Dana P. Edelson

Part 4: CPR Overview: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

Cardiopulmonary resuscitation (CPR) is a series of lifesaving actions that improve the chance of survival following cardiac arrest.1 Although the optimal approach to CPR may vary, depending on the rescuer, the victim, and the available resources, the fundamental challenge remains: how to achieve early and effective CPR. Given this challenge, recognition of arrest and prompt action by the rescuer continue to be priorities for the 2010 AHA Guidelines for CPR and ECC. This chapter provides an overview of cardiac arrest epidemiology, the principles behind each link in the Chain of Survival, an overview of the core components of CPR (see Table 1), and the approaches of the 2010 AHA Guidelines for CPR and ECC to improving the quality of CPR. The goal of this chapter is to integrate resuscitation science with real-world practice in order to improve the outcomes of CPR. View this table: Table 1. Summary of Key BLS Components for Adults, Children and Infants Despite important advances in prevention, cardiac arrest remains a substantial public health problem and a leading cause of death in many parts of the world.2 Cardiac arrest occurs both in and out of the hospital. In the US and Canada, approximately 350 000 people/year (approximately half of them in-hospital) suffer a cardiac arrest and receive attempted resuscitation.3,–,7 This estimate does not include the substantial number of victims who suffer an arrest without attempted resuscitation. While attempted resuscitation is not always appropriate, there are many lives and life-years lost because appropriate resuscitation is not attempted. The estimated incidence of EMS-treated out-of-hospital cardiac arrest in the US and Canada is about 50 to 55/100 000 persons/year and approximately 25% of these present with pulseless ventricular arrhythmias.3,8 The estimated incidence of in-hospital cardiac arrest is 3 to 6/1000 admissions4,– …

Improving In-Hospital Cardiac Arrest Process and Outcomes With Performance Debriefing

BACKGROUND Recent investigations have documented poor cardiopulmonary resuscitation (CPR) performance in clinical practice. We hypothesized that a debriefing intervention using CPR quality data from actual in-hospital cardiac arrests (resuscitation with actual performance integrated debriefing [RAPID]) would improve CPR performance and initial patient survival. METHODS Internal medicine residents at a university hospital attended weekly debriefing sessions of the prior weeks resuscitations, between March 2006 and February 2007, reviewing CPR performance transcripts obtained from a CPR-sensing and feedback-enabled defibrillator. Objective metrics of CPR performance and initial return of spontaneous circulation were compared with a historical cohort in which a similar feedback-delivering defibrillator was used but without RAPID. RESULTS Cardiopulmonary resuscitation quality and outcome data from 123 patients resuscitated during the intervention period were compared with 101 patients in the baseline cohort. Compared with the control period, the mean (SD) ventilation rate decreased (13 [7]/min vs 18 [8]/min; P < .001) and compression depth increased (50 [10] vs 44 [10] mm; P = .001), among other CPR improvements. These changes correlated with an increase in the rate of return of spontaneous circulation in the RAPID group (59.4% vs 44.6%; P = .03) but no change in survival to discharge (7.4% vs 8.9%; P = .69). CONCLUSIONS The combination of RAPID and real-time audiovisual feedback improved CPR quality compared with the use of feedback alone and was associated with an increased rate of return of spontaneous circulation. Cardiopulmonary resuscitation sensing and recording devices allow for methods of debriefing that were previously available only for simulation-based education; such methods have the potential to fundamentally alter resuscitation training and improve patient outcomes. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00228293.

Therapeutic hypothermia utilization among physicians after resuscitation from cardiac arrest

Objective:We sought to evaluate current physician use of therapeutic hypothermia after cardiac arrest, to ascertain reasons for nonadoption of this treatment, and to determine current cooling techniques employed. Design:Web-based survey. Setting:International physician cohort in the United States, UK, and Finland. Subjects:Physicians (MD or DO) caring for resuscitated cardiac arrest patients. Interventions:An anonymous Web-based survey was distributed to physicians identified through United States–based critical care, cardiology, and emergency medicine directories and critical care networks in the UK and Finland. Recipients were queried regarding use of postresuscitation therapeutic hypothermia. Measurements and Main Results:Of the final 13,272 surveys actually distributed to physicians, 2,248 (17%) were completed. Most respondents were attending physicians (82%) at teaching hospitals (76%) who practiced critical care (35%), cardiology (20%), or emergency medicine (22%). Of all replies, 74% of United States respondents and 64% of non–United States respondents had never used therapeutic hypothermia. United States emergency medicine physician adoption of cooling was significantly less than that of United States intensivists (16% vs. 34%, p < .05). The most often cited reasons for nonuse by respondents were “not enough data,” “not part of Advanced Cardiac Life Support guidelines,” and “too technically difficult to use.” Factors associated with increased use included non–United States residence, critical care specialty, and larger hospital size. Conclusions:Physician utilization of cooling after cardiac arrest remains low. For improved adoption of therapeutic hypothermia, our data suggest that development of better cooling methodology and recent incorporation into resuscitation guidelines may improve use.

