Prognostication In Cardiac Arrest Patients Research Articles

Continuous amplitude-integrated electroencephalography for prognostication of cardiac arrest patients undergoing extracorporeal cardiopulmonary resuscitation with targeted temperature management

BackgroundExtracorporeal cardiopulmonary resuscitation (ECPR) has been increasingly used for adult cardiac arrest (CA) patients refractory to conventional CPR. However, data on early prognosticators of neurological outcome are lacking. MethodsCA patients undergoing ECPR were prospectively monitored via amplitude-integrated EEG (aEEG). Targeted temperature management (TTM) was induced using an extracorporeal membrane oxygenation system. aEEG background patterns were classified into continuous normal voltage (CNV), discontinuous normal voltage (DNV), low voltage (LV), flat trace (FT), burst suppression (BS), and status epilepticus (SE). The Cerebral Performance Category (CPC) scale scores at hospital discharge and at 6 months after discharge were assessed, as was wakefulness after TTM. Good neurological outcome was defined as a CPC score of 1 or 2. ResultsTwenty-two patients were studied. Six patients who showed CNV within 24 hours after arrival, including one with initial FT and two with initial LV, regained consciousness and had good neurological outcome except for one who died of haemorrhagic complication. Patients with persistent FT or BS at any time did not regain consciousness. Regarding 19 patients in whom aEEG data were obtained within 24 hours, CNV background predicted good outcome at 6 months with 100% sensitivity, 93% specificity, 83% positive predictive values, and 100% negative predictive values. All these indices were 100% concerning wakefulness after TTM. ConclusionaEEG monitoring was feasible and practical in adult CA patients undergoing ECPR and TTM. Evolution of aEEG background within 24 hours provides early accurate information for neurological prognostication.

Routine blood markers from different biological pathways improve early risk stratification in cardiac arrest patients: Results from the prospective, observational COMMUNICATE study

IntroductionPrognostication of cardiac arrest patients admitted to the intensive care unit (ICU) may influence treatment decision, but remains challenging. We evaluated the incremental usefulness of routine blood markers from different biological pathways for predicting fatal outcome and neurological deficits in cardiac arrest patients. MethodsWe prospectively included consecutive, adult cardiac arrest patients upon ICU admission. We recorded initial clinical parameters and measured blood markers of cardiac injury/stress (troponin, BNP, CK), inflammation/infection (WBC, CRP, procalcitonin) and shock (lactate, creatinine, urea). The primary and secondary endpoints were all-cause in-hospital mortality and bad neurological outcome defined by the Cerebral Performance Category (CPC) score. ResultsMortality in the 321 included patients was 49% (n = 156). Procalcitonin (adjusted odds ratio 1.84, 95%CI 1.34 to 2.53, p < 0.001; AUC 0.73) and lactate (adjusted odds ratio 7.29, 95%CI 3.05 to 17.42, p < 0.001; AUC 0.70) were identified as independent prognostic factors for mortality and significantly improved discrimination of a parsimonious clinical model including resuscitation measures (no-flow time, shockable rhythm) and initial vital signs (Glasgow coma scale, respiratory rate) from an AUC of 0.79 to 0.84 (p < 0.001). Cardiac markers did not further improve the model. Results for neurological outcome were similar with model improvements by procalcitonin and lactate from AUC 0.83 to 0.87 (p = 0.004). ConclusionAssessment of routine markers of inflammation/infection and shock provide significant improvements for prognostication of cardiac arrest patients, while cardiac markers did not further improve statistical models. Combination of blood markers and clinical parameters may help to improve initial management decisions in this vulnerable patient population.

Early prognostication markers in cardiac arrest patients treated with hypothermia

Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA.

Low apparent diffusion coefficient cluster-based analysis of diffusion-weighted MRI for prognostication of out-of-hospital cardiac arrest survivors

ObjectiveRecent studies suggested quantitative analysis of diffusion-weighted magnetic resonance imaging as a promising tool for early prognostication of cardiac arrest patients. However, most of their methods involve significant manual image handling often subjective and difficult to reproduce. Therefore developing a computerized analysis method using easy-to-define characteristics would be useful. MethodsComatose out-of-hospital cardiac arrest (OHCA) patients who underwent brain MRI between January 2008 and July 2012 were identified from an OHCA registry. Apparent diffusion coefficient (ADC) axial images were analyzed using a program to detect and characterize clusters of low ADC pixels from six brain regions including frontal, occipital, parietal, rolandic and temporal and basal ganglia region. Identified clusters were ranked according to size, mean ADC and minimum ADC to assess the regional maximum cluster size (MCS), lowest mean ADC (LMEAN) and lowest minimum ADC (LMIN). Their power to predict poor outcome, defined as 6-month CPC 3 or higher, was assessed by contingency table analyses. Results51 OHCA patients were eligible during the study period. The sensitivities of MCS, LMEAN and LMIN to detect poor outcome varied according to brain region from 62.5 to 90.0%, 50.0 to 72.5% and 42.5 to 82.5% with their specificities set to 100%, respectively. The MCS of occipital region showed most favorable test profile (sensitivity 90%, specificity 100%; AUROC 0.940, 95% confidence interval 0.874–1.000). ConclusionThe cluster-based computerized image analysis might be a simple but useful method for prediction of poor neurologic outcome. Future studies validating its prognostic performance are required.

Serial measurement of neuron specific enolase improves prognostication in cardiac arrest patients treated with hypothermia: A prospective study

BackgroundNeuron specific enolase (NSE) has repeatedly been evaluated for neurological prognostication in patients after cardiac arrest. However, it is unclear whether current guidelines for NSE cutoff levels also apply to cardiac arrest patients treated with hypothermia. Thus, we investigated the prognostic significance of absolute NSE levels and NSE kinetics in cardiac arrest patients treated with hypothermia.MethodsIn a prospective study of 35 patients resuscitated from cardiac arrest, NSE was measured daily for four days following admission. Outcome was assessed at ICU discharge using the CPC score. All patients received hypothermia treatment for 24 hours at 33°C with a surface cooling device according to current guidelines.ResultsThe cutoff for absolute NSE levels in patients with unfavourable outcome (CPC 3-5) 72 hours after cardiac arrest was 57 μg/l with an area under the curve (AUC) of 0.82 (sensitivity 47%, specificity 100%). The cutoff level for NSE kinetics in patients with unfavourable outcome (CPC 3-5) was an absolute increase of 7.9 μg/l (AUC 0.78, sensitivity 63%, specificity 100%) and a relative increase of 33.1% (AUC 0.803, sensitivity 67%, specificity 100%) at 48 hours compared to admission.ConclusionIn cardiac arrest patients treated with hypothermia, prognostication of unfavourable outcome by NSE kinetics between admission and 48 hours after resuscitation may be superior to prognostication by absolute NSE levels.