RESUMEN
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.
Asunto(s)
Reanimación Cardiopulmonar , Paro Cardíaco Extrahospitalario , Adulto , Retroalimentación , Humanos , Paro Cardíaco Extrahospitalario/terapia , Presión , TóraxRESUMEN
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.
Asunto(s)
Reanimación Cardiopulmonar , Paro Cardíaco Extrahospitalario , Humanos , Paro Cardíaco Extrahospitalario/terapia , TóraxRESUMEN
BACKGROUND: Current resuscitation guidelines emphasize the use of waveform capnography to help guide rescuers during cardiopulmonary resuscitation (CPR). However, chest compressions often cause oscillations in the capnogram, impeding its reliable interpretation, either visual or automated. The aim of the study was to design an algorithm to enhance waveform capnography by suppressing the chest compression artefact. METHODS: Monitor-defibrillator recordings from 202 patients in out-of-hospital cardiac arrest were analysed. Capnograms were classified according to the morphology of the artefact. Ventilations were annotated using the transthoracic impedance signal acquired through defibrillation pads. The suppression algorithm is designed to operate in real-time, locating distorted intervals and restoring the envelope of the capnogram. We evaluated the improvement in automated ventilation detection, estimation of ventilation rate, and detection of excessive ventilation rates (over-ventilation) using the capnograms before and after artefact suppression. RESULTS: A total of 44â¯267 ventilations were annotated. After artefact suppression, sensitivity (Se) and positive predictive value (PPV) of the ventilation detector increased from 91.9/89.5% to 98.0/97.3% in the distorted episodes (83/202). Improvement was most noticeable for high-amplitude artefact, for which Se/PPV raised from 77.6/73.5% to 97.1/96.1%. Estimation of ventilation rate and detection of over-ventilation also upgraded. The suppression algorithm had minimal impact in non-distorted data. CONCLUSION: Ventilation detection based on waveform capnography improved after chest compression artefact suppression. Moreover, the algorithm enhances the capnogram tracing, potentially improving its clinical interpretation during CPR. Prospective research in clinical settings is needed to understand the feasibility and utility of the method.
Asunto(s)
Apoyo Vital Cardíaco Avanzado/métodos , Artefactos , Capnografía/estadística & datos numéricos , Masaje Cardíaco/efectos adversos , Algoritmos , Desfibriladores/efectos adversos , Humanos , Paro Cardíaco Extrahospitalario/terapia , Evaluación de Resultado en la Atención de Salud , Sistema de Registros , Frecuencia Respiratoria , Estudios RetrospectivosRESUMEN
BACKGROUND: Measurement of chest velocity has been proposed as an alternative method to identify responder leaning during cardiopulmonary resuscitation (CPR). Leaning is defined in terms of force, but no study has tested the utility of chest velocity in the presence of force measurements that directly measure leaning. MATERIALS AND METHODS: We analyzed 1004 out-of-hospital cardiac arrest (OHCA) files collected with Q-CPR monitors in the Portland, Oregon, USA metro region from 2006 to 2017. Records contained accelerometry and force signals. For each chest compression, the following metrics were computed: minimum force at the end of the compression (Frelease), compression depth, compression rate, maximum chest velocity during recoil (vrecoil) and maximum rate of change in force during chest release (Êrelease). A compression was classified as having leaning if Frelease was greater than 2.5â¯kg-f. The ability of vrecoil and Êrelease to predict Frelease was estimated with generalized linear models, and their ability to identify leaning with logistic regression. RESULTS: The data set contained over 1.5 million chest compressions, 21% compliant with 2015 rate and depth guidelines for CPR (the G2015 population). Leaning was uncommon generally (12%), and less common in G2015 compliant compressions (5%). Leaning and Frelease decreased with both vrecoil and Êrelease but with extensive overlap. Neither vrecoil nor Êrelease, alone or in combination with chest compression rate and depth, reliably predicted leaning or Frelease. CONCLUSION: Leaning cannot be reliably identified from vrecoil or Êrelease, alone or in combination with currently recommended chest compression metrics in out-of-hospital CPR.
