Recovery of arterial blood pressure after chest compression pauses in patients with out-of-hospital cardiac arrest.

BACKGROUND AND AIMS: Chest compressions generating good perfusion during cardiopulmonary resuscitation (CPR) in cardiac arrest patients are critical for positive patient outcomes. Conventional wisdom advises minimizing compression pauses because several compressions are required to recover arterial blood pressure (ABP) back to pre-pause values. Our study examines how compression pauses influence ABP recovery post-pause in out-of-hospital cardiac arrest. METHODS: We analyzed data from a subset of a prospective, randomized LUCAS 2 Active Decompression trial. Patients were treated by an anesthesiologist-staffed rapid response car program in Oslo, Norway (2015-2017) with mechanical chest compressions using the LUCAS device at 102 compressions/min. Patients with an ABP signal during CPR and at least one compression pause >2 sec were included. Arterial cannulation, compression pauses, and ECG during the pause were verified by physician review of patient records and physiological signals. Pauses were excluded if return of spontaneous circulation occurred during the pause (pressure pulses associated with ECG complexes). Compression, mean, and decompression ABP for 10 compressions before/after each pause and the mean ABP during the pause were measured with custom MATLAB code. The relationship between pause duration and ABP recovery was investigated using linear regression. RESULTS: We included 56 patients with a total of 271 pauses (pause duration: median = 11 sec, Q1 = 7 sec, Q3 = 18 sec). Mean ABP dropped from 53 ± 10 mmHg for the last pre-pause compression to 33 ± 7 mmHg during the pause. Compression and mean ABP recovered to >90% of pre-pause pressure within 2 compressions, or 1.7 sec. Pause duration did not affect the recovery of ABP post-pause (R2: 0.05, 0.03, 0.01 for compression, mean, and decompression ABP, respectively). CONCLUSIONS: ABP generated by mechanical CPR recovered quickly after pauses. Recovery of ABP after a pause was independent of pause duration.

Wolf Creek XVII Part 6: Physiology-Guided CPR.

Introduction: Physiology-guided cardiopulmonary resuscitation (CPR) offers the potential to optimize resuscitation and enable early prognosis. Methods: Physiology-Guided CPR was one of six focus topic for the Wolf Creek XVII Conference held on June 14-17, 2023 in Ann Arbor, Michigan, USA. International thought leaders and scientists in the field of cardiac arrest resuscitation from academia and industry were invited. Participants submitted via online survey knowledge gaps, barriers to translation and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category, which was then debated, revised and ranked by all attendees to identify the top 5 for each category. Results: Top knowledge gaps include identifying optimal strategies for the evaluation of physiology-guided CPR and the optimal values for existing patients using patient outcomes. The main barriers to translation are the limited usability outside of critical care environments and the training and equipment required for monitoring. The top research priorities are the development of clinically feasible and reliable methods to continuously and non-invasively monitor physiology during CPR and prospective human studies proving targeting parameters during CPR improves outcomes. Conclusion: Physiology-guided CPR has the potential to provide individualized resuscitation and move away from a one-size-fits-all approach. Current understanding is limited, and clinical trials are lacking. Future developments need to consider the clinical application and applicability of measurement to all healthcare settings. Therefore, clinical trials using physiology-guided CPR for individualisation of resuscitation efforts are needed.

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.

Cardiac output estimation using ballistocardiography: a feasibility study in healthy subjects.

There is no reliable automated non-invasive solution for monitoring circulation and guiding treatment in prehospital emergency medicine. Cardiac output (CO) monitoring might provide a solution, but CO monitors are not feasible/practical in the prehospital setting. Non-invasive ballistocardiography (BCG) measures heart contractility and tracks CO changes. This study analyzed the feasibility of estimating CO using morphological features extracted from BCG signals. In 20 healthy subjects ECG, carotid/abdominal BCG, and invasive arterial blood pressure based CO were recorded. BCG signals were adaptively processed to isolate the circulatory component from carotid (CCc) and abdominal (CCa) BCG. Then, 66 features were computed on a beat-to-beat basis to characterize amplitude/duration/area/length of the fluctuation in CCc and CCa. Subjects' data were split into development set (75%) to select the best feature subset with which to build a machine learning model to estimate CO and validation set (25%) to evaluate model's performance. The model showed a mean absolute error, percentage error and 95% limits of agreement of 0.83 L/min, 30.2% and - 2.18-1.89 L/min respectively in the validation set. BCG showed potential to reliably estimate/track CO. This method is a promising first step towards an automated, non-invasive and reliable CO estimator that may be tested in prehospital emergencies.

