Predicting ROSC in out-of-hospital cardiac arrest using expiratory carbon dioxide concentration: Is trend-detection instead of absolute threshold values the key?

Volumetric capnography and return of spontaneous circulation in an experimental model of pediatric asphyxial cardiac arrest

A secondary analysis of a randomized study was performed to study the relationship between volumetric capnography (VCAP) and arterial CO2 partial pressure (PCO2) during cardiopulmonary resuscitation (CPR) and to analyze the ability of these parameters to predict the return of spontaneous circulation (ROSC) in a pediatric animal model of asphyxial cardiac arrest (CA). Asphyxial CA was induced by sedation, muscle relaxation and extubation. CPR was started 2 min after CA occurred. Airway management was performed with early endotracheal intubation or bag-mask ventilation, according to randomization group. CPR was continued until ROSC or 24 min of resuscitation. End-tidal carbon dioxide (EtCO2), CO2 production (VCO2), and EtCO2/VCO2/kg ratio were continuously recorded. Seventy-nine piglets were included, 26 (32.9%) of whom achieved ROSC. EtCO2 was the best predictor of ROSC (AUC 0.72, p < 0.01 and optimal cutoff point of 21.6 mmHg). No statistical differences were obtained regarding VCO2, VCO2/kg and EtCO2/VCO2/kg ratios. VCO2 and VCO2/kg showed an inverse correlation with PCO2, with a higher correlation coefficient as resuscitation progressed. EtCO2 also had an inverse correlation with PCO2 from minute 18 to 24 of resuscitation. Our findings suggest that EtCO2 is the best VCAP-derived parameter for predicting ROSC. EtCO2 and VCO2 showed an inverse correlation with PCO2. Therefore, these parameters are not adequate to measure ventilation during CPR.

End-tidal carbon dioxide (ETCO2) at intubation and its increase after 10 minutes resuscitation predicts survival with good neurological outcome in out-of-hospital cardiac arrest patients

AIM

To evaluate whether end-tidal carbon dioxide (ETCO2) value at intubation and its early increase (10 min) after intubation predict both the survival to hospital admission and the survival at hospital discharge, including good neurological outcome (CPC 1-2), in patients with out-of-hospital cardiac arrest (OHCA).

METHODS

All consecutive OHCA patients of any etiology between 2015 and 2018 in Pavia Province (Italy) and Ticino Region (Switzerland) were considered. Patients died before ambulance arrival, with a "do-not-resuscitate" order, without ETCO2 value or with incomplete data were excluded.

RESULTS

The study population consisted of 668 patients. An ETCO2 value at intubation > 20 mmHg and its increase 10 min after intubation were independent predictors (after correction for known predictors of OHCA outcome) of survival to hospital admission and survival at hospital discharge. Relative to hospital discharge with good neurological outcome, ETCO2 at intubation and its 10-min change were confirmed predictors both individually and in a bivariable analysis (OR 1.83, 95 %CI 1.02-3.3; p = 0.04 and OR 3.9, 95 %CI 1.97-7.74; p < 0.001, respectively). This was confirmed also when accounting for gender, age, etiology and location. After further adjustment for bystander and CPR status, presenting rhythm and EMS arrival time, the ETCO2 change remained an independent predictor.

CONCLUSIONS

ETCO2 value > 20 mmHg at intubation and its increase during resuscitation improve the prediction of survival at hospital discharge with good neurological outcome of OHCA patients. ETCO2 increase during resuscitation is a more powerful predictor than ETCO2 at intubation. A larger prospective study to confirm this finding appears warranted.

Capnography for Monitoring of the Critically Ill Patient

Capnography has been widely adopted in multiple clinical areas. The capnogram and end-tidal carbon dioxide offer a wealth of information, in the right clinical setting, and when properly interpreted. In this article, the authors aim to review the most common clinical scenarios during which capnography has been shown to be of benefit. This includes the areas of fluid responsiveness, cardiopulmonary resuscitation, and conscious sedation. They review the published literature, highlighting its pitfalls and identifying its limitations.

