Systematic review and meta-analysis of transcranial doppler biomarkers for the prediction of delayed cerebral ischemia following subarachnoid hemorrhage
Hanna Schenck, Céline van Craenenbroeck, Sander M. J. van Kuijk, Erik D. Gommer, Michael Veldeman, Yasin Temel, Marcel Aries, Werner H. Mess, Roel Haeren
Abstract
Delayed cerebral ischemia (DCI) following an aneurysmal subarachnoid hemorrhage (aSAH) significantly impacts mortality, morbidity, and healthcare costs. This study assessed the diagnostic accuracy of Transcranial Doppler (TCD)-derived biomarkers for predicting DCI via a systematic review and meta-analysis. Included studies had to correctly define DCI and report data on sensitivity, specificity, positive predictive value, and negative predictive value. Univariate or bivariate analyses with a random effects model were used, and risk of bias was evaluated with the Quality Assessment of Diagnostic Accuracy Studies. From 23 eligible articles (n = 2371 patients), three biomarker categories were identified: cerebral blood flow velocities (CBFV), cerebral autoregulation, and microembolic signals (MES). The highest sensitivity (0.86, 95% CI 0.71-0.94) and specificity (0.75, 95% CI 0.52-0.94) for DCI prediction were achieved with a mean CBFV of 120 cm/s combined with a Lindegaard ratio. The transient hyperemic response test showed the best performance among autoregulatory biomarkers with a sensitivity of 0.88, (95% CI 0.54-0.98) and specificity of 0.82 (95% CI 0.52-0.94). MES were less effective predictors. Combining CBFV with autoregulatory biomarkers enhanced TCD's predictive value. High heterogeneity and risk of bias were noted, indicating the need for a standardized TCD approach for improved DCI evaluation.