Does Non-Neurologic Multiorgan Dysfunction After Out-of-Hospital Cardiac Arrest among Children Admitted in Coma Predict Outcome 1 Year Later?
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ABSTRACT:
SUBMITTER: Corbett KL
PROVIDER: S-EPMC8354356 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
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Does Non-Neurologic Multiorgan Dysfunction After Out-of-Hospital Cardiac Arrest among Children Admitted in Coma Predict Outcome 1 Year Later?
Corbett Kelly L KL Presson Angela P AP Zhang Chong C Xu Yizhe Y Bratton Susan L SL Dixon Rebecca R RR
Journal of pediatric intensive care 20200911 3
In this article, we investigated whether non-neurologic multiorgan dysfunction syndrome (MODS) following out-of-hospital cardiac arrest (OHCA) predicts poor 12-month survival. We conducted a secondary data analysis of therapeutic hypothermia after pediatric cardiac arrest out-of-hospital randomized trial involving children who remained unconscious and intubated after OHCA ( <i>n</i> = 237). Associations between MODS and 12-month outcomes were assessed using multivariable logistic regression. No ...[more]
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Project description:Aim of the reviewThe primary aim of this systematic review was to investigate the most common electroencephalogram (EEG)-based machine learning (ML) model with the highest Area Under Receiver Operating Characteristic Curve (AUC) in two ML categories, conventional ML and Deep Neural Network (DNN), to predict the neurologic outcomes after cardiac arrest; the secondary aim was to investigate common EEG features applied to ML models.MethodsSystematic search of medical literature from PubMed and engineering literature from Compendex up to June 2, 2023. One reviewer screened studies that used EEG-based ML models to predict the neurologic outcomes after cardiac arrest. Four reviewers validated that the studies met selection criteria. Nine variables were manually extracted. The top-five common EEG features were calculated. We evaluated each study's risk of bias using the Quality in Prognosis Studies guideline.ResultsOut of 351 identified studies, 17 studies met the inclusion criteria. Random Forest (RF) (n = 7) was the most common ML model in the conventional ML category (n = 11), followed by Convolutional Neural Network (CNN) (n = 4) in the DNN category (n = 6). The AUCs for RF ranged between 0.8 and 0.97, while CNN had AUCs between 0.7 and 0.92. The top-three commonly used EEG features were band power (n = 12), Shannon's Entropy (n = 11), burst-suppression ratio (n = 9).ConclusionsRF and CNN were the two most common ML models with the highest AUCs for predicting the neurologic outcomes after cardiac arrest. Using a multimodal model that combines EEG features and electronic health record data may further improve prognostic performance.
| S-EPMC11023717 | biostudies-literature
Project description:Background. Out-of-hospital cardiac arrest (OHCA) remains a challenge for emergency physicians, given the poor prognosis. In 2020, MIRACLE2, a new and easier to apply score, was established to predict the neurological outcome of OHCA. Objective. The aim of this study is to compare the discrimination of MIRACLE2 score with cardiac arrest hospital prognosis (CAHP) score for OHCA neurologic outcomes. Methods. This retrospective cohort study was conducted between January 2015 and December 2019. Adult patients (>17 years) with cardiac arrest who were brought to the hospital by an emergency medical service crew were included. Deaths due to trauma, burn, drowning, resuscitation not initiated due to pre-ordered “do not resuscitate” orders, and patients who did not achieve return of spontaneous circulation were excluded. Receiver operating characteristic curve analysis with Youden Index was performed to calculate optimal cut-off values for both scores. Results. Overall, 200 adult OHCA cases were analyzed. The threshold of the MIRACLE2 score for favorable neurologic outcomes was 5.5, with an area under the curve (AUC) value of 0.70 (0.61−0.80, p < 0.001); the threshold of the CAHP score was 223.4, with an AUC of 0.77 (0.68−0.86, p < 0.001). On setting the MIRACLE2 score cut-off value, we documented 64.7% sensitivity (95% confidence interval [CI], 56.9−71.9%), 66.7.0% specificity (95% CI, 48.2−82.0%), 90.8% positive predictive value (PPV; 95% CI, 85.6−94.2%), and 27.2% negative predictive value (NPV; 95% CI, 21.4−33.9%). On establishing a CAHP cut-off value, we observed 68.2% sensitivity (95% CI, 60.2−75.5%), 80.6% specificity (95% CI, 62.5−92.6%), 94.6% PPV (95% CI, 88.6%−98.0%), and 33.8% NPV (95% CI, 23.2−45.7%) for unfavorable neurologic outcomes. Conclusions. The CAHP score demonstrated better discrimination than the MIRACLE2 score, affording superior sensitivity, specificity, PPV, and NPV; however, the CAHP score remains relatively difficult to apply. Further studies are warranted to establish scores with better discrimination and ease of application.
