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Scharink D, Hunfeld M, Albrecht M, Dulfer K, de Hoog M, van Gils A, de Jonge R, Buysse C. An 18-year, single centre, retrospective study of long-term neurological outcomes in paediatric submersion-related cardiac arrests. Resusc Plus 2024; 18:100632. [PMID: 38646092 PMCID: PMC11026833 DOI: 10.1016/j.resplu.2024.100632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/27/2024] [Accepted: 04/01/2024] [Indexed: 04/23/2024] Open
Abstract
Aim Investigate long-term outcome in paediatric submersion-related cardiac arrests (CA). Methods Children (age one day-17 years) were included if admitted to the Erasmus MC Sophia Children's Hospital, after drowning with CA, between 2002 and 2019. Primary outcome was survival with favourable neurological outcome, defined as a Paediatric Cerebral Performance Category (PCPC) score of 1-3 at longest available follow-up. Secondary outcome were age-appropriate neuropsychological assessments at longest available follow-up. Results Upon hospital admission, 99 children were included (median age at time of CA 3.2 years [IQR 2.0-5.9] and 65% males). Forty children died in-hospital (no return of circulation (45%) or withdrawal of life sustaining therapies (55%)) and 4 children deceased after hospital discharge due to complications following the drowning-incident. Among survivors, with a median follow-up of 2.3 years [IQR 0.2-5.5], 47 children had favourable neurological outcome (i.e. PCPC 1-3) and 8 children unfavourable (unfavourable outcome group total n = 52, i.e. PCPC 4-5 or deceased). Twenty-six (47%) children participated in a neuropsychological assessment (median follow-up 4.0 years [IQR 2.3-8.7]). Compared with normative test data, participants obtained worse general (p = 0.008) and performance (p = 0.003) intelligence scores, processing speed (p = 0.002) and visual motor integration scores (p = 0.0012). Conclusions Although overall outcome in survivors was favourable at longest available follow-up, significant deficits in neuropsychological assessments were found. This study underlines the need for a standardized long term follow-up program as standard of care in paediatric drowning with CA.
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Affiliation(s)
- Denne Scharink
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Maayke Hunfeld
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
- Department of Paediatric Neurology, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Marijn Albrecht
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Karolijn Dulfer
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Matthijs de Hoog
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Annabel van Gils
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Rogier de Jonge
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
| | - Corinne Buysse
- Department of Neonatal and Paediatric Intensive Care, Division of Paediatric Intensive Care, Erasmus MC Sophia Children’s Hospital, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, the Netherlands
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Bach AM, Kirschen MP, Fung FW, Abend NS, Ampah S, Mondal A, Huh JW, Chen SSL, Yuan I, Graham K, Berman JI, Vossough A, Topjian A. Association of EEG Background With Diffusion-Weighted Magnetic Resonance Neuroimaging and Short-Term Outcomes After Pediatric Cardiac Arrest. Neurology 2024; 102:e209134. [PMID: 38350044 PMCID: PMC11384654 DOI: 10.1212/wnl.0000000000209134] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/16/2023] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND AND OBJECTIVES EEG and MRI features are independently associated with pediatric cardiac arrest (CA) outcomes, but it is unclear whether their combination improves outcome prediction. We aimed to assess the association of early EEG background category with MRI ischemia after pediatric CA and determine whether addition of MRI ischemia to EEG background features and clinical variables improves short-term outcome prediction. METHODS This was a single-center retrospective cohort study of pediatric CA with EEG initiated ≤24 hours and MRI obtained ≤7 days of return of spontaneous circulation. Initial EEG background was categorized as normal, slow/disorganized, discontinuous/burst-suppression, or attenuated-featureless. MRI ischemia was defined as percentage of brain tissue with apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s and categorized as high (≥10%) or low (<10%). Outcomes were mortality and unfavorable neurologic outcome (Pediatric Cerebral Performance Category increase ≥1 from baseline resulting in ICU discharge score ≥3). The Kruskal-Wallis test evaluated the association of EEG with MRI. Area under the receiver operating characteristic (AUROC) curve evaluated predictive accuracy. Logistic regression and likelihood ratio tests assessed multivariable outcome prediction. RESULTS We evaluated 90 individuals. EEG background was normal in 16 (18%), slow/disorganized in 42 (47%), discontinuous/burst-suppressed in 12 (13%), and attenuated-featureless in 20 (22%) individuals. The