Asunto(s)
Acelerometría/métodos , Reanimación Cardiopulmonar , Masaje Cardíaco , Paro Cardíaco Extrahospitalario/terapia , Reanimación Cardiopulmonar/métodos , Reanimación Cardiopulmonar/estadística & datos numéricos , Femenino , Masaje Cardíaco/métodos , Masaje Cardíaco/normas , Humanos , Masculino , Persona de Mediana Edad , Mejoramiento de la Calidad , Reproducibilidad de los ResultadosRESUMEN
BACKGROUND: Out-of-hospital cardiac arrest is common in public locations, including public transportation sites. Feedback devices are increasingly being used to improve chest-compression quality. However, their performance during public transportation has not been studied yet. OBJECTIVE: To test two CPR feedback devices representative of the current technologies (accelerometer and electromag- netic-field) in a long-distance train. METHODS: Volunteers applied compressions on a manikin during the train route using both feedback devices. Depth and rate measurements computed by the devices were compared to the gold-standard values. RESULTS: Sixty-four 4-min records were acquired. The accelerometer-based device provided visual help in all experiments. Median absolute errors in depth and rate were 2.4 mm and 1.3 compressions per minute (cpm) during conventional speed, and 2.5 mm and 1.2 cpm during high speed. The electromagnetic-field-based device never provided CPR feedback; alert messages were shown instead. However, measurements were stored in its internal memory. Absolute errors for depth and rate were 2.6 mm and 0.7 cpm during conventional speed, and 2.6 mm and 0.7 cpm during high speed. CONCLUSIONS: Both devices were accurate despite the accelerations and the electromagnetic interferences induced by the train. However, the electromagnetic-field-based device would require modifications to avoid excessive alerts impeding feedback.
Asunto(s)
Reanimación Cardiopulmonar/métodos , Retroalimentación Formativa , Maniquíes , Paro Cardíaco Extrahospitalario/terapia , Vías Férreas , Aceleración , Campos Electromagnéticos , HumanosRESUMEN
AIM: To design and evaluate a simple algorithm able to discriminate pulsatile rhythms from pulseless electrical activity during automated external defibrillator (AED) analysis intervals, using the ECG and the transthoracic impedance (TI) acquired from defibrillation pads. METHODS: ECG and TI signals from out-of-hospital AED recordings were retrospectively analysed. Experts annotated the cardiac rhythm during AED analysis intervals and at the end of each episode. We developed an algorithm to classify 3-s segments of non-shockable and non-asystole rhythms as either pulsatile rhythm or pulseless electrical activity. The algorithm consisted on a decision tree based on two features: the mean power of the TI segment and the mean cross-power between ECG and TI segments. RESULTS: From the 302 annotated episodes, 167 contained segments eligible for the study. The circulation detector algorithm presented a sensitivity (ability of detecting pulsatile rhythms) of 98.3% (95% CI: 95.1-100) and a specificity (ability to detect pulseless electrical activity) of 98.4% (95% CI: 97.1-99.8) in the validation subset. Absence of pulsatile rhythm was confirmed during the first AED analysis interval in 98.9% of the episodes, and presence of a pulse was confirmed in the first 3â¯s of all intervals with annotated return of spontaneous circulation. CONCLUSION: Accurate automated detection of circulation based on TI and ECG is possible during AED analysis intervals. This functionality could potentially contribute to enhance patient's care by laypersons using AEDs.