Perishock Pause An Independent Predictor of Survival From Out-of-Hospital Shockable Cardiac Arrest

Background— Perishock pauses are pauses in chest compressions before and after defibrillatory shock. We examined the relationship between perishock pauses and survival to hospital discharge. Methods and Results— We included out-of-hospital cardiac arrest patients in the Resuscitation Outcomes Consortium Epistry–Cardiac Arrest who suffered arrest between December 2005 and June 2007, presented with a shockable rhythm (ventricular fibrillation or pulseless ventricular tachycardia), and had cardiopulmonary resuscitation process data for at least 1 shock (n=815). We used multivariable logistic regression to determine the association between survival and perishock pauses. In an analysis adjusted for Utstein predictors of survival, the odds of survival were significantly lower for patients with preshock pause ≥20 seconds (odds ratio, 0.47; 95% confidence interval, 0.27 to 0.82) and perishock pause ≥40 seconds (odds ratio, 0.54; 95% confidence interval, 0.31 to 0.97) compared with patients with preshock pause <10 seconds and perishock pause <20 seconds. Postshock pause was not independently associated with a significant change in the odds of survival. Log-linear modeling depicted a decrease in survival to hospital discharge of 18% and 14% for every 5-second increase in both preshock and perishock pause interval (up to 40 and 50 seconds, respectively), with no significant association noted with changes in the postshock pause interval. Conclusions— In patients with cardiac arrest presenting in a shockable rhythm, longer perishock and preshock pauses were independently associated with a decrease in survival to hospital discharge. The impact of preshock pause on survival suggests that refinement of automatic defibrillator software and paramedic education to minimize preshock pause delays may have a significant impact on survival. # Clinical Perspective {#article-title-32}Background— Perishock pauses are pauses in chest compressions before and after defibrillatory shock. We examined the relationship between perishock pauses and survival to hospital discharge. Methods and Results— We included out-of-hospital cardiac arrest patients in the Resuscitation Outcomes Consortium Epistry–Cardiac Arrest who suffered arrest between December 2005 and June 2007, presented with a shockable rhythm (ventricular fibrillation or pulseless ventricular tachycardia), and had cardiopulmonary resuscitation process data for at least 1 shock (n=815). We used multivariable logistic regression to determine the association between survival and perishock pauses. In an analysis adjusted for Utstein predictors of survival, the odds of survival were significantly lower for patients with preshock pause ≥20 seconds (odds ratio, 0.47; 95% confidence interval, 0.27 to 0.82) and perishock pause ≥40 seconds (odds ratio, 0.54; 95% confidence interval, 0.31 to 0.97) compared with patients with preshock pause <10 seconds and perishock pause <20 seconds. Postshock pause was not independently associated with a significant change in the odds of survival. Log-linear modeling depicted a decrease in survival to hospital discharge of 18% and 14% for every 5-second increase in both preshock and perishock pause interval (up to 40 and 50 seconds, respectively), with no significant association noted with changes in the postshock pause interval. Conclusions— In patients with cardiac arrest presenting in a shockable rhythm, longer perishock and preshock pauses were independently associated with a decrease in survival to hospital discharge. The impact of preshock pause on survival suggests that refinement of automatic defibrillator software and paramedic education to minimize preshock pause delays may have a significant impact on survival.

Strategies for Improving Survival After In-Hospital Cardiac Arrest in the United States: 2013 Consensus Recommendations A Consensus Statement From the American Heart Association

The goal of this statement is to develop consensus recommendations aimed at measuring and optimizing outcomes after in-hospital cardiac arrest (IHCA). For the purposes of this statement, IHCA is defined as a cardiac arrest that occurs in a hospital (whether the patient is admitted or not) and for which resuscitation is attempted with chest compressions, defibrillation, or both. Members of the writing group were selected for their expertise in cardiac resuscitation and post–cardiac arrest care. Monthly telephone conferences and “webinars” over a 10-month period were used to define the scope of the statement and to assign writing teams for each section. The first draft of each section was discussed and sent to the chair to be compiled into a single document. Revised versions were then sent to all writing group members until consensus was achieved. The final draft underwent 3 sets of independent peer review before publication. The American Heart Association (AHA) is committed to the highest ethical standards. The AHA believes that having experts who have a relationship with industry or other relevant relationships on writing groups can strengthen the writing group effort when these relationships are transparent and managed. The AHA conflict of interest policy requires each member to declare relevant and current conflicts of interest. The chair may not have any relationship with industry relevant to the topic. The majority of writing group members (defined as>50% +1) must be free of relevant relationships with industry. Every writing group member agrees to maintain his or her current status with respect to relationships with industry throughout the development of the manuscript to publication. In addition, each member formally declares his or her conflict of interest or relationship with industry at the time of publication. All members of this writing group were compliant with this policy (“Writing Group Disclosures”). IHCA …

