Chest Compressions in the Delivery Room.
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ABSTRACT:
SUBMITTER: Garcia-Hidalgo C
PROVIDER: S-EPMC6352088 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
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Chest Compressions in the Delivery Room.
Garcia-Hidalgo Catalina C Schmölzer Georg M GM
Children (Basel, Switzerland) 20190103 1
Annually, an estimated 13⁻26 million newborns need respiratory support and 2⁻3 million newborns need extensive resuscitation, defined as chest compression and 100% oxygen with or without epinephrine in the delivery room. Despite such care, there is a high incidence of mortality and neurologic morbidity. The poor prognosis associated with receiving chest compression alone or with medications in the delivery room raises questions as to whether improved cardiopulmonary resuscitation methods specifi ...[more]
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Project description:BackgroundThe Nuss procedure temporarily places intrathoracic bars for repair of pectus excavatum (PE). The bars may impact excursion and compliance of the anterior chest wall while in place. Effective chest compressions during cardiopulmonary resuscitation (CPR) require depressing the anterior chest wall enough to compress the heart between sternum and spine. We assessed the force required to perform the American Heart Association's recommended chest compression depth after Nuss repair.MethodsA lumped element elastic model was developed to simulate the relationship between chest compression forces and displacement with focus on the amount of force required to achieve a depth of 5 cm in the presence of 1-3 Nuss bars. Literature review was conducted for evidence supporting potential use of active abdominal compressions and decompression (AACD) as an alternative method of CPR.ResultsThe presence of bars notably lowered compression depth by a minimum of 69% compared to a chest without bar(s). The model also demonstrated a dramatic increase (minimum of 226%) in compressive forces required to achieve recommended 5 cm depth. Literature review suggests AACD could be an alternative CPR in patients with Nuss bar(s).ConclusionsIn our model, Nuss bars limited the ability to perform chest compressions due to increased force required to achieve a 5 cm compression. The greater the number of Nuss bars present the greater the force required. This may prevent effective CPR. Use of active abdominal compressions and decompressions should be studied further as an alternative resuscitation modality for patients after the Nuss procedure.
| S-EPMC7475523 | biostudies-literature
Project description:PurposeCurrent knowledge about pulmonary/systemic hemodynamics and gas exchange during neonatal resuscitation in a model of transitioning fetal circulation with fetal shunts and fluid-filled alveoli is limited. Using a fetal lamb asphyxia model, we sought to determine whether hemodynamic or gas-exchange parameters predicted successful return of spontaneous circulation (ROSC).MethodsThe umbilical cord was occluded in 22 lambs to induce asphyxial cardiac arrest. Following five minutes of asystole, resuscitation as per AHA-Neonatal Resuscitation Program guidelines was initiated. Hemodynamic parameters and serial arterial blood gases were assessed during resuscitation.ResultsROSC occurred in 18 lambs (82%) at a median (IQR) time of 120 (105-180) seconds. There were no differences in hemodynamic parameters at baseline and at any given time point during resuscitation between the lambs that achieved ROSC and those that did not. Blood gases at arrest prior to resuscitation were comparable between groups. However, lambs that achieved ROSC had lower PaO2, higher PaCO2, and lower lactate during resuscitation. Increase in diastolic blood pressures induced by epinephrine in lambs that achieved ROSC (11 ±4 mmHg) did not differ from those that were not resuscitated (10 ±6 mmHg). Low diastolic blood pressures were adequate to achieve ROSC.ConclusionsHemodynamic parameters in a neonatal lamb asphyxia model with transitioning circulation did not predict success of ROSC. Lactic acidosis, higher PaO2 and lower PaCO2 observed in the lambs that did not achieve ROSC may represent a state of inadequate tissue perfusion and/or mitochondrial dysfunction.
| S-EPMC5404764 | biostudies-literature
Project description:BackgroundOut-of-hospital ventricular fibrillation (VF) cardiac arrest is a leading cause of death. Quantitative analysis of the VF electrocardiogram (ECG) can predict patient outcomes and could potentially enable a patient-specific, guided approach to resuscitation. However, VF analysis during resuscitation is confounded by cardiopulmonary resuscitation (CPR) artifact in the ECG, challenging continuous application to guide therapy throughout resuscitation. We therefore sought to design a method to predict VF shock outcomes during CPR.MethodsStudy data included 4577 5-s VF segments collected during and without CPR prior to defibrillation attempts in N = 1151 arrest patients. Using training data (460 patients), an algorithm was designed to predict the VF shock outcomes of defibrillation success (return of organized ventricular rhythm) and functional survival (Cerebral Performance Category 1-2). The algorithm was designed with variable-frequency notch filters to reduce CPR artifact in the ECG based on real-time chest compression rate. Ten ECG features and three dichotomous patient characteristics were developed to predict outcomes. These variables were combined using support vector machines and logistic regression. Algorithm performance was evaluated by area under the receiver operating characteristic curve (AUC) to predict outcomes in validation data (691 patients).ResultsAUC (95% Confidence Interval) for predicting defibrillation success was 0.74 (0.71-0.77) during CPR and 0.77 (0.74-0.79) without CPR. AUC for predicting functional survival was 0.75 (0.72-0.78) during CPR and 0.76 (0.74-0.79) without CPR.ConclusionA novel algorithm predicted defibrillation success and functional survival during ongoing CPR following VF arrest, providing a potential proof-of-concept towards real-time guidance of resuscitation therapy.
