Standardisation facilitates reliable interpretation of ETCO2 during manual cardiopulmonary resuscitation.

BACKGROUND: Interpretation of end-tidal CO2 (ETCO2) during manual cardiopulmonary resuscitation (CPR) is affected by variations in ventilation and chest compressions. This study investigates the impact of standardising ETCO2 to constant ventilation rate (VR) and compression depth (CD) on absolute values and trends. METHODS: Retrospective study of out-of-hospital cardiac arrest cases with manual CPR, including defibrillator and clinical data. ETCO2, VR and CD values were averaged by minute. ETCO2 was standardised to 10 vpm and 50 mm. We compared standardised (ETs) and measured (ETm) values and trends during resuscitation. RESULTS: Of 1,036 cases, 287 met the inclusion criteria. VR was mostly lower than recommended, 8.8 vpm, and highly variable within and among patients. CD was mostly within guidelines, 49.8 mm, and less varied. ETs was lower than ETm by 7.3 mmHg. ETs emphasized differences by sex (22.4 females vs. 25.6 mmHg males), initial rhythm (29.1 shockable vs. 22.7 mmHg not), intubation type (25.6 supraglottic vs. 22.4 mmHg endotracheal) and return of spontaneous circulation (ROSC) achieved (34.5 mmHg) vs. not (20.1 mmHg). Trends were different between non-ROSC and ROSC patients before ROSC (-0.3 vs. + 0.2 mmHg/min), and between sustained and rearrest after ROSC (-0.7 vs. -2.1 mmHg/min). Peak ETs was higher for sustained than for rearrest (53.0 vs. 42.5 mmHg). CONCLUSION: Standardising ETCO2 eliminates effects of VR and CD variations during manual CPR and facilitates comparison of values and trends among and within patients. Its clinical application for guidance of resuscitation warrants further investigation.

Metrics of impulsiveness of manual chest compressions for out-of-hospital cardiopulmonary resuscitation.

Aim: Propose new metrics of impulsiveness of manual chest compressions (CCs) that account for shape and duration, separate the characteristics of the compressive part of the CC cycle from those of the recoil part, and are uncorrelated to CC depth and rate. Methods: We conducted a retrospective analysis of adult out-of-hospital cardiac arrest monitor-defibrillator recordings having CPR data. Specifically, episodes of adult patients with ≥ 1000 compressions free of leaning were examined. CCs were obtained from the depth signal of the valid episodes, and we calculated the novel metrics: compression area index (CAI), recoil area index (RAI), compression impulsiveness index (CII) and recoil impulsiveness index (RII). Generalized linear mixed-effects models and Jonckheere-Terpstra trend analyses were employed to measure differences between populations and trends, and the absolute value of Pearson's correlation coefficient |r| was used to report dependence between variables. Statistics are reported as median and interquartile range. Results: We analyzed 982,340 CCs corresponding to 453 episodes, for which we calculated their CAI, RAI and duty cycle (DC). We analyzed the metrics for various populations: age, sex, any ROSC achieved and disposition, and found that CAI was significantly different according to patient disposition and RAI relative to age and sex (p<0.05). None of the metrics was correlated strongly to depth or rate (|r| values of 0.22 or smaller), and all of them varied for CC series corresponding to the same rescuer over the course of resuscitation (ptrend<0.05). However, we observed that the metrics are not balanced, in that for any value of DC, CAI and RAI span almost their entire ranges. Conclusion: The proposed metrics correctly and completely describe manual CC waveforms, improve upon the DC, since they depend on the signal waveform, and provide additional information to current indicators of quality CPR, depth and rate. Furthermore, they allow to differentiate the compressive and recoil parts of the CC cycle, reflecting influence of the rescuer (via CAI or CII) and of the biomechanics of the patient's chest (via RAI or RII). Thus, they have the potential to contribute to better understanding CPR dynamics and, eventually, to enhanced quality of CPR practice as additional indicators of proper manual CC technique.

