscitation 96S (2015) 43–157
AP255
AP256
Neurological prognostication in out of hospital cardiac arrest: Which role for lactate clearance?
Looking a “metabolic watch”. The analytical parameters found at the beginning of the resuscitation are predictors of the neurological prognostic in the prehospital cardiac arrest
Michele Zuliani 1,∗ , Francesca Verginella 1 , Alberto Peratoner 2 , Erik Roman-Pognuz 2 , Alice Scamperle 1 , Perla Rossini 1 , Margarita Nieto Yabar 1 , Marco Crisman 1 , Alice Pravisani 1 , Vincenzo Campanile 3 , Giorgio Berlot 2
Ervigio Corral ∗ , Isabel Casado, María José García-Ochoa, Rosa Suárez SAMUR P. Civil, Madrid, Spain
1
Università degli studi di Trieste, Trieste, Italy 2 DMPTIE, Trieste, Italy 3 Servizio di Emergenza Territoriale, ASS1, Trieste, Italy Purpose of the study: Cardiac arrest (CA) is an important cause of death and disability. With the standardized use of target temperature management and on going sedation for 48–72 h, early prognostication after CA is a challenge. The pathophysiology of post CA syndrome is a systemic ischemia/reperfusion response called sepsis-like syndrome.1 Early serum lactate clearance (LC) and lower serum lactate levels have been shown to be associated with decreased mortality in a diverse set of critical illnesses2 : why don’t use LC as a prognostic factor of neurological outcome? We analysed the reliability of serum LC as a predictor in patients treated with therapeutic hypothermia after out of hospital CA. Material and methods: through a retrospective analysis of 60 patients admitted to our ICU, we analysed the lactate-level (mg/dl) at ICU admission and after 24 h, then we evaluated the lactate clearance. The LC was calculated as follows: 24-h LC (%) = (0 h lactate − 24 h lactate)/0 h lactate × 100. Neurological outcome has been evaluated at 6 month using the Pittsburgh Cerebral Performance Category Scale (CPC). Results: the median value of lactate at T0 was 26.35 (15.9–65.1); the median value of lactate at T24 was 17.3 (10.15–24.6). 32 patients had a good neurological outcome (CPC 1–2). 28 patients had a bad neurological outcome (CPC 3–5). In the CPC1-2 group the median LC was 73% (−10% to 179%), in the CPC3-5 group the median LC was 74% (17%–114%). The comparison of LC between the two group showed a p-value of 0.7 Conclusions: there is no correlation for LC in the first 24 h after CA between both groups. This conclusion is in contrast with current evidence based in literature.3 Despite Lactacidemia is a sign of microcirculatory damage, our study shows that LC cannot be used to predict the neurological outcome. References 1. Nolan, et al. Post-cardiac arrest syndrome. Resuscitation 2008:79. 2. Starodub, et al. Association of serum lactate and survival outcomes in patients undergoing TH after CA. Resuscitation 2013. 3. Donnino, et al. Initial lactate and lactate change in post-cardiac arrest: a multicentre validation study. Crit Care Med 2014.