| S-EPMC8950818 | biostudies-literature
Project description:BackgroundPrognosticating outcome following cardiac arrest is challenging and requires a multimodal approach. We tested the hypothesis that the combination of initial neurologic examination, quantitative analysis of head computed tomography (CT) and continuous EEG (cEEG) improve outcome prediction after cardiac arrest.MethodsReview of consecutive patients receiving head CT within 24h and cEEG monitoring between April 2010 and May 2013. Initial neurologic examination (Full Outline of UnResponsiveness_Brainstem reflexes (FOUR_B) score and initial Pittsburgh Post-Cardiac Arrest Category (PCAC)), gray matter to white matter attenuation ratio (GWR) on head CT and cEEG patterns were evaluated. The primary outcome was in-hospital mortality.ResultsOf 240 subjects, 70 (29%) survived and 22 (9%) had a good neurologic outcome at hospital discharge. Combined determination of GW ratio and malignant cEEG had an incremental predictive value (AUC: 0.776 for mortality and 0.792 for poor neurologic outcome), with 0% false positive rate when compared with either test alone (AUC of GW ratio: 0.683 for mortality and 0.726 for poor outcome, AUC of malignant cEEG: 0.650 for mortality and 0.647 for poor outcome). Addition of FOUR_B or PCAC to this model improved prediction of mortality (p=0.014 for FOUR_B and 0.001 for PCAC) but not of poor outcome (p=0.786 for FOUR_B and 0.099 for PCAC).ConclusionsCombining GWR with cEEG was superior to any individual test for predicting mortality and neurologic outcome. Addition of clinical variables further improved prognostication for mortality but not neurologic outcome. These preliminary data support a multi-modal prognostic workup in this population.
| S-EPMC5167630 | biostudies-literature
Project description:ImportanceTherapeutic hypothermia may increase survival with good neurologic outcome after cardiac arrest. Trans-nasal evaporative cooling is a method used to induce cooling, primarily of the brain, during cardiopulmonary resuscitation (ie, intra-arrest).ObjectiveTo determine whether prehospital trans-nasal evaporative intra-arrest cooling improves survival with good neurologic outcome compared with cooling initiated after hospital arrival.Design, setting, and participantsThe PRINCESS trial was an investigator-initiated, randomized, clinical, international multicenter study with blinded assessment of the outcome, performed by emergency medical services in 7 European countries from July 2010 to January 2018, with final follow-up on April 29, 2018. In total, 677 patients with bystander-witnessed out-of-hospital cardiac arrest were enrolled.InterventionsPatients were randomly assigned to receive trans-nasal evaporative intra-arrest cooling (n = 343) or standard care (n = 334). Patients admitted to the hospital in both groups received systemic therapeutic hypothermia at 32°C to 34°C for 24 hours.Main outcomes and measuresThe primary outcome was survival with good neurologic outcome, defined as Cerebral Performance Category (CPC) 1-2, at 90 days. Secondary outcomes were survival at 90 days and time to reach core body temperature less than 34°C.ResultsAmong the 677 randomized patients (median age, 65 years; 172 [25%] women), 671 completed the trial. Median time to core temperature less than 34°C was 105 minutes in the intervention group vs 182 minutes in the control group (P < .001). The number of patients with CPC 1-2 at 90 days was 56 of 337 (16.6%) in the intervention cooling group vs 45 of 334 (13.5%) in the control group (difference, 3.1% [95% CI, -2.3% to 8.5%]; relative risk [RR], 1.23 [95% CI, 0.86-1.72]; P = .25). In the intervention group, 60 of 337 patients (17.8%) were alive at 90 days vs 52 of 334 (15.6%) in the control group (difference, 2.2% [95% CI, -3.4% to 7.9%]; RR, 1.14 [95% CI, 0.81-1.57]; P = .44). Minor nosebleed was the most common device-related adverse event, reported in 45 of 337 patients (13%) in the intervention group. The adverse event rate within 7 days was similar between groups.Conclusions and relevanceAmong patients with out-of-hospital cardiac arrest, trans-nasal evaporative intra-arrest cooling compared with usual care did not result in a statistically significant improvement in survival with good neurologic outcome at 90 days.Trial registrationClinicalTrials.gov Identifier: NCT01400373.