Assessment of a new volumetric capnography-derived parameter to reflect compression quality and to predict return of spontaneous circulation during cardiopulmonary resuscitation in a porcine model

We aimed to evaluate a volumetric capnography (Vcap)-derived parameter, the volume of CO2 eliminated per minute and per kg body weight (VCO2/kg), as an indicator of the quality of chest compression (CC) and to predict the return to spontaneous circulation (ROSC) under stable ventilation status. Twelve male domestic pigs were utilized for the randomized crossover study. After 4 min of untreated ventricular fibrillation (VF), mechanical cardiopulmonary resuscitation and ventilation were administered. Following 5-min washout periods, each animal underwent two sessions of experiments: three types of CC quality for 5 min stages in the first session, followed by advanced life support, consecutively in two sessions. Different CC quality had a significant effect on the partial pressure of end-tidal carbon dioxide (PetCO2), VCO2/kg, aortic pressure (mean), aortic systolic pressure, aortic diastolic pressure, right atrial pressure (mean), and carotid blood flow (P < 0.05). With the improvement in CC quality, the values of PetCO2 and VCO2/kg also increased, and the difference between the groups was statistically significant (P < 0.05). The Spearman rank test revealed a significant correlation between the Vcap-derived parameters and hemodynamics. PetCO2 and VCO2/kg have similar capabilities for discriminating survivors from non-survivors, and the area under the curve for both was 0.97. VCO2/kg had similar performance as PetCO2 in reflecting the quality of CC and prediction of achieving ROSC under stable ventilation status in a porcine model of VF-related cardiac arrest. However, VCO2/kg requires a longer time to achieve a stable state after adjusting for quality of CC than PetCO2.

[Adult advanced life support]

These European Resuscitation Council Advanced Life Support guidelines are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the prevention of and ALS treatments for both in-hospital cardiac arrest and out-of-hospital cardiac arrest.

Assessment of the evolution of end-tidal carbon dioxide within chest compression pauses to detect restoration of spontaneous circulation

Background

Measurement of end-tidal CO₂ (ETCO₂) can help to monitor circulation during cardiopulmonary resuscitation (CPR). However, early detection of restoration of spontaneous circulation (ROSC) during CPR using waveform capnography remains a challenge. The aim of the study was to investigate if the assessment of ETCO₂ variation during chest compression pauses could allow for ROSC detection. We hypothesized that a decay in ETCO₂ during a compression pause indicates no ROSC while a constant or increasing ETCO2 indicates ROSC.

Methods

We conducted a retrospective analysis of adult out-of-hospital cardiac arrest (OHCA) episodes treated by the advanced life support (ALS). Continuous chest compressions and ventilations were provided manually. Segments of capnography signal during pauses in chest compressions were selected, including at least three ventilations and with durations less than 20 s. Segments were classified as ROSC or non-ROSC according to case chart annotation and examination of the ECG and transthoracic impedance signals. The percentage variation of ETCO₂ between consecutive ventilations was computed and its average value, ΔET_avg, was used as a single feature to discriminate between ROSC and non-ROSC segments.

Results

A total of 384 segments (130 ROSC, 254 non-ROSC) from 205 OHCA patients (30.7% female, median age 66) were analyzed. Median (IQR) duration was 16.3 (12.9,18.1) s. ΔET_avg was 0.0 (-0.7, 0.9)% for ROSC segments and -11.0 (-14.1, -8.0)% for non-ROSC segments (p < 0.0001). Best performance for ROSC detection yielded a sensitivity of 95.4% (95% CI: 90.1%, 98.1%) and a specificity of 94.9% (91.4%, 97.1%) for all ventilations in the segment. For the first 2 ventilations, duration was 7.7 (6.0, 10.2) s, and sensitivity and specificity were 90.0% (83.5%, 94.2%) and 89.4 (84.9%, 92.6%), respectively. Our method allowed for ROSC detection during the first compression pause in 95.4% of the patients.

Conclusion

Average percent variation of ETCO₂ during pauses in chest compressions allowed for ROSC discrimination. This metric could help confirm ROSC during compression pauses in ALS settings.

Association of Prehospital Oxygen Saturation to Inspired Oxygen Ratio With 1-, 2-, and 7-Day Mortality

IMPORTANCE

The early identification of patients at high risk of clinical deterioration represents one of the greatest challenges for emergency medical services (EMS).

OBJECTIVE

To assess whether use of the ratio of prehospital oxygen saturation measured by pulse oximetry (Spo2) to fraction of inspired oxygen (Fio2) measured during initial contact by EMS with the patient (ie, the first Spo2 to Fio2 ratio) and 5 minutes before the patient's arrival at the hospital (ie, the second Spo2 to Fio2 ratio) can predict the risk of early in-hospital deterioration.