| S-EPMC10860689 | biostudies-literature
Project description:The Resuscitation Outcomes Consortium is conducting a randomized trial comparing survival with hospital discharge after continuous chest compressions without interruption for ventilation versus currently recommended American Heart Association cardiopulmonary resuscitation with interrupted chest compressions in adult patients with out-of-hospital cardiac arrest without obvious trauma or respiratory cause. Emergency medical services perform study cardiopulmonary resuscitation for 3 intervals of manual chest compressions (each ~2 minutes) or until restoration of spontaneous circulation. Patients randomized to the continuous chest compression intervention receive 200 chest compressions with positive pressure ventilations at a rate of 10/min without interruption in compressions. Those randomized to the interrupted chest compression study arm receive chest compressions interrupted for positive pressure ventilations at a compression:ventilation ratio of 30:2. In either group, each interval of compressions is followed by rhythm analysis and defibrillation as required. Insertion of an advanced airway is deferred for the first ≥6 minutes to reduce interruptions in either study arm. The study uses a cluster randomized design with every-6-month crossovers. The primary outcome is survival to hospital discharge. Secondary outcomes are neurologically intact survival and adverse events. A maximum of 23,600 patients (11,800 per group) enrolled during the post-run-in phase of the study will provide ≥90% power to detect a relative change of 16% in the rate of survival to discharge, 8.1% to 9.4% with overall significance level of 0.05. If this trial demonstrates improved survival with either strategy, >3,000 premature deaths from cardiac arrest would be averted annually.
| S-EPMC4363111 | biostudies-literature
Project description:AIM OF THE STUDY:Bystander-initiated basic life support (BLS) for the treatment of prehospital cardiac arrest increases survival but is frequently not performed due to fear and a lack of knowledge. A simple flowchart can improve motivation and the quality of performance. Furthermore, guidelines do recommend a chest compression (CC)-only algorithm for dispatcher-assisted bystander resuscitation, which may lead to increased fatigue and a loss of compression depth. Consequently, we wanted to test the hypothesis that CCs are more correctly delivered in a flowchart-assisted standard resuscitation algorithm than in a CC-only algorithm. METHODS:With the use of a manikin model, 84 laypersons were randomized to perform either flowchart-assisted standard resuscitation or CC-only resuscitation for 5min. The primary outcome was the total number of CCs. RESULTS:The total number of correct CCs did not significantly differ between the CC-only group and the standard group (63 [±81] vs. 79 [±86]; p = 0.394; 95% CI of difference: 21-53). The total hand-off time was significantly lower in the CC-only group than in the standard BLS group. The relative number of correct CCs (the fraction of the total number of CCs achieving 5-6cm) and the level of exhaustion after BLS did not significantly differ between the groups. CONCLUSION:Standard BLS did not lead to an increase in correctly delivered CCs compared to CC-only resuscitation and exhibited significantly more hand-off time. The low rate of CCs in both groups indicates the need for an increased focus on performance during BLS training.
| S-EPMC7017996 | biostudies-literature
Project description:Current resuscitation protocols require pausing chest compressions during cardiopulmonary resuscitation (CPR) to check for a pulse. However, pausing CPR when a patient is pulseless can worsen patient outcomes. Our objective was to design and evaluate an ECG-based algorithm that predicts pulse presence with or without CPR. We evaluated 383 patients being treated for out-of-hospital cardiac arrest with real-time ECG, impedance and audio recordings. Paired ECG segments having an organized rhythm immediately preceding a pulse check (during CPR) and during the pulse check (without CPR) were extracted. Patients were randomly divided into 60% training and 40% test groups. From training data, we developed an algorithm to predict the clinical pulse presence based on the wavelet transform of the bandpass-filtered ECG. Principal component analysis was used to reduce dimensionality, and we then trained a linear discriminant model using three principal component modes as input features. Overall, 38% (351/912) of checks had a spontaneous pulse. AUCs for predicting pulse presence with and without CPR on test data were 0.84 (95% CI (0.80, 0.88)) and 0.89 (95% CI (0.86, 0.92)), respectively. This ECG-based algorithm demonstrates potential to improve resuscitation by predicting the presence of a spontaneous pulse without pausing CPR with moderate accuracy.