Lung tissue injury and hemodynamic effects of ventilations synchronized or unsynchronized to continuous chest compressions in a porcine cardiac arrest model.

Aim: Compare lung injury and hemodynamic effects in synchronized ventilations (between two chest compressions) vs. unsynchronized ventilations during cardiopulmonary resuscitation (CPR) in a porcine model of cardiac arrest. Methods: Twenty pigs were randomized to either synchronized or unsynchronized group. Ventricular fibrillation was induced electrically and left for 1.5 minutes. Four minutes of basic chest compression:ventilation (30:2) CPR was followed by eight minutes of either synchronized or unsynchronized ventilations (10/min) during continuous compressions before defibrillation was attempted. Aortic, right atrial and intracerebral pressures, carotid and cerebral blood flow and cardiac output were measured. Airway monitoring included capnography and respiratory function monitor. Macro- and microscopic lung injuries were assessed post-mortem. Results: There were no significant differences between groups in any of the measured hemodynamic variables or inspiration time (0.4 vs. 1.0 s, p = 0.05). The synchronized ventilation group had lower median peak inspiratory airway pressure (57 vs. 94 cm H2O, p < 0.001), lower minute ventilation (3.7 vs. 9.4 l min-1, p < 0.001), lower pH (7.31 vs. 7.53, p < 0.001), higher pCO2 (5.2 vs. 2.5 kPa, p < 0.001) and lower pO2 (31.6 vs. 54.7 kPa, p < 0.001) compared to the unsynchronized group after 12 minutes of CPR. There was significant lung injury after CPR in both synchronized and unsynchronized groups. Conclusion: Synchronized and unsynchronized ventilations resulted in similar hemodynamics and lung injury during continuous mechanical compressions of pigs in cardiac arrest. Animals that received unsynchronized ventilations with one second inspiration time at a rate of ten ventilations per minute were hyperventilated and hyperoxygenated.Institutional protocol number: FOTS, id 6948.

Amplitude spectral area of ventricular fibrillation and defibrillation success at low energy in out-of-hospital cardiac arrest.

The optimal energy for defibrillation has not yet been identified and very often the maximum energy is delivered. We sought to assess whether amplitude spectral area (AMSA) of ventricular fibrillation (VF) could predict low energy level defibrillation success in out-of-hospital cardiac arrest (OHCA) patients. This is a multicentre international study based on retrospective analysis of prospectively collected data. We included all OHCAs with at least one manual defibrillation. AMSA values were calculated by analyzing the data collected by the monitors/defibrillators used in the field (Corpuls 3 and Lifepak 12/15) and using a 2-s-pre-shock electrocardiogram interval. We run two different analyses dividing the shocks into three tertiles (T1, T2, T3) based on AMSA values. 629 OHCAs were included and 2095 shocks delivered (energy ranging from 100 to 360 J; median 200 J). Both in the "extremes analysis" and in the "by site analysis", the AMSA values of the effective shocks at low energy were significantly higher than those at high energy (p = 0.01). The likelihood of shock success increased significantly from the lowest to the highest tertile. After correction for age, call to shock time, use of mechanical CPR, presence of bystander CPR, sex and energy level, high AMSA value was directly associated with the probability of shock success [T2 vs T1 OR 3.8 (95% CI 2.5-6) p < 0.001; T3 vs T1 OR 12.7 (95% CI 8.2-19.2), p < 0.001]. AMSA values are associated with the probability of low-energy shock success so that they could guide energy optimization in shockable cardiac arrest patients.

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.

Amplitude Spectrum Area of ventricular fibrillation to guide defibrillation: a small open-label, pseudo-randomized controlled multicenter trial.

