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Plante V, Basu M, Gettings JV, Luchette M, LaRovere KL. Update in Pediatric Neurocritical Care: What a Neurologist Caring for Critically Ill Children Needs to Know. Semin Neurol 2024; 44:362-388. [PMID: 38788765 DOI: 10.1055/s-0044-1787047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
Currently nearly one-quarter of admissions to pediatric intensive care units (PICUs) worldwide are for neurocritical care diagnoses that are associated with significant morbidity and mortality. Pediatric neurocritical care is a rapidly evolving field with unique challenges due to not only age-related responses to primary neurologic insults and their treatments but also the rarity of pediatric neurocritical care conditions at any given institution. The structure of pediatric neurocritical care services therefore is most commonly a collaborative model where critical care medicine physicians coordinate care and are supported by a multidisciplinary team of pediatric subspecialists, including neurologists. While pediatric neurocritical care lies at the intersection between critical care and the neurosciences, this narrative review focuses on the most common clinical scenarios encountered by pediatric neurologists as consultants in the PICU and synthesizes the recent evidence, best practices, and ongoing research in these cases. We provide an in-depth review of (1) the evaluation and management of abnormal movements (seizures/status epilepticus and status dystonicus); (2) acute weakness and paralysis (focusing on pediatric stroke and select pediatric neuroimmune conditions); (3) neuromonitoring modalities using a pathophysiology-driven approach; (4) neuroprotective strategies for which there is evidence (e.g., pediatric severe traumatic brain injury, post-cardiac arrest care, and ischemic stroke and hemorrhagic stroke); and (5) best practices for neuroprognostication in pediatric traumatic brain injury, cardiac arrest, and disorders of consciousness, with highlights of the 2023 updates on Brain Death/Death by Neurological Criteria. Our review of the current state of pediatric neurocritical care from the viewpoint of what a pediatric neurologist in the PICU needs to know is intended to improve knowledge for providers at the bedside with the goal of better patient care and outcomes.
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Affiliation(s)
- Virginie Plante
- Division of Critical Care Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts
| | - Meera Basu
- Division of Critical Care Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
| | | | - Matthew Luchette
- Division of Critical Care Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts
| | - Kerri L LaRovere
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
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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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Berg KM, Bray JE, Ng KC, Liley HG, Greif R, Carlson JN, Morley PT, Drennan IR, Smyth M, Scholefield BR, Weiner GM, Cheng A, Djärv T, Abelairas-Gómez C, Acworth J, Andersen LW, Atkins DL, Berry DC, Bhanji F, Bierens J, Bittencourt Couto T, Borra V, Böttiger BW, Bradley RN, Breckwoldt J, Cassan P, Chang WT, Charlton NP, Chung SP, Considine J, Costa-Nobre DT, Couper K, Dainty KN, Dassanayake V, Davis PG, Dawson JA, Fernanda de Almeida M, De Caen AR, Deakin CD, Dicker B, Douma MJ, Eastwood K, El-Naggar W, Fabres JG, Fawke J, Fijacko N, Finn JC, Flores GE, Foglia EE, Folke F, Gilfoyle E, Goolsby CA, Granfeldt A, Guerguerian AM, Guinsburg R, Hatanaka T, Hirsch KG, Holmberg MJ, Hosono S, Hsieh MJ, Hsu CH, Ikeyama T, Isayama T, Johnson NJ, Kapadia VS, Daripa Kawakami M, Kim HS, Kleinman ME, Kloeck DA, Kudenchuk P, Kule A, Kurosawa H, Lagina AT, Lauridsen KG, Lavonas EJ, Lee HC, Lin Y, Lockey AS, Macneil F, Maconochie IK, John Madar R, Malta Hansen C, Masterson S, Matsuyama T, McKinlay CJD, Meyran D, Monnelly V, Nadkarni V, Nakwa FL, Nation KJ, Nehme Z, Nemeth M, Neumar RW, Nicholson T, Nikolaou N, Nishiyama C, Norii T, Nuthall GA, Ohshimo S, Olasveengen TM, Gene Ong YK, Orkin AM, Parr MJ, Patocka C, Perkins GD, Perlman JM, Rabi Y, Raitt J, Ramachandran S, Ramaswamy VV, Raymond TT, Reis AG, Reynolds JC, Ristagno G, Rodriguez-Nunez A, Roehr CC, Rüdiger M, Sakamoto T, Sandroni C, Sawyer TL, Schexnayder SM, Schmölzer GM, Schnaubelt S, Semeraro F, Singletary EM, Skrifvars MB, Smith CM, Soar J, Stassen W, Sugiura T, Tijssen JA, Topjian AA, Trevisanuto D, Vaillancourt C, Wyckoff MH, Wyllie JP, Yang CW, Yeung J, Zelop CM, Zideman DA, Nolan JP. 2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces. Resuscitation 2024; 195:109992. [PMID: 37937881 DOI: 10.1016/j.resuscitation.2023.109992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.
