Acute ischemic heart disease alters ventricular fibrillation waveform characteristics in out-of hospital cardiac arrest

Amplitude spectral area of ventricular fibrillation can discriminate survival of patients with out-of-hospital cardiac arrest

Background

Evidence of the association between AMplitude Spectral Area (AMSA) of ventricular fibrillation and outcome after out-of-hospital cardiac arrest (OHCA) is limited to short-term follow-up. In this study, we assess whether AMSA can stratify the risk of death or poor neurological outcome at 30 days and 1 year after OHCA in patients with an initial shockable rhythm or with an initial non-shockable rhythm converted to a shockable one.

Methods

This is a multicentre retrospective study of prospectively collected data in two European Utstein-based OHCA registries. We included all cases of OHCAs with at least one manual defibrillation. AMSA values were calculated after data extraction from the monitors/defibrillators used in the field by using a 2-s pre-shock electrocardiogram interval. The first detected AMSA value, the maximum value, the average value, and the minimum value were computed, and their outcome prediction accuracy was compared. Multivariable Cox regression models were run for both 30-day and 1-year deaths or poor neurological outcomes. Neurological cerebral performance category 1-2 was considered a good neurological outcome.

Results

Out of the 578 patients included, 494 (85%) died and 10 (2%) had a poor neurological outcome at 30 days. All the AMSA values considered (first value, maximum, average, and minimum) were significantly higher in survivors with good neurological outcome at 30 days. The average AMSA showed the highest area under the receiver operating characteristic curve (0.778, 95% CI: 0.7-0.8, p < 0.001). After correction for confounders, the highest tertiles of average AMSA (T3 and T2) were significantly associated with a lower risk of death or poor neurological outcome compared with T1 both at 30 days (T2: HR 0.6, 95% CI: 0.4-0.9, p = 0.01; T3: HR 0.6, 95% CI: 0.4-0.9, p = 0.02) and at 1 year (T2: HR 0.6, 95% CI: 0.4-0.9, p = 0.01; T3: HR 0.6, 95% CI: 0.4-0.9, p = 0.01). Among survivors at 30 days, a higher AMSA was associated with a lower risk of mortality or poor neurological outcome at 1 year (T3: HR 0.03, 95% CI: 0-0.3, p = 0.02).

Discussion

Lower AMSA values were significantly and independently associated with the risk of death or poor neurological outcome at 30 days and at 1 year in OHCA patients with either an initial shockable rhythm or a conversion rhythm from non-shockable to shockable. The average AMSA value had the strongest association with prognosis.

aMplitude spectral area of ventricular fibrillation and amiOdarone Study in patients with out-of-hospital cArdIaC arrest. The MOSAIC study

Objective

Antiarrhythmic drugs are recommended for out of hospital cardiac arrest (OHCA) with shock-refractory ventricular fibrillation (VF). Amplitude Spectral Area (AMSA) of VF is a quantitative waveform measure that describes the amplitude-weighted mean frequency of VF, it correlates with intramyocardial adenosine triphosphate (ATP) concentration, it is a predictor of shock efficacy and an emerging indicator to guide defibrillation and resuscitation efforts. How AMSA might be influenced by amiodarone administration is unknown.

Methods

In this international multicentre observational study, all OHCAs receiving at least one shock were included. AMSA values were calculated by retrospectively analysing the pre-shock ECG interval of 2 s. Multivariable models were run and a propensity score based on the probability of receiving amiodarone was created to compare two randomly matched samples.

Results

2,077 shocks were included: 1,407 in the amiodarone group and 670 in the non-amiodarone group. AMSA values were lower in the amiodarone group [8.8 (6-12.7) mV·Hz vs. 9.8 (6-14) mV·Hz, p = 0.035]. In two randomly matched propensity score-based groups of 261 shocks, AMSA was lower in the amiodarone group [8.2 (5.8-13.5) mV·Hz vs. 9.6 (5.6-11.6), p = 0.042]. AMSA was a predictor of shock success in both groups but the predictive power was lower in the amiodarone group [Area Under the Curve (AUC) non-amiodarone group 0.812, 95%CI: 0.78-0.841 vs. AUC amiodarone group 0.706, 95%CI: 0.68-0.73; p < 0.001].