median percentage of MRI ischemia was 5% (interquartile range 1-18); 32 (36%) individuals had high MRI ischemia burden. Twenty-eight (31%) individuals died, and 58 (64%) had unfavorable neurologic outcome. Worse EEG background category was associated with more MRI ischemia (p < 0.001). The combination of EEG background and MRI ischemia burden had higher predictive accuracy than EEG alone (AUROC: mortality: 0.92 vs 0.87, p = 0.03) or MRI alone (AUROC: mortality: 0.92 vs 0.84, p = 0.02; unfavorable: 0.83 vs 0.73, p < 0.01). Addition of percentage of MRI ischemia to clinical variables and EEG background category improved prediction for mortality (χ2 = 19.1, p < 0.001) and unfavorable neurologic outcome (χ2 = 4.8, p = 0.03) and achieved high predictive accuracy (AUROC: mortality: 0.97; unfavorable: 0.92). DISCUSSION Early EEG background category was associated with MRI ischemia after pediatric CA. Combining EEG and MRI data yielded higher outcome predictive accuracy than either modality alone. The addition of MRI ischemia to clinical variables and EEG background improved short-term outcome prediction.
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Affiliation(s)
- Ashley M Bach
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Matthew P Kirschen
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - France W Fung
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Nicholas S Abend
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Steve Ampah
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Antara Mondal
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Jimmy W Huh
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Shih-Shan L Chen
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Ian Yuan
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Kathryn Graham
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Jeffrey I Berman
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Arastoo Vossough
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
| | - Alexis Topjian
- From the Department of Neurology (A.M.B., M.P.K., F.W.F., N.S.A.), Departments of Anesthesia and Critical Care Medicine (M.P.K., N.S.A., J.W.H., I.Y., K.G., A.T.), Department of Pediatrics (M.P.K., N.S.A., J.W.H., A.T.), Department of Biomedical and Health Informatics (S.A., A.M.), Department of Neurosurgery (S.-S.L.C.), and Department of Radiology (J.I.B., A.V.), Children's Hospital of Philadelphia, PA
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Vassar R, Mehta N, Epps L, Jiang F, Amorim E, Wietstock S. Mortality and Timing of Withdrawal of Life-Sustaining Therapies After Out-of-Hospital Cardiac Arrest: Two-Center Retrospective Pediatric Cohort Study. Pediatr Crit Care Med 2024; 25:241-249. [PMID: 37982686 DOI: 10.1097/pcc.0000000000003412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
OBJECTIVES Pediatric out-of-hospital cardiac arrest (OHCA) is associated with substantial morbidity and mortality. Limited data exist to guide timing and method of neurologic prognostication after pediatric OHCA, making counseling on withdrawal of life-sustaining therapies (WLSTs) challenging. This study investigates the timing and mode of death after pediatric OHCA and factors associated with mortality. Additionally, this study explores delayed recovery after comatose examination on day 3 postarrest. DESIGN This is a retrospective, observational study based on data collected from hospital databases and chart reviews. SETTING Data collection occurred in two pediatric academic hospitals between January 1, 2016, and December 31, 2020. PATIENTS Patients were identified from available databases and electronic medical record queries for the International Classification of Diseases , 10th Edition (ICD-10) code I46.9 (Cardiac Arrest). Patient inclusion criteria included age range greater than or equal to 48 hours to less than 18 years, OHCA within 24 hours of admission, greater than or equal to 1 min of cardiopulmonary resuscitation, and return-of-spontaneous circulation for greater than or equal to 20 min. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS One hundred thirty-five children (65% male) with a median age of 3 years (interquartile range 0.6-11.8) met inclusion criteria. Overall, 63 of 135 patients (47%) died before hospital discharge, including 34 of 63 patients (54%) after WLST. Among these, 20 of 34 patients underwent WLST less than or equal to 3 days postarrest, including 10 of 34 patients who underwent WLST within 1 day. WLST occurred because of poor perceived neurologic prognosis in all cases, although 7 of 34 also had poor perceived systemic prognosis. Delayed neurologic recovery from coma on day 3 postarrest was observed in 7 of 72 children (10%) who ultimately survived to discharge. CONCLUSIONS In our two centers between 2016 and 2020, more than half the deaths after pediatric OHCA occurred after WLST, and a majority of WLST occurred within 3 days postarrest. Additional research is warranted to determine optimal timing and predictors of neurologic prognosis after pediatric OHCA to better inform families during goals of care discussions.
