Perioperative cardiac arrest and its mortality in children. A 9-year survey in a Brazilian tertiary teaching hospital

Background: the incidence of perioperative cardiac arrest and mortality in children is higher than in adults. This survey evaluated the incidence, causes, and outcome of perioperative cardiac arrests in a pediatric surgical population in a tertiary teaching hospital between 1996 and 2004.Methods: the incidence of cardiac arrest during anesthesia was identified from an anesthesia database. During the study period, 15 253 anesthetics were performed in children. Data collected included patient demographics, surgical procedures (elective, urgent, or emergency), ASA physical status classification, anesthesia provider information, type of surgery, surgical areas, and outcome. All cardiac arrests were reviewed and grouped by the cause of arrest and death into one of four groups: totally anesthesia-related, partially anesthesia-related, totally surgery-related, or totally child disease or condition-related.Results: There were 35 cardiac arrests (22.9 : 10 000) and 15 deaths (9.8 : 10 000). Major risk factors for cardiac arrest were neonates and children under 1 year of age (P < 0.05) with ASA III or poorer physical status (P < 0.05), in emergency surgery (P < 0.05), and general anesthesia (P < 0.05). Child disease/condition was the major cause of cardiac arrest or death (P < 0.05). There were seven cardiac arrests because of anesthesia (4.58 : 10 000) - four totally (2.62 : 10 000) and three partially related to anesthesia (1.96 : 10 000). There were no anesthesia attributable deaths reported. The main causes of anesthesia attributable cardiac arrest were respiratory events (71.5%) and medication-related events (28.5%).Conclusions: Perioperative cardiac arrests were relatively higher in neonates and infants than in older children with severe underlying disease and during emergency surgery. The fact that all anesthesia attributable cardiac arrests were related to airway management and medication administration is important in prevention strategies.

Intraoperative Cardiac Arrest and Mortality in Trauma Patients. A 14-Yr Survey from a Brazilian Tertiary Teaching Hospital

Background: Little information on the factors influencing intraoperative cardiac arrest and its outcomes in trauma patients is available. This survey evaluated the associated factors and outcomes of intraoperative cardiac arrest in trauma patients in a Brazilian teaching hospital between 1996 and 2009.Methods: Cardiac arrest during anesthesia in trauma patients was identified from an anesthesia database. The data collected included patient demographics, ASA physical status classification, anesthesia provider information, type of surgery, surgical areas and outcome. All intraoperative cardiac arrests and deaths in trauma patients were reviewed and grouped by associated factors and also analyzed as totally anesthesia-related, partially anesthesia-related, totally surgery-related or totally trauma patient condition-related.Findings: Fifty-one cardiac arrests and 42 deaths occurred during anesthesia in trauma patients. They were associated with male patients (P<0.001) and young adults (18-35 years) (P = 0.04) with ASA physical status IV or V (P<0.001) undergoing gastroenterological or multiclinical surgeries (P<0.001). Motor vehicle crashes and violence were the main causes of trauma (P<0.001). Uncontrolled hemorrhage or head injury were the most significant associated factors of intraoperative cardiac arrest and mortality (P<0.001). All cardiac arrests and deaths reported were totally related to trauma patient condition.Conclusions: Intraoperative cardiac arrest and mortality incidence was highest in male trauma patients at a younger age with poor clinical condition, mainly related to uncontrolled hemorrhage and head injury, resulted from motor vehicle accidents and violence.

Pediatric Perioperative Cardiac Arrest and Mortality: A Study From a Tertiary Teaching Hospital

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Postreperfusion cardiac arrest and resuscitation during orthotopic liver transplantation: dynamic visualization and analysis of physiologic recordings

We recently reported on the Multi Wave Animator (MWA), a novel open-source tool with capability of recreating continuous physiologic signals from archived numerical data and presenting them as they appeared on the patient monitor. In this report, we demonstrate for the first time the power of this technology in a real clinical case, an intraoperative cardiopulmonary arrest following reperfusion of a liver transplant graft. Using the MWA, we animated hemodynamic and ventilator data acquired before, during, and after cardiac arrest and resuscitation. This report is accompanied by an online video that shows the most critical phases of the cardiac arrest and resuscitation and provides a basis for analysis and discussion. This video is extracted from a 33-min, uninterrupted video of cardiac arrest and resuscitation, which is available online. The unique strength of MWA, its capability to accurately present discrete and continuous data in a format familiar to clinicians, allowed us this rare glimpse into events leading to an intraoperative cardiac arrest. Because of the ability to recreate and replay clinical events, this tool should be of great interest to medical educators, researchers, and clinicians involved in quality assurance and patient safety.

