A pilot study of methods for prediction of poor outcome by head computed tomography after cardiac arrest. (October 2022) - Lang, Margareta
Abstract: Introduction: In Sweden, head computed tomography (CT) is commonly used for prediction of neurological outcome after cardiac arrest, as recommended by guidelines. We compare the prognostic ability and interrater variability of routine and novel CT methods for prediction of poor outcome. Methods: Retrospective study including patients from Swedish sites within the Target Temperature Management after out-of-hospital cardiac arrest trial examined with CT. Original images were assessed by two independent radiologists blinded from clinical data with eye-balling without pre-specified criteria, and with a semi-quantitative assessment. Grey-white-matter ratios (GWR) were quantified using models with 4–20 manually placed regions of interest. Prognostic abilities and interrater variability were calculated for prediction of poor outcome (modified Rankin Scale 4–6 at 6 months) for early (<24 h) and late (≥24 h) examinations. Results: 68/106 (64 %) of included patients were examined < 24 h post-arrest. Eye-balling predicted poor outcome with 89–100 % specificity and 15–78 % sensitivity. GWR < 24 h predicted neurological outcome with unsatisfactory to satisfactory Area Under the Receiver Operating Characteristics Curve (AUROC: 0.54–0.64). GWR ≥ 24 h yielded very good to excellent AUROC (0.80–0.93). Sensitivities increased > 2–3-fold in examinations performed after 24 h compared to early examinations. Combining eye-balling with GWR < 1.15 predicted poor outcome without false positives with sensitivities remaining acceptable. Conclusion: In our cohort, qualitative and quantitative CT methods predicted poor outcome with high specificity and low to moderate sensitivity. Sensitivity increased relevantly after the first 24 h after CA. Interrater variability poses a problem and indicates the need to standardise brain CT evaluation to increase the methods' safety.