| S-EPMC8580432 | biostudies-literature
Project description:Compressions at the left ventricle increase rate of return of spontaneous circulation. This study aimed to identify the landmark of the point of maximal left ventricular diameter on the sternum (LVmax) by using chest computed tomography (CCT) in the arms-down position, which was similar to an actual cardiac arrest patient. A retrospective study was conducted between September 2014 and November 2020. We included adult patients who underwent CCT in an arms-down position and measured the rescuer’s hand. We measured the distance from the sternal notch to LVmax (DLVmax), to the lower half of sternum (DLH), and to the point of maximal force of hand, which placed the lowest palmar margin of the rescuer’s reference hand at the xiphisternal junction. Thirty-nine patients were included. The LVmax was located below the lower half of the sternum; DLVmax and DLH were 12.6 and 10.0 cm, respectively (p < 0.001). Distance from the sternal notch to the point of maximal force of the left hand, with the ulnar border located at the xiphisternal junction, was close to DLVmax; 11.3 and 12.6 cm, respectively (p = 0.076). In conclusion, LVmax was located below the lower half of the sternum, which is recommended by current guidelines.
| S-EPMC9033090 | biostudies-literature
Project description:BACKGROUND:Quantitative measures of the ventricular fibrillation (VF) ECG waveform can assess myocardial physiology and predict cardiac arrest outcomes, making these measures a candidate to help guide resuscitation. Chest compressions are typically paused for waveform measure calculation because compressions cause ECG artifact. However, such pauses contradict resuscitation guideline recommendations to minimize cardiopulmonary resuscitation interruptions. We evaluated a comprehensive group of VF measures with and without ongoing compressions to determine their performance under both conditions for predicting functionally-intact survival, the study's primary outcome. METHODS:Five-second VF ECG segments were collected with and without chest compressions before 2755 defibrillation shocks from 1151 out-of-hospital cardiac arrest patients. Twenty-four individual measures and 3 combination measures were implemented. Measures were optimized to predict functionally-intact survival (Cerebral Performance Category score ?2) using 460 training cases, and their performance evaluated using 691 independent test cases. RESULTS:Measures predicted functionally-intact survival on test data with an area under the receiver operating characteristic curve ranging from 0.56 to 0.75 (median, 0.73) without chest compressions and from 0.53 to 0.75 (median, 0.69) with compressions ( P<0.001 for difference). Of all measures evaluated, the support vector machine model ranked highest both without chest compressions (area under the receiver operating characteristic curve, 0.75; 95% CI, 0.73-0.78) and with compressions (area under the receiver operating characteristic curve, 0.75; 95% CI, 0.72-0.78; P=0.75 for difference). CONCLUSIONS:VF waveform measures predict functionally-intact survival when calculated during chest compressions, but prognostic performance is generally reduced compared with compression-free analysis. However, support vector machine models exhibited similar performance with and without compressions while also achieving the highest area under the receiver operating characteristic curve. Such machine learning models may, therefore, offer means to guide resuscitation during uninterrupted cardiopulmonary resuscitation.
| S-EPMC6532650 | biostudies-literature
Project description:ObjectiveInterruptions in chest compressions during treatment of out-of-hospital cardiac arrest are associated with lower likelihood of successful resuscitation. Real-time automated detection of chest compressions may improve CPR administration during resuscitation, and could facilitate application of next-generation ECG algorithms that employ different parameters depending on compression state. In contrast to accelerometer sensors, transthoracic impedance (TTI) is commonly acquired by defibrillators. We sought to develop and evaluate the performance of a TTI-based algorithm to automatically detect chest compressions.MethodsFive-second TTI segments were collected from patients with out-of-hospital cardiac arrest treated by one of four defibrillator models. Segments with and without chest compressions were collected prior to each of the first four defibrillation shocks (when available) from each case. Patients were divided randomly into 40% training and 60% validation groups. From the training segments, we identified spectral and time-domain features of the TTI associated with compressions. We used logistic regression to predict compression state from these features. Performance was measured by sensitivity and specificity in the validation set. The relationship between performance and TTI segment length was also evaluated.ResultsThe algorithm was trained using 1859 segments from 460 training patients. Validation sensitivity and specificity were >98% using 2727 segments from 691 validation patients. Validation performance was significantly reduced using segments shorter than 3.2 s.ConclusionsA novel method can reliably detect the presence of chest compressions using TTI. These results suggest potential to provide real-time feedback in order to improve CPR performance or facilitate next-generation ECG rhythm algorithms during resuscitation.
| S-EPMC7235095 | biostudies-literature
Project description:AimPropose 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.MethodsWe 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.ResultsWe 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.ConclusionThe 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.
| S-EPMC11004537 | biostudies-literature