Sudden cardiac arrest in sports - need for uniform registration: A Position Paper from the Sport Cardiology Section of the European Association for Cardiovascular Prevention and Rehabilitation

There are large variations in the incidence, registration methods and reported causes of sudden cardiac arrest/sudden cardiac death (SCA/SCD) in competitive and recreational athletes. A crucial question is to which degree these variations are genuine or partly due to methodological incongruities. This paper discusses the uncertainties about available data and provides comprehensive suggestions for standard definitions and a guide for uniform registration parameters of SCA/SCD. The parameters include a definition of what constitutes an 'athlete', incidence calculations, enrolment of cases, the importance of gender, ethnicity and age of the athlete, as well as the type and level of sporting activity. A precise instruction for autopsy practice in the case of a SCD of athletes is given, including the role of molecular samples and evaluation of possible doping. Rational decisions about cardiac preparticipation screening and cardiac safety at sport facilities requires increased data quality concerning incidence, aetiology and management of SCA/SCD in sports. Uniform standard registration of SCA/SCD in athletes and leisure sportsmen would be a first step towards this goal.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Advantages of a cohort study on cardiac arrest conducted by nurses

AbstractOBJECTIVEIdentifying factors associated to survival after cardiac arrest.METHODAn experience report of a cohort study conducted in a university hospital, with a consecutive sample comprised of 285 patients. Data were collected for a year by trained nurses. The training strategy was conducted through an expository dialogue lecture. Collection monitoring was carried out by nurses via telephone calls, visits to the emergency room and by medical record searches. The neurological status of survivors was evaluated at discharge, after six months and one year.RESULTSOf the 285 patients, 16 survived until hospital discharge, and 13 remained alive after one year, making possible to identify factors associated with survival. There were no losses in the process.CONCLUSIONCohort studies help identify risks and disease outcomes. Considering cardiac arrest, they can subsidize public policies, encourage future studies and training programs for CPR, thereby improving the prognosis of patients.

Perioperative cardiac arrest: a study of 53718 anaesthetics over 9 yr from a Brazilian teaching hospital

Background. Little information exists regarding factors influencing perioperative cardiac arrests and their outcome. This survey evaluated the incidence, causes and outcome of perioperative cardiac arrests in a Brazilian tertiary general teaching hospital between April 1996 and March 2005.Methods. The incidence of cardiac arrest during anaesthesia was prospectively identified from an anaesthesia database. There were 53 718 anaesthetics during the study period. Data collected included patient characteristics, surgical procedures (elective, urgent or emergency), ASA physical status classification, anaesthesia provider information, type of surgery, surgical areas and outcome. All cardiac arrests were retrospectively reviewed and grouped by cause of arrest and death into one of four groups: totally anaesthesia related, partially anaesthesia related, totally surgery related or totally patient disease or condition related.Results. One hundred and eighty-six cardiac arrests (34.6:10 000) and 118 deaths (21.97:10 000) were found. Major risk factors for cardiac arrest were neonates, children under 1 yr and the elderly (P < 0.05), male patients with ASA III or poorer physical status (P < 0.05), in emergency surgery (P < 0.05) and under general anaesthesia (P < 0.05). Patient disease/condition was the major cause of cardiac arrest or death (P < 0.05). There were 18 anaesthesia-related cardiac arrests (3.35:10 000)-10 totally attributed (1.86:10 000) and 8 partially related to anaesthesia (1.49:10 000). There were 6 anaesthesia-related deaths (1.12:10 000)-3 totally attributable and 3 partially related to anaesthesia (0.56:10 000 in both cases). The main causes of anaesthesia-related cardiac arrest were respiratory events (55.5%) and medication-related events (44.5%).Conclusions. Perioperative cardiac arrests were relatively higher in neonates, infants, the elderly and in males with severe underlying disease and under emergency surgery. All anaesthesia-related cardiac arrests were related to airway management and medication administration which is important for prevention strategies.