| S-EPMC6506882 | biostudies-literature
Project description:Assessing the integrity of neural functions in coma after cardiac arrest remains an open challenge. Prognostication of coma outcome relies mainly on visual expert scoring of physiological signals, which is prone to subjectivity and leaves a considerable number of patients in a 'grey zone', with uncertain prognosis. Quantitative analysis of EEG responses to auditory stimuli can provide a window into neural functions in coma and information about patients' chances of awakening. However, responses to standardized auditory stimulation are far from being used in a clinical routine due to heterogeneous and cumbersome protocols. Here, we hypothesize that convolutional neural networks can assist in extracting interpretable patterns of EEG responses to auditory stimuli during the first day of coma that are predictive of patients' chances of awakening and survival at 3 months. We used convolutional neural networks (CNNs) to model single-trial EEG responses to auditory stimuli in the first day of coma, under standardized sedation and targeted temperature management, in a multicentre and multiprotocol patient cohort and predict outcome at 3 months. The use of CNNs resulted in a positive predictive power for predicting awakening of 0.83 ± 0.04 and 0.81 ± 0.06 and an area under the curve in predicting outcome of 0.69 ± 0.05 and 0.70 ± 0.05, for patients undergoing therapeutic hypothermia and normothermia, respectively. These results also persisted in a subset of patients that were in a clinical 'grey zone'. The network's confidence in predicting outcome was based on interpretable features: it strongly correlated to the neural synchrony and complexity of EEG responses and was modulated by independent clinical evaluations, such as the EEG reactivity, background burst-suppression or motor responses. Our results highlight the strong potential of interpretable deep learning algorithms in combination with auditory stimulation to improve prognostication of coma outcome.
| S-EPMC9924902 | biostudies-literature
Project description:BackgroundPrevious reports have shown that prolonged duration of resuscitation efforts in out-of-hospital cardiac arrest (OHCA) is associated with poor neurologic outcome. This concept has recently been questioned with advancements in post-cardiac arrest care including the use of therapeutic hypothermia (TH). The aim of this study was to determine the rate of good neurologic outcome based on the duration of resuscitation efforts in OHCA patients treated with TH.MethodsThis prospective, observational, study was conducted between January 2008 and September 2012. Inclusion criteria consisted of adult non-traumatic OHCA patients who were comatose after return of spontaneous circulation (ROSC) and received TH. The primary endpoint was good neurologic outcome defined as a cerebral performance category score of 1 or 2. Downtime was calculated as the length of time between the patient being recognized as pulseless and ROSC.Results105 patients were treated with TH and 19 were excluded due to unknown downtime, leaving 86 patients for analysis. The median downtime was 18.5 (10.0-32.3)min and 33 patients (38.0%) had a good neurologic outcome. When downtime was divided into four groups (≤10min, 11-20min, 21-30min, >30min), good neurologic outcomes were 62.5%, 37%, 25%, and 21.7%, respectively (p=0.02). However, even with downtime >20min, 22.9% had a good neurologic outcome, and this percentage increased to 37.5% in patients with an initial shockable rhythm.ConclusionsAlthough longer downtime is associated with worse outcome in OHCA patients, we found that comatose patients who have been successfully resuscitated and treated with TH have neurologically intact survival rates of 23% even with downtime >20min.
