Ventricular Fibrillation Waveform Analysis during Cardiopulmonary Resuscitation

Ventricular fibrillation (VF) is the primary rhythm associated with cardiac arrest characterized as rapid, disorganized contractions of the heart with complex electrocardiogram (ECG) patterns. Recent studies have reported that performing cardiopulmonary resuscitation (CPR) procedure prior to shock increases the survival rate especially especially when VF is untreated for more than 5 minutes. The waveform analysis is objective help in the choice of the right therapy (shock parameters, shock first or CPR first, drug administration). This analysis is a precondition of individually optimized defibrillation and contribute substantially to an increased quality of CPR and reduce delivery of failed rescue shock. Animal and clinical studies confirmed that ventricular fibrillation waveform analysis contains information to reliably predict the countershock success rate and further improved countershock outcome prediction

Reduction of CPR artifacts in the ventricular fibrillation ECG by coherent line removal

<p>Abstract</p> <p>Background</p> <p>Interruption of cardiopulmonary resuscitation (CPR) impairs the perfusion of the fibrillating heart, worsening the chance for successful defibrillation. Therefore ECG-analysis <it>during ongoing chest compression </it>could provide a considerable progress in comparison with standard analysis techniques working only during "hands-off" intervals.</p> <p>Methods</p> <p>For the reduction of CPR-related artifacts in ventricular fibrillation ECG we use a localized version of the <it>coherent line removal </it>algorithm developed by Sintes and Schutz. This method can be used for removal of periodic signals with sufficiently coupled harmonics, and can be adapted to specific situations by optimal choice of its parameters (e.g., the number of harmonics considered for analysis and reconstruction). Our testing was done with 14 different human ventricular fibrillation (VF) ECGs, whose fibrillation band lies in a frequency range of [1 Hz, 5 Hz]. The VF-ECGs were mixed with 12 different ECG-CPR-artifacts recorded in an animal experiment during asystole. The length of each of the ECG-data was chosen to be 20 sec, and testing was done for all 168 = 14 × 12 pairs of data. VF-to-CPR ratio was chosen as -20 dB, -15 dB, -10 dB, -5 dB, 0 dB, 5 dB and 10 dB. Here -20 dB corresponds to the highest level of CPR-artifacts.</p> <p>Results</p> <p>For non-optimized <it>coherent line removal </it>based on signals with a VF-to-CPR ratio of -20 dB, -15 dB, -10 dB, -5 dB and 0 dB, the signal-to-noise gains (SNR-gains) were 9.3 ± 2.4 dB, 9.4 ± 2.4 dB, 9.5 ± 2.5 dB, 9.3 ± 2.5 dB and 8.0 ± 2.7 (mean ± std, <it>n </it>= 168), respectively. Characteristically, an original VF-to-CPR ratio of -10 dB, corresponds to a variance ratio <it>var</it>(VF):<it>var</it>(CPR) = 1:10. An improvement by 9.5 dB results in a restored VF-to-CPR ratio of -0.5 dB, corresponding to a variance ratio <it>var</it>(VF):<it>var</it>(CPR) = 1:1.1, the variance of the CPR in the signal being reduced by a factor of 8.9.</p> <p>Discussion</p> <p>The <it>localized coherent line removal </it>algorithm uses the information of a single ECG channel. In contrast to multi-channel algorithms, no additional information such as thorax impedance, blood pressure, or pressure exerted on the sternum during CPR is required. Predictors of defibrillation success such as mean and median frequency of VF-ECGs containing CPR-artifacts are prone to being governed by the harmonics of the artifacts. Reduction of CPR-artifacts is therefore necessary for determining reliable values for estimators of defibrillation success.</p> <p>Conclusions</p> <p>The <it>localized coherent line removal </it>algorithm reduces CPR-artifacts in VF-ECG, but does not eliminate them. Our SNR-improvements are in the same range as offered by multichannel methods of Rheinberger et al., Husoy et al. and Aase et al. The latter two authors dealt with different ventricular rhythms (VF and VT), whereas here we dealt with VF, only. Additional developments are necessary before the algorithm can be tested in real CPR situations.</p

Seinale prozesaketan eta ikasketa automatikoan oinarritutako ekarpenak bihotz-erritmoen analisirako bihotz-biriketako berpiztean