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Berg KM, Bray JE, Ng KC, Liley HG, Greif R, Carlson JN, Morley PT, Drennan IR, Smyth M, Scholefield BR, Weiner GM, Cheng A, Djärv T, Abelairas-Gómez C, Acworth J, Andersen LW, Atkins DL, Berry DC, Bhanji F, Bierens J, Bittencourt Couto T, Borra V, Böttiger BW, Bradley RN, Breckwoldt J, Cassan P, Chang WT, Charlton NP, Chung SP, Considine J, Costa-Nobre DT, Couper K, Dainty KN, Dassanayake V, Davis PG, Dawson JA, de Almeida MF, De Caen AR, Deakin CD, Dicker B, Douma MJ, Eastwood K, El-Naggar W, Fabres JG, Fawke J, Fijacko N, Finn JC, Flores GE, Foglia EE, Folke F, Gilfoyle E, Goolsby CA, Granfeldt A, Guerguerian AM, Guinsburg R, Hatanaka T, Hirsch KG, Holmberg MJ, Hosono S, Hsieh MJ, Hsu CH, Ikeyama T, Isayama T, Johnson NJ, Kapadia VS, Kawakami MD, Kim HS, Kleinman ME, Kloeck DA, Kudenchuk P, Kule A, Kurosawa H, Lagina AT, Lauridsen KG, Lavonas EJ, Lee HC, Lin Y, Lockey AS, Macneil F, Maconochie IK, Madar RJ, Malta Hansen C, Masterson S, Matsuyama T, McKinlay CJD, Meyran D, Monnelly V, Nadkarni V, Nakwa FL, Nation KJ, Nehme Z, Nemeth M, Neumar RW, Nicholson T, Nikolaou N, Nishiyama C, Norii T, Nuthall GA, Ohshimo S, Olasveengen TM, Ong YKG, Orkin AM, Parr MJ, Patocka C, Perkins GD, Perlman JM, Rabi Y, Raitt J, Ramachandran S, Ramaswamy VV, Raymond TT, Reis AG, Reynolds JC, Ristagno G, Rodriguez-Nunez A, Roehr CC, Rüdiger M, Sakamoto T, Sandroni C, Sawyer TL, Schexnayder SM, Schmölzer GM, Schnaubelt S, Semeraro F, Singletary EM, Skrifvars MB, Smith CM, Soar J, Stassen W, Sugiura T, Tijssen JA, Topjian AA, Trevisanuto D, Vaillancourt C, Wyckoff MH, Wyllie JP, Yang CW, Yeung J, Zelop CM, Zideman DA, Nolan JP. 2023 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces. Circulation 2023; 148:e187-e280. [PMID: 37942682 PMCID: PMC10713008 DOI: 10.1161/cir.0000000000001179] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The International Liaison Committee on Resuscitation engages in a continuous review of new, peer-reviewed, published cardiopulmonary resuscitation and first aid science. Draft Consensus on Science With Treatment Recommendations are posted online throughout the year, and this annual summary provides more concise versions of the final Consensus on Science With Treatment Recommendations from all task forces for the year. Topics addressed by systematic reviews this year include resuscitation of cardiac arrest from drowning, extracorporeal cardiopulmonary resuscitation for adults and children, calcium during cardiac arrest, double sequential defibrillation, neuroprognostication after cardiac arrest for adults and children, maintaining normal temperature after preterm birth, heart rate monitoring methods for diagnostics in neonates, detection of exhaled carbon dioxide in neonates, family presence during resuscitation of adults, and a stepwise approach to resuscitation skills training. Members from 6 International Liaison Committee on Resuscitation task forces have assessed, discussed, and debated the quality of the evidence, using Grading of Recommendations Assessment, Development, and Evaluation criteria, and their statements include consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections. In addition, the task forces list priority knowledge gaps for further research. Additional topics are addressed with scoping reviews and evidence updates.