The Role of Chest Compressions on Ventilation during Advanced Cardiopulmonary Resuscitation.

Background: There is growing interest in the quality of manual ventilation during cardiopulmonary resuscitation (CPR), but accurate assessment of ventilation parameters remains a challenge. Waveform capnography is currently the reference for monitoring ventilation rate in intubated patients, but fails to provide information on tidal volumes and inspiration-expiration timing. Moreover, the capnogram is often distorted when chest compressions (CCs) are performed during ventilation compromising its reliability during CPR. Our main purpose was to characterize manual ventilation during CPR and to assess how CCs may impact on ventilation quality. Methods: Retrospective analysis were performed of CPR recordings fromtwo databases of adult patients in cardiac arrest including capnogram, compression depth, and airway flow, pressure and volume signals. Using automated signal processing techniques followed by manual revision, individual ventilations were identified and ventilation parameters were measured. Oscillations on the capnogram plateau during CCs were characterized, and its correlation with compression depth and airway volume was assessed. Finally, we identified events of reversed airflow caused by CCs and their effect on volume and capnogram waveform. Results: Ventilation rates were higher than the recommended 10 breaths/min in 66.7% of the cases. Variability in ventilation rates correlated with the variability in tidal volumes and other ventilatory parameters. Oscillations caused by CCs on capnograms were of high amplitude (median above 74%) and were associated with low pseudo-volumes (median 26 mL). Correlation between the amplitude of those oscillations with either the CCs depth or the generated passive volumes was low, with correlation coefficients of -0.24 and 0.40, respectively. During inspiration and expiration, reversed airflow events caused opposed movement of gases in 80% of ventilations. Conclusions: Our study confirmed lack of adherence between measured ventilation rates and the guideline recommendations, and a substantial dispersion in manual ventilation parameters during CPR. Oscillations on the capnogram plateau caused by CCs did not correlate with compression depth or associated small tidal volumes. CCs caused reversed flow during inspiration, expiration and in the interval between ventilations, sufficient to generate volume changes and causing oscillations on capnogram. Further research is warranted to assess the impact of these findings on ventilation quality during CPR.

Characterization of mechanical properties of adult chests during pre-hospital manual chest compressions through a simple viscoelastic model.

AIM: The purpose of this study was to develop a simple viscoelastic model to characterize the mechanical properties of chests during manual chest compressions in pre-hospital cardiopulmonary resuscitation (CPR). METHODS: Force and acceleration signals were extracted from CPR monitors used during pre-hospital resuscitation attempts on adult patients. Individual chest compressions were identified and segmented from the chest displacement computed using the force and acceleration. Each compression-recoil cycle was characterized by its elastic coefficient k (a measure of stiffness) and its compression and recoil damping coefficients, dc and dr, respectively (measures of viscosity). We compared the estimated and the calculated chest displacement to assess the goodness of fit of the model. We characterized the chest of patients at the beginning of CPR in relation to sex and age, and their variation as CPR progressed. RESULTS: A total of 1,156,608 chest compressions from 615 patients were analysed. Mean (95% CI) coefficient of determination R2 for the viscoelastic model was 97.9% (97.8-98.1). At the beginning of CPR, k was 104.9 N⋅cm-1 (102.0-107.8), dc was 2.868 N⋅s⋅cm-1 (2.751-2.984) and dr was 4.889 N⋅s⋅cm-1 (4.648-5.129). Damping during recoil was significantly higher than during compression. Stiffness was lower in women than in men. There were no differences in damping coefficients with sex but a higher dr with increasing age. All model coefficients decreased with compression count, with an overall decrease after 3,000 chest compressions of 34.6%, 48.8% and 37.2%, respectively. CONCLUSION: The model accurately described adult chest mechanical properties during CPR, highlighting differences between compression and recoil, sex and age, and a progressive reduction in chest stiffness and viscosity along resuscitation. Our findings may merit further investigation into whether patient-tailored and time-sensitive chest compression technique may be appropriate.