Tesis inglés 218 p. -- Tesis euskera 220 p.Out-of-hospital cardiac arrest (OHCA ) is characterized by the sudden loss of the cardiac function, andcauses around 10% of the total mortality in developed countries. Survival from OHCA depends largelyon two factors: early defibrillation and early cardiopulmonary resuscitation (CPR). The electrical shock isdelivered using a shock advice algorithm (SAA) implemented in defibrillators. Unfortunately, CPR mustbe stopped for a reliable SAA analysis because chest compressions introduce artefacts in the ECG. Theseinterruptions in CPR have an adverse effect on OHCA survival. Since the early 1990s, many efforts havebeen made to reliably analyze the rhythm during CPR. Strategies have mainly focused on adaptive filtersto suppress the CPR artefact followed by SAAs of commercial defibrillators. However, these solutionsdid not meet the American Heart Association¿s (AHA) accuracy requirements for shock/no-shockdecisions. A recent approach, which replaces the commercial SAA by machine learning classifiers, hasdemonstrated that a reliable rhythm analysis during CPR is possible. However, defibrillation is not theonly treatment needed during OHCA, and depending on the clinical context a finer rhythm classificationis needed. Indeed, an optimal OHCA scenario would allow the classification of the five cardiac arrestrhythm types that may be present during resuscitation. Unfortunately, multiclass classifiers that allow areliable rhythm analysis during CPR have not yet been demonstrated. On all of these studies artefactsoriginate from manual compressions delivered by rescuers. Mechanical compression devices, such as theLUCAS or the AutoPulse, are increasingly used in resuscitation. Thus, a reliable rhythm analysis duringmechanical CPR is becoming critical. Unfortunately, no AHA compliant algorithms have yet beendemonstrated during mechanical CPR. The focus of this thesis work is to provide new or improvedsolutions for rhythm analysis during CPR, including shock/no-shock decision during manual andmechanical CPR and multiclass classification during manual CPR

Diagnóstico del ritmo cardiaco durante la realización de compresiones torácicas en paradas cardiorrespiratorias atendidas con desfibrilador externo automático (DEA).

[ES]La parada cardiorrespiratoria extra hospitalaria es una de las principales causas de mortalidad en los países desarrollados. La única manera de combatir su fatal desenlace es efectuar una intervención rápida y eficaz. En este país, ambos factores se ven condicionados por los servicios que cada comunidad ofrece en relación a la cardioprotección de espacios públicos. Estos servicios van desde el despliegue de flotas de ambulancias garantizando la llegada del equipo de salvamento en tiempos de en torno a diez minutos hasta la colocación estratégica de desfibriladores externos automáticos en lugares públicos concurridos. Este trabajo pretende mejorar la eficiencia de los desfibriladores externos automáticos mediante el desarrollo de un algoritmo de diagnostico que posibilite una desfibrilación más temprana y eficiente, aumentando así las probabilidades de supervivencia de los pacientes de paradas cardiorrespiratorias extrahospitalarias.[EU]Ospitale kanpoko bihotz-biriken gelditzea garatutako herrialdeen heriotza-kausa nagusietako bat da. Bere bukaera larriari aurre egiteko bide bakarra esku-hartze arina eta eraginkorra da. Herrialde honetan, bi faktore hauek, komunitate bakoitzak eskaintzen dituzten espazio publikoen kardio-babeserako zerbitzuen aurrean baldintzatuak ikusten dira. Zerbitzu hauek anbulantzien hedapenetik, hamar minutuko denboran erreskate taldearen etorrera bermatuz kanpoko desfibriladore automatikoen kokapen estrategikora doaz. Lan honek kanpoko desfibriladore automatikoen eraginkortasuna hobetu nahi du, desfibrilazioa lehenago eta eraginkorrago ahalbidetzen duen diagnostiko algoritmo bat garatuz. Horrela, kanpoko bihotz-biriken gelditzearen jasaileen biziraupen aukerak areagotuko dira.[EN]Out of hospital cardiac arrest is one of the main causes of mortality in developed countries. The only way to fight its fatal outcome is to make a quick and effective intervention. In this country, both factors are conditioned by the services that each community offers in relation to the heart protecction of public spaces. These services range from the deployment of ambulance fleets guaranteeing the arrival of the rescue team in times of ten minutes to the strategic placement of automatic external defibrillators in crowded public places. This work aims to improve the efficiency of automatic external defibrillators by developing a diagnostic algorithm that enables earlier and more efficient defibrillation, thus increasing the chances of survival of patients with out-of-hospital cardiopulmonary arrest

Diagnóstico del ritmo cardiaco durante la realización de compresiones torácicas en paradas cardiorrespiratorias atendidas con desfibrilador externo automático (DEA).