Conclusions

Amiodarone administration was independently associated with the probability of recording lower values of AMSA. In patients who have received amiodarone during cardiac arrest the predictive value of AMSA for shock success is significantly lower, but still statistically significant.

Targeted Delivery of Electrical Shocks and Epinephrine, Guided by Ventricular Fibrillation Amplitude Spectral Area, Reduces Electrical and Adrenergic Myocardial Burden, Improving Survival in Swine

Background

We previously reported that resuscitation delivering electrical shocks guided by real‐time ventricular fibrillation amplitude spectral area (AMSA) enabled return of spontaneous circulation (ROSC) with fewer shocks, resulting in less myocardial dysfunction. We now hypothesized that AMSA could also guide delivery of epinephrine, expecting further outcome improvement consequent to less electrical and adrenergic burdens.

Methods and Results

A swine model of ventricular fibrillation was used to compare after 10 minutes of untreated ventricular fibrillation a guidelines‐driven (n=8) resuscitation protocol, delivering shocks every 2 minutes and epinephrine every 4 minutes, with an AMSA‐driven shocks (n=8) protocol, delivering epinephrine every 4 minutes, and with an AMSA‐driven shocks and epinephrine (ADSE; n=8) protocol. For guidelines‐driven, AMSA‐driven shocks, and ADSE protocols, the time to ROSC (mean±SD) was 569±164, 410±111, and 400±80 seconds (P=0.045); the number of shocks (mean±SD) was 5±2, 3±1, and 3±2 (P=0.024) with ADSE fewer than guidelines‐driven (P=0.03); and the doses of epinephrine (median [interquartile range]) were 2.0 (1.3–3.0), 1.0 (1.0–2.8), and 1.0 (0.3–3.0) (P=0.419). The ROSC rate was similar, yet survival after ROSC favored AMSA‐driven protocols (guidelines‐driven, 3/6; AMSA‐driven shocks, 6/6; and ADSE, 7/7; P=0.019 by log‐rank test). Left ventricular function and survival after ROSC correlated inversely with electrical burden (ie, cumulative unsuccessful shocks, J/kg; P=0.020 and P=0.046) and adrenergic burden (ie, total epinephrine doses, mg/kg; P=0.042 and P=0.002).

Conclusions

Despite similar ROSC rates achieved with all 3 protocols, AMSA‐driven shocks and ADSE resulted in less postresuscitation myocardial dysfunction and better survival, attributed to attaining ROSC with less electrical and adrenergic myocardial burdens.

The effect of the localisation of an underlying ST-elevation myocardial infarction on the VF-waveform: A multi-centre cardiac arrest study

INTRODUCTION

In cardiac arrest, ventricular fibrillation (VF) waveform characteristics such as amplitude spectrum area (AMSA) are studied to identify an underlying myocardial infarction (MI). Observational studies report lower AMSA-values in patients with than without underlying MI. Moreover, experimental studies with 12-lead ECG-recordings show lowest VF-characteristics when the MI-localisation matches the ECG-recording direction. However, out-of-hospital cardiac arrest (OHCA)-studies with defibrillator-derived VF-recordings are lacking.

METHODS

Multi-centre (Amsterdam/Nijmegen, the Netherlands) cohort-study on the association between AMSA, ST-elevation MI (STEMI) and its localisation. AMSA was calculated from defibrillator pad-ECG recordings (proxy for lead II, inferior vantage point); STEMI-localisation was determined using ECG/angiography/autopsy findings.

RESULTS

We studied AMSA-values in 754 OHCA-patients. There were statistically significant differences between no STEMI, anterior STEMI and inferior STEMI (Nijmegen: no STEMI 13.0mVHz [7.9-18.6], anterior STEMI 7.5mVHz [5.6-13.8], inferior STEMI 7.5mVHz [5.4-11.8], p = 0.006. Amsterdam: 11.7mVHz [5.0-21.9], 9.6mVHz [4.6-17.2], and 6.9mVHz [3.2-16.0], respectively, p = 0.001). Univariate analyses showed significantly lower AMSA-values in inferior STEMI vs. no STEMI; there was no significant difference between anterior and no STEMI. After correction for confounders, adjusted absolute AMSA-values were numerically lowest for inferior STEMI in both cohorts, and the relative differences in AMSA between inferior and no STEMI was 1.4-1.7 times larger than between anterior and no STEMI.