Contribution of chest compressions to end-tidal carbon dioxide levels generated during out-of-hospital cardiopulmonary resuscitation.

AIM: Characterise how changes in chest compression depth and rate affect variations in end-tidal CO2 (ETCO2) during manual cardiopulmonary resuscitation (CPR) in out-of-hospital cardiac arrest (OHCA). METHODS: Retrospective analysis of adult OHCA monitor-defibrillator recordings having concurrent capnogram, compression depth, transthoracic impedance and ECG, and with atleast 1,000 compressions. Within each patient, during no spontaneous circulation, nearby segments with changes in chest compression depth and rate were identified. Average ETCO2 within each segment was standardised to compensate for ventilation rate variability. Contributions of relative variations in depth and rate to relative variations in standardised ETCO2 were characterised using linear and non-linear models. Normalisation between paired segments removed intra and inter-patient variation and made coefficients of the model independent of the scale of measurement and therefore directly comparable. RESULTS: A total of 394 pairs of segments from 221 patients were analysed (33% female, median (IQR) age 66 (55-74) years). Chest compression depth and rate were 50.4 (43.2-57.0)mm and 111.1 (106.5-116.1)compressions per minute. ETCO2 before and after standardization was 32.1 (23.0-41.4)mmHg and 28.5 (19.4-38.7)mmHg. Linear model coefficient of determination was 0.89. Variation in compression depth mainly explained ETCO2 variation (coefficient 0.95, 95% confidence interval (CI): 0.93-0.98) while changes in compression rate did not (coefficient 0.04, 95% CI: 0.01-0.07). Non-linear trend analysis confirmed the results. CONCLUSION: This study quantified the relative importance of chest compression characteristics in terms of their impact on CO2 production during CPR. With ventilation rate standardised, variation in chest compression depth explained variations in ETCO2 better than variation in chest compression rate.

Chest compression release and recoil dynamics in prolonged manual cardiopulmonary resuscitation.

AIM OF THE STUDY: Characterize release and recoil dynamics in chest compressions during prolonged cardiopulmonary resuscitation (CPR) efforts, which are increasingly prevalent. METHODS: Force and depth of chest compressions, and their rates of change, were calculated from records extracted from CPR monitors used during prolonged resuscitation efforts for out-of-hospital cardiac arrest and tracked over time. Metrics were normalized to the median of the first 100 compressions. Kruskal-Wallis ANOVA and Jonckheere-Terpstra trend analyses were used for differences and trends. Averages are reported as median (interquartile range). Correlations among metrics are reported as coefficients of determination. RESULTS: In 471 cases of adult subjects receiving at least 1000 compressions, peak depths varied modestly over the course of extended resuscitation efforts, staying within a narrow range without a trend over the course of resuscitation efforts. Increases in recoil velocity and decreases in recoil interval also remained within limited ranges (5%, 6% variation respectively). By contrast, force waveforms changed substantially. Peak force decreased monotonically reaching a 38% decrease for compression numbers > 3500, similar to a decrease in release rate (39%) and an increase in release interval (39%). CONCLUSION: Depth waveforms change markedly less than do force waveforms over the course of prolonged CPR. With the benefit of feedback, CPR providers effectively adjust the application of force to compensate for changes in chest stiffness, documented previously. Despite slowing release and quickening recoil, interference between release of force and recoil of depth appears limited. Spontaneous chest recoil is well preserved in prolonged duration manual CPR.

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, ΔETavg, 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. ΔETavg 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.

Chest stiffness dynamics in extended continuous compressions cardiopulmonary resuscitation.

