Ventricular fibrillation detection in ventricular fibrillation signals corrupted by cardiopulmonary resuscitation artifact

This study is focused on the removal of artifacts due to Cardio Pulmonary Resuscitation (CPR) on Ventricular Fibrillation ECG signals. The aim is to allow a reliable analysis of the cardiac rhythm by an AED or the defibrillation success analysis during CPR episodes. The research is based on a human model for the CPR artifact and the VF ECG signals. The test signals were generated adding the CPR artifact (noise) to the VF (signal), with a known Signal-to-Noise Ratio (SNR). The results of the adaptive Kalman filtering have been obtained according to three different levels: SNR improvement; Sensitivity improvement in the AED algorithm for the detection of shockable rhythm; and Variations of the significant frequencies, compared to the values obtained with the original VF signals. In all cases, remarkable results have been achieved regarding to the efficiency in the artifact removal. 1

Pulseless electrical activity in in-hospital cardiac arrest - A crossroad for decisions

Background PEA is often seen during resuscitation, either as the presenting clinical state in cardiac arrest or as a secondary rhythm following transient return of spontaneous circulation (ROSC), ventricular fibrillation/tachycardia (VF/VT), or asystole (ASY). The aim of this study was to explore and quantify the evolution from primary/secondary PEA to ROSC in adults during in-hospital cardiac arrest (IHCA). Methods We analyzed 700 IHCA episodes at one Norwegian hospital and three U.S. hospitals at different time periods between 2002 and 2021. During resuscitation ECG, chest compressions, and ventilations were recorded by defibrillators. Each event was manually annotated using a graphical application. We quantified the transition intensities, i.e., the propensity to change from PEA to another clinical state using time-to-event statistical methods. Results Most patients experienced PEA at least once before achieving ROSC or being declared dead. Time average transition intensities to ROSC from primary PEA (n = 230) and secondary PEA after ASY (n = 72) were 0.1 per min, peaking at 4 and 7 minutes, respectively; thus, a patient in these types of PEA showed a 10% chance of achieving ROSC in one minute. Much higher transition intensities to ROSC, average of 0.15 per min, were observed for secondary PEA after VF/VT (n = 83) or after ROSC (n = 134). Discussion PEA is a crossroad in which the subsequent course is determined. The four distinct presentations of PEA behave differently on important characteristics. A transition to PEA during resuscitation should encourage the resuscitation team to continue resuscitative efforts.This work was partially supported by the Spanish Ministerio de Ciencia, Innovacion y Universidades through grant RTI2018-101475-BI00, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), and by the Basque Government through grant IT1229-19. This study has been made possible by DAM foundation and the Norwegian Health Association

Factors Affecting the Course of Resuscitation From Cardiac Arrest With Pulseless Electrical Activity in Children and Adolescents

Background: Although in-hospital pediatric cardiac arrests and cardiopulmonary resuscitation occur >15,000/year in the US, few studies have assessed which factors affect the course of resuscitation in these patients. We investigated transitions from Pulseless Electrical Activity (PEA) to Ventricular Fibrillation/pulseless Ventricular Tachycardia (VF/pVT), Return of Spontaneous Circulation (ROSC) and recurrences from ROSC to PEA in children and adolescents with in-hospital cardiac arrest. Methods: Episodes of cardiac arrest at the Children's Hospital of Philadelphia were prospectively registered. Defibrillators that recorded chest compression depth/rate and ventilation rate were applied. CPR variables, patient characteristics and etiology, and dynamic factors (e.g. the proportion of time spent in PEA or ROSC) were entered as time-varying covariates for the transition intensities under study. Results: In 67 episodes of CPR in 59 patients (median age 15 years) with cardiac arrest, there were 52 transitions from PEA to ROSC, 22 transitions from PEA to VF/pVT, and 23 recurrences of PEA from ROSC. Except for a nearly significant effect of mean compression depth beyond a threshold of 5.7 cm, only dynamic factors that evolved during CPR favored a transition from PEA to ROSC. The latter included a lower proportion of PEA over the last 5 min and a higher proportion of ROSC over the last 5 min. Factors associated with PEA to VF/pVT development were age, weight, the proportion spent in VF/pVT or PEA the last 5 min, and the general transition intensity, while PEA recurrence from ROSC only depended on the general transition intensity. Conclusion: The clinical course during pediatric cardiac arrest was mainly influenced by dynamic factors associated with time in PEA and ROSC. Transitions from PEA to ROSC seemed to be favored by deeper compressions.publishedVersio

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators

Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survivalof out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrilla-tors (AED). AED algorithms for VF-detection are customarily assessed using Holter record-ings from public electrocardiogram (ECG) databases, which may be different from the ECGseen during OHCA events. This study evaluates VF-detection using data from both OHCApatients and public Holter recordings. ECG-segments of 4-s and 8-s duration were ana-lyzed. For each segment 30 features were computed and fed to state of the art machinelearning (ML) algorithms. ML-algorithms with built-in feature selection capabilities wereused to determine the optimal feature subsets for both databases. Patient-wise bootstraptechniques were used to evaluate algorithm performance in terms of sensitivity (Se), speci-ficity (Sp) and balanced error rate (BER). Performance was significantly better for publicdata with a mean Se of 96.6%, Sp of 98.8% and BER 2.2% compared to a mean Se of94.7%, Sp of 96.5% and BER 4.4% for OHCA data. OHCA data required two times morefeatures than the data from public databases for an accurate detection (6 vs 3). No signifi-cant differences in performance were found for different segment lengths, the BER differ-ences were below 0.5-points in all cases. Our results show that VF-detection is morechallenging for OHCA data than for data from public databases, and that accurate VF-detection is possible with segments as short as 4-s

VETTONIA PROJECT: A VIRTUAL ENVIRONMENT FOR THE EDUCATIONAL DISSEMINATION OF THE IRON AGE

The VETTONIA project aims to disseminate the rich heritage from the Iron Age of the western Iberian Peninsula and the archaeological investigations carried out on this topic in recent years. The project utilizes new technologies such as virtual tours, 3D models, and impressions to create interactive and stimulating ways to access the results of the most recent archaeological research. Using these resources, lectures and seminars are being given in various forums with diverse types of audiences to present the virtual tours and the rest of the dissemination initiatives. In addition, the project presents its different initiatives during the annual archaeological interventions developed in the oppidum of Ulaca (Solosancho, Ávila, Spain), with good reception by the attending public. The VETTONIA project represents a pioneering dissemination experience that takes advantage of the educational opportunities offered by new technologies. In the future, tools such as virtual tours to archaeological sites may prove essential in classroom teaching at different levels and could promote sustainable tourism in fragile natural environments such as those that constitute the major settlements of the Late Iron Age (ca. 400–50 BC)

Role of age and comorbidities in mortality of patients with infective endocarditis

Purpose: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. Methods: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015. Patients were stratified into three age groups:<65 years, 65 to 80 years, and = 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. Results: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 = 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients =80 years who underwent surgery were significantly lower compared with other age groups (14.3%, 65 years; 20.5%, 65-79 years; 31.3%, =80 years). In-hospital mortality was lower in the <65-year group (20.3%, <65 years;30.1%, 65-79 years;34.7%, =80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%, =80 years; p = 0.003).Independent predictors of mortality were age = 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI = 3 (HR:1.62; 95% CI:1.39–1.88), and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared, the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. Conclusion: There were no differences in the clinical presentation of IE between the groups. Age = 80 years, high comorbidity (measured by CCI), and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]