The Bernese Hypothermia Algorithm: a consensus paper on in-hospital decision-making and treatment of patients in hypothermic cardiac arrest at an alpine level 1 trauma centre

INTRODUCTION: Guidelines for the treatment of patients in severe hypothermia and mainly in hypothermic cardiac arrest recommend the rewarming using the extracorporeal circulation (ECC). However,guidelines for the further in-hospital diagnostic and therapeutic approach of these patients, who often suffer from additional injuries—especially in avalanche casualties, are lacking. Lack of such algorithms may relevantly delay treatment and put patients at further risk. Together with a multidisciplinary team, the Emergency Department at the University Hospital in Bern, a level I trauma centre, created an algorithm for the in-hospital treatment of patients with hypothermic cardiac arrest. This algorithm primarily focuses on the decision-making process for the administration of ECC. THE BERNESE HYPOTHERMIA ALGORITHM: The major difference between the traditional approach, where all hypothermic patients are primarily admitted to the emergency centre, and our new algorithm is that hypothermic cardiac arrest patients without obvious signs of severe trauma are taken to the operating theatre without delay. Subsequently, the interdisciplinary team decides whether to rewarm the patient using ECC based on a standard clinical trauma assessment, serum potassium levels, core body temperature, sonographic examinations of the abdomen, pleural space, and pericardium, as well as a pelvic X-ray, if needed. During ECC, sonography is repeated and haemodynamic function as well as haemoglobin levels are regularly monitored. Standard radiological investigations according to the local multiple trauma protocol are performed only after ECC. Transfer to the intensive care unit, where mild therapeutic hypothermia is maintained for another 12 h, should not be delayed by additional X-rays for minor injuries. DISCUSSION: The presented algorithm is intended to facilitate in-hospital decision-making and shorten the door-to-reperfusion time for patients with hypothermic cardiac arrest. It was the result of intensive collaboration between different specialties and highlights the importance of high-quality teamwork for rare cases of severe accidental hypothermia. Information derived from the new International Hypothermia Registry will help to answer open questions and further optimize the algorithm.

Prognostication after cardiac arrest and hypothermia: a prospective study.

Current American Academy of Neurology (AAN) guidelines for outcome prediction in comatose survivors of cardiac arrest (CA) have been validated before the therapeutic hypothermia era (TH). We undertook this study to verify the prognostic value of clinical and electrophysiological variables in the TH setting. A total of 111 consecutive comatose survivors of CA treated with TH were prospectively studied over a 3-year period. Neurological examination, electroencephalography (EEG), and somatosensory evoked potentials (SSEP) were performed immediately after TH, at normothermia and off sedation. Neurological recovery was assessed at 3 to 6 months, using Cerebral Performance Categories (CPC). Three clinical variables, assessed within 72 hours after CA, showed higher false-positive mortality predictions as compared with the AAN guidelines: incomplete brainstem reflexes recovery (4% vs 0%), myoclonus (7% vs 0%), and absent motor response to pain (24% vs 0%). Furthermore, unreactive EEG background was incompatible with good long-term neurological recovery (CPC 1-2) and strongly associated with in-hospital mortality (adjusted odds ratio for death, 15.4; 95% confidence interval, 3.3-71.9). The presence of at least 2 independent predictors out of 4 (incomplete brainstem reflexes, myoclonus, unreactive EEG, and absent cortical SSEP) accurately predicted poor long-term neurological recovery (positive predictive value = 1.00); EEG reactivity significantly improved the prognostication. Our data show that TH may modify outcome prediction after CA, implying that some clinical features should be interpreted with more caution in this setting as compared with the AAN guidelines. EEG background reactivity is useful in determining the prognosis after CA treated with TH.

Comparison of in-hospital mortality for acute myocardial infarction in Switzerland with admission during routine duty hours versus admission during out of hours (insight into the AMIS plus registry).

To improve long-term survival, prompt revascularization of the infarct-related artery should be done in patients with acute myocardial infarction (AMI); therefore, a large proportion of these patients would be hospitalized during out of hours. The clinical effects of out-of-hours AMI management were already questioned, with conflicting results. The purpose of this investigation was to compare the in-hospital outcome of patients admitted for AMI during out of hours and working hours. All patients with AMI included in the AMIS Plus Registry from January 1, 1997, to March 30, 2006, were analyzed. The working-hours group included patients admitted from 7 a.m. to 7 p.m. on weekdays, and the out-of-hours group included patients admitted from 7 p.m. to 7 a.m. on weekdays or weekends. Major cardiac events were defined as cardiovascular death, reinfarction, and stroke. The study primary end points were in-hospital death and major adverse cardiac event (MACE) rates. A total of 12,480 patients met the inclusion criteria, with 52% admitted during normal working hours, and 48%, during out of hours. Patients admitted during weekdays included more women (28.1% vs 26%; p = 0.009), older patients (65.5 +/- 13 vs 64.1 +/- 13 years; p = 0.0011), less current smokers (40.1% vs 43.5%; p <0.001), and less patients with a history of ischemic heart disease (31.5% vs 34.5%; p = 0.001). A significantly higher proportion of patients admitted during out of hours had Killip's class III and IV. No differences in terms of in-hospital survival rates between the 2 groups (91.5% vs 91.2%; p = 0.633) or MACE-free survival rates (both 88.5%; p = 1.000) were noted. In conclusion, the outcome of patients with AMI admitted out of hours was the same compared with those with a weekday admission. Of predictors for in-hospital outcome, timing of admission had no significant influence on mortality and/or MACE incidence.

