Background: Previous studies have stated that hyperventilation often occurs in cardiopulmonary resuscitation (CPR) mainly due to excessive ventilation frequencies, especially when a manual valve bag is used. Transport ventilators may provide mandatory ventilation with predetermined tidal volumes and without the risk of hyperventilation. Nonetheless, interactions between chest compressions and ventilations are likely to occur. We investigated whether transport ventilators can provide adequate alveolar ventilation during continuous chest compression in adult CPR. Methods: A three-period crossover study with three common transport ventilators in a cadaver model of CPR was carried out. The three ventilators ‘MEDUMAT Standard²’, ‘Oxylog 3000 plus’, and ‘Monnal T60’ represent three different interventions, providing volume-controlled continuous mandatory ventilation (VC-CMV) via an endotracheal tube with a tidal volume of 6 mL/kg predicted body weight. Proximal airflow was measured, and the net tidal volume was derived for each respiratory cycle. The deviation from the predetermined tidal volume was calculated and analysed. Several mixed linear models were calculated with the cadaver as a random factor and ventilator, height, sex, crossover period and incremental number of each ventilation within the period as covariates to evaluate differences between ventilators. Results: Overall median deviation of net tidal volume from predetermined tidal volume was − 21.2 % (IQR: 19.6, range: [− 87.9 %; 25.8 %]) corresponding to a tidal volume of 4.75 mL/kg predicted body weight (IQR: 1.2, range: [0.7; 7.6]). In a mixed linear model, the ventilator model, the crossover period, and the cadaver’s height were significant factors for decreased tidal volume. The estimated effects of tidal volume deviation for each ventilator were − 14.5 % [95 %-CI: −22.5; −6.5] (p = 0.0004) for ‘Monnal T60’, − 30.6 % [95 %-CI: −38.6; −22.6] (p < 0.0001) for ‘Oxylog 3000 plus’ and − 31.0 % [95 %-CI: −38.9; −23.0] (p < 0.0001) for ‘MEDUMAT Standard²’. Conclusions: All investigated transport ventilators were able to provide alveolar ventilation even though chest compressions considerably decreased tidal volumes. Our results support the concept of using ventilators to avoid excessive ventilatory rates in CPR. This experimental study suggests that healthcare professionals should carefully monitor actual tidal volumes to recognise the occurrence of hypoventilation during continuous chest compressions.

Manual and mechanical ventilation during cardiopulmonary resuscitation are critical yet poorly understood components of resuscitation care. In recent years, intra-arrest ventilation has been the subject of a growing number of laboratory and clinical investigations. Essential components to accurately interpret or reproduce original investigations are the exact measurement and transparent reporting of key ventilation parameters, such as volumes and airway pressures obtained during ongoing cardiopulmonary resuscitation. Chest compressions lead to frequent intrathoracic and intrapulmonary pressure rises which interact with artificial ventilation. The resulting unique phenomena during continuous chest compressions with asynchronous ventilation and an advanced airway, necessitate a nuanced conceptualization supported by a common terminology. Based on previous original investigations and observations, we describe intra-arrest ventilation parameters and propose a common terminology integrating established and novel concepts. The proposed terminology may serve as a methodological and reporting consideration for future research of intra-arrest ventilation. Additionally, it may serve as a foundation for an authoritative scientific consensus process, which may further facilitate the transparent reporting and reproducible science needed to understand cardiopulmonary resuscitation and improve survival for cardiac arrest patients.

To introduce and evaluate a new, open-source algorithm to detect chest compression periods automatically by the rhythmic, high amplitude signals from an accelerometer, without processing single chest compression events, and to consecutively calculate the chest compression fraction (CCF). A consecutive sample of defibrillator records from the German Resuscitation Registry was obtained and manually annotated in consensus as ground truth. Chest compression periods were determined by different automatic approaches, including the new algorithm. The diagnostic performance of these approaches was assessed. Further, using the different approaches in conjunction with different granularities of manual annotation, several CCF versions were calculated and compared by intraclass correlation coefficient (ICC). 131 defibrillator recordings with a total duration of 5755 minutes were analysed. The new algorithm had a sensitivity of 99.39 (95% CI 99.38, 99.41)% and specificity of 99.17 (95% CI 99.15; 99.18)% to detect chest compressions at any given timepoint. The ICC compared to ground truth was 0.998 for the new algorithm and 0.999 for manual annotation, while the ICC of the proposed algorithm compared to the proprietary software was 0.978. The time required for manual annotation to calculate CCF was reduced by 70.48 (22.55, [94.35, 14.45])%. The proposed algorithm reliably detects chest compressions in defibrillator recordings. It can markedly reduce the workload for manual annotation, which may facilitate uniform reporting of measured quality of cardiopulmonary resuscitation. The algorithm is made freely available and may be used in big data analysis and machine learning approaches.