CONCLUSION

This multi-centre VF-waveform OHCA-study showed significantly lower AMSA in case of underlying STEMI, with a more pronounced difference for inferior than for anterior STEMI. Confirmative studies on the impact of STEMI-localisation on the VF-waveform are warranted, and might contribute to earlier diagnosis of STEMI during VF.

A method to predict ventricular fibrillation shock outcome during chest compressions

BACKGROUND

Out-of-hospital ventricular fibrillation (VF) cardiac arrest is a leading cause of death. Quantitative analysis of the VF electrocardiogram (ECG) can predict patient outcomes and could potentially enable a patient-specific, guided approach to resuscitation. However, VF analysis during resuscitation is confounded by cardiopulmonary resuscitation (CPR) artifact in the ECG, challenging continuous application to guide therapy throughout resuscitation. We therefore sought to design a method to predict VF shock outcomes during CPR.

METHODS

Study data included 4577 5-s VF segments collected during and without CPR prior to defibrillation attempts in N = 1151 arrest patients. Using training data (460 patients), an algorithm was designed to predict the VF shock outcomes of defibrillation success (return of organized ventricular rhythm) and functional survival (Cerebral Performance Category 1-2). The algorithm was designed with variable-frequency notch filters to reduce CPR artifact in the ECG based on real-time chest compression rate. Ten ECG features and three dichotomous patient characteristics were developed to predict outcomes. These variables were combined using support vector machines and logistic regression. Algorithm performance was evaluated by area under the receiver operating characteristic curve (AUC) to predict outcomes in validation data (691 patients).

RESULTS

AUC (95% Confidence Interval) for predicting defibrillation success was 0.74 (0.71-0.77) during CPR and 0.77 (0.74-0.79) without CPR. AUC for predicting functional survival was 0.75 (0.72-0.78) during CPR and 0.76 (0.74-0.79) without CPR.

CONCLUSION

A novel algorithm predicted defibrillation success and functional survival during ongoing CPR following VF arrest, providing a potential proof-of-concept towards real-time guidance of resuscitation therapy.

End-tidal carbon dioxide (ETCO2) and ventricular fibrillation amplitude spectral area (AMSA) for shock outcome prediction in out-of-hospital cardiac arrest. Are they two sides of the same coin?

AIM

Ventricular fibrillation amplitude spectral area (AMSA) and end-tidal carbon dioxide (ETCO₂) are predictors of shock success, understood as restoration of an organized rhythm, and return of spontaneous circulation (ROSC). However, little is known about their combined use. We aimed to assess the prediction accuracy when combined, and to clarify if they are correlated in out of hospital cardiac arrest' victims.

MATERIALS AND METHODS

Records acquired by external defibrillators in out-of-hospital cardiac arrest patients of the Lombardia Cardiac Arrest registry were processed. The 1-min pre-shock ETCO₂ median value (METCO₂) was computed from the capnogram and AMSA (2-48 mV.Hz range) computed applying the Fast Fourier Transform to a 2-second pre-shock filtered ECG interval (0.5-30 Hz). Support Vector Machine (SVM) predictive models based on METCO₂, AMSA and their combination were fit; results were given as the area under the curve (AUC) of the receiver operating characteristic (ROC) curves.

RESULTS

We considered 112 patients with 391 shocks delivered. METCO₂ and AMSA were predictors of shock success [AUC (IQR) of the ROC curve: 0.59 (0.56-0.62); 0.68 (0.65-0.72), respectively] and of ROSC [0.56 (0.53-0.59); 0.74 (0.71-0.78),]. Their combination in a SVM model increased the accuracy for predicting shock success [AUC (IQR) of the ROC curve: 0.71 (0.68-0.75)] and ROSC [0.77 (0.73-0.8)]. AMSA and METCO₂ were significantly correlated only in patients who achieved ROSC (rho = 0.33 p = 0.03).

CONCLUSIONS

AMSA and ETCO₂ predict shock success and ROSC after every shock, and their predictive power increases if combined. Notably, they were correlated only in patients who achieved ROSC.

Computerized Analysis of the Ventricular Fibrillation Waveform Allows Identification of Myocardial Infarction: A Proof-of-Concept Study for Smart Defibrillator Applications in Cardiac Arrest

Background

In cardiac arrest, computerized analysis of the ventricular fibrillation (VF) waveform provides prognostic information, while its diagnostic potential is subject of study. Animal studies suggest that VF morphology is affected by prior myocardial infarction (MI), and even more by acute MI. This experimental in‐human study reports on the discriminative value of VF waveform analysis to identify a prior MI. Outcomes may provide support for in‐field studies on acute MI.