BACKGROUND: Ventricular fibrillation (VF) waveform analysis has been proposed as a potential non-invasive guide to optimize timing of defibrillation. METHODS: The AMplitude Spectrum Area (AMSA) trial is an open-label, multicenter randomized controlled study reporting the first in-human use of AMSA analysis in out-of-hospital cardiac arrest (OHCA). The primary efficacy endpoint was the termination of VF for an AMSA ≥ 15.5 mV-Hz. Adult shockable OHCAs randomly received either an AMSA-guided cardiopulmonary resuscitation (CPR) or a standard-CPR. Randomization and allocation to trial group were carried out centrally. In the AMSA-guided CPR, an initial AMSA ≥ 15.5 mV-Hz prompted for immediate defibrillation, while lower values favored chest compression (CC). After completion of the first 2-min CPR cycle, an AMSA < 6.5 mV-Hz deferred defibrillation in favor of an additional 2-min CPR cycle. AMSA was measured and displayed in real-time during CC pauses for ventilation with a modified defibrillator. FINDINGS: The trial was early discontinued for low recruitment due to the COVID-19 pandemics. A total of 31 patients were recruited in 3 Italian cities, 19 in AMSA-CPR and 12 in standard-CPR, and included in the data analysis. No difference in primary outcome was observed between the two groups. Termination of VF occurred in 74% of patients in the AMSA-CPR compared to 75% in the standard CPR (OR 0.93 [95% CI 0.18-4.90]). No adverse events were reported. INTERPRETATION: AMSA was used prospectively in human patients during ongoing CPR. In this small trial, an AMSA-guided defibrillation provided no evidence of an improvement in termination of VF. TRIAL REGISTRATION: NCT03237910. FUNDING: European Commission - Horizon 2020; ZOLL Medical Corp., Chelmsford, USA (unrestricted grant); Italian Ministry of Health - Current research IRCCS.

Injuries associated with mechanical chest compressions and active decompressions after out-of-hospital cardiac arrest: A subgroup analysis of non-survivors from a randomized study.

Background: Both skeletal and visceral injuries are reported after cardiopulmonary resuscitation (CPR). This subgroup analysis of a randomized clinical study describes/compares autopsy documented injury patterns caused by two mechanical, piston-based chest compression devices: standard LUCAS® 2 (control) and LUCAS® 2 with active decompression (AD, intervention) in non-survivors with out-of-hospital cardiac arrest (CA). Method: We compared injuries documented by autopsies (medical/forensic) after control and intervention CPR based on written relatives consent to use patients' data. The pathologists were blinded for the device used. The cause of CA and injuries reported were based on a prespecified study autopsy template. We used Pearson's chi-squared test and logistic regression analysis with an alpha level of 0.05. Results: 221 patients were included in the main study (April 2015-April 2017) and 207 did not survive. Of these, 114 (55%, 64 control and 50 intervention) underwent medical (N = 73) or forensic (N = 41) autopsy. The cause of CA was cardiac 53%, respiratory 17%, overdose/intoxication 14%, ruptured aorta 10%, neurological 1%, and other 5%. There were no differences between control and intervention in the incidence of rib fractures (67% vs 72%; p-value = 0.58), or sternal fractures (44% vs 48%; p-value = 0.65), respectively. The most frequent non-skeletal complication was bleeding (26% of all patients) and intrathoracic was the most common location. Ten of the 114 patients had internal organ injuries, where lungs were most affected. Conclusion: In non-survivors of OHCA patients, the most frequent cause of cardiac arrest was cardiogenic. Skeletal and non-skeletal fractures/injuries were found in both control and intervention groups. Bleeding was the most common non-skeletal complication. Internal organ injuries were rare.

Efficacy of defibrillator pads placement during ventricular arrhythmias, a before and after analysis.

BACKGROUND: European resuscitation guidelines describe several acceptable placements of defibrillator pads during resuscitation of cardiac arrest. However, no clinical trial has compared defibrillation efficacy between any of the different pad placements. Houston Fire Department emergency medical system (EMS) used anterior-posterior (AP) defibrillator pad placement before becoming a study site in the circulation improving resuscitation care trial (CIRC). During CIRC, Houston Fire EMS used sternal-apical (SA) pad placement. METHODS: Data from electronic defibrillator records was compared between a pre-CIRC dataset and patients in the CIRC trial receiving manual cardiopulmonary resuscitation (CPR). Only shocks from patients with initial ventricular fibrillation (VF) or pulseless ventricular tachycardia (VT) were included. Measured outcome was defibrillation efficacy, defined as termination of VF/VT. The general estimatingequations model was used to study the association between defibrillation efficacy rates in the AP vs SA group. RESULTS: In the pre-CIRC dataset, 207 included patients received 1023 shocks with AP pad placement, compared with 277 patients from the CIRC trial who received 1020 shocks with SA pad placement. There was no significant difference in defibrillation efficacy between AP and SA pads placement (82.1 % vs 82.2 %, p = 0.98). CONCLUSION: No difference was observed in defibrillation efficacy between AP and SA pad placement in this study. A randomized clinical trial may be indicated.