Asunto(s)
Cardiografía de Impedancia , Desfibriladores/estadística & datos numéricos , Electrocardiografía/estadística & datos numéricos , Paro Cardíaco Extrahospitalario/diagnóstico , Flujo Pulsátil , Circulación Sanguínea , Reanimación Cardiopulmonar/métodos , Femenino , Humanos , Masculino , Paro Cardíaco Extrahospitalario/terapia , Estudios RetrospectivosRESUMEN
BACKGROUND: Capnography has been proposed as a method for monitoring the ventilation rate during cardiopulmonary resuscitation (CPR). A high incidence (above 70%) of capnograms distorted by chest compression induced oscillations has been previously reported in out-of-hospital (OOH) CPR. The aim of the study was to better characterize the chest compression artefact and to evaluate its influence on the performance of a capnogram-based ventilation detector during OOH CPR. METHODS: Data from the MRx monitor-defibrillator were extracted from OOH cardiac arrest episodes. For each episode, presence of chest compression artefact was annotated in the capnogram. Concurrent compression depth and transthoracic impedance signals were used to identify chest compressions and to annotate ventilations, respectively. We designed a capnogram-based ventilation detection algorithm and tested its performance with clean and distorted episodes. RESULTS: Data were collected from 232 episodes comprising 52â¯654 ventilations, with a mean (±SD) of 227 (±118) per episode. Overall, 42% of the capnograms were distorted. Presence of chest compression artefact degraded algorithm performance in terms of ventilation detection, estimation of ventilation rate, and the ability to detect hyperventilation. CONCLUSION: Capnogram-based ventilation detection during CPR using our algorithm was compromised by the presence of chest compression artefact. In particular, artefact spanning from the plateau to the baseline strongly degraded ventilation detection, and caused a high number of false hyperventilation alarms. Further research is needed to reduce the impact of chest compression artefact on capnographic ventilation monitoring.
Asunto(s)
Artefactos , Capnografía/métodos , Masaje Cardíaco/efectos adversos , Respiración , Algoritmos , Capnografía/estadística & datos numéricos , Reanimación Cardiopulmonar/métodos , Desfibriladores , Cardioversión Eléctrica/estadística & datos numéricos , Humanos , Sensibilidad y EspecificidadRESUMEN
Background. Cardiopulmonary resuscitation (CPR) feedback devices are being increasingly used. However, current accelerometer-based devices overestimate chest displacement when CPR is performed on soft surfaces, which may lead to insufficient compression depth. Aim. To assess the performance of a new algorithm for measuring compression depth and rate based on two accelerometers in a simulated resuscitation scenario. Materials and Methods. Compressions were provided to a manikin on two mattresses, foam and sprung, with and without a backboard. One accelerometer was placed on the chest and the second at the manikin's back. Chest displacement and mattress displacement were calculated from the spectral analysis of the corresponding acceleration every 2 seconds and subtracted to compute the actual sternal-spinal displacement. Compression rate was obtained from the chest acceleration. Results. Median unsigned error in depth was 2.1 mm (4.4%). Error was 2.4 mm in the foam and 1.7 mm in the sprung mattress (p < 0.001). Error was 3.1/2.0 mm and 1.8/1.6 mm with/without backboard for foam and sprung, respectively (p < 0.001). Median error in rate was 0.9 cpm (1.0%), with no significant differences between test conditions. Conclusion. The system provided accurate feedback on chest compression depth and rate on soft surfaces. Our solution compensated mattress displacement, avoiding overestimation of compression depth when CPR is performed on soft surfaces.
Asunto(s)
Acelerometría , Algoritmos , Reanimación Cardiopulmonar/instrumentación , Reanimación Cardiopulmonar/métodos , Tórax/fisiopatología , Estudios Cruzados , Femenino , Humanos , Masculino , ManiquíesRESUMEN
BACKGROUND: Quality of cardiopulmonary resuscitation (CPR) is key to increase survival from cardiac arrest. Providing chest compressions with adequate rate and depth is difficult even for well-trained rescuers. The use of real-time feedback devices is intended to contribute to enhance chest compression quality. These devices are typically based on the double integration of the acceleration to obtain the chest displacement during compressions. The integration process is inherently unstable and leads to important errors unless boundary conditions are applied for each compression cycle. Commercial solutions use additional reference signals to establish these conditions, requiring additional sensors. Our aim was to study the accuracy of three methods based solely on the acceleration signal to provide feedback on the compression rate and depth. MATERIALS AND METHODS: We simulated a CPR scenario with several volunteers grouped in couples providing chest compressions on a resuscitation manikin. Different target rates (80, 100, 120, and 140 compressions per minute) and a target depth of at least 50 mm were indicated. The manikin was equipped with a displacement sensor. The accelerometer was placed between the rescuer's hands and the manikin's chest. We designed three alternatives to direct integration based on different principles (linear filtering, analysis of velocity, and spectral analysis of acceleration). We evaluated their accuracy by comparing the estimated depth and rate with the values obtained from the reference displacement sensor. RESULTS: The median (IQR) percent error was 5.9% (2.8-10.3), 6.3% (2.9-11.3), and 2.5% (1.2-4.4) for depth and 1.7% (0.0-2.3), 0.0% (0.0-2.0), and 0.9% (0.4-1.6) for rate, respectively. Depth accuracy depended on the target rate (p < 0.001) and on the rescuer couple (p < 0.001) within each method. CONCLUSIONS: Accurate feedback on chest compression depth and rate during CPR is possible using exclusively the chest acceleration signal. The algorithm based on spectral analysis showed the best performance. Despite these encouraging results, further research should be conducted to asses the performance of these algorithms with clinical data.