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Affiliation(s)
- Rachel Vassar
- Division of Pediatric Neurology, Department of Neurology, Benioff Children's Hospital, University of California, San Francisco, CA
| | - Nehali Mehta
- Division of Pediatric Neurology, Department of Neurology, Benioff Children's Hospital, University of California, San Francisco, CA
- Department of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Lane Epps
- Department of Emergency Medicine, University of California, San Francisco, CA
| | - Fei Jiang
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Edilberto Amorim
- Department of Neurology, University of California, San Francisco, San Francisco, CA
- Division of Neurology, Zuckerberg San Francisco General Hospital, San Francisco, CA
| | - Sharon Wietstock
- Division of Pediatric Neurology, Department of Neurology, Benioff Children's Hospital, University of California, San Francisco, CA
- Division of Pediatric Neurology, Department of Neurology, Benioff Children's Hospital Oakland, University of California, San Francisco, Oakland, CA
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Lissak IA, Edlow BL, Rosenthal E, Young MJ. Ethical Considerations in Neuroprognostication Following Acute Brain Injury. Semin Neurol 2023; 43:758-767. [PMID: 37802121 DOI: 10.1055/s-0043-1775597] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patient's likely trajectory of neurologic recovery. In this setting, critically evaluating salient ethical questions is imperative, and the implications often inform high-stakes conversations about the continuation, limitation, or withdrawal of life-sustaining therapy. While neuroprognostication is central to these clinical "life-or-death" decisions, the ethical underpinnings of neuroprognostication itself have been underexplored for patients with ABI. In this article, we discuss the ethical challenges of individualized neuroprognostication including parsing and communicating its inherent uncertainty to surrogate decision-makers. We also explore the population-based ethical considerations that arise in the context of heterogenous prognostication practices. Finally, we examine the emergence of artificial intelligence-aided neuroprognostication, proposing an ethical framework relevant to both modern and longstanding prognostic tools.