Physiological effects of providing supplemental air for avalanche victims. A randomised trial.

BACKGROUND: Survival from avalanche burial is dependent on time to extraction, breathing ability, air pocket oxygen content, and avoiding rebreathing of carbon dioxide (CO2). Mortality from asphyxia increases rapidly after burial. Rescue services often arrive too late. Our objective was to evaluate the physiological effects of providing personal air supply in a simulated avalanche scenario as a possible concept to delay asphyxia. We hypothesize that supplemental air toward victim's face into the air pocket will prolong the window of potential survival. METHODS: A prospective randomized crossover experimental field study enrolled 20 healthy subjects in Hemsedal, Norway in March 2019. Subjects underwent in randomized order two sessions (receiving 2 litres per minute of air in front of mouth/nose into the air pocket or no air) in a simulated avalanche scenario with extensive monitoring serving as their own control. RESULTS: A significant increase comparing Control vs Intervention were documented for minimum and maximum end-tidal CO2 (EtCO2), respiration rate, tidal volume, minute ventilation, heart rate, invasive arterial blood pressures, but lower peripheral and cerebral oximetry. Controls compared to Intervention group subjects had a lower study completion rate (26% vs 74%), and minutes in the air pocket before interruption (13.1 ± 8.1 vs 22.4 ± 5.6 vs), respectively. CONCLUSIONS: Participants subject to simulated avalanche burial can maintain physiologic parameters within normal levels for a significantly longer period if they receive supplemental air in front of their mouth/nose into the air pocket. This may extend the time for potential rescue and lead to increased survival.

Mechanical active compression-decompression versus standard mechanical cardiopulmonary resuscitation: A randomised haemodynamic out-of-hospital cardiac arrest study.

BACKGROUND: Active compression-decompression cardiopulmonary resuscitation (ACD-CPR) utilises a suction cup to lift the chest-wall actively during the decompression phase (AD). We hypothesised that mechanical ACD-CPR (Intervention), with AD up to 30 mm above the sternal resting position, would generate better haemodynamic results than standard mechanical CPR (Control). METHODS: This out-of-hospital adult non-traumatic cardiac arrest trial was prospective, block-randomised and non-blinded. We included intubated patients with capnography recorded during mechanical CPR. Exclusion criteria were pregnancy, prisoners, and prior chest surgery. The primary endpoint was maximum tidal carbon dioxide partial pressure (pMTCO2) and secondary endpoints were oxygen saturation of cerebral tissue (SctO2), invasive arterial blood pressures and CPR-related injuries. Intervention device lifting force performance was categorised as Complete AD (≥30 Newtons) or Incomplete AD (≤10 Newtons). Haemodynamic data, analysed as one measurement for each parameter per ventilation (Observation Unit, OU) with non-linear regression statistics are reported as mean (standard deviation). A two-sided p-value < 0.05 was considered as statistically significant. RESULTS: Of 221 enrolled patients, 210 were deemed eligible (Control 109, Intervention 101). The Control vs. Intervention results showed no significant differences for pMTCO2: 29(17) vs 29(18) mmHg (p = 0.86), blood pressures during compressions: 111(45) vs. 101(68) mmHg (p = 0.93) and decompressions: 21(20) vs. 18(18) mmHg (p = 0.93) or for SctO2%: 55(36) vs. 57(9) (p = 0.42). The 48 patients who received Complete AD in > 50% of their OUs had higher SctO2 than Control patients: 58(11) vs. 55(36)% (p < 0.001). CONCLUSIONS: Mechanical ACD-CPR provided similar haemodynamic results to standard mechanical CPR. The Intervention device did not consistently provide Complete AD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier (NCT number): NCT02479152. The Haemodynamic Effects of Mechanical Standard and Active Chest Compression-decompression During Out-of-hospital CPR.