AIM OF THE STUDY: To characterize the effects of extended duration continuous compressions cardiopulmonary resuscitation (CPR) on chest stiffness, and its association with adherence to CPR guidelines. METHODS: Records of force and acceleration were extracted from CPR monitors used during attempts of resuscitation from out-of-hospital cardiac arrest. Cases of patients receiving at least 1000 compressions were selected for analysis to focus on extended CPR efforts. Stiffness was normalized per patient to their initial stiffness. Force remaining at the end of compression was used to identify complete release. Non-parametric statistical methods were used throughout as underlying distributions of all types of measurements were non-Gaussian. Averages are reported as median (interquartile range). RESULTS: More than 1000 chest compressions were delivered in 471 of 703 cases. Rate of change in normalized stiffness (Sn) was unrelated to patient age, sex or initial ECG rhythm, and did not predict survival. Most (76%) chests became less stiff over the course of resuscitation efforts. While the remainder (24%) exhibited increased stiffness, overall Sn decreased monotonically, declining by 31% through 3500 compressions. Rate adherence did not show a consistent trend with Sn. Depth adherence and complete release improved modestly with decreasing Sn. CONCLUSION: Chest compressions during extended CPR reduced the stiffness of most patients' chests, in the aggregate by 31% after 3500 compressions. This softening was associated with modestly improved adherence to depth and release guidelines, with inconsistent relation to rate adherence to guidelines.

The impact of ventilation rate on end-tidal carbon dioxide level during manual cardiopulmonary resuscitation.

AIM: Ventilation rate is a confounding factor for interpretation of end-tidal carbon dioxide (ETCO2) during cardiopulmonary resuscitation (CPR). The aim of our study was to model the effect of ventilation rate on ETCO2 during manual CPR in adult out-of-hospital cardiac arrest (OHCA). METHODS: We conducted a retrospective analysis of OHCA monitor-defibrillator files with concurrent capnogram, compression depth, transthoracic impedance and ECG. We annotated pairs of capnogram segments presenting differences in average ventilation rate and average ETCO2 value but with other influencing factors (e.g. compression rate and depth) presenting similar values within the pair. ETCO2 variation as a function of ventilation rate was adjusted through curve fitting using non-linear least squares as a measure of goodness of fit. RESULTS: A total of 141 pairs of segments from 102 patients were annotated. Each pair provided a single data point for curve fitting. The best goodness of fit yielded a coefficient of determination R2 of 0.93. Our model described that ETCO2 decays exponentially with increasing ventilation rate. The model showed no differences attributable to the airway type (endotracheal tube or supraglottic King-LT-D). CONCLUSION: Capnogram interpretation during CPR is challenging since many factors influence ETCO2. For adequate interpretation, we need to know the effect of each factor on ETCO2. Our model allows quantifying the effect of ventilation rate on ETCO2 variation. Our findings could contribute to better interpretation of ETCO2 during CPR.

Chest compressions induce errors in end-tidal carbon dioxide measurement.

BACKGROUND: Real-time measurement of end-tidal carbon dioxide (ETCO2) is used as a non-invasive estimate of cardiac output and perfusion during cardiopulmonary resuscitation (CPR). However, capnograms are often distorted by chest compressions (CCs) and this may affect ETCO2 measurement. The aim of the study was to quantify the effect of CC-artefact on the accuracy of ETCO2 measurements obtained during out-of-hospital manual CPR. METHODS: We retrospectively analysed monitor-defibrillator recordings collected by two advanced life support agencies during out-of-hospital cardiac arrest. These two agencies, represented as A and B used different side-stream capnometers and monitor-defibrillators. One-minute capnogram segments were reviewed. Each ventilation within each segment was identified using the transthoracic impedance signal and the capnogram. ETCO2 values per ventilation were manually annotated and compared to the corresponding capnometry values stored in the monitor-defibrillator. Ventilations were classified as distorted or non-distorted by CC-artefact. RESULTS: A total of 407 1-min capnogram segments from 65 patients were analysed. Overall, 4095 ventilations were annotated, 2170 (32.4% distorted) and 1925 (31.8% distorted) for agency A and B, respectively. Median (IQR) unsigned error in ETCO2 measurement increased from 1.5 (0.6-3.1)% for non-distorted to 5.5 (1.8-14.1)% for distorted ventilations; from 0.7 (0.3-1.2)% to 3.7 (1.0-9.9)% in agency A and from 2.3 (1.2-3.9)% to 8.3 (3.9-19.5)% in agency B (p < 0.001). Errors were higher than 10 mmHg in 9% and higher than 15 mmHg in 5% of the distorted ventilations. CONCLUSION: CC-artefact causes ETCO2 measurement errors in the two studied devices. This suggests that capnometer algorithms may need to be adapted to reliably perform in the presence of CC-artefact during CPR.