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Affiliation(s)
- India A Lissak
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Eric Rosenthal
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Michael J Young
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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Kirschen MP, Vossough A. Introducing advanced neuroimaging into pediatric post-arrest neuroprognostication. Resuscitation 2023; 182:109657. [PMID: 36481241 DOI: 10.1016/j.resuscitation.2022.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Affiliation(s)
- Matthew P Kirschen
- Departments of Anesthesiology and Critical Care Medicine, Neurology and Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Arastoo Vossough
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
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Kirschen MP, Berman JI, Liu H, Ouyang M, Mondal A, Griffis H, Levow C, Winters M, Lang SS, Huh J, Huang H, Berg RA, Vossough A, Topjian A. Association Between Quantitative Diffusion-Weighted Magnetic Resonance Neuroimaging and Outcome After Pediatric Cardiac Arrest. Neurology 2022; 99:e2615-e2626. [PMID: 36028319 PMCID: PMC9754647 DOI: 10.1212/wnl.0000000000201189] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Diffusion MRI can quantify the extent of hypoxic-ischemic brain injury after cardiac arrest. Our objective was to determine the association between the adult-derived threshold of apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s in >10% of brain tissue and an unfavorable outcome after pediatric cardiac arrest. Since ADC decreases exponentially as a function of increasing age, we determined the association between (1) having >10% of brain tissue below a novel age-dependent ADC threshold, and (2) age-normalized whole-brain mean ADC and unfavorable outcome. METHODS This was a retrospective study of patients aged ≤18 years who had cardiac arrest and a clinically obtained brain MRI within 7 days. The primary outcome was unfavorable neurologic status at hospital discharge based on the Pediatric Cerebral Performance Category score. ADC images were extracted from 3-direction diffusion imaging. We determined whether each patient had >10% of voxels with an ADC below prespecified thresholds. We computed the whole-brain mean ADC for each patient. RESULTS One hundred thirty-four patients were analyzed. Patients with ADC <650 × 10-6 mm2/s in >10% of voxels had 15 times higher odds (95% CI 5-65) of an unfavorable outcome compared with patients with ADC <650 × 10-6 mm2/s (area under the receiver operating characteristic curve [AUROC] 0.72 [95% CI 0.63-0.80]). These ADC criteria had a sensitivity and specificity of 0.49 and 0.94, respectively, and positive and negative predictive values of 0.93 and 0.52, respectively, for an unfavorable outcome. The age-dependent ADC threshold that yielded optimal sensitivity and specificity for unfavorable outcomes was <300 × 10-6 mm2/s below each patient's predicted whole-brain mean ADC. The sensitivity, specificity, and positive and negative predictive values for this ADC threshold were 0.53, 0.96, 0.96, and 0.54, respectively (odds ratio [OR] 26.4 [95% CI 7.5-168.3]; AUROC 0.74 [95% CI 0.66-0.83]). Lower age-normalized whole-brain mean ADC was also associated with an unfavorable outcome (OR 0.42 [0.24-0.64], AUROC 0.76 [95% CI 0.66-0.82]). DISCUSSION Quantitative diffusion thresholds on MRI within 7 days after cardiac arrest were associated with an unfavorable outcome in children. The age-independent ADC threshold was highly specific for predicting an unfavorable outcome. However, the specificity and sensitivity increased when using age-dependent ADC thresholds. Age-dependent ADC thresholds may improve prognostic accuracy and require further investigation in larger cohorts. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that quantitative diffusion-weighted imaging within 7 days postarrest can predict an unfavorable clinical outcome in children.
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Affiliation(s)
- Matthew P Kirschen
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia.
| | - Jeffrey I Berman
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Hongyan Liu
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Minhui Ouyang
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Antara Mondal
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Heather Griffis
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Cindee Levow
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Madeline Winters
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Shih-Shan Lang
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Jimmy Huh
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Hao Huang
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Robert A Berg
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Arastoo Vossough
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Alexis Topjian
- From the Departments of Anesthesiology and Critical Care Medicine (M.P.K., C.L., M.W., J.H., R.A.B., A.T.), and Radiology (J.I.B., M.O., H.H., A.V.); Data Science and Biostatistics Unit (H.L., A.M., H.G.), Department of Biomedical and Health Informatics, and Department of Neurosurgery (S.-S.L.), Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