Multimodal Algorithms for the Classification of Circulation States During Out-of-Hospital Cardiac Arrest.

GOAL: Identifying the circulation state during out-of-hospital cardiac arrest (OHCA) is essential to determine what life-saving therapies to apply. Currently algorithms discriminate circulation (pulsed rhythms, PR) from no circulation (pulseless electrical activity, PEA), but PEA can be classified into true (TPEA) and pseudo (PPEA) depending on cardiac contractility. This study introduces multi-class algorithms to automatically determine circulation states during OHCA using the signals available in defibrillators. METHODS: A cohort of 60 OHCA cases were used to extract a dataset of 2506 5-s segments, labeled as PR (1463), PPEA (364) and TPEA (679) using the invasive blood pressure, experimentally recorded through a radial/femoral cannulation. A multimodal algorithm using features obtained from the electrocardiogram, the thoracic impedance and the capnogram was designed. A random forest model was trained to discriminate three (TPEA/PPEA/PR) and two (PEA/PR) circulation states. The models were evaluated using repeated patient-wise 5-fold cross-validation, with the unweighted mean of sensitivities (UMS) and F 1-score as performance metrics. RESULTS: The best model for 3-class had a median (interquartile range, IQR) UMS and F 1 of 69.0% (68.0-70.1) and 61.7% (61.0-62.5), respectively. The best two class classifier had median (IQR) UMS and F 1 of 83.9% (82.9-84.5) and 76.2% (75.0-76.9), outperforming all previous proposals in over 3-points in UMS. CONCLUSIONS: The first multiclass OHCA circulation state classifier was demonstrated. The method improved previous algorithms for binary pulse/no-pulse decisions. SIGNIFICANCE: Automatic multiclass circulation state classification during OHCA could contribute to improve cardiac arrest therapy and improve survival rates.

Rhythm Analysis during Cardiopulmonary Resuscitation Using Convolutional Neural Networks.

Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The objective of this study was to design an algorithm to produce reliable shock/no-shock decisions during CPR using convolutional neural networks (CNN). A total of 3319 ECG segments of 9 s extracted during chest compressions were used, whereof 586 were shockable and 2733 nonshockable. Chest compression artifacts were removed using a Recursive Least Squares (RLS) filter, and the filtered ECG was fed to a CNN classifier with three convolutional blocks and two fully connected layers for the shock/no-shock classification. A 5-fold cross validation architecture was adopted to train/test the algorithm, and the proccess was repeated 100 times to statistically characterize the performance. The proposed architecture was compared to the most accurate algorithms that include handcrafted ECG features and a random forest classifier (baseline model). The median (90% confidence interval) sensitivity, specificity, accuracy and balanced accuracy of the method were 95.8% (94.6-96.8), 96.1% (95.8-96.5), 96.1% (95.7-96.4) and 96.0% (95.5-96.5), respectively. The proposed algorithm outperformed the baseline model by 0.6-points in accuracy. This new approach shows the potential of deep learning methods to provide reliable diagnosis of the cardiac rhythm without interrupting chest compression therapy.

Diagnostic performance of the basic and advanced life support termination of resuscitation rules: A systematic review and diagnostic meta-analysis.

