Injuries associated with mechanical chest compressions and active decompressions after out-of-hospital cardiac arrest: A subgroup analysis of non-survivors from a randomized study.

Background: Both skeletal and visceral injuries are reported after cardiopulmonary resuscitation (CPR). This subgroup analysis of a randomized clinical study describes/compares autopsy documented injury patterns caused by two mechanical, piston-based chest compression devices: standard LUCAS® 2 (control) and LUCAS® 2 with active decompression (AD, intervention) in non-survivors with out-of-hospital cardiac arrest (CA). Method: We compared injuries documented by autopsies (medical/forensic) after control and intervention CPR based on written relatives consent to use patients' data. The pathologists were blinded for the device used. The cause of CA and injuries reported were based on a prespecified study autopsy template. We used Pearson's chi-squared test and logistic regression analysis with an alpha level of 0.05. Results: 221 patients were included in the main study (April 2015-April 2017) and 207 did not survive. Of these, 114 (55%, 64 control and 50 intervention) underwent medical (N = 73) or forensic (N = 41) autopsy. The cause of CA was cardiac 53%, respiratory 17%, overdose/intoxication 14%, ruptured aorta 10%, neurological 1%, and other 5%. There were no differences between control and intervention in the incidence of rib fractures (67% vs 72%; p-value = 0.58), or sternal fractures (44% vs 48%; p-value = 0.65), respectively. The most frequent non-skeletal complication was bleeding (26% of all patients) and intrathoracic was the most common location. Ten of the 114 patients had internal organ injuries, where lungs were most affected. Conclusion: In non-survivors of OHCA patients, the most frequent cause of cardiac arrest was cardiogenic. Skeletal and non-skeletal fractures/injuries were found in both control and intervention groups. Bleeding was the most common non-skeletal complication. Internal organ injuries were rare.

Mechanical active compression-decompression versus standard mechanical cardiopulmonary resuscitation: A randomised haemodynamic out-of-hospital cardiac arrest study.

BACKGROUND: Active compression-decompression cardiopulmonary resuscitation (ACD-CPR) utilises a suction cup to lift the chest-wall actively during the decompression phase (AD). We hypothesised that mechanical ACD-CPR (Intervention), with AD up to 30 mm above the sternal resting position, would generate better haemodynamic results than standard mechanical CPR (Control). METHODS: This out-of-hospital adult non-traumatic cardiac arrest trial was prospective, block-randomised and non-blinded. We included intubated patients with capnography recorded during mechanical CPR. Exclusion criteria were pregnancy, prisoners, and prior chest surgery. The primary endpoint was maximum tidal carbon dioxide partial pressure (pMTCO2) and secondary endpoints were oxygen saturation of cerebral tissue (SctO2), invasive arterial blood pressures and CPR-related injuries. Intervention device lifting force performance was categorised as Complete AD (≥30 Newtons) or Incomplete AD (≤10 Newtons). Haemodynamic data, analysed as one measurement for each parameter per ventilation (Observation Unit, OU) with non-linear regression statistics are reported as mean (standard deviation). A two-sided p-value < 0.05 was considered as statistically significant. RESULTS: Of 221 enrolled patients, 210 were deemed eligible (Control 109, Intervention 101). The Control vs. Intervention results showed no significant differences for pMTCO2: 29(17) vs 29(18) mmHg (p = 0.86), blood pressures during compressions: 111(45) vs. 101(68) mmHg (p = 0.93) and decompressions: 21(20) vs. 18(18) mmHg (p = 0.93) or for SctO2%: 55(36) vs. 57(9) (p = 0.42). The 48 patients who received Complete AD in > 50% of their OUs had higher SctO2 than Control patients: 58(11) vs. 55(36)% (p < 0.001). CONCLUSIONS: Mechanical ACD-CPR provided similar haemodynamic results to standard mechanical CPR. The Intervention device did not consistently provide Complete AD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier (NCT number): NCT02479152. The Haemodynamic Effects of Mechanical Standard and Active Chest Compression-decompression During Out-of-hospital CPR.

Multimodal Algorithms for the Classification of Circulation States During Out-of-Hospital Cardiac Arrest.

GOAL: Identifying the circulation state during out-of-hospital cardiac arrest (OHCA) is essential to determine what life-saving therapies to apply. Currently algorithms discriminate circulation (pulsed rhythms, PR) from no circulation (pulseless electrical activity, PEA), but PEA can be classified into true (TPEA) and pseudo (PPEA) depending on cardiac contractility. This study introduces multi-class algorithms to automatically determine circulation states during OHCA using the signals available in defibrillators. METHODS: A cohort of 60 OHCA cases were used to extract a dataset of 2506 5-s segments, labeled as PR (1463), PPEA (364) and TPEA (679) using the invasive blood pressure, experimentally recorded through a radial/femoral cannulation. A multimodal algorithm using features obtained from the electrocardiogram, the thoracic impedance and the capnogram was designed. A random forest model was trained to discriminate three (TPEA/PPEA/PR) and two (PEA/PR) circulation states. The models were evaluated using repeated patient-wise 5-fold cross-validation, with the unweighted mean of sensitivities (UMS) and F 1-score as performance metrics. RESULTS: The best model for 3-class had a median (interquartile range, IQR) UMS and F 1 of 69.0% (68.0-70.1) and 61.7% (61.0-62.5), respectively. The best two class classifier had median (IQR) UMS and F 1 of 83.9% (82.9-84.5) and 76.2% (75.0-76.9), outperforming all previous proposals in over 3-points in UMS. CONCLUSIONS: The first multiclass OHCA circulation state classifier was demonstrated. The method improved previous algorithms for binary pulse/no-pulse decisions. SIGNIFICANCE: Automatic multiclass circulation state classification during OHCA could contribute to improve cardiac arrest therapy and improve survival rates.

Transthoracic Impedance Measured with Defibrillator Pads-New Interpretations of Signal Change Induced by Ventilations.

Compressions during the insufflation phase of ventilations may cause severe pulmonary injury during cardiopulmonary resuscitation (CPR). Transthoracic impedance (TTI) could be used to evaluate how chest compressions are aligned with ventilations if the insufflation phase could be identified in the TTI waveform without chest compression artifacts. Therefore, the aim of this study was to determine whether and how the insufflation phase could be precisely identified during TTI. We synchronously measured TTI and airway pressure (Paw) in 21 consenting anaesthetised patients, TTI through the defibrillator pads and Paw by connecting the monitor-defibrillator's pressure-line to the endotracheal tube filter. Volume control mode with seventeen different settings were used (5-10 ventilations/setting): Six volumes (150-800 mL) with 12 min-1 frequency, four frequencies (10, 12, 22 and 30 min-1) with 400 mL volume, and seven inspiratory times (0.5-3.5 s ) with 400 mL/10 min-1 volume/frequency. Median time differences (quartile range) between timing of expiration onset in the Paw-line (PawEO) and the TTI peak and TTI maximum downslope were measured. TTI peak and PawEO time difference was 579 (432-723) m s for 12 min-1, independent of volume, with a negative relation to frequency, and it increased linearly with inspiratory time (slope 0.47, R 2 = 0.72). PawEO and TTI maximum downslope time difference was between -69 and 84 m s for any ventilation setting (time aligned). It was independent ( R 2 < 0.01) of volume, frequency and inspiratory time, with global median values of -47 (-153-65) m s , -40 (-168-68) m s and 20 (-93-128) m s , for varying volume, frequency and inspiratory time, respectively. The TTI peak is not aligned with the start of exhalation, but the TTI maximum downslope is. This knowledge could help with identifying the ideal ventilation pattern during CPR.