| S-EPMC4087050 | biostudies-literature
Project description:AimWe examined the association between the location of cardiac arrest and outcomes of patients with out-of-hospital cardiac arrest (OHCA) who underwent extracorporeal cardiopulmonary resuscitation (ECPR).MethodsThis was a secondary analysis of SAVE-J II, a multicentre retrospective registry with 36 participating institutions across Japan, which enrolled adult patients with OHCA who underwent ECPR. The outcomes of interest were favourable neurologic outcome at discharge. We compared the outcome between OHCA cases that occurred at residential and public locations, using a multilevel logistic regression model allowing for the random effect of each hospital.ResultsAmong 1,744 enrolled OHCAs, 809 and 935 occurred at residential (house: 603; apartment: 206) and public (street: 260; workplace: 210; others: 465) locations, respectively. The proportion of favourable neurologic outcomes was lower in OHCAs at residential locations than those at public locations (88/781 (11.3%) vs.131/891 (14.7%); adjusted odds ratio, 0.72 [95% confidence interval, 0.53-0.99]). However, subgroup analyses for patients with EMS aged <65 years call to hospital arrival within 30 minutes or during daytime revealed less difference between residential and public locations.ConclusionWhen cardiac arrests occurred at residential locations, lower proportions of favourable neurologic outcomes were exhibited among patients with OHCA who underwent ECPR. However, the event's location may not affect the prognosis among appropriate and select cases when transported within a limited timeframe.
| S-EPMC10497793 | biostudies-literature
Project description:PurposeThe majority of unconscious patients after cardiac arrest (CA) do not fulfill guideline criteria for a likely poor outcome, their prognosis is considered "indeterminate". We compared brain injury markers in blood for prediction of good outcome and for identifying false positive predictions of poor outcome as recommended by guidelines.MethodsRetrospective analysis of prospectively collected serum samples at 24, 48 and 72 h post arrest within the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Clinically available markers neuron-specific enolase (NSE) and S100B, and novel markers neurofilament light chain (NFL), total tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) were analysed. Normal levels with a priori cutoffs specified by reference laboratories or defined from literature were used to predict good outcome (no to moderate disability, Cerebral Performance Category scale 1-2) at 6 months.ResultsSeven hundred and seventeen patients were included. Normal NFL, tau and GFAP had the highest sensitivities (97.2-98% of poor outcome patients had abnormal serum levels) and NPV (normal levels predicted good outcome in 87-95% of patients). Normal S100B and NSE predicted good outcome with NPV 76-82.2%. Normal NSE correctly identified 67/190 (35.3%) patients with good outcome among those classified as "indeterminate outcome" by guidelines. Five patients with single pathological prognostic findings despite normal biomarkers had good outcome.ConclusionLow levels of brain injury markers in blood are associated with good neurological outcome after CA. Incorporating biomarkers into neuroprognostication may help prevent premature withdrawal of life-sustaining therapy.