AIM: To minimize termination of resuscitation (TOR) in potential survivors, the desired positive predictive value (PPV) for mortality and specificity of universal TOR-rules are ≥99%. In lack of a quantitative summary of the collective evidence, we performed a diagnostic meta-analysis to provide an overall estimate of the performance of the basic and advanced life support (BLS and ALS) termination rules. DATA SOURCES: We searched PubMed/EMBASE/Web-of-Science/CINAHL and Cochrane (until September 2019) for studies on either or both TOR-rules in non-traumatic, adult cardiac arrest. PRISMA-DTA-guidelines were followed. RESULTS: There were 19 studies: 16 reported on the BLS-rule (205.073 patients, TOR-advice in 57%), 11 on the ALS-rule (161.850 patients, TOR-advice in 24%). Pooled specificities were 0.95 (0.89-0.98) and 0.98 (0.95-1.00) respectively, with a PPV of 0.99 (0.99-1.00) and 1.00 (0.99-1.00). Specificities were significantly lower in non-Western than Western regions: 0.84 (0.73-0.92) vs. 0.99 (0.97-0.99), p < 0.001 for the BLS rule. For the ALS-rule, specificities were 0.94 (0.87-0.97) vs. 1.00 (0.99-1.00), p < 0.001. For non-Western regions, 16 (BLS) or 6 (ALS) out of 100 potential survivors met the TOR-criteria. Meta-regression demonstrated decreasing performance in settings with lower rates of in-field shocks. CONCLUSIONS: Despite an overall high PPV, this meta-analysis highlights a clinically important variation in diagnostic performance of the BLS and ALS TOR-rules. Lower specificity and PPV were seen in non-Western regions, and populations with lower rates of in-field defibrillation. Improved insight in the varying diagnostic performance is highly needed, and local validation of the rules is warranted to prevent in-field termination of potential survivors.

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia.

Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning have been successfully used to detect ventricular fibrillation (VF) in AED shock decision algorithms. Recently, deep learning architectures based on 1D Convolutional Neural Networks (CNN) have been proposed for this task. This study introduces a deep learning architecture based on 1D-CNN layers and a Long Short-Term Memory (LSTM) network for the detection of VF. Two datasets were used, one from public repositories of Holter recordings captured at the onset of the arrhythmia, and a second from OHCA patients obtained minutes after the onset of the arrest. Data was partitioned patient-wise into training (80%) to design the classifiers, and test (20%) to report the results. The proposed architecture was compared to 1D-CNN only deep learners, and to a classical approach based on VF-detection features and a support vector machine (SVM) classifier. The algorithms were evaluated in terms of balanced accuracy (BAC), the unweighted mean of the sensitivity (Se) and specificity (Sp). The BAC, Se, and Sp of the architecture for 4-s ECG segments was 99.3%, 99.7%, and 98.9% for the public data, and 98.0%, 99.2%, and 96.7% for OHCA data. The proposed architecture outperformed all other classifiers by at least 0.3-points in BAC in the public data, and by 2.2-points in the OHCA data. The architecture met the 95% Sp and 90% Se requirements of the American Heart Association in both datasets for segment lengths as short as 3-s. This is, to the best of our knowledge, the most accurate VF detection algorithm to date, especially on OHCA data, and it would enable an accurate shock no shock diagnosis in a very short time.

Transthoracic Impedance Measured with Defibrillator Pads-New Interpretations of Signal Change Induced by Ventilations.

Compressions during the insufflation phase of ventilations may cause severe pulmonary injury during cardiopulmonary resuscitation (CPR). Transthoracic impedance (TTI) could be used to evaluate how chest compressions are aligned with ventilations if the insufflation phase could be identified in the TTI waveform without chest compression artifacts. Therefore, the aim of this study was to determine whether and how the insufflation phase could be precisely identified during TTI. We synchronously measured TTI and airway pressure (Paw) in 21 consenting anaesthetised patients, TTI through the defibrillator pads and Paw by connecting the monitor-defibrillator's pressure-line to the endotracheal tube filter. Volume control mode with seventeen different settings were used (5-10 ventilations/setting): Six volumes (150-800 mL) with 12 min-1 frequency, four frequencies (10, 12, 22 and 30 min-1) with 400 mL volume, and seven inspiratory times (0.5-3.5 s ) with 400 mL/10 min-1 volume/frequency. Median time differences (quartile range) between timing of expiration onset in the Paw-line (PawEO) and the TTI peak and TTI maximum downslope were measured. TTI peak and PawEO time difference was 579 (432-723) m s for 12 min-1, independent of volume, with a negative relation to frequency, and it increased linearly with inspiratory time (slope 0.47, R 2 = 0.72). PawEO and TTI maximum downslope time difference was between -69 and 84 m s for any ventilation setting (time aligned). It was independent ( R 2 < 0.01) of volume, frequency and inspiratory time, with global median values of -47 (-153-65) m s , -40 (-168-68) m s and 20 (-93-128) m s , for varying volume, frequency and inspiratory time, respectively. The TTI peak is not aligned with the start of exhalation, but the TTI maximum downslope is. This knowledge could help with identifying the ideal ventilation pattern during CPR.