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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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Smith AE, Ganninger AP, Mian AY, Friess SH, Guerriero RM, Guilliams KP. Magnetic Resonance Imaging Adds Prognostic Value to EEG After Pediatric Cardiac Arrest. Resuscitation 2022; 173:91-100. [PMID: 35227820 PMCID: PMC9001021 DOI: 10.1016/j.resuscitation.2022.02.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/11/2022] [Accepted: 02/20/2022] [Indexed: 10/19/2022]
Abstract
AIM To investigate how combined electrographic and radiologic data inform outcomes in children after cardiac arrest. METHODS Retrospective observational study of children admitted to the pediatric intensive care unit (PICU) of a tertiary children's hospital with diagnosis of cardiac arrest from 2009 to 2016. The first 20 min of electroencephalogram (EEG) background was blindly scored. Presence and location of magnetic resonance imaging (MRI) diffusion-weighted image (DWI) abnormalities were correlated with T2-weighted signal. Outcomes were categorized using Pediatric Cerebral Performance Category (PCPC) scores at hospital discharge, with "poor outcome" reflecting a PCPC score of 4-6. Logistic regression models examined the association of EEG and MRI variables with outcome. RESULTS 41 children met inclusion criteria and had both post-arrest EEG monitoring within 72 hours after ROSC and brain MRI performed within 8 days. Among the 19 children with poor outcome, 10 children did not survive to discharge. Severely abnormal EEG background (p < 0.0001) and any diffusion restriction (p < 0.0001) were associated with poor outcome. The area under the ROC curve (AUC) for identifying outcome based on EEG background alone was 0.86, which improved to 0.94 with combined EEG and MRI data (p = 0.02). CONCLUSION Diffusion abnormalities on MRI within 8 days after ROSC add to the prognostic value of EEG background in children surviving cardiac arrest.
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Sperotto F, Saengsin K, Danehy A, Godsay M, Geisser DL, Rivkin M, Amigoni A, Thiagarajan RR, Kheir JN. Modeling severe functional impairment or death following ECPR in pediatric cardiac patients: Planning for an interventional trial. Resuscitation 2021; 167:12-21. [PMID: 34389452 DOI: 10.1016/j.resuscitation.2021.07.041] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/16/2021] [Accepted: 07/22/2021] [Indexed: 10/20/2022]
Abstract
AIM We aimed to characterize extracorporeal CPR (ECPR) outcomes in our center and to model prediction of severe functional impairment or death at discharge. METHODS All ECPR events between 2011 and 2019 were reviewed. The primary outcome measure was severe functional impairment or death at discharge (Functional Status Score [FSS] ≥ 16). Organ dysfunction was graded using the Pediatric Logistic Organ Dysfunction Score-2, neuroimaging using the modified Alberta Stroke Program Early Computed Tomography Score. Multivariable logistic regression was used to model FSS ≥ 16 at discharge. RESULTS Of the 214 patients who underwent ECPR, 182 (median age 148 days, IQR 14-827) had an in-hospital cardiac arrest and congenital heart disease and were included in the analysis. Of the 110 patients who underwent neuroimaging, 52 (47%) had hypoxic-ischemic injury and 45 (41%) had hemorrhage. In-hospital mortality was 52% at discharge. Of these, 87% died from the withdrawal of life-sustaining therapies; severe neurologic injury was a contributing factor in the decision to withdraw life-sustaining therapies in 50%. The median FSS among survivors was 8 (IQR 6-8), and only one survivor had severe functional impairment. At 6 months, mortality was 57%, and the median FSS among survivors was 6 (IQR 6-8, n = 79). Predictive models identified FSS at admission, single ventricle physiology, extracorporeal membrane oxygenation (ECMO) duration, mean PELOD-2, and worst mASPECTS (or DWI-ASPECTS) as independent predictors of FSS ≥ 16 (AUC = 0.931) and at 6 months (AUC = 0.924). CONCLUSION Mortality and functional impairment following ECPR in children remain high. It is possible to model severe functional impairment or death at discharge with high accuracy using daily post-ECPR data up to 28 days. This represents a prognostically valuable tool and may identify endpoints for future interventional trials.