Methods and Results

We conducted a prospective registry of implantable cardioverter defibrillator recipients with defibrillation testing (2010–2014). From 12‐lead surface ECG VF recordings, we calculated 10 VF waveform characteristics. First, we studied detection of prior MI with lead II, using one key VF characteristic (amplitude spectrum area [AMSA]). Subsequently, we constructed diagnostic machine learning models: model A, lead II, all VF characteristics; model B, 12‐lead, AMSA only; and model C, 12‐lead, all VF characteristics. Prior MI was present in 58% (119/206) of patients. The approach using the AMSA of lead II demonstrated a C‐statistic of 0.61 (95% CI, 0.54–0.68). Model A performance was not significantly better: 0.66 (95% CI, 0.59–0.73), P=0.09 versus AMSA lead II. Model B yielded a higher C‐statistic: 0.75 (95% CI, 0.68–0.81), P<0.001 versus AMSA lead II. Model C did not improve this further: 0.74 (95% CI, 0.67–0.80), P=0.66 versus model B.

Conclusions

This proof‐of‐concept study provides the first in‐human evidence that MI detection seems feasible using VF waveform analysis. Information from multiple ECG leads rather than from multiple VF characteristics may improve diagnostic accuracy. These results require additional experimental studies and may serve as pilot data for in‐field smart defibrillator studies, to try and identify acute MI in the earliest stages of cardiac arrest.

Predictive value of amplitude spectrum area of ventricular fibrillation waveform in patients with acute or previous myocardial infarction in out-of-hospital cardiac arrest

BACKGROUND

Amplitude spectrum area (AMSA) of ventricular fibrillation (VF) has been associated with survival from out-of-hospital cardiac arrest (OHCA). Ischemic heart disease has been shown to change AMSA. We studied whether the association between AMSA and survival changes with acute ST-elevation myocardial infarction (STEMI) as cause of the OHCA and/or previous MI.

METHODS

Multivariate logistic regression with log-transformed AMSA of first artifact-free VF segment was used to assess the association between AMSA and survival, according to presence of STEMI or previous MI, adjusting for resuscitation characteristics, medication use and comorbidities.

RESULTS

Of 716 VF-patients included from an OHCA-registry in the Netherlands, 328 (46%) had STEMI as cause of OHCA. Previous MI was present in 186 (26%) patients. Survival was 66%; neither previous MI (P=0.11) nor STEMI (P=0.78) altered survival. AMSA was a predictor of survival (ORadj: 1.52, 95%-CI: 1.28-1.82). STEMI was associated with lower AMSA (8.4mV-Hz [3.7-16.5] vs. 12.3mV-Hz [5.6-23.0]; P<0.001), but previous MI was not (9.5mV-Hz [3.9-18.0] vs 10.6mV-Hz [4.6-19.3]; P=0.27). When predicting survival, there was no interaction between previous MI and AMSA (P=0.14). STEMI and AMSA had a significant interaction (P=0.002), whereby AMSA was no longer a predictor of survival (ORadj: 1.03, 95%-CI: 0.77-1.37) in STEMI-patients. In patients without STEMI, higher AMSA was associated with higher survival rates (ORadj: 1.80, 95%-CI: 1.39-2.35).

CONCLUSIONS

The prognostic value of AMSA is altered by the presence of STEMI: while AMSA has strong predictive value in patients without STEMI, AMSA is not a predictor of survival in STEMI-patients.

Ventricular fibrillation waveform measures and the etiology of cardiac arrest

BACKGROUND

Early determination of the acute etiology of cardiac arrest could help guide resuscitation or post-resuscitation care. In experimental studies, quantitative measures of the ventricular fibrillation waveform distinguish ischemic from non-ischemic etiology.