Modeling the impact of ventilations on the capnogram in out-of-hospital cardiac arrest.

AIM: Current resuscitation guidelines recommend waveform capnography as an indirect indicator of perfusion during cardiopulmonary resuscitation (CPR). Chest compressions (CCs) and ventilations during CPR have opposing effects on the exhaled carbon dioxide (CO2) concentration, which need to be better characterized. The purpose of this study was to model the impact of ventilations in the exhaled CO2 measured from capnograms collected during out-of-hospital cardiac arrest (OHCA) resuscitation. METHODS: We retrospectively analyzed OHCA monitor-defibrillator files with concurrent capnogram, compression depth, transthoracic impedance and ECG signals. Segments with CC pauses, two or more ventilations, and with no pulse-generating rhythm were selected. Thus, only ventilations should have caused the decrease in CO2 concentration. The variation in the exhaled CO2 concentration with each ventilation was modeled with an exponential decay function using non-linear-least-squares curve fitting. RESULTS: Out of the original 1002 OHCA dataset (one per patient), 377 episodes had the required signals, and 196 segments from 96 patients met the inclusion criteria. Airway type was endotracheal tube in 64.8% of the segments, supraglottic King LT-D™ in 30.1%, and unknown in 5.1%. Median (IQR) decay factor of the exhaled CO2 concentration was 10.0% (7.8 - 12.9) with R2 = 0.98(0.95 - 0.99). Differences in decay factor with airway type were not statistically significant (p = 0.17). From these results, we propose a model for estimating the contribution of CCs to the end-tidal CO2 level between consecutive ventilations and for estimating the end-tidal CO2 variation as a function of ventilation rate. CONCLUSION: We have modeled the decrease in exhaled CO2 concentration with ventilations during chest compression pauses in CPR. This finding allowed us to hypothesize a mathematical model for explaining the effect of chest compressions on ETCO2 compensating for the influence of ventilation rate during CPR. However, further work is required to confirm the validity of this model during ongoing chest compressions.

Association of chest compression and recoil velocities with depth and rate in manual cardiopulmonary resuscitation.

AIM: Maximum velocity during chest recoil has been proposed as a metric for chest compression quality during cardiopulmonary resuscitation (CPR). This study investigated the relationship of the maximum velocities during compression and recoil phases with compression depth and rate in manual CPR. METHODS: We measured compression instances in out-of-hospital cardiac arrest recordings using custom Matlab programs. Each compression cycle was characterized by depth and rate, maximum compression and recoil velocities (CV and RV), and compression and recoil durations (total and effective). Mean compression and recoil velocities were computed as depth divided by compression and recoil durations, respectively. We correlated CV and RV with their corresponding mean velocities (total and effective), characterized by Pearson's correlation coefficient. RESULTS: CV/RV were strongly correlated with their corresponding mean velocities, with a median r of 0.83 (0.77-0.88)/0.82 (0.76-0.87) in per patient analysis, 0.86/0.88 for all the population. Correlation with mean effective velocities had a median r of 0.91 (0.87-0.94)/0.92 (0.89-0.94) in per-patient, 0.92/0.94 globally (p < 0.001). Total and effective compression and recoil durations were inversely proportional to compression rate. We observed similar RV values among compressions regardless of whether they were compliant with recommended depth and rate. Conversely, we observed different RV values among compressions having the same depth and rate, but presenting very distinct compression waveforms. CONCLUSION: CV and RV were highly correlated with compression depth and compression and recoil times, respectively. Better understanding of the relationship between novel and current quality metrics could help with the interpretation of CPR quality studies.