http://dx.doi.org/10.1016/j.resuscitation.2015.09.352
Introduction: The uncertainty of the time of the cardiac arrest is one of the specific difficulties for staff of the Emergency Medical Services. Clinical signs and pupillary values, ECG rhythm, etc., help to value, but none is completely reliable. Objective: Analyze what analytical parameters can become good predictors of neurological outcome, in order to achieve a “metabolic clock” for the medical staff on the scene. Methodology: Analytical observation study. Population: cohort of patients with cardiac arrest, attended by an EMS. Years: 2012–2014. Epidemiological variables (age, sex) Explanatory variables: pH, PCO2 , EB, lactate and bicarbonate (previous analytical values at the beginning of resuscitation). Result: Neurological recovery, CPC I–II. Hypothesis testing: ANOVA. To determine the cut-off associated with the ultimate goal, ROC curves were drawn. To associate the independent variables a multivariate analysis was performed using a binary logistic regression model. Odds ratio (OR) and confidence intervals p < 0.05 were estimated. Results: 742 patients, median age – 65 years (IQR 52–78), 79% men. 35.7% have shockable rhythm Area under the curve analytical values: Ph 0.646 (95% CI 0595-0697) p < 0.0001; PCO2 0.366 (95% CI 0,314-0417) p < 0.0001; BE 0.570 (95% CI -0.622-0.518) p = 0.012; Lactate 0.431 (95% CI -0.487-0.376) p = 0.014. The bicarbonate showed no statistical association. The cut-off values with greater sensitivity and specificity in the logistic regression were: Ph = 7.07; PCO2 = 54.65; BE = −10.7; Lactate = 4.3. In the logistic regression model as independent variables are associated to recovery “ad integrum”: pH OR: 2.16 (95% CI −3.8 1.21) p = 0.008 and pCO2 : OR: 1.72 (95% CI 1.13 −2.6) p = 0.012. Conclusion: The results enable to take into account these diagnostic parameters (pH and pCO2 ), as “chronological values” for taking decisions regarding the management and prognosis of patients in the prehospital cardiac arrest. http://dx.doi.org/10.1016/j.resuscitation.2015.09.353 AP257 Evaluation of biomarkers and use of echocardiography in survival prognosis post cardio-respiratory arrest Antoniu Petris, Didona Ungureanu, Tudor Ovidiu Popa, Irina Costache, Diana Cimpoesu ∗ UMF “Gr. T. Popa”, Iasi, Romania Information on biomarkers dynamics during and immediately after cardiopulmonary resuscitation (CPR) are limited and fragmented. Along with clinical data, some biomarkers and intracardiac volume changes assessed by transthoracic echocardiography can provide important prognostic information especially if measurements are made early, even at the event. Objectives: The objective of the current study (RESSUR) is to analyse the dynamics (during and post-CPR) of biochemical markers (myoglobin, CK-MB, troponin I, NT-BNP/BNP, D-dimers, high-sensitivity C-reactive protein, serum ions, glycaemia, lactate and base deficit), markers of ischemia/reperfusion (cytochrome-c,
Abstracts / Resuscitation 96S (2015) 43–157
interleukin 6) and echocardiography to quantify how these variables can help to predict the evolution of patients who developed cardiac arrest. Method: In this study we prospectively analysed a sample of 47 patients with cardio-respiratory arrest, presented consecutively in the Emergency Unit of the Clinical Emergency County Hospital “St. Spiridon” in the period 1 January to 15 July 2014. Data were collected and analysed using specialized statistical software (SPSS 20.0). Results: Lot analysed included a 70.2% percentage of male patients, the average age in the study group was 65.66 ± 15.45 years. CPC score 4 was the most common 53.19%, initial rhythm was asystole-bradyarrhythmia (48.945) and pulseless electrical activity in 14.89%. RCP duration was 21.19 ± 10.98 min, cardiopulmonary arrest occurred frequently in the patient’s home only 63.83%. On 95.74% achieved return to spontaneous circulation (ROSC) and of these, 9 patients survived to hospital discharge. The study reveals statistically significant differences between patients who died or not in terms of CPC score (p = 0.031), duration CPR (p = 0.045), syncope onset event (p = 0.035), performing mouth-to-mouth ventilation (p = 0.041), echocardiographic parameters of the presence of aortic stenosis (p = 0.032) and inferior vena cava diameter as a marker of hypovolemic status (p < 0.001), and during CPR: administration of epinephrine (p = 0.002), amiodarone (p = 0.006) and performing coronary angiography (p = 0.039). Conclusions: Assessing the role of inflammatory markers (interleukin-6 and hsCRP) and apoptosis (cytochrome c) in determining prognosis (survival and neurologic) showed no statistically significant relationship. Although well-known difficulties, the study in cardiac arrest patient is the only way to improve survival in this patient population. http://dx.doi.org/10.1016/j.resuscitation.2015.09.354