DESIGN, SETTING, AND PARTICIPANTS

A prospective, derivation-validation prognostic cohort study of 3606 adults with acute diseases referred to 5 tertiary care hospitals in Spain was conducted between October 26, 2018, and June 30, 2020. Eligible patients were recruited from among all telephone requests for EMS assistance for adults who were later evacuated with priority in advanced life support units to the referral hospitals during the study period.

MAIN OUTCOMES AND MEASURES

The primary outcome was hospital mortality from any cause within the first, second, third, or seventh day after EMS transport to the hospital. The main measure was the Spo2 to Fio2 ratio.

RESULTS

A total of 3606 participants comprised 2 separate cohorts: the derivation cohort (3081 patients) and the validation cohort (525 patients). The median age was 69 years (interquartile range, 54-81 years), and 2122 patients (58.8%) were men. The overall mortality rate of the patients in the study cohort ranged from 3.6% for 1-day mortality (131 patients) to 7.1% for 7-day mortality (256 patients). The best model performance was for 2-day mortality with the second Spo2 to Fio2 ratio with an area under the curve of 0.890 (95% CI, 0.829-0.950; P < .001), although the other outcomes also presented good results. In addition, a risk-stratification model was generated. The optimal cutoff resulted in the following ranges of Spo2 to Fio2 ratios: 50 to 100 for high risk of mortality, 101 to 426 for intermediate risk, and 427 to 476 for low risk.

CONCLUSIONS AND RELEVANCE

This study suggests that use of the prehospital Spo2 to Fio2 ratio was associated with improved management of patients with acute disease because it accurately predicts short-term mortality.

European Resuscitation Council Guidelines 2021: Adult advanced life support

These European Resuscitation Council Advanced Life Support guidelines, are based on the 2020 International Consensus on Cardiopulmonary Resuscitation Science with Treatment Recommendations. This section provides guidelines on the prevention of and ALS treatments for both in-hospital cardiac arrest and out-of-hospital cardiac arrest.

Modified volumetric capnography-derived parameter: A potentially stable indicator in monitoring cardiopulmonary resuscitation efficacy in a porcine model

AIM

We aimed to investigate whether the ability of the volumetric capnography-derived parameter, the volume of CO₂ eliminated per minute and per kg body weight (V'CO₂ kg^-1), in monitoring the quality of CPR and predicting the return of spontaneous circulation (ROSC) remains undisturbed by hyperventilation.

METHODS

This randomised crossover study included 12 male domestic pigs. After 4 min of untreated ventricular fibrillation, mechanical CPR was administered. Following 5-min washout periods, each animal underwent two sessions of experiments; four 5-min ventilation trials followed by advanced life support, consecutively in the two sessions.

RESULTS

Different ventilation types had no significant impact on V'CO₂ kg^-1 or haemodynamics. However, PETCO₂ was significantly affected by the ventilation type and coronary perfusion pressure (P < 0.05). The means ± standard deviations of PETCO₂ decreased linearly with an increase in the respiratory rate (RR) (P < 0.05). The PETCO₂ decreased from 20.42 ± 9.51 to 16.16 ± 5.07 (P < 0.05) as the tidal volume increased from 10 to 20 mL min^-1. No significant differences in V'CO₂ kg^-1 were observed between the three RR levels of ventilation types (P = 0.274). Post hoc analysis demonstrated a significant difference between the highest value of V'CO₂ kg^-1 in double tidal volume hyperventilation and normal ventilation and triple respiratory rate hyperventilation (P < 0.05). The AUC for V'CO₂ kg^-1 and PETCO₂ in discriminating between survivors and non-survivors was 0.80 and 0.71, respectively.

CONCLUSIONS

V'CO₂ kg^-1 performs better than PETCO₂ in monitoring the quality of CPR during hyperventilation. In predicting ROSC during variations in a ventilation state, V'CO₂ kg^-1 has good predictive ability.

Capnography: A support tool for the detection of return of spontaneous circulation in out-of-hospital cardiac arrest

BACKGROUND

Automated detection of return of spontaneous circulation (ROSC) is still an unsolved problem during cardiac arrest. Current guidelines recommend the use of capnography, but most automatic methods are based on the analysis of the ECG and thoracic impedance (TI) signals. This study analysed the added value of EtCO₂ for discriminating pulsed (PR) and pulseless (PEA) rhythms and its potential to detect ROSC.