Quick Sepsis-related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores for Detecting Clinical Deterioration in Infected Patients outside the Intensive Care Unit

Rationale: The 2016 definitions of sepsis included the quick Sepsis‐related Organ Failure Assessment (qSOFA) score to identify high‐risk patients outside the intensive care unit (ICU). Objectives: We sought to compare qSOFA with other commonly used early warning scores. Methods: All admitted patients who first met the criteria for suspicion of infection in the emergency department (ED) or hospital wards from November 2008 until January 2016 were included. The qSOFA, Systemic Inflammatory Response Syndrome (SIRS), Modified Early Warning Score (MEWS), and the National Early Warning Score (NEWS) were compared for predicting death and ICU transfer. Measurements and Main Results: Of the 30,677 included patients, 1,649 (5.4%) died and 7,385 (24%) experienced the composite outcome (death or ICU transfer). Sixty percent (n = 18,523) first met the suspicion criteria in the ED. Discrimination for in‐hospital mortality was highest for NEWS (area under the curve [AUC], 0.77; 95% confidence interval [CI], 0.76‐0.79), followed by MEWS (AUC, 0.73; 95% CI, 0.71‐0.74), qSOFA (AUC, 0.69; 95% CI, 0.67‐0.70), and SIRS (AUC, 0.65; 95% CI, 0.63‐0.66) (P < 0.01 for all pairwise comparisons). Using the highest non‐ICU score of patients, ≥2 SIRS had a sensitivity of 91% and specificity of 13% for the composite outcome compared with 54% and 67% for qSOFA ≥2, 59% and 70% for MEWS ≥5, and 67% and 66% for NEWS ≥8, respectively. Most patients met ≥2 SIRS criteria 17 hours before the combined outcome compared with 5 hours for ≥2 and 17 hours for ≥1 qSOFA criteria. Conclusions: Commonly used early warning scores are more accurate than the qSOFA score for predicting death and ICU transfer in non‐ICU patients. These results suggest that the qSOFA score should not replace general early warning scores when risk‐stratifying patients with suspected infection.

Incidence and Prognostic Value of the Systemic Inflammatory Response Syndrome and Organ Dysfunctions in Ward Patients

RATIONALE Tools that screen inpatients for sepsis use the systemic inflammatory response syndrome (SIRS) criteria and organ dysfunctions, but most studies of these criteria were performed in intensive care unit or emergency room populations. OBJECTIVES To determine the incidence and prognostic value of SIRS and organ dysfunctions in a multicenter dataset of hospitalized ward patients. METHODS Hospitalized ward patients at five hospitals from November 2008 to January 2013 were included. SIRS and organ system dysfunctions were defined using 2001 International Consensus criteria. Patient characteristics and in-hospital mortality were compared among patients meeting two or more SIRS criteria and by the presence or absence of organ system dysfunction. MEASUREMENTS AND MAIN RESULTS A total of 269,951 patients were included in the study, after excluding 48 patients with missing discharge status. Forty-seven percent (n = 125,841) of the included patients met two or more SIRS criteria at least once during their ward stay. On ward admission, 39,105 (14.5%) patients met two or more SIRS criteria, and patients presenting with SIRS had higher in-hospital mortality than those without SIRS (4.3% vs. 1.2%; P < 0.001). Fourteen percent of patients (n = 36,767) had at least one organ dysfunction at ward admission, and those presenting with organ dysfunction had increased mortality compared with those without organ dysfunction (5.3% vs. 1.1%; P < 0.001). CONCLUSIONS Almost half of patients hospitalized on the wards developed SIRS at least once during their ward stay. Our findings suggest that screening ward patients using SIRS criteria for identifying those with sepsis would be impractical.