Simulation AP258 Innovative media technology for recognition of cardiac arrest Patrick Chow-In Ko 1,∗ , Jie-Zhi Cheng 1 , Yuan-Hsiang Lin 2 1
Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan 2 Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan Purpose: Recognition of cardiac arrest with checking carotid pulse is less than a half correct by the public. Poor recognition of cardiac arrest or patient of agonizing situation delays early bystander cardiopulmonary resuscitation (BCPR) that should be critically provided in the first five minutes before emergency ambulance arrival. Globally we still lack of effective technology to assist better recognition of cardiac arrest to facilitate early BCPR and public access defibrillation (PAD). In this study, we aim to innovate a video signals analysis tool to assist recognition of cardiac arrest. Method: We designed an innovative skill algorithm for transforming and analysing the signals of the video recordings filmed with mobile smartphone for part of human body. Fast Fourier Transform (FFT) signals were evaluated in our skill algorithm. The time length for each video recording was fifteen seconds, which was filmed within the first five minutes after cardiac arrest witnessed in the intensive care unit. This signal analysis skill algorithm
149
was applied on the video recordings of cardiac arrest patients and compared with that of normal volunteers. Results: We applied our skill algorithm analysis on video segments from twenty cardiac arrest patients (asystole for 18, ventricular fibrillation for 2) and twenty non-arrest volunteers (median heart rate 74/min, IQR 65–88/min), matched in age and sex. We innovated a mathematic formula to calculate a value (we called it Slope Alfa) mainly from the cluster of FFT signals evaluated by the skill algorithm. The Slope Alfa value (Mean, [SD]) of cardiac arrest patients was significantly different from the value of non-arrest volunteers (0.14, [0.09] vs 1.96, [0.37], p < 0.01). The results also indicated a tendency that for cardiac arrest patient the Slope Alfa would be less than 1.0. Conclusions: The skill algorithm we innovated for smartphone video signals analysis may successfully recognize patient after cardiac arrest. http://dx.doi.org/10.1016/j.resuscitation.2015.09.355 AP259 Assessment of the management of a sudden cardiac arrest (CA) in primary care setting by means of high-fidelity simulation Antonio Casal Sanchez 1,∗ , Luis Sanchez Santos 1 , ˜ 2 , Jose Flores Arias 1 , Antonio Rodriguez Nunez Antonio Iglesias Vazquez 1 1 2
Emergencies Medical System, Galicia, Spain University Hospital of Santiago, Galicia, Spain
Purpose: To assess the management of the cardiac arrest (CA) secondary to a ventricular fibrillation (VF), in the primary care setting. Material and methods: A simulated clinical scenario of a CA with a shockable rhythm (VF) was designed and performed by sanitary personnel of primary care, throughout Laerdal SimMan 3G® high fidelity simulator system. Audio and video were recorded throughout the Laerdal Advanced Video System® , and systematically reviewed after the period of the studio was completed. The main outcomes were: to identify the CA, to identify the rhythm, mean time to identify the CA, time to initiate chest compressions (CC), quality of chest compressions (including rate and depth, and time elapsed from the recognition of the VF to the first shock. Results: 52 emergency teams (crew: 3–4) were included. The results are presented as % of the total. 100% recognized CA, the first rhythm was adequately identified as VF by the 78,84%. Mean time to identify the CA was 10.96 s. The time ellapsed from the recognition of the CA to the first CC provided was 43.56 s. Mean CC rate was 110,82 per minute, and mean of depth compressions 37.34 mm. Time elapsed from the recognition of the VF to the first shock was 94.27 s. Conclusion: Despite they recognize adequately both the CA and the rhythm, the sanitary personnel of primary care, took too much time to initiate the CC and to deliver the shock. In addition, the CC provided were far away from the minimal depth recommended. High fidelity simulation can be useful to address specifically the training programs, to optimize the management of CA by the sanitary personnel. http://dx.doi.org/10.1016/j.resuscitation.2015.09.356
Abstracts / Resuscitation 96S (2015) 43–157
AP255
AP256
Neurological prognostication in out of hospital cardiac arrest: Which role for lactate clearance?
