AI Article Synopsis
- The study aimed to use standardized and automated CT assessments to predict outcomes for patients who suffered out-of-hospital cardiac arrest.
- Involving 140 unconscious patients, results showed that while qualitative assessments and various gray-white-matter ratio (GWR) models achieved 100% specificity in predicting poor outcomes, sensitivity rates varied, with automated GWR proving robust.
- The research concluded that these CT assessment methods could reliably indicate poor functional outcomes, and automated GWR could enhance accessibility for medical centers handling cardiac arrest cases.
Article Abstract
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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245448 | PMC |
| http://dx.doi.org/10.1007/s00134-024-07497-2 | DOI Listing |
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