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Affiliation(s)
- Francesca Sperotto
- Departments of Cardiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA; Pediatric Intensive Care Unit, Department of Women's and Children's Health, University of Padova, Via Giustiniani 2, Padova 35128, Italy
| | - Kwannapas Saengsin
- Departments of Cardiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
| | - Amy Danehy
- Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
| | - Manasee Godsay
- Departments of Cardiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Diana L Geisser
- Departments of Cardiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
| | - Michael Rivkin
- Neurology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
| | - Angela Amigoni
- Pediatric Intensive Care Unit, Department of Women's and Children's Health, University of Padova, Via Giustiniani 2, Padova 35128, Italy
| | - Ravi R Thiagarajan
- Departments of Cardiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA
| | - John N Kheir
- Departments of Cardiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.
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Choi YH, Kim DK, Kang EK, Kim JT, Na JY, Park B, Yeom SR, Oh JS, Lee J, Jhang WK, Jeong SI, Jung JH, Choi JY, Park JD, Hwang SO. 2020 Korean Guidelines for Cardiopulmonary Resuscitation. Part 7. Pediatric advanced life support. Clin Exp Emerg Med 2021; 8:S81-S95. [PMID: 34034451 PMCID: PMC8171177 DOI: 10.15441/ceem.21.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 03/28/2021] [Indexed: 02/05/2023] Open
Affiliation(s)
- Yu Hyeon Choi
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea
| | - Do Kyun Kim
- Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea
| | - Eun Kyeong Kang
- Department of Pediatrics, Dongguk University Ilsan Hospital, Goyang, Korea
| | - Jin-Tae Kim
- Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Jae Yoon Na
- Department of Pediatrics, Hanyang University Medical Center, Hanyang University College of Medicine, Seoul, Korea
| | - Bobae Park
- Department of Nursing, Seoul National University Hospital, Seoul, Korea
| | - Seok Ran Yeom
- Department of Emergency Medicine, Pusan National University College of Medicine, Busan, Korea
| | - Joo Suk Oh
- Department of Emergency Medicine, The Catholic University of Korea College of Medicine, Seoul, Korea
| | - Jisook Lee
- Department of Emergency Medicine, Ajou University College of Medicine, Suwon, Korea
| | - Won Kyoung Jhang
- Department of Pediatrics, Children's Hospital, Asan Medical Center, Seoul, Korea
| | - Soo In Jeong
- Department of Pediatrics, Ajou University Hospital, Suwon, Korea
| | - Jin Hee Jung
- Department of Emergency Medicine, SMG-SNU Boramae Medical Center, Seoul, Korea
| | - Jea Yeon Choi
- Department of Emergency Medicine, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - June Dong Park
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Korea
| | - Sung Oh Hwang
- Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
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10
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Kirschen MP, Licht DJ, Faerber J, Mondal A, Graham K, Winters M, Balu R, Diaz-Arrastia R, Berg RA, Topjian A, Vossough A. Association of MRI Brain Injury With Outcome After Pediatric Out-of-Hospital Cardiac Arrest. Neurology 2020; 96:e719-e731. [PMID: 33208547 DOI: 10.1212/wnl.0000000000011217] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 09/23/2020] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE To determine the association between the extent of diffusion restriction and T2/fluid-attenuated inversion recovery (FLAIR) injury on brain MRI and outcomes after pediatric out-of-hospital cardiac arrest (OHCA). METHODS Diffusion restriction and T2/FLAIR injury were described according to the pediatric MRI modification of the Alberta Stroke Program Early Computed Tomography Score (modsASPECTS) for children from 2005 to 2013 who had an MRI within 14 days of OHCA. The primary outcome was unfavorable neurologic outcome defined as ≥1 change in Pediatric Cerebral Performance Category (PCPC) from baseline resulting in a hospital discharge PCPC score 3, 4, 5, or 6. Patients with unfavorable outcomes were further categorized into alive with PCPC 3-5, dead due to withdrawal of life-sustaining therapies for poor neurologic prognosis (WLST-neuro), or dead by neurologic criteria. RESULTS We evaluated MRI scans from 77 patients (median age 2.21 [interquartile range 0.44, 13.07] years) performed 