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Multimodal monitoring including early EEG improves stratification of brain injury severity after pediatric cardiac arrest. Resuscitation 2021; 167:282-288. [PMID: 34237356 DOI: 10.1016/j.resuscitation.2021.06.020] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 06/11/2021] [Accepted: 06/20/2021] [Indexed: 12/14/2022]
Abstract
AIMS Assessment of brain injury severity early after cardiac arrest (CA) may guide therapeutic interventions and help clinicians counsel families regarding neurologic prognosis. We aimed to determine whether adding EEG features to predictive models including clinical variables and examination signs increased the accuracy of short-term neurobehavioral outcome prediction. METHODS This was a prospective, observational, single-center study of consecutive infants and children resuscitated from CA. Standardized EEG scoring was performed by an electroencephalographer for the initial EEG timepoint after return of spontaneous circulation (ROSC) and each 12-h segment from the time of ROSC up to 48 h. EEG Background Category was scored as: (1) normal; (2) slow-disorganized; (3) discontinuous or burst-suppression; or (4) attenuated-featureless. The primary outcome was neurobehavioral outcome at discharge from the Pediatric Intensive Care Unit. To develop the final predictive model, we compared areas under the receiver operating characteristic curves (AUROC) from models with varying combinations of Demographic/Arrest Variables, Examination Signs, and EEG Features. RESULTS We evaluated 89 infants and children. Initial EEG Background Category was normal in 9 subjects (10%), slow-disorganized in 44 (49%), discontinuous or burst suppression in 22 (25%), and attenuated-featureless in 14 (16%). The final model included Demographic/Arrest Variables (witnessed status, doses of epinephrine, initial lactate after ROSC) and EEG Background Category which achieved AUROC of 0.9 for unfavorable neurobehavioral outcome and 0.83 for mortality. CONCLUSIONS The addition of standardized EEG Background Categories to readily available CA variables significantly improved early stratification of brain injury severity after pediatric CA.
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Albrecht M, de Jonge RCJ, Nadkarni VM, de Hoog M, Hunfeld M, Kammeraad JAE, Moors XRJ, van Zellem L, Buysse CMP. Association between shockable rhythms and long-term outcome after pediatric out-of-hospital cardiac arrest in Rotterdam, the Netherlands: An 18-year observational study. Resuscitation 2021; 166:110-120. [PMID: 34082030 DOI: 10.1016/j.resuscitation.2021.05.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 05/06/2021] [Accepted: 05/23/2021] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Shockable rhythm following pediatric out-of-hospital cardiac arrest (pOHCA) is consistently associated with hospital and short-term survival. Little is known about the relationship between shockable rhythm and long-term outcomes (>1 year) after pOHCA. The aim was to investigate the association between first documented rhythm and long-term outcomes in a pOHCA cohort over 18 years. METHODS All children aged 1 day-18 years who experienced non-traumatic pOHCA between 2002-2019 and were subsequently admitted to the emergency department (ED) or pediatric intensive care unit (PICU) of Erasmus MC-Sophia Children's Hospital were included. Data was abstracted retrospectively from patient files, (ground) ambulance and Helicopter Emergency Medical Service (HEMS) records, and follow-up clinics. Long-term outcome was determined using a Pediatric Cerebral Performance Category (PCPC) score at the longest available follow-up interval through august 2020. The primary outcome measure was survival with favorable neurologic outcome, defined as PCPC 1-2 or no difference between pre- and post-arrest PCPC. The association between first documented rhythm and the primary outcome was calculated in a multivariable regression model. RESULTS 369 children were admitted, nine children were lost to follow-up. Median age at arrest was age 3.4 (IQR 0.8-9.9) years, 63% were male and 14% had a shockable rhythm (66% non-shockable, 20% unknown or return of spontaneous circulation (ROSC) before emergency medical service (EMS) arrival). In adolescents (aged 12-18 years), 39% had shockable rhythm. 142 (39%) of children survived to hospital discharge. On median follow-up interval of 25 months (IQR 5.1-49.6), 115/142 (81%) of hospital survivors had favorable neurologic outcome. In multivariable analysis, shockable rhythm was associated with survival with favorable long-term neurologic outcome (OR 8.9 [95%CI 3.1-25.9]). CONCLUSION In children with pOHCA admitted to ED or PICU shockable rhythm had significantly higher odds of survival with long-term favorable neurologic outcome compared to non-shockable rhythm. Survival to hospital discharge after pOHCA was 39% over the 18-year study period. Of survivors to discharge, 81% had favorable long-term (median 25 months, IQR 5.1-49.6) neurologic outcome. Efforts for improving outcome of pOHCA should focus on early recognition and treatment of shockable pOHCA at scene.