Survival to hospital discharge with biphasic fixed 360 joules versus 200 escalating to 360 joules defibrillation strategies in out-of-hospital cardiac arrest of presumed cardiac etiology.

INTRODUCTION: Guidelines recommend constant or escalating energy levels for shocks after the initial defibrillation attempt. Studies comparing survival to hospital discharge with escalating vs fixed high energy level shocks are lacking. We compared survival to hospital discharge for 200 J escalating to 360 J vs fixed 360 J in patients with initial ventricular fibrillation/pulseless ventricular tachycardia in a post-hoc analysis of the Circulation Improving Resuscitation Care trial database. METHODS AND RESULTS: Pre-shock rhythm, rhythm 5 s after shock, shock energy levels, termination of ventricular fibrillation/pulseless ventricular tachycardia (TOF), and survival to hospital discharge were recorded. Association between defibrillation strategy and survival to hospital discharge was investigated with multivariable logistic regression. The escalating energy group included 260 patients and 883 shocks vs 478 patients and 1736 shocks in the fixed-high energy group. There was no difference in survival to hospital discharge between escalating (70/255 patients, 28%) and fixed energy group (132/478 patients, 28%) (unadjusted OR 1.00, 95% CI 0.72-1.42 and adjusted OR 0.81, 95% CI 0.54-1.22, p = 0.32). First shock TOF was 86% in the escalating group compared to 83% in the fixed-high group, p = 0.27. CONCLUSION: There was no difference in survival to hospital discharge or the frequency of TOF between escalating energy and fixed-high energy group. ClinicalTrials.gov Identifier: NCT00597207.

The effect of intravenous adrenaline on electrocardiographic changes during resuscitation in patients with initial pulseless electrical activity in out of hospital cardiac arrest.

INTRODUCTION: Presence of electrocardiographic rhythm in the absence of palpable pulses defines pulseless electrical activity (PEA) and the electrocardiogram (ECG) may provide a source of information during resuscitation. The aim of this study was to examine the development of ECG characteristics during advanced life support (ALS) from Out-of-hospital cardiac arrest (OHCA) with initial PEA, and to explore the potential effects of adrenaline on these characteristics. METHODS: Patients with OHCA and initial PEA, part of randomized controlled trial of ALS with or without intravenous access and medications, were included. A total of 4840 combined observations of QRS complex rate (heart rate) and width were made by examining defibrillator recordings from 170 episodes of cardiac arrest. RESULTS: We found Increased heart rate (47 beats per minute) and reduced QRS complex width (62 ms) during ALS in patients who obtained return of spontaneous circulation (ROSC); while patients who received adrenaline but died increased their heart rate (22 beats per minute) without any concomitant decrease in QRS complex width. CONCLUSION: ECG changes during ALS in cardiac arrest were associated with prognosis, and the administration of adrenaline impacted on these changes.

A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR.

Chest compressions delivered during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may make the shock advice algorithms (SAA) of defibrillators inaccurate. There is evidence that methods consisting of adaptive filters that remove the CPR artifact followed by machine learning (ML) based algorithms are able to make reliable shock/no-shock decisions during compressions. However, there is room for improvement in the performance of these methods. The objective was to design a robust ML framework for a reliable shock/no-shock decision during CPR. The study dataset contained 596 shockable and 1697 nonshockable ECG segments obtained from 273 cases of out-of-hospital cardiac arrest. Shock/no-shock labels were adjudicated by expert reviewers using ECG intervals without artifacts. First, CPR artifacts were removed from the ECG using a Least Mean Squares (LMS) filter. Then, 38 shock/no-shock decision features based on the Stationary Wavelet Transform (SWT) were extracted from the filtered ECG. A wapper-based feature selection method was applied to select the 6 best features for classification. Finally, 4 state-of-the-art ML classifiers were tested to make the shock/no-shock decision. These diagnoses were compared with the rhythm annotations to compute the Sensitivity (Se) and Specificity (Sp). All classifiers achieved an Se above 94.5%, Sp above 95.5% and an accuracy around 96.0%. They all exceeded the 90% Se and 95% Sp minimum values recommended by the American Heart Association.