Looking a “metabolic watch”. The analytical parameters found at the beginning of the resuscitation are predictors of the neurological prognostic in the prehospital cardiac arrest
Michele Zuliani 1,∗ , Francesca Verginella 1 , Alberto Peratoner 2 , Erik Roman-Pognuz 2 , Alice Scamperle 1 , Perla Rossini 1 , Margarita Nieto Yabar 1 , Marco Crisman 1 , Alice Pravisani 1 , Vincenzo Campanile 3 , Giorgio Berlot 2
Ervigio Corral ∗ , Isabel Casado, María José García-Ochoa, Rosa Suárez SAMUR P. Civil, Madrid, Spain
1
Università degli studi di Trieste, Trieste, Italy 2 DMPTIE, Trieste, Italy 3 Servizio di Emergenza Territoriale, ASS1, Trieste, Italy Purpose of the study: Cardiac arrest (CA) is an important cause of death and disability. With the standardized use of target temperature management and on going sedation for 48–72 h, early prognostication after CA is a challenge. The pathophysiology of post CA syndrome is a systemic ischemia/reperfusion response called sepsis-like syndrome.1 Early serum lactate clearance (LC) and lower serum lactate levels have been shown to be associated with decreased mortality in a diverse set of critical illnesses2 : why don’t use LC as a prognostic factor of neurological outcome? We analysed the reliability of serum LC as a predictor in patients treated with therapeutic hypothermia after out of hospital CA. Material and methods: through a retrospective analysis of 60 patients admitted to our ICU, we analysed the lactate-level (mg/dl) at ICU admission and after 24 h, then we evaluated the lactate clearance. The LC was calculated as follows: 24-h LC (%) = (0 h lactate − 24 h lactate)/0 h lactate × 100. Neurological outcome has been evaluated at 6 month using the Pittsburgh Cerebral Performance Category Scale (CPC). Results: the median value of lactate at T0 was 26.35 (15.9–65.1); the median value of lactate at T24 was 17.3 (10.15–24.6). 32 patients had a good neurological outcome (CPC 1–2). 28 patients had a bad neurological outcome (CPC 3–5). In the CPC1-2 group the median LC was 73% (−10% to 179%), in the CPC3-5 group the median LC was 74% (17%–114%). The comparison of LC between the two group showed a p-value of 0.7 Conclusions: there is no correlation for LC in the first 24 h after CA between both groups. This conclusion is in contrast with current evidence based in literature.3 Despite Lactacidemia is a sign of microcirculatory damage, our study shows that LC cannot be used to predict the neurological outcome. References 1. Nolan, et al. Post-cardiac arrest syndrome. Resuscitation 2008:79. 2. Starodub, et al. Association of serum lactate and survival outcomes in patients undergoing TH after CA. Resuscitation 2013. 3. Donnino, et al. Initial lactate and lactate change in post-cardiac arrest: a multicentre validation study. Crit Care Med 2014.