A1 Point-of-care ultrasound examination of cervical spine in emergency department Yahya Acar, Onur Tezel, Necati Salman A2 A new technique in verifying the placement of a nasogastric tube: obtaining the longitudinal view of nasogastric tube in addition to transverse view with ultrasound Yahya Acar, Necati Salman, Onur Tezel, Erdem Cevik A3 Pseudoaneurysm of the femoral artery after cannulation of a central venous line. Should we always use ultrasound in these procedures? Margarita Algaba-Montes, Alberto Oviedo-García, Mayra Patricio-Bordomás A4 Ultrasound-guided supraclavicular subclavian vein catheterization. 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Atlanto-occipital dislocation is a rare and severe injury of the upper spine associated with a very poor prognosis. We report the case of a 59-year-old European man who suffered from out-of-hospital cardiac arrest following a motor vehicle accident. Cardiopulmonary resuscitation was initiated immediately by bystanders and continued by emergency medical services. After 30 minutes of cardiopulmonary resuscitation with a total of five shocks following initial ventricular fibrillation, return of spontaneous circulation was achieved. An electrocardiogram recorded after return of spontaneous circulation at the scene showed signs of myocardial ischemia as a possible cause for the cardiac arrest. No visible signs of injury were found. He was transferred to the regional academic trauma center. Following an extended diagnostic and therapeutic workup in the emergency room, including extended focused assessment with sonography for trauma ultrasound, whole-body computed tomography, and magnetic resonance imaging (of his head and neck), a diagnosis of major trauma (atlanto-occipital dislocation, bilateral serial rip fractures and pneumothoraces, several severe intracranial bleedings, and other injuries) was made. An unfavorable outcome was initially expected due to suspected tetraplegia and his inability to breathe following atlanto-occipital dislocation. Contrary to initial prognostication, after 22 days of intensive care treatment and four surgical interventions (halo fixation, tracheostomy, intracranial pressure probe, chest drains) he was awake and oriented, spontaneously breathing, and moving his arms and legs. Six weeks after the event he was able to walk without aid. After 2 months of clinical treatment he was able to manage all the activities of daily life on his own. It remains unclear, whether cardiac arrest due to a cardiac cause resulted in complete atony of the paravertebral muscles and caused this extremely severe lesion (atlanto-occipital dislocation) or whether cardiac arrest was caused by apnea due the paraplegia following the spinal injury of the trauma. A plausible cause for the trauma was myocardial infarction which led to the car accident and the major trauma in relation to the obviously minor trauma mechanism. With this case report we aim to familiarize clinicians with the mechanism of injury that will assist in the diagnosis of atlanto-occipital dislocation. Furthermore, we seek to emphasize that patients presenting with electrocardiographic signs of myocardial ischemia after high-energy trauma should primarily be transported to a trauma facility in a percutaneous coronary intervention-capable center rather than the catheterization laboratory directly.

Objective: Exploit accelerometry data for an automatic, reliable, and prompt detection of spontaneous circulation during cardiac arrest, as this is both vital for patient survival and practically challenging. Methods: We developed a machine learning algorithm to automatically predict the circulatory state during cardiopulmonary resuscitation from 4-second-long snippets of accelerometry and electrocardiogram (ECG) data from pauses of chest compressions of real-world defibrillator records. The algorithm was trained based on 422 cases from the German Resuscitation Registry, for which ground truth labels were created by a manual annotation of physicians. It uses a kernelized Support Vector Machine classifier based on 49 features, which partially reflect the correlation between accelerometry and electrocardiogram data. Results: Evaluating 50 different test-training data splits, the proposed algorithm exhibits a balanced accuracy of 81.2%, a sensitivity of 80.6%, and a specificity of 81.8%, whereas using only ECG leads to a balanced accuracy of 76.5%, a sensitivity of 80.2%, and a specificity of 72.8%. Conclusion: The first method employing accelerometry for pulse/no-pulse decision yields a significant increase in performance compared to single ECG-signal usage. Significance: This shows that accelerometry provides relevant information for pulse/no-pulse decisions. In application, such an algorithm may be used to simplify retrospective annotation for quality management and, moreover, to support clinicians to assess circulatory state during cardiac arrest treatment.