Predicting Cardiac Arrest on the Wards : A Nested Case-Control Study

BACKGROUND Current rapid response team activation criteria were not statistically derived using ward vital signs, and the best vital sign predictors of cardiac arrest (CA) have not been determined. In addition, it is unknown when vital signs begin to accurately detect this event prior to CA. METHODS We conducted a nested case-control study of 88 patients experiencing CA on the wards of a university hospital between November 2008 and January 2011, matched 1:4 to 352 control subjects residing on the same ward at the same time as the case CA. Vital signs and Modified Early Warning Scores (MEWS) were compared on admission and during the 48 h preceding CA. RESULTS Case patients were older (64 ± 16 years vs 58 ± 18 years; P = .002) and more likely to have had a prior ICU admission than control subjects (41% vs 24%; P = .001), but had similar admission MEWS (2.2 ± 1.3 vs 2.0 ± 1.3; P = .28). In the 48 h preceding CA, maximum MEWS was the best predictor (area under the receiver operating characteristic curve [AUC] 0.77; 95% CI, 0.71-0.82), followed by maximum respiratory rate (AUC 0.72; 95% CI, 0.65-0.78), maximum heart rate (AUC 0.68; 95% CI, 0.61-0.74), maximum pulse pressure index (AUC 0.61; 95% CI, 0.54-0.68), and minimum diastolic BP (AUC 0.60; 95% CI, 0.53-0.67). By 48 h prior to CA, the MEWS was higher in cases (P = .005), with increasing disparity leading up to the event. CONCLUSIONS The MEWS was significantly different between patients experiencing CA and control patients by 48 h prior to the event, but includes poor predictors of CA such as temperature and omits significant predictors such as diastolic BP and pulse pressure index.

Multicenter Development and Validation of a Risk Stratification Tool for Ward Patients

RATIONALE Most ward risk scores were created using subjective opinion in individual hospitals and only use vital signs. OBJECTIVES To develop and validate a risk score using commonly collected electronic health record data. METHODS All patients hospitalized on the wards in five hospitals were included in this observational cohort study. Discrete-time survival analysis was used to predict the combined outcome of cardiac arrest (CA), intensive care unit (ICU) transfer, or death on the wards. Laboratory results, vital signs, and demographics were used as predictor variables. The model was developed in the first 60% of the data at each hospital and then validated in the remaining 40%. The final model was compared with the Modified Early Warning Score (MEWS) using the area under the receiver operating characteristic curve and the net reclassification index (NRI). MEASUREMENTS AND MAIN RESULTS A total of 269,999 patient admissions were included, with 424 CAs, 13,188 ICU transfers, and 2,840 deaths occurring during the study period. The derived model was more accurate than the MEWS in the validation dataset for all outcomes (area under the receiver operating characteristic curve, 0.83 vs. 0.71 for CA; 0.75 vs. 0.68 for ICU transfer; 0.93 vs. 0.88 for death; and 0.77 vs. 0.70 for the combined outcome; P value < 0.01 for all comparisons). This accuracy improvement was seen across all hospitals. The NRI for the electronic Cardiac Arrest Risk Triage compared with the MEWS was 0.28 (0.18-0.38), with a positive NRI of 0.19 (0.09-0.29) and a negative NRI of 0.09 (0.09-0.09). CONCLUSIONS We developed an accurate ward risk stratification tool using commonly collected electronic health record variables in a large multicenter dataset. Further study is needed to determine whether implementation in real-time would improve patient outcomes.

Derivation of a cardiac arrest prediction model using ward vital signs

Objective:Rapid response team activation criteria were created using expert opinion and have demonstrated variable accuracy in previous studies. We developed a cardiac arrest risk triage score to predict cardiac arrest and compared it to the Modified Early Warning Score, a commonly cited rapid response team activation criterion. Design:A retrospective cohort study. Setting:An academic medical center in the United States. Patients:All patients hospitalized from November 2008 to January 2011 who had documented ward vital signs were included in the study. These patients were divided into three cohorts: patients who suffered a cardiac arrest on the wards, patients who had a ward to intensive care unit transfer, and patients who had neither of these outcomes (controls). Interventions:None. Measurements and Main Results:Ward vital signs from admission until discharge, intensive care unit transfer, or ward cardiac arrest were extracted from the medical record. Multivariate logistic regression was used to predict cardiac arrest, and the cardiac arrest risk triage score was calculated using the regression coefficients. The model was validated by comparing its accuracy for detecting intensive care unit transfer to the Modified Early Warning Score. Each patient’s maximum score prior to cardiac arrest, intensive care unit transfer, or discharge was used to compare the areas under the receiver operating characteristic curves between the two models. Eighty-eight cardiac arrest patients, 2,820 intensive care unit transfers, and 44,519 controls were included in the study. The cardiac arrest risk triage score more accurately predicted cardiac arrest than the Modified Early Warning Score (area under the receiver operating characteristic curve 0.84 vs. 0.76; p = .001). At a specificity of 89.9%, the cardiac arrest risk triage score had a sensitivity of 53.4% compared to 47.7% for the Modified Early Warning Score. The cardiac arrest risk triage score also predicted intensive care unit transfer better than the Modified Early Warning Score (area under the receiver operating characteristic curve 0.71 vs. 0.67; p < .001). Conclusions:The cardiac arrest risk triage score is simpler and more accurately detected cardiac arrest and intensive care unit transfer than the Modified Early Warning Score. Implementation of this tool may decrease rapid response team resource utilization and provide a better opportunity to improve patient outcomes than the modified early warning score.