Enhancing ventilation detection during cardiopulmonary resuscitation by filtering chest compression artifact from the capnography waveform.

BACKGROUND: During cardiopulmonary resuscitation (CPR), there is a high incidence of capnograms distorted by chest compression artifact. This phenomenon adversely affects the reliability of automated ventilation detection based on the analysis of the capnography waveform. This study explored the feasibility of several filtering techniques for suppressing the artifact to improve the accuracy of ventilation detection. MATERIALS AND METHODS: We gathered a database of 232 out-of-hospital cardiac arrest defibrillator recordings containing concurrent capnograms, compression depth and transthoracic impedance signals. Capnograms were classified as non-distorted or distorted by chest compression artifact. All chest compression and ventilation instances were also annotated. Three filtering techniques were explored: a fixed-coefficient (FC) filter, an open-loop (OL) adaptive filter, and a closed-loop (CL) adaptive filter. The improvement in ventilation detection was assessed by comparing the performance of a capnogram-based ventilation detection algorithm with original and filtered capnograms. RESULTS: Sensitivity and positive predictive value of the ventilation algorithm improved from 91.9%/89.5% to 97.7%/96.5% (FC filter), 97.6%/96.7% (OL), and 97.0%/97.1% (CL) for the distorted capnograms (42% of the whole set). The highest improvement was obtained for the artifact named type III, for which performance improved from 77.8%/74.5% to values above 95.5%/94.5%. In addition, errors in the measurement of ventilation rate decreased and accuracy in the detection of over-ventilation increased with filtered capnograms. CONCLUSIONS: Capnogram-based ventilation detection during CPR was enhanced after suppressing the artifact caused by chest compressions. All filtering approaches performed similarly, so the simplicity of fixed-coefficient filters would take advantage for a practical implementation.

Monitoring chest compression quality during cardiopulmonary resuscitation: Proof-of-concept of a single accelerometer-based feedback algorithm.

BACKGROUND: The use of real-time feedback systems to guide rescuers during cardiopulmonary resuscitation (CPR) significantly contributes to improve adherence to published resuscitation guidelines. Recently, we designed a novel method for computing depth and rate of chest compressions relying solely on the spectral analysis of chest acceleration. That method was extensively tested in a simulated manikin scenario. The purpose of this study is to report the results of this method as tested in human out-of-hospital cardiac arrest (OHCA) cases. MATERIALS AND METHODS: The algorithm was evaluated retrospectively with seventy five OHCA episodes recorded by monitor-defibrillators equipped with a CPR feedback device. The acceleration signal and the compression signal computed by the CPR feedback device were stored in each episode. The algorithm was continuously applied to the acceleration signals. The depth and rate values estimated every 2-s from the acceleration data were compared to the reference values obtained from the compression signal. The performance of the algorithm was assesed in terms of the sensitivity and positive predictive value (PPV) for detecting compressions and in terms of its accuracy through the analysis of measurement error. RESULTS: The algorithm reported a global sensitivity and PPV of 99.98% and 99.79%, respectively. The median (P75) unsigned error in depth and rate was 0.9 (1.7) mm and 1.0 (1.7) cpm, respectively. In 95% of the analyzed 2-s windows the error was below 3.5 mm and 3.1 cpm, respectively. CONCLUSIONS: The CPR feedback algorithm proved to be reliable and accurate when tested retrospectively with human OHCA episodes. A new CPR feedback device based on this algorithm could be helpful in the resuscitation field.