4 (2, 6) days postarrest. Patients with unfavorable outcomes had more extensive diffusion restriction (median 7 [4, 10.3] vs 0 [0, 0] regions, p < 0.001) and T2/FLAIR injury (5.5 [2.3, 8.2] vs 0 [0, 0.75] regions, p < 0.001) compared to patients with favorable outcomes. Area under the receiver operating characteristic curve for the extent of diffusion restriction and unfavorable outcome was 0.96 (95% confidence interval [CI] 0.91, 0.99) and 0.92 (95% CI 0.85, 0.97) for T2/FLAIR injury. There was no difference in extent of diffusion restriction between patients who were alive with an unfavorable outcome and patients who died from WLST-neuro (p = 0.11). CONCLUSIONS More extensive diffusion restriction and T2/FLAIR injury on the modsASPECTS score within the first 14 days after pediatric cardiac arrest was associated with unfavorable outcomes at hospital discharge.
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Affiliation(s)
- Matthew P Kirschen
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia.
| | - Daniel J Licht
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Jennifer Faerber
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Antara Mondal
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Kathryn Graham
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Madeline Winters
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Ramani Balu
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Ramon Diaz-Arrastia
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Robert A Berg
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Alexis Topjian
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Arastoo Vossough
- From the Department of Anesthesiology and Critical Care Medicine (M.P.K., K.G., M.W., R.A.B., A.T.), Department of Pediatrics (M.P.K., D.J.L., R.A.B., A.T.), Health Analytics Unit (J.F., A.M.), and Department of Radiology (A.V.), Children's Hospital of Philadelphia; and Department of Neurology (M.P.K., D.J.L., R.B., R.D.-A.), Perelman School of Medicine at the University of Pennsylvania, Philadelphia
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A Systematic Review of Neuromonitoring Modalities in Children Beyond Neonatal Period After Cardiac Arrest. Pediatr Crit Care Med 2020; 21:e927-e933. [PMID: 32541373 DOI: 10.1097/pcc.0000000000002415] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Postresuscitation care in children focuses on preventing secondary neurologic injury and attempts to provide (precise) prognostication for both caregivers and the medical team. This systematic review provides an overview of neuromonitoring modalities and their potential role in neuroprognostication in postcardiac arrest children. DATA RESOURCES Databases EMBASE, Web of Science, Cochrane, MEDLINE Ovid, Google Scholar, and PsycINFO Ovid were searched in February 2019. STUDY SELECTION Enrollment of children after in- and out-of-hospital cardiac arrest between 1 month and 18 years and presence of a neuromonitoring method obtained within the first 2 weeks post cardiac arrest. Two reviewers independently selected appropriate studies based on the citations. DATA EXTRACTION Data collected included study characteristics and methodologic quality, populations enrolled, neuromonitoring modalities, outcome, and limitations. Evidence tables per neuromonitoring method were constructed using a standardized data extraction form. Each included study was graded according to the Oxford Evidence-Based Medicine scoring system. DATA SYNTHESIS Of 1,195 citations, 27 studies met the inclusion criteria. There were 16 retrospective studies, nine observational prospective studies, one observational exploratory study, and one pilot randomized controlled trial. Neuromonitoring methods included neurologic examination, routine electroencephalography and continuous electroencephalography, transcranial Doppler, MRI, head CT, plasma biomarkers, somatosensory evoked potentials, and brainstem auditory evoked potential. All evidence was graded 2B-2C. CONCLUSIONS The appropriate application and precise interpretation of available modalities still need to be determined in relation to the individual patient. International collaboration in standardized data collection during the (acute) clinical course together with detailed long-term outcome measurements (including functional outcome, neuropsychologic assessment, and health-related quality of life) are the first steps toward more precise, patient-specific neuroprognostication after pediatric cardiac arrest.
