Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study.
Crit Care Med
; 49(12): e1212-e1222, 2021 12 01.
Article
en En
| MEDLINE
| ID: mdl-34374503
ABSTRACT
OBJECTIVES:
Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential source of error and interrater variability. Our objective was to assess the performance of poor outcome prediction by automated quantification of changes in brain CTs after cardiac arrest.DESIGN:
Observational, derivation/validation cohort study design. Outcome was determined using the Cerebral Performance Category upon hospital discharge. Poor outcome was defined as death or unresponsive wakefulness syndrome/coma. CTs were automatically decomposed using coregistration with a brain atlas.SETTING:
ICUs at a large, academic hospital with circulatory arrest center. PATIENTS We identified 433 cardiac arrest patients from a large previously established database with brain CTs within 10 days after cardiac arrest.INTERVENTIONS:
None. MEASUREMENTS AND MAINRESULTS:
Five hundred sixteen brain CTs were evaluated (derivation cohort n = 309, validation cohort n = 207). Patients with poor outcome had significantly lower radiodensities in gray matter regions. Automated GWR_si (putamen/posterior limb of internal capsule) was performed with an area under the curve of 0.86 (95%-CI 0.80-0.93) for CTs taken later than 24 hours after cardiac arrest (similar performance in the validation cohort). Poor outcome (Cerebral Performance Category 4-5) was predicted with a specificity of 100% (95% CI, 87-100%, derivation; 88-100%, validation) at a threshold of less than 1.10 and a sensitivity of 49% (95% CI, 36-58%, derivation) and 38% (95% CI, 27-50%, validation) for CTs later than 24 hours after cardiac arrest. Sensitivity and area under the curve were lower for CTs performed within 24 hours after cardiac arrest.CONCLUSIONS:
Automated gray-white-matter ratio from brain CT is a promising tool for prediction of poor neurologic outcome after cardiac arrest with high specificity and low-to-moderate sensitivity. Prediction by gray-white-matter ratio at the basal ganglia level performed best. Sensitivity increased considerably for CTs performed later than 24 hours after cardiac arrest.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Encéfalo
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Tomografía Computarizada por Rayos X
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Aprendizaje Automático
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Paro Cardíaco
Tipo de estudio:
Etiology_studies
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Guideline
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Crit Care Med
Año:
2021
Tipo del documento:
Article
País de afiliación:
Alemania