Asunto(s)
Acelerometría/métodos , Reanimación Cardiopulmonar/métodos , Paro Cardíaco/terapia , Tórax/fisiopatología , Acelerometría/instrumentación , Algoritmos , Reanimación Cardiopulmonar/instrumentación , Retroalimentación , Humanos , Maniquíes , Modelos Teóricos , Presión , Reproducibilidad de los Resultados , Factores de TiempoRESUMEN
BACKGROUND: Quality of cardiopulmonary resuscitation (CPR) is an important determinant of survival from cardiac arrest. The use of feedback devices is encouraged by current resuscitation guidelines as it helps rescuers to improve quality of CPR performance. AIM: To determine the feasibility of a generic algorithm for feedback related to chest compression (CC) rate using the transthoracic impedance (TTI) signal recorded through the defibrillation pads. METHODS: We analysed 180 episodes collected equally from three different emergency services, each one using a unique defibrillator model. The new algorithm computed the CC-rate every 2s by analysing the TTI signal in the frequency domain. The obtained CC-rate values were compared with the gold standard, computed using the compression force or the ECG and TTI signals when the force was not recorded. The accuracy of the CC-rate, the proportion of alarms of inadequate CC-rate, chest compression fraction (CCF) and the mean CC-rate per episode were calculated. RESULTS: Intervals with CCs were detected with a mean sensitivity and a mean positive predictive value per episode of 96.3% and 97.0%, respectively. Estimated CC-rate had an error below 10% in 95.8% of the time. Mean percentage of accurate alarms per episode was 98.2%. No statistical differences were found between the gold standard and the estimated values for any of the computed metrics. CONCLUSION: We developed an accurate algorithm to calculate and provide feedback on CC-rate using the TTI signal. This could be integrated into automated external defibrillators and help improve the quality of CPR in basic-life-support settings.
Asunto(s)
Algoritmos , Cardiografía de Impedancia/métodos , Reanimación Cardiopulmonar , Servicios Médicos de Urgencia/normas , Retroalimentación , Paro Cardíaco/terapia , Reanimación Cardiopulmonar/instrumentación , Reanimación Cardiopulmonar/métodos , Reanimación Cardiopulmonar/normas , Desfibriladores , Electrocardiografía/métodos , Estudios de Factibilidad , Humanos , Valor Predictivo de las Pruebas , Presión , Garantía de la Calidad de Atención de Salud/métodos , Mejoramiento de la Calidad , Reproducibilidad de los ResultadosRESUMEN
Quality of cardiopulmonary resuscitation (CPR) improves through the use of CPR feedback devices. Most feedback devices integrate the acceleration twice to estimate compression depth. However, they use additional sensors or processing techniques to compensate for large displacement drifts caused by integration. This study introduces an accelerometer-based method that avoids integration by using spectral techniques on short duration acceleration intervals. We used a manikin placed on a hard surface, a sternal triaxial accelerometer, and a photoelectric distance sensor (gold standard). Twenty volunteers provided 60 s of continuous compressions to test various rates (80-140 min(-1)), depths (3-5 cm), and accelerometer misalignment conditions. A total of 320 records with 35312 compressions were analysed. The global root-mean-square errors in rate and depth were below 1.5 min(-1) and 2 mm for analysis intervals between 2 and 5 s. For 3 s analysis intervals the 95% levels of agreement between the method and the gold standard were within -1.64-1.67 min(-1) and -1.69-1.72 mm, respectively. Accurate feedback on chest compression rate and depth is feasible applying spectral techniques to the acceleration. The method avoids additional techniques to compensate for the integration displacement drift, improving accuracy, and simplifying current accelerometer-based devices.