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12
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The current practice regarding neuro-prognostication for comatose children after cardiac arrest differs between and within European PICUs: A survey. Eur J Paediatr Neurol 2020; 28:44-51. [PMID: 32669214 DOI: 10.1016/j.ejpn.2020.06.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 06/19/2020] [Accepted: 06/30/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To describe current practices in European Paediatric Intensive Care Units (PICUs) regarding neuro-prognostication in comatose children after cardiac arrest (CA). METHODS An anonymous online survey was conducted among members of the European Society of Paediatric and Neonatal Intensive Care (ESPNIC) and the European Paediatric Neurology Society (EPNS) throughout January and February 2019. The survey consisted of 49 questions divided into 4 sections: general information, cardiac arrest, neuro-prognostication and follow-up. RESULTS The survey was sent to 1310 EPNS and 611 ESPNIC members. Of the 108 respondents, 71 (66%) (23 countries, 45 PICUs) completed the "neuro-prognostication" section. Eight PICUs (20%) had a local neuro-prognostication guideline. The 3 methods considered as most useful were neurological examination (92%), magnetic resonance imaging (MRI) (82%) and continuous electroencephalography (cEEG) (45%). In 50% a Pediatric Cerebral Performance Category (PCPC) score ≥ 4 was considered as poor neurological outcome. In 63% timing of determining neurological prognosis was based on the individual patient. Once decided that neurological prognosis was futile, 55% indicated that withdrawing life-sustaining therapy (WLST) was (one of) the options, whereas 44% continued PICU treatment (with or without restrictions). In 28 PICUs (68%) CA-survivors were scheduled for follow-up visits. CONCLUSION Local guidelines for neuro-prognostication in comatose children after CA are uncommon. Methods to assess neurological outcome were mainly neurological examination, MRI and cEEG. Consequences of poor outcome differed between respondents. Inaccuracies in neuro-prognostication can result in premature WLST, thereby biasing outcome research and creating a self-fulfilling cycle. Further research is needed to develop scientifically based international guidelines for neuro-prognostication in comatose children after CA.
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Smith AE, Friess SH. Neurological Prognostication in Children After Cardiac Arrest. Pediatr Neurol 2020; 108:13-22. [PMID: 32381279 PMCID: PMC7354677 DOI: 10.1016/j.pediatrneurol.2020.03.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 03/03/2020] [Accepted: 03/04/2020] [Indexed: 01/08/2023]
Abstract
Early after pediatric cardiac arrest, families and care providers struggle with the uncertainty of long-term neurological prognosis. Cardiac arrest characteristics such as location, intra-arrest factors, and postarrest events have been associated with outcome. We paid particular attention to postarrest modalities that have been shown to predict neurological outcome. These modalities include neurological examination, somatosensory evoked potentials, electroencephalography, and neuroimaging. There is no one modality that accurately predicts neurological prognosis. Thus, a multimodal approach should be undertaken by both neurologists and intensivists to present a clear and consistent message to families. Methods used for the prediction of long-term neurological prognosis need to be specific enough to identify indivuals with a poor outcome. We review the evidence evaluating children with coma, each with various etiologies of cardiac arrest, outcome measures, and timing of follow-up.
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Affiliation(s)
- Alyssa E Smith
- Division of Pediatric Neurology, Department of Neurology, Washington University in St. Louis, St. Louis, Missouri.
| | - Stuart H Friess
- Division of Critical Care Medicine, Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri
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