MATERIALS AND METHODS

A total of 426 out-of-hospital cardiac arrest cases, 117 with ROSC and 309 without ROSC, were analysed. First, EtCO₂ values were compared for ROSC and no ROSC cases. Second, 5098 artefact free 3-s long segments were automatically extracted and labelled as PR (3639) or PEA (1459) using the instant of ROSC annotated by the clinician on scene as gold standard. Machine learning classifiers were designed using features obtained from the ECG, TI and the EtCO₂ value. Third, the cases were retrospectively analysed using the classifier to discriminate cases with and without ROSC.

RESULTS

EtCO₂ values increased significantly from 41 mmHg 3-min before ROSC to 57 mmHg 1-min after ROSC, and EtCO₂ was significantly larger for PR than for PEA, 46 mmHg/20 mmHg (p < 0.05). Adding EtCO₂ to the machine learning models increased their area under the curve (AUC) by over 2 percentage points. The combination of ECG, TI and EtCO₂ had an AUC for the detection of pulse of 0.92. Finally, the retrospective analysis showed a sensitivity and specificity of 96.6% and 94.5% for the detection of ROSC and no-ROSC cases, respectively.

CONCLUSION

Adding EtCO₂ improves the performance of automatic algorithms for pulse detection based on ECG and TI. These algorithms can be used to identify pulse on site, and to retrospectively identify cases with ROSC.

Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest

The automatic detection of pulse during out-of-hospital cardiac arrest (OHCA) is necessary for the early recognition of the arrest and the detection of return of spontaneous circulation (end of the arrest). The only signal available in every single defibrillator and valid for the detection of pulse is the electrocardiogram (ECG). In this study we propose two deep neural network (DNN) architectures to detect pulse using short ECG segments (5 s), i.e., to classify the rhythm into pulseless electrical activity (PEA) or pulse-generating rhythm (PR). A total of 3914 5-s ECG segments, 2372 PR and 1542 PEA, were extracted from 279 OHCA episodes. Data were partitioned patient-wise into training (80%) and test (20%) sets. The first DNN architecture was a fully convolutional neural network, and the second architecture added a recurrent layer to learn temporal dependencies. Both DNN architectures were tuned using Bayesian optimization, and the results for the test set were compared to state-of-the art PR/PEA discrimination algorithms based on machine learning and hand crafted features. The PR/PEA classifiers were evaluated in terms of sensitivity (Se) for PR, specificity (Sp) for PEA, and the balanced accuracy (BAC), the average of Se and Sp. The Se/Sp/BAC of the DNN architectures were 94.1%/92.9%/93.5% for the first one, and 95.5%/91.6%/93.5% for the second one. Both architectures improved the performance of state of the art methods by more than 1.5 points in BAC.

Quantitative pupillometry and neuron-specific enolase independently predict return of spontaneous circulation following cardiogenic out-of-hospital cardiac arrest: a prospective pilot study

This study aimed to identify neurological and pathophysiological factors that predicted return of spontaneous circulation (ROSC) among patients with out-of-hospital cardiac arrest (OHCA). This prospective 1-year observational study evaluated patients with cardiogenic OHCA who were admitted to a tertiary medical center, Nippon Medical School Hospital. Physiological and neurological examinations were performed at admission for quantitative infrared pupillometry (measured with NPi-200, NeurOptics, CA, USA), arterial blood gas, and blood chemistry. Simultaneous blood samples were also collected to determine levels of neuron-specific enolase (NSE), S-100b, phosphorylated neurofilament heavy subunit, and interleukin-6. In-hospital standard advanced cardiac life support was performed for 30 minutes.The ROSC (n = 26) and non-ROSC (n = 26) groups were compared, which a revealed significantly higher pupillary light reflex ratio, which was defined as the percent change between maximum pupil diameter before light stimuli and minimum pupil diameter after light stimuli, in the ROSC group (median: 1.3% [interquartile range (IQR): 0.0–2.0%] vs. non-ROSC: (median: 0%), (Cut-off: 0.63%). Furthermore, NSE provided the great sensitivity and specificity for predicting ROSC, with an area under the receiver operating characteristic curve of 0.86, which was created by plotting sensitivity and 1-specificity. Multivariable logistic regression analyses revealed that the independent predictors of ROSC were maximum pupillary diameter (odds ratio: 0.25, 95% confidence interval: 0.07–0.94, P = 0.04) and NSE at admission (odds ratio: 0.96, 95% confidence interval: 0.93–0.99, P = 0.04). Pupillary diameter was also significantly correlated with NSE concentrations (r = 0.31, P = 0.027). Conclusively, the strongest predictors of ROSC among patients with OHCA were accurate pupillary diameter and a neuronal biomarker, NSE. Quantitative pupillometry may help guide the decision to terminate resuscitation in emergency departments using a neuropathological rationale. Further large-scale studies are needed.