METHODS

We investigated whether waveform measures distinguished arrest etiology among adults treated by EMS for out-of-hospital ventricular fibrillation between January 1, 2006-December 31, 2014. Etiology was classified using hospital information into three exclusive groups: acute coronary syndrome (ACS) with ST elevation myocardial infarction (STEMI), ACS without ST elevation (non-STEMI), or non-ischemic arrest. Waveform measures included amplitude spectrum area (AMSA), centroid frequency (CF), mean frequency (MF), and median slope (MS) assessed during CPR-free epochs immediately prior to the initial and second shock. Waveform measures prior to the initial shock and the changes between first and second shock were compared by etiology group. We a priori chose a significance level of 0.01 due to multiple comparisons.

RESULTS

Of the 430 patients, 35% (n=150) were classified as STEMI, 29% (n=123) as non-STEMI, and 37% (n=157) with non-ischemic arrest. We did not observe differences by etiology in any of the waveform measures prior to shock 1 (Kruskal-Wallis Test) (p=0.28 for AMSA, p=0.07 for CF, p=0.63 for MF, and p=0.39 for MS). We also did not observe differences for change in waveform between shock 1 and 2, or when the two acute ischemia groups (STEMI and non-STEMI) were combined and compared to the non-ischemic group.

CONCLUSION

This clinical investigation suggests that waveform measures may not be useful in distinguishing cardiac arrest etiology.

Combining Amplitude Spectrum Area with Previous Shock Information Using Neural Networks Improves Prediction Performance of Defibrillation Outcome for Subsequent Shocks in Out-Of-Hospital Cardiac Arrest Patients

Objective

Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether combining VF features with additional attributes that related to the previous shock could enhance the prediction performance for subsequent shocks is still uncertain.

Methods

A total of 528 defibrillation shocks from 199 patients experienced out-of-hospital cardiac arrest were analyzed in this study. VF waveform was quantified using amplitude spectrum area (AMSA) from defibrillator's ECG recordings prior to each shock. Combinations of AMSA with previous shock index (PSI) or/and change of AMSA (ΔAMSA) between successive shocks were exercised through a training dataset including 255shocks from 99patientswith neural networks. Performance of the combination methods were compared with AMSA based single feature prediction by area under receiver operating characteristic curve(AUC), sensitivity, positive predictive value (PPV), negative predictive value (NPV) and prediction accuracy (PA) through a validation dataset that was consisted of 273 shocks from 100patients.

Results

A total of61 (61.0%) patients required subsequent shocks (N = 173) in the validation dataset. Combining AMSA with PSI and ΔAMSA obtained highest AUC (0.904 vs. 0.819, p<0.001) among different combination approaches for subsequent shocks. Sensitivity (76.5% vs. 35.3%, p<0.001), NPV (90.2% vs. 76.9%, p = 0.007) and PA (86.1% vs. 74.0%, p = 0.005)were greatly improved compared with AMSA based single feature prediction with a threshold of 90% specificity.

Conclusion

In this retrospective study, combining AMSA with previous shock information using neural networks greatly improves prediction performance of defibrillation outcome for subsequent shocks.

Application of the chaotic power law to the study of cardiac dynamics in patients with arrhythmias

<p>Background. An exponential law for chaotic cardiac dynamics,<br />found previously, allows the quantification of the differences<br />between normal cardiac dynamics and those with acute<br />diseases, as well as the cardiac dynamics of the evolution<br />between these states.</p><p><br />Objective. To confirm the clinical applicability of the developed<br />methodology through the mathematical law for cardiac<br />dynamics in dynamics with arrhythmias.</p><p><br />Materials and methods. 60 Holter electrocardiograms were<br />analyzed, 10 corresponded to normal subjects, and 50 to subjects with different arrhythmias. For each Holter, an attractor was performed, and its fractal dimension and spatial occupancy were measured. A mathematical evaluation was applied in order to differentiate normal dynamics from pathological ones. Sensitivity, specificity and the Kappa coefficient were calculated.</p><p><br />Results. The mathematical evaluation differentiated occupation spaces, normal dynamics, acute illness dynamics, and evolution between these states. The sensitivity and specificity values were 100%, and the Kappa coefficient was 1.</p><p>Conclusions. The clinical applicability of the methodology<br />for cases with arrhythmia was shown. It is also applicable for<br />the detection of changes in dynamics that are not classified<br />clinically as pathological.</p>

Towards cardiopulmonary resuscitation without vasoactive drugs

PURPOSE OF REVIEW

Whereas there is clear evidence for improved survival with cardiopulmonary resuscitation (CPR) and defibrillation during cardiac arrest management, there is today lacking evidence that any of the recommended and used drugs lead to any long-term benefit for the patients. In this review, we try to discuss our current view on why advanced life support (ALS) today can be performed without the use of drugs, and instead gain all focus on improving the tasks we know improve survival: CPR and defibrillation.

