Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre studyShow others and affiliations
2024 (English)In: Intensive Care Medicine, ISSN 0342-4642, E-ISSN 1432-1238, Vol. 50, no 7, p. 1096-1107Article in journal (Refereed) Published
Abstract [en]
Purpose: Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest. Methods: Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h <= 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey-white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4-6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated. Results: 140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59-76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90-100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77-0.91) did not significantly differ from manually obtained GWR. Conclusion: Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.
Place, publisher, year, edition, pages
SPRINGER , 2024. Vol. 50, no 7, p. 1096-1107
Keywords [en]
Cardiac arrest; Computed tomography; Prognosis; Hypoxic-ischaemic encephalopathy; GWR
National Category
Anesthesiology and Intensive Care
Identifiers
URN: urn:nbn:se:liu:diva-206650DOI: 10.1007/s00134-024-07497-2ISI: 001251781400001PubMedID: 38900283Scopus ID: 2-s2.0-85196384410OAI: oai:DiVA.org:liu-206650DiVA, id: diva2:1891347
Note
Funding Agencies|Vetenskapsrdet
2024-08-222024-08-222025-06-27