| S-EPMC8421280 | biostudies-literature
Project description:Rationale. The value of microRNAs (miRNAs) as biomarkers has been addressed in various clinical contexts. Initial studies suggested that miRNAs, such as the brain-enriched miR-124-3p, might improve outcome prediction after out-of-hospital cardiac arrest. The aim of this study is to determine the prognostic value of miR-122-5p in a large cohort of comatose survivors of out-of-hospital cardiac arrest. Methods. We analyzed 590 patients from the Targeted Temperature Management trial (TTM-trial). Circulating levels of miR-122-5p were measured in serum samples obtained 48 hours after return of spontaneous circulation. The primary end-point was poor neurological outcome at 6 months evaluated by the cerebral performance category score. The secondary end-point was survival at the end of the trial. Results. Forty-eight percent of patients had a poor neurological outcome at 6 months and 43% were dead at the end of the trial. Levels of miR-122-5p were lower in patients with poor neurological outcome compared to patients with good neurological outcome (p<0.001), independently of targeted temperature management regimen. Levels of miR-122-5p were significant univariate predictors of neurological outcome (odds ratios (OR), 95% confidence intervals (CI): 0.71 [0.57-0.88]). In multivariable analyses, miR-122-5p was an independent predictor of neurological outcome and improved the predictive value of a clinical model including miR-124-3p (integrated discrimination improvement of 0.03 [0.02-0.04]). In Cox proportional hazards models, miR-122-5p was a significant predictor of survival at the end of the trial. Conclusion. Circulating levels of miR-122-5p improve the prediction of outcome after out-of-hospital cardiac arrest.
| S-EPMC5558552 | biostudies-literature
Project description:ImportanceInternational resuscitation guidelines recommend targeted temperature management (TTM) at 33°C to 36°C in unconscious patients with out-of-hospital cardiac arrest for at least 24 hours, but the optimal duration of TTM is uncertain.ObjectiveTo determine whether TTM at 33°C for 48 hours results in better neurologic outcomes compared with currently recommended, standard, 24-hour TTM.Design, setting, and participantsThis was an international, investigator-initiated, blinded-outcome-assessor, parallel, pragmatic, multicenter, randomized clinical superiority trial in 10 intensive care units (ICUs) at 10 university hospitals in 6 European countries. Three hundred fifty-five adult, unconscious patients with out-of-hospital cardiac arrest were enrolled from February 16, 2013, to June 1, 2016, with final follow-up on December 27, 2016.InterventionsPatients were randomized to TTM (33 ± 1°C) for 48 hours (n = 176) or 24 hours (n = 179), followed by gradual rewarming of 0.5°C per hour until reaching 37°C.Main outcomes and measuresThe primary outcome was 6-month neurologic outcome, with a Cerebral Performance Categories (CPC) score of 1 or 2 used to define favorable outcome. Secondary outcomes included 6-month mortality, including time to death, the occurrence of adverse events, and intensive care unit resource use.ResultsIn 355 patients who were randomized (mean age, 60 years; 295 [83%] men), 351 (99%) completed the trial. Of these patients, 69% (120/175) in the 48-hour group had a favorable outcome at 6 months compared with 64% (112/176) in the 24-hour group (difference, 4.9%; 95% CI, -5% to 14.8%; relative risk [RR], 1.08; 95% CI, 0.93-1.25; P = .33). Six-month mortality was 27% (48/175) in the 48-hour group and 34% (60/177) in the 24-hour group (difference, -6.5%; 95% CI, -16.1% to 3.1%; RR, 0.81; 95% CI, 0.59-1.11; P = .19). There was no significant difference in the time to mortality between the 48-hour group and the 24-hour group (hazard ratio, 0.79; 95% CI, 0.54-1.15; P = .22). Adverse events were more common in the 48-hour group (97%) than in the 24-hour group (91%) (difference, 5.6%; 95% CI, 0.6%-10.6%; RR, 1.06; 95% CI, 1.01-1.12; P = .04). The median length of intensive care unit stay (151 vs 117 hours; P < .001), but not hospital stay (11 vs 12 days; P = .50), was longer in the 48-hour group than in the 24-hour group.Conclusions and relevanceIn unconscious survivors from out-of-hospital cardiac arrest admitted to the ICU, targeted temperature management at 33°C for 48 hours did not significantly improve 6-month neurologic outcome compared with targeted temperature management at 33°C for 24 hours. However, the study may have had limited power to detect clinically important differences, and further research may be warranted.Trial registrationclinicaltrials.gov Identifier: NCT01689077.
| S-EPMC5541324 | biostudies-literature