http://dx.doi.org/10.1016/j.resuscitation.2015.09.352
Introduction: The uncertainty of the time of the cardiac arrest is one of the specific difficulties for staff of the Emergency Medical Services. Clinical signs and pupillary values, ECG rhythm, etc., help to value, but none is completely reliable. Objective: Analyze what analytical parameters can become good predictors of neurological outcome, in order to achieve a “metabolic clock” for the medical staff on the scene. Methodology: Analytical observation study. Population: cohort of patients with cardiac arrest, attended by an EMS. Years: 2012–2014. Epidemiological variables (age, sex) Explanatory variables: pH, PCO2 , EB, lactate and bicarbonate (previous analytical values at the beginning of resuscitation). Result: Neurological recovery, CPC I–II. Hypothesis testing: ANOVA. To determine the cut-off associated with the ultimate goal, ROC curves were drawn. To associate the independent variables a multivariate analysis was performed using a binary logistic regression model. Odds ratio (OR) and confidence intervals p < 0.05 were estimated. Results: 742 patients, median age – 65 years (IQR 52–78), 79% men. 35.7% have shockable rhythm Area under the curve analytical values: Ph 0.646 (95% CI 0595-0697) p < 0.0001; PCO2 0.366 (95% CI 0,314-0417) p < 0.0001; BE 0.570 (95% CI -0.622-0.518) p = 0.012; Lactate 0.431 (95% CI -0.487-0.376) p = 0.014. The bicarbonate showed no statistical association. The cut-off values with greater sensitivity and specificity in the logistic regression were: Ph = 7.07; PCO2 = 54.65; BE = −10.7; Lactate = 4.3. In the logistic regression model as independent variables are associated to recovery “ad integrum”: pH OR: 2.16 (95% CI −3.8 1.21) p = 0.008 and pCO2 : OR: 1.72 (95% CI 1.13 −2.6) p = 0.012. Conclusion: The results enable to take into account these diagnostic parameters (pH and pCO2 ), as “chronological values” for taking decisions regarding the management and prognosis of patients in the prehospital cardiac arrest. http://dx.doi.org/10.1016/j.resuscitation.2015.09.353 AP257 Evaluation of biomarkers and use of echocardiography in survival prognosis post cardio-respiratory arrest Antoniu Petris, Didona Ungureanu, Tudor Ovidiu Popa, Irina Costache, Diana Cimpoesu ∗ UMF “Gr. T. Popa”, Iasi, Romania Information on biomarkers dynamics during and immediately after cardiopulmonary resuscitation (CPR) are limited and fragmented. Along with clinical data, some biomarkers and intracardiac volume changes assessed by transthoracic echocardiography can provide important prognostic information especially if measurements are made early, even at the event. Objectives: The objective of the current study (RESSUR) is to analyse the dynamics (during and post-CPR) of biochemical markers (myoglobin, CK-MB, troponin I, NT-BNP/BNP, D-dimers, high-sensitivity C-reactive protein, serum ions, glycaemia, lactate and base deficit), markers of ischemia/reperfusion (cytochrome-c,
Abstracts / Resuscitation 96S (2015) 43–157
interleukin 6) and echocardiography to quantify how these variables can help to predict the evolution of patients who developed cardiac arrest. Method: In this study we prospectively analysed a sample of 47 patients with cardio-respiratory arrest, presented consecutively in the Emergency Unit of the Clinical Emergency County Hospital “St. Spiridon” in the period 1 January to 15 July 2014. Data were collected and analysed using specialized statistical software (SPSS 20.0). Results: Lot analysed included a 70.2% percentage of male patients, the average age in the study group was 65.66 ± 15.45 years. CPC score 4 was the most common 53.19%, initial rhythm was asystole-bradyarrhythmia (48.945) and pulseless electrical activity in 14.89%. RCP duration was 21.19 ± 10.98 min, cardiopulmonary arrest occurred frequently in the patient’s home only 63.83%. On 95.74% achieved return to spontaneous circulation (ROSC) and of these, 9 patients survived to hospital discharge. The study reveals statistically significant differences between patients who died or not in terms of CPC score (p = 0.031), duration CPR (p = 0.045), syncope onset event (p = 0.035), performing mouth-to-mouth ventilation (p = 0.041), echocardiographic parameters of the presence of aortic stenosis (p = 0.032) and inferior vena cava diameter as a marker of hypovolemic status (p < 0.001), and during CPR: administration of epinephrine (p = 0.002), amiodarone (p = 0.006) and performing coronary angiography (p = 0.039). Conclusions: Assessing the role of inflammatory markers (interleukin-6 and hsCRP) and apoptosis (cytochrome c) in determining prognosis (survival and neurologic) showed no statistically significant relationship. Although well-known difficulties, the study in cardiac arrest patient is the only way to improve survival in this patient population. http://dx.doi.org/10.1016/j.resuscitation.2015.09.354