[ES]La parada cardiorrespiratoria extra hospitalaria es una de las principales causas de mortalidad en los países desarrollados. La única manera de combatir su fatal desenlace es efectuar una intervención rápida y eficaz. En este país, ambos factores se ven condicionados por los servicios que cada comunidad ofrece en relación a la cardioprotección de espacios públicos. Estos servicios van desde el despliegue de flotas de ambulancias garantizando la llegada del equipo de salvamento en tiempos de en torno a diez minutos hasta la colocación estratégica de desfibriladores externos automáticos en lugares públicos concurridos. Este trabajo pretende mejorar la eficiencia de los desfibriladores externos automáticos mediante el desarrollo de un algoritmo de diagnostico que posibilite una desfibrilación más temprana y eficiente, aumentando así las probabilidades de supervivencia de los pacientes de paradas cardiorrespiratorias extrahospitalarias.[EU]Ospitale kanpoko bihotz-biriken gelditzea garatutako herrialdeen heriotza-kausa nagusietako bat da. Bere bukaera larriari aurre egiteko bide bakarra esku-hartze arina eta eraginkorra da. Herrialde honetan, bi faktore hauek, komunitate bakoitzak eskaintzen dituzten espazio publikoen kardio-babeserako zerbitzuen aurrean baldintzatuak ikusten dira. Zerbitzu hauek anbulantzien hedapenetik, hamar minutuko denboran erreskate taldearen etorrera bermatuz kanpoko desfibriladore automatikoen kokapen estrategikora doaz. Lan honek kanpoko desfibriladore automatikoen eraginkortasuna hobetu nahi du, desfibrilazioa lehenago eta eraginkorrago ahalbidetzen duen diagnostiko algoritmo bat garatuz. Horrela, kanpoko bihotz-biriken gelditzearen jasaileen biziraupen aukerak areagotuko dira.[EN]Out of hospital cardiac arrest is one of the main causes of mortality in developed countries. The only way to fight its fatal outcome is to make a quick and effective intervention. In this country, both factors are conditioned by the services that each community offers in relation to the heart protecction of public spaces. These services range from the deployment of ambulance fleets guaranteeing the arrival of the rescue team in times of ten minutes to the strategic placement of automatic external defibrillators in crowded public places. This work aims to improve the efficiency of automatic external defibrillators by developing a diagnostic algorithm that enables earlier and more efficient defibrillation, thus increasing the chances of survival of patients with out-of-hospital cardiopulmonary arrest

Biochemical and electrophysiological markers predictive of return of spontaneous circulation and post-resuscitation outcome

The majority of patients resuscitated from cardiac arrest (CA) subsequently die due to post-cardiac arrest syndrome (PCAS), whose mechanisms are only partially understood. We adopted an approach of untargeted/targeted plasma metabolomics in rats to identify metabolites involved in the mechanisms of PCAS to be tested as predictors of outcome. Activation of the kynurenine pathway (KP) for tryptophan (TRP) degradation was demonstrated in rats, pigs and in a small cohort of patients. Decreases in TRP occurred during the post-CA period and were accompanied by significant increases in KP metabolites, 3-hydroxyanthranilic acid (3 -HAA) and kynurenic acid in each species, that persisted up to 3-5 days post-CA (p<0.01). KP metabolites changes were significantly related to the severity of myocardial and cerebral injuries and survival. Finally, when tested in 155 patients resuscitated from CA, KP metabolites were significantly higher in patients with poor outcomes. The quality of chest compression (CC) is another major issue for cardiopulmonary resuscitation (CPR) success and survival. The decision whether to interrupt CC to deliver a defibrillation (DF) is difficult. The potential benefit of a DF guided by a real time ventricular fibrillation (YF) waveform analysis would maximize DF success, minimize CC interruptions and myocardial damage by repetitive and unnecessary DFs. We evaluated amplitude spectrum area (AMSA) as predictor of DF outcome in two large databases of out-of-hospital VFs, from US (609 patients) and Italy (1.617 patients). AMSA was significantly higher prior to a successful DF than prior to an unsuccessful one (p<0.0001). Thresholds for prediction of successful and unsuccessful DFs were 16-17 mV-Hz for success and <7 mV-Hz for failure, with a positive predictive value of 80% and a negative predictive value of 97%. AMSA was a better predictor of DF outcome (AUC 0.86, p<0.0001) compared to other VF parameters, i.e. amplitude and frequencies. In conclusion, AMSA would be a useful tool for guiding CPR

Quality framework for semantic interoperability in health informatics: definition and implementation

Aligned with the increased adoption of Electronic Health Record (EHR) systems, it is recognized that semantic interoperability provides benefits for promoting patient safety and continuity of care. This thesis proposes a framework of quality metrics and recommendations for developing semantic interoperability resources specially focused on clinical information models, which are defined as formal specifications of structure and semantics for representing EHR information for a specific domain or use case. This research started with an exploratory stage that performed a systematic literature review with an international survey about the clinical information modelling best practice and barriers. The results obtained were used to define a set of quality models that were validated through Delphi study methodologies and end user survey, and also compared with related quality standards in those areas that standardization bodies had a related work programme. According to the obtained research results, the defined framework is based in the following models: Development process quality model: evaluates the alignment with the best practice in clinical information modelling and defines metrics for evaluating the tools applied as part of this process. Product quality model: evaluates the semantic interoperability capabilities of clinical information models based on the defined meta-data, data elements and terminology bindings. Quality in use model: evaluates the suitability of adopting semantic interoperability resources by end users in their local projects and organisations. Finally, the quality in use model was implemented within the European Interoperability Asset register developed by the EXPAND project with the aim of applying this quality model in a broader scope to contain any relevant material for guiding the definition, development and implementation of interoperable eHealth systems in our continent. Several European projects already expressed interest in using the register, which will now be sustained by the European Institute for Innovation through Health Data