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Affiliation(s)
- M Albrecht
- Pediatric Intensive Care Unit, Department of Pediatrics and Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - R C J de Jonge
- Pediatric Intensive Care Unit, Department of Pediatrics and Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - V M Nadkarni
- Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, United States
| | - M de Hoog
- Pediatric Intensive Care Unit, Department of Pediatrics and Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - M Hunfeld
- Pediatric Intensive Care Unit, Department of Pediatrics and Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands; Department of Pediatric Neurology, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - J A E Kammeraad
- Department of Pediatric Cardiology, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - X R J Moors
- Department of Pediatric Anesthesiology, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands; Helicopter Emergency Medical Services, Erasmus MC, Rotterdam, The Netherlands
| | - L van Zellem
- Department of Youth Health Care, Public Health Service (GGD), Amsterdam, The Netherlands
| | - C M P Buysse
- Pediatric Intensive Care Unit, Department of Pediatrics and Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands.
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Baird TD, Miller MR, Cameron S, Fraser DD, Tijssen JA. Clinical and Physiologic Factors Associated With Mode of Death in Pediatric Severe TBI. Front Pediatr 2021; 9:793008. [PMID: 34966706 PMCID: PMC8710712 DOI: 10.3389/fped.2021.793008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 11/15/2021] [Indexed: 11/13/2022] Open
Abstract
Aims and Objectives: Severe traumatic brain injury (sTBI) is the leading cause of death in children. Our aim was to determine the mode of death for children who died with sTBI in a Pediatric Critical Care Unit (PCCU) and evaluate factors associated with mortality. Methods: We performed a retrospective cohort study of all severely injured trauma patients (Injury Severity Score ≥ 12) with sTBI (Glasgow Coma Scale [GCS] ≤ 8 and Maximum Abbreviated Injury Scale ≥ 4) admitted to a Canadian PCCU (2000-2016). We analyzed mode of death, clinical factors, interventions, lab values within 24 h of admission (early) and pre-death (48 h prior to death), and reviewed meeting notes in patients who died in the PCCU. Results: Of 195 included patients with sTBI, 55 (28%) died in the PCCU. Of these, 31 (56%) had a physiologic death (neurologic determination of death or cardiac arrest), while 24 (44%) had withdrawal of life-sustaining therapies (WLST). Median (IQR) times to death were 35.2 (11.8, 86.4) hours in the physiologic group and 79.5 (17.6, 231.3) hours in the WLST group (p = 0.08). The physiologic group had higher partial thromboplastin time (PTT) within 24 h of admission (p = 0.04) and lower albumin prior to death (p = 0.04). Conclusions: Almost half of sTBI deaths in the PCCU were by WLST. There was a trend toward a longer time to death in these patients. We found few early and late (pre-death) factors associated with mode of death, namely higher PTT and lower albumin.
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Affiliation(s)
- Talia D Baird
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Michael R Miller
- Department of Paediatrics, Western University, London, ON, Canada.,Children's Health Research Institute, London, ON, Canada
| | - Saoirse Cameron
- Department of Paediatrics, Western University, London, ON, Canada.,Children's Health Research Institute, London, ON, Canada
| | - Douglas D Fraser
- Department of Paediatrics, Western University, London, ON, Canada.,Children's Health Research Institute, London, ON, Canada.,Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Janice A Tijssen
- Department of Paediatrics, Western University, London, ON, Canada.,Children's Health Research Institute, London, ON, Canada.,Department of Epidemiology and Biostatistics, Western University, London, ON, Canada
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Rener-Primec Z. Can we improve prediction of neurological outcome in children after cardiac arrest? Eur J Paediatr Neurol 2020; 28:4-5. [PMID: 32878719 DOI: 10.1016/j.ejpn.2020.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Zvonka Rener-Primec
- University Children's Hospital Ljubljana, Department of Child, Adolescent & Developmental Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia; Medical Faculty University of Ljubljana, Ljubljana, Slovenia.
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