Simulation AP258 Innovative media technology for recognition of cardiac arrest Patrick Chow-In Ko 1,∗ , Jie-Zhi Cheng 1 , Yuan-Hsiang Lin 2 1
Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan 2 Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan Purpose: Recognition of cardiac arrest with checking carotid pulse is less than a half correct by the public. Poor recognition of cardiac arrest or patient of agonizing situation delays early bystander cardiopulmonary resuscitation (BCPR) that should be critically provided in the first five minutes before emergency ambulance arrival. Globally we still lack of effective technology to assist better recognition of cardiac arrest to facilitate early BCPR and public access defibrillation (PAD). In this study, we aim to innovate a video signals analysis tool to assist recognition of cardiac arrest. Method: We designed an innovative skill algorithm for transforming and analysing the signals of the video recordings filmed with mobile smartphone for part of human body. Fast Fourier Transform (FFT) signals were evaluated in our skill algorithm. The time length for each video recording was fifteen seconds, which was filmed within the first five minutes after cardiac arrest witnessed in the intensive care unit. This signal analysis skill algorithm
149
was applied on the video recordings of cardiac arrest patients and compared with that of normal volunteers. Results: We applied our skill algorithm analysis on video segments from twenty cardiac arrest patients (asystole for 18, ventricular fibrillation for 2) and twenty non-arrest volunteers (median heart rate 74/min, IQR 65–88/min), matched in age and sex. We innovated a mathematic formula to calculate a value (we called it Slope Alfa) mainly from the cluster of FFT signals evaluated by the skill algorithm. The Slope Alfa value (Mean, [SD]) of cardiac arrest patients was significantly different from the value of non-arrest volunteers (0.14, [0.09] vs 1.96, [0.37], p < 0.01). The results also indicated a tendency that for cardiac arrest patient the Slope Alfa would be less than 1.0. Conclusions: The skill algorithm we innovated for smartphone video signals analysis may successfully recognize patient after cardiac arrest. http://dx.doi.org/10.1016/j.resuscitation.2015.09.355 AP259 Assessment of the management of a sudden cardiac arrest (CA) in primary care setting by means of high-fidelity simulation Antonio Casal Sanchez 1,∗ , Luis Sanchez Santos 1 , ˜ 2 , Jose Flores Arias 1 , Antonio Rodriguez Nunez Antonio Iglesias Vazquez 1 1 2
Emergencies Medical System, Galicia, Spain University Hospital of Santiago, Galicia, Spain
Purpose: To assess the management of the cardiac arrest (CA) secondary to a ventricular fibrillation (VF), in the primary care setting. Material and methods: A simulated clinical scenario of a CA with a shockable rhythm (VF) was designed and performed by sanitary personnel of primary care, throughout Laerdal SimMan 3G® high fidelity simulator system. Audio and video were recorded throughout the Laerdal Advanced Video System® , and systematically reviewed after the period of the studio was completed. The main outcomes were: to identify the CA, to identify the rhythm, mean time to identify the CA, time to initiate chest compressions (CC), quality of chest compressions (including rate and depth, and time elapsed from the recognition of the VF to the first shock. Results: 52 emergency teams (crew: 3–4) were included. The results are presented as % of the total. 100% recognized CA, the first rhythm was adequately identified as VF by the 78,84%. Mean time to identify the CA was 10.96 s. The time ellapsed from the recognition of the CA to the first CC provided was 43.56 s. Mean CC rate was 110,82 per minute, and mean of depth compressions 37.34 mm. Time elapsed from the recognition of the VF to the first shock was 94.27 s. Conclusion: Despite they recognize adequately both the CA and the rhythm, the sanitary personnel of primary care, took too much time to initiate the CC and to deliver the shock. In addition, the CC provided were far away from the minimal depth recommended. High fidelity simulation can be useful to address specifically the training programs, to optimize the management of CA by the sanitary personnel. http://dx.doi.org/10.1016/j.resuscitation.2015.09.356