ECG-based pulse detection during cardiac arrest using random forest classifier

Sudden cardiac arrest is one of the leading causes of death in the industrialized world. Pulse detection is essential for the recognition of the arrest and the recognition of return of spontaneous circulation during therapy, and it is therefore crucial for the survival of the patient. This paper introduces the first method based exclusively on the ECG for the automatic detection of pulse during cardiopulmonary resuscitation. Random forest classifier is used to efficiently combine up to nine features from the time, frequency, slope, and regularity analysis of the ECG. Data from 191 cardiac arrest patients was used, and 1177 ECG segments were processed, 796 with pulse and 381 without pulse. A leave-one-patient out cross validation approach was used to train and test the algorithm. The statistical distributions of sensitivity (SE) and specificity (SP) for pulse detection were estimated using 500 patient-wise bootstrap partitions. The mean (std) SE/SP for nine-feature classifier was 88.4 (1.8) %/89.7 (1.4) %, respectively. The designed algorithm only requires 4-s-long ECG segments and could be integrated in any commercial automated external defibrillator. The method permits to detect the presence of pulse accurately, minimizing interruptions in cardiopulmonary resuscitation therapy, and could contribute to improve survival from cardiac arrest.

Capnography during cardiac arrest

Successful resuscitation from cardiac arrest depends on provision of adequate blood flow to vital organs generated by cardiopulmonary resuscitation (CPR). Measurement of end-tidal expiratory pressure of carbon dioxide (ETCO₂) using capnography provides a noninvasive estimate of cardiac output and organ perfusion during cardiac arrest and can therefore be used to monitor the quality of CPR and predict return of spontaneous circulation (ROSC). In clinical observational studies, mean ETCO₂ levels in patients with ROSC are higher than those in patients with no ROSC. In prolonged out of hospital cardiac arrest, ETCO₂ levels <10 mmHg are consistently associated with a poor outcome, while levels above this threshold have been suggested as a criterion for considering patients for rescue extracorporeal resuscitation. An abrupt rise of ETCO₂ during CPR suggests that ROSC has occurred. Finally, detection of CO₂ in exhaled air following intubation is the most specific criterion for confirming endotracheal tube placement during CPR. The aetiology of cardiac arrest, variations in ventilation patterns during CPR, and the effects of drugs such as adrenaline or sodium bicarbonate administered as a bolus may significantly affect ETCO₂ levels and its clinical significance. While identifying ETCO₂ as a useful monitoring tool during resuscitation, current guidelines for advanced life support recommend against using ETCO₂ values in isolation for decision making in cardiac arrestmanagement.

De l’entrée à la sortie du service de réanimation adulte : une mise au point sur l’utilisation courante du monitoring du CO2 expiré

L’objectif de cette mise au point est d’effectuer une revue des indications de l’utilisation du monitorage du CO2 expiré en réanimation adulte. De par sa physiologie, sa mesure est un reflet de l’état hémodynamique, respiratoire et métabolique du patient. La spectrométrie infrarouge est la méthode de mesure la plus courante. La capnographie commune (CO2 expiré en fonction du temps) est divisée en plusieurs phases dont l’analyse visuelle peut faire évoquer de nombreuses anomalies ventilatoires. La capnographie volumétrique fournit une mesure de l’espace mort. La capnométrie est recommandée en réanimation pour contrôler l’intubation trachéale ou bien au cours d’un arrêt cardiorespiratoire comme facteur pronostique. Tout patient traité par ventilation mécanique invasive, surtout lors d’un transport, doit être équipé d’un capnomètre afin d’anticiper toute complication respiratoire (extubation, bronchospasme, hypoventilation). La pression de fin d’expiration en CO2 (PetCO2) est une évaluation de la pression artérielle en CO2 (PaCO2) utile pour limiter le nombre de prélèvements biologiques, par exemple en neuroréanimation, mais de nombreux facteurs font varier le gradient entre ces deux valeurs. Les études n’apportent pas de preuve pour l’utilisation de la capnographie volumétrique dans le diagnostic d’embolie pulmonaire en réanimation. Chez les patients souffrant de syndrome de détresse respiratoire aiguë, la littérature médicale n’apporte pas de preuve suffisante pour un intérêt en pratique clinique courante de la capnométrie volumétrique qui semble limitée dans ce cas à la recherche.