Dataset Information

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.

ABSTRACT:

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 (?AMSA) 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 ?AMSA 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.

SUBMITTER: He M

PROVIDER: S-EPMC4749245 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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.

He Mi M Lu Yubao Y Zhang Lei L Zhang Hehua H Gong Yushun Y Li Yongqin Y

PloS one 20160210 2

<h4>Objective</h4>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.<h4>Methods</h4>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 amp ...[more]

PMID: 26863222

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Project description:ImportanceBystander-delivered defibrillation (hereinafter referred to as bystander defibrillation) of patients with out-of-hospital cardiac arrests (OHCAs) remains limited despite the widespread dissemination of automated external defibrillators (AEDs).ObjectiveTo examine calendar changes in bystander defibrillation and subsequent survival according to a public or a residential location of the cardiac arrest after nationwide initiatives in Denmark to facilitate bystander-mediated resuscitative efforts, including bystander defibrillation.Design, setting, and participantsThis nationwide study identified 18 688 patients in Denmark with first-time OHCA from June 1, 2001, to December 31, 2012, using the Danish Cardiac Arrest Registry. Patients had a presumed cardiac cause of arrest that was not witnessed by emergency medical services personnel. Data were analyzed from April 1, 2015, to December 10, 2016.ExposuresNationwide initiatives to facilitate bystander resuscitative efforts, including bystander defibrillation, consisted of resuscitation training of Danish citizens, dissemination of on-site AEDs, foundation of an AED registry linked to emergency medical dispatch centers, and dispatcher-assisted guidance of bystander resuscitation efforts.Main outcomes and measuresThe proportion of patients who received bystander defibrillation according to the location of the cardiac arrest and their subsequent 30-day survival.ResultsOf the 18 688 patients with OHCAs (67.8% men and 32.2% women; median [interquartile range] age, 72 [62-80] years), 4783 (25.6%) had a cardiac arrest in a public location and 13 905 (74.4%) in a residential location. The number of registered AEDs increased from 141 in 2007 to 7800 in 2012. The distribution of AED location was consistently skewed in favor of public locations. Bystander defibrillation increased in public locations from 3 of 245 (1.2%; 95% CI, 0.4%-3.5%) in 2001 to 78 of 510 (15.3%; 95% CI, 12.4%-18.7%) in 2012 (P < .001) but remained unchanged in residential locations from 7 of 542 (1.3%; 95% CI, 0.6%-2.6%) in 2001 to 21 of 1669 (1.3%; 95% CI, 0.8%-1.9%) in 2012 (P = .17). Thirty-day survival after bystander defibrillation increased in public locations from 8.3% (95% CI, 1.5%-35.4%) in 2001/2002 to 57.5% (95% CI, 48.6%-66.0%) in 2011/2012 (P < .001) in residential locations, from 0.0% (95% CI, 0.0%-19.4%) in 2001/2002 to 25.6% (95% CI, 14.6%-41.1%) in 2011/2012 (P < .001).Conclusions and relevanceInitiatives to facilitate bystander defibrillation were associated with a marked increase in bystander defibrillation in public locations, whereas bystander defibrillation remained limited in residential locations. Concomitantly, survival increased after bystander defibrillation in residential and public locations.

Project description:BackgroundCurrent 2005 guidelines for advanced cardiac life support strongly recommend immediate defibrillation for out-of-hospital cardiac arrest. However, findings from experimental and clinical studies have indicated a potential advantage of pretreatment with chest compression-only cardiopulmonary resuscitation (CPR) prior to defibrillation in improving outcomes. The aim of this meta-analysis is to evaluate the beneficial effect of chest compression-first versus defibrillation-first on survival in patients with out-of-hospital cardiac arrest.MethodsMain outcome measures were survival to hospital discharge (primary endpoint), return of spontaneous circulation (ROSC), neurologic outcome and long-term survival. Randomized, controlled clinical trials that were published between January 1, 1950, and June 19, 2010, were identified by a computerized search using SCOPUS, MEDLINE, BIOS, EMBASE, the Cochrane Central Register of Controlled Trials, International Pharmaceutical Abstracts database, and Web of Science and supplemented by conference proceedings. Random effects models were used to calculate pooled odds ratios (ORs). A subgroup analysis was conducted to explore the effects of response interval greater than 5 min on outcomes.ResultsA total of four trials enrolling 1503 subjects were integrated into this analysis. No difference was found between chest compression-first versus defibrillation-first in the rate of return of spontaneous circulation (OR 1.01 [0.82-1.26]; P = 0.979), survival to hospital discharge (OR 1.10 [0.70-1.70]; P = 0.686) or favorable neurologic outcomes (OR 1.02 [0.31-3.38]; P = 0.979). For 1-year survival, however, the OR point estimates favored chest compression first (OR 1.38 [0.95-2.02]; P = 0.092) but the 95% CI crossed 1.0, suggesting insufficient estimate precision. Similarly, for cases with prolonged response times (> 5 min) point estimates pointed toward superiority of chest compression first (OR 1.45 [0.66-3.20]; P = 0.353), but the 95% CI again crossed 1.0.ConclusionsCurrent evidence does not support the notion that chest compression first prior to defibrillation improves the outcome of patients in out-of-hospital cardiac arrest. It appears that both treatments are equivalent. However, subgroup analyses indicate that chest compression first may be beneficial for cardiac arrests with a prolonged response time.

Project description:Post-resuscitation hemodynamic instability following out-of-hospital cardiac arrest (OHCA) may occur from myocardial dysfunction underlying cardiogenic shock and/or inflammation-mediated distributive shock. Distinguishing the predominant shock subtype with widely available clinical metrics may have prognostic and therapeutic value.A two-hospital cohort was assembled of patients in shock following OHCA. Left ventricular ejection fraction (LVEF) was assessed via echocardiography or cardiac ventriculography within 1 day post arrest and used to delineate shock physiology. The study evaluated whether higher LVEF, indicating distributive-predominant shock physiology, was associated with neurocognitive outcome (primary endpoint), survival, and duration of multiple organ failures. The study also investigated whether volume resuscitation exhibited a subtype-specific association with outcome.Of 162 patients with post-resuscitation shock, 48% had normal LVEF (>?40%), consistent with distributive shock physiology. Higher LVEF was associated with less favorable neurocognitive outcome (OR 0.74, 95% CI 0.58-0.94 per 10% increase in LVEF; p?=?0.01). Higher LVEF also was associated with worse survival (OR 0.81, 95% CI 0.67-0.97; p?=?0.02) and fewer organ failure-free days (? = - 0.67, 95% CI - 1.28 to -?0.06; p?=?0.03). Only 51% of patients received a volume challenge of at least 30 ml/kg body weight in the first 6 h post arrest, and the volume received did not differ by LVEF. Greater volume resuscitation in the first 6 h post arrest was associated with favorable neurocognitive outcome (OR 1.59, 95% CI 0.99-2.55 per liter; p?=?0.03) and survival (OR 1.44, 95% CI 1.02-2.04; p?=?0.02) among patients with normal LVEF but not low LVEF.In post-resuscitation shock, higher LVEF-indicating distributive shock physiology-was associated with less favorable neurocognitive outcome, fewer days without organ failure, and higher mortality. Greater early volume resuscitation was associated with more favorable neurocognitive outcome and survival in patients with this shock subtype. Additional studies with repeated measures of complementary hemodynamic parameters are warranted to validate the clinical utility for subtyping post-resuscitation shock.

Dataset Information

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

Methods

Results

Conclusion

Publications

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.

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