A pilot feasibility, safety and biological efficacy multicentre trial of therapeutic hypercapnia after cardiac arrest: study protocol for a randomized controlled trial.

BACKGROUND: Cardiac arrest causes ischaemic brain injury. Arterial carbon dioxide tension (PaCO2) is a major determinant of cerebral blood flow. Thus, mild hypercapnia in the 24 h following cardiac arrest may increase cerebral blood flow and attenuate such injury. We describe the Carbon Control and Cardiac Arrest (CCC) trial. METHODS/DESIGN: The CCC trial is a pilot multicentre feasibility, safety and biological efficacy randomized controlled trial recruiting adult cardiac arrest patients admitted to the intensive care unit after return of spontaneous circulation. At admission, using concealed allocation, participants are randomized to 24 h of either normocapnia (PaCO2 35 to 45 mmHg) or mild hypercapnia (PaCO2 50 to 55 mmHg). Key feasibility outcomes are recruitment rate and protocol compliance rate. The primary biological efficacy and biological safety measures are the between-groups difference in serum neuron-specific enolase and S100b protein levels at 24 h, 48 h and 72 h. Secondary outcome measure include adverse events, in-hospital mortality, and neurological assessment at 6 months. DISCUSSION: The trial commenced in December 2012 and, when completed, will provide clinical evidence as to whether targeting mild hypercapnia for 24 h following intensive care unit admission for cardiac arrest patients is feasible and safe and whether it results in decreased concentrations of neurological injury biomarkers compared with normocapnia. Trial results will also be used to determine whether a phase IIb study powered for survival at 90 days is feasible and justified. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12612000690853 .

Intraoperative and Anesthesia-Related Cardiac Arrest and Its Mortality in Older Patients: A 15-Year Survey in a Tertiary Teaching Hospital

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A randomized trial of the effects of the noble gases helium and argon on neuroprotection in a rodent cardiac arrest model.

BACKGROUND The noble gas xenon is considered as a neuroprotective agent, but availability of the gas is limited. Studies on neuroprotection with the abundant noble gases helium and argon demonstrated mixed results, and data regarding neuroprotection after cardiac arrest are scant. We tested the hypothesis that administration of 50% helium or 50% argon for 24 h after resuscitation from cardiac arrest improves clinical and histological outcome in our 8 min rat cardiac arrest model. METHODS Forty animals had cardiac arrest induced with intravenous potassium/esmolol and were randomized to post-resuscitation ventilation with either helium/oxygen, argon/oxygen or air/oxygen for 24 h. Eight additional animals without cardiac arrest served as reference, these animals were not randomized and not included into the statistical analysis. Primary outcome was assessment of neuronal damage in histology of the region I of hippocampus proper (CA1) from those animals surviving until day 5. Secondary outcome was evaluation of neurobehavior by daily testing of a Neurodeficit Score (NDS), the Tape Removal Test (TRT), a simple vertical pole test (VPT) and the Open Field Test (OFT). Because of the non-parametric distribution of the data, the histological assessments were compared with the Kruskal-Wallis test. Treatment effect in repeated measured assessments was estimated with a linear regression with clustered robust standard errors (SE), where normality is less important. RESULTS Twenty-nine out of 40 rats survived until day 5 with significant initial deficits in neurobehavioral, but rapid improvement within all groups randomized to cardiac arrest. There were no statistical significant differences between groups neither in the histological nor in neurobehavioral assessment. CONCLUSIONS The replacement of air with either helium or argon in a 50:50 air/oxygen mixture for 24 h did not improve histological or clinical outcome in rats subjected to 8 min of cardiac arrest.