RECENT FINDINGS

Previous and recent cardiac arrest drug studies have been reviewed. These are mostly consisting of retrospective register data, some experimental data and a few new randomized trials. The alternative drug-free ALS concept is also discussed with relevant studies.

SUMMARY

There is currently no evidence to support any specific drugs during cardiac arrest. Good-quality CPR, early defibrillation and goal-directed postresuscitation care is more important. Healthcare systems should not prioritize implementation of unproven drugs before good quality of care can be documented. More drug studies are indeed required, and future research needs to incorporate better diagnostic tools to test more specific and tailored therapies that account for underlying causes and individual responsiveness.

Postresuscitation care with mild therapeutic hypothermia and coronary intervention after out-of-hospital cardiopulmonary resuscitation: a prospective registry analysis

Introduction

Mild therapeutic hypothermia (MTH) has been shown to result in better neurological outcome after cardiopulmonary resuscitation. Percutaneous coronary intervention (PCI) may also be beneficial in patients after out-of-hospital cardiac arrest (OHCA).

Methods

A selected cohort study of 2,973 prospectively documented adult OHCA patients within the German Resuscitation Registry between 2004 and 2010. Data were analyzed by backwards stepwise binary logistic regression to identify the impact of MTH and PCI on both 24-hour survival and neurological outcome that was based on cerebral performance category (CPC) at hospital discharge. Odds ratios (95% confidence intervals) were calculated adjusted for the following confounding factors: age, location of cardiac arrest, presumed etiology, bystander cardiopulmonary resuscitation, witnessing, first electrocardiogram rhythm, and thrombolysis.

Results

The Preclinical care dataset included 2,973 OHCA patients with 44% initial return of spontaneous circulation (n = 1,302) and 35% hospital admissions (n = 1,040). Seven hundred and eleven out of these 1,040 OHCA patients (68%) were also registered within the Postresuscitation care dataset. Checking for completeness of datasets required the exclusion of 127 Postresuscitation care cases, leaving 584 patients with complete data for final analysis. In patients without PCI (n = 430), MTH was associated with increased 24-hour survival (8.24 (4.24 to 16.0), P < 0.001) and the proportion of patients with CPC 1 or CPC 2 at hospital discharge (2.13 (1.17 to 3.90), P < 0.05) as an independent factor. In normothermic patients (n = 405), PCI was independently associated with increased 24-hour survival (4.46 (2.26 to 8.81), P < 0.001) and CPC 1 or CPC 2 (10.81 (5.86 to 19.93), P < 0.001). Additional analysis of all patients (n = 584) revealed that 24-hour survival was increased by MTH (7.50 (4.12 to 13.65), P < 0.001) and PCI (3.88 (2.11 to 7.13), P < 0.001), while the proportion of patients with CPC 1 or CPC 2 was significantly increased by PCI (5.66 (3.54 to 9.03), P < 0.001) but not by MTH (1.27 (0.79 to 2.03), P = 0.33), although an unadjusted Fisher exact test suggested a significant effect of MTH (unadjusted odds ratio 1.83 (1.23 to 2.74), P < 0.05).

Conclusions

PCI may be an independent predictor for good neurological outcome (CPC 1 or CPC 2) at hospital discharge. MTH was associated with better neurological outcome, although subsequent logistic regression analysis did not show statistical significance for MTH as an independent predictor for good neurological outcome. Thus, postresuscitation care on the basis of standardized protocols including coronary intervention and hypothermia may be beneficial after successful resuscitation. One of the main limitations may be a selection bias for patients subjected to PCI and MTH.

Part 8: adult advanced cardiovascular life support: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

The goal of therapy for bradycardia or tachycardia is to rapidly identify and treat patients who are hemodynamically unstable or symptomatic due to the arrhythmia. Drugs or, when appropriate, pacing may be used to control unstable or symptomatic bradycardia. Cardioversion or drugs or both may be used to control unstable or symptomatic tachycardia. ACLS providers should closely monitor stable patients pending expert consultation and should be prepared to aggressively treat those with evidence of decompensation.