Biochemical and electrophysiological markers predictive of return of spontaneous circulation and post-resuscitation outcome

Ristagno, Giuseppe (2013). Biochemical and electrophysiological markers predictive of return of spontaneous circulation and post-resuscitation outcome. PhD thesis The Open University.



The majority of patients resuscitated from cardiac arrest (CA) subsequently die due to post-cardiac arrest syndrome (PCAS), whose mechanisms are only partially understood. We adopted an approach of untargeted/targeted plasma metabolomics in rats to identify metabolites involved in the mechanisms of PCAS to be tested as predictors of outcome. Activation of the kynurenine pathway (KP) for tryptophan (TRP) degradation was demonstrated in rats, pigs and in a small cohort of patients. Decreases in TRP occurred during the post-CA period and were accompanied by significant increases in KP metabolites, 3-hydroxyanthranilic acid (3 -HAA) and kynurenic acid in each species, that persisted up to 3-5 days post-CA (p<0.01). KP metabolites changes were significantly related to the severity of myocardial and cerebral injuries and survival. Finally, when tested in 155 patients resuscitated from CA, KP metabolites were significantly higher in patients with poor outcomes. The quality of chest compression (CC) is another major issue for cardiopulmonary resuscitation (CPR) success and survival. The decision whether to interrupt CC to deliver a defibrillation (DF) is difficult. The potential benefit of a DF guided by a real time ventricular fibrillation (YF) waveform analysis would maximize DF success, minimize CC interruptions and myocardial damage by repetitive and unnecessary DFs. We evaluated amplitude spectrum area (AMSA) as predictor of DF outcome in two large databases of out-of-hospital VFs, from US (609 patients) and Italy (1.617 patients). AMSA was significantly higher prior to a successful DF than prior to an unsuccessful one (p<0.0001). Thresholds for prediction of successful and unsuccessful DFs were 16-17 mV-Hz for success and <7 mV-Hz for failure, with a positive predictive value of 80% and a negative predictive value of 97%. AMSA was a better predictor of DF outcome (AUC 0.86, p<0.0001) compared to other VF parameters, i.e. amplitude and frequencies. In conclusion, AMSA would be a useful tool for guiding CPR.

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