ROLE OF BISPECTRAL INDEX AND SUPPRESSION RATIO MONITORING WITHIN THE EMERGENCY DEPARTMENT AFTER RETURN OF SPONTANEOUS CIRCULATION FOLLOWING CARDIAC ARREST?: A META-ANALYSIS
Authors: Ramage L , Simillis C , Patil S 
Published: November 2016

Objectives & Background

Prognostication following return of spontaneous circulation (ROSC) after cardiac arrest (CA) is of growing interest. Several studies have shown early use of the bispectral index (BIS) monitor to calculate the BIS and suppression ratio (SR) can be useful in predicting neurological outcome. This non-invasive technique can be initiated within the emergency department and used alongside other prognostication markers to help early decison-making.

The aim of this meta-analysis is to assess early use of BIS and SR following CA to prognosticate neurologically favourable outcome measured using Cerebral Performance Category (CPC) score.

Methods

Database searches of Pubmed, Web of Science and the Cochrane database were performed independently by two reviewers using the search terms: bispectral index, suppression-ratio, burst-suppression, prognostication, cardiac-arrest, return of spontaneous circulation.

Papers included discussed early measurement (<24 hours) of BIS and/or SR following CA and prognostication of CPC outcomes at hospital discharge. Weighted means were calculated and compared using the independent T-samples test. Pooled sensitivity and specificity analysis was undertaken of BIS values.

Results

1524 records were returned; 967 were excluded based on title; 498 were excluded based on abstract, and 50 were excluded on manuscript review. 9 papers were included: 5 considered BIS index monitoring alone; 2 considered BIS and SR and 2 considered SR alone.

The weighted means comparison of BIS within 24 hours of ROSC for patients with a CPC of 1–2 was 42.67+/−10.45 (n=175) versus 14.58+/−14.45 (n=197) in patients with a CPC category of 3–5 at discharge (p<0.0001). The pooled sensitivity, specificity, diagnostic odds ratio, and positive and negative likelihood ratios for early BIS monitoring were 70% (95% CI, 49%-85%), 93% (95% CI, 83%–97%), 30.42 (95% CI, 8.34–110.91), 9.74 (95% CI, 3.88–24.46), and 0.32 (95% CI 0.17–0.61) (figure 1).

The weighted means comparison of SR measurements for patients with a CPC of 1–2 at discharge was 18.80+/−21.31% (n=94) versus 73.65+/−21.32% (n=90) in those with CPC 3–5 (p<0.0001).

Conclusion

BIS and SR monitoring along with other markers may have a role as part of neuroprognostication within the emergency department. Further work is needed in the form of large scale trials.

Figure 1

summary ROC curve for the use of early (<24 h) BIS monitoring to predict neurological outcome.

Table 1

A comparison of mean BIS values in good versus poor neurological outcome at discharge

StudyCPC 1–2CPC 3–5MeanSDNMeanSDNStammet 201438946171250Leary 201049132030206Burjek 201442.679.055714.6718.8684Selig 201460.6717.451927.6712.177Seder 2009359.30338.339.1650WEIGHTED MEAN42.6710.4517514.5814.45197

*Original data expressed as median [IQR]: converted to mean +/− standard deviation using formula described by Wanet al(2014) SD=Standard deviation, N=Number of cases.

Table 2

Sensitivity and specificity of BIS monitoring for predicting poor neurological outcome after cardiac arrest

StudyTPTNFPFNSensitivity (95% CI)Specificity (95% CI)Cut-off BIS value used in studyLeary 2010417320.67 (0.22–0.96)0.85 (0.62–0.97)23Seder 20094331270.86 (0.73–0.94)0.94 (0.80–0.99)22Selig 2014617210.86 (0.42–1.00)0.89 (0.67–0.99)40Shibata 200514140170.45 (0.27–0.64)1.00 (0.77–1.00)40Stammet 200933030.50 (0.12–0.88)1.00 (0.29–1.00)0POOLED RESULTS0.70 (0.49–0.85)0.93 (0.83–0.97)

TP, true positives; TN, true negatives; FP, false positives; FN, false negatives.

Table 3

A comparison of mean Suppression Ratios in good versus poor neurological outcomes at discharge

StudyCPC 1–2CPC 3–5Mean (%)SDNMean (%)SDNSelig 2014*1016.821954.6718.377Noirhomme 20143121217221.324Wennervita 2009*29.2521.43215223.429Seder 2009*1324.02338121.3750WEIGHTED MEAN18.8021.319473.6521.3290

*Original data expressed as median [IQR]: converted to mean +/− standard deviation using formula described by Wanet al(2014) SD=Standard deviation, N=Number of cases.