Systemic inflammatory response syndrome after transcatheter or surgical aortic valve replacement

Abstract

Objective: An inflammatory response after cardiac surgery is associated with worse clinical outcomes, but recent trials to attenuate it have been neutral. We evaluated the association between systemic inflammatory response syndrome (SIRS) and mortality after transcatheter (TAVR) and surgical aortic valve replacement (SAVR) for aortic stenosis (AS) and evaluated whether diabetes influenced this relationship.

Methods: Patients (n=747) with severe AS treated with TAVR (n=264) or SAVR (n=483) between January 2008 and December 2013 were included and 37% had diabetes mellitus. SIRS was defined by four criteria 12-48 h after aortic valve replacement (AVR): (1) white blood cell count <4 or >12; (2) heart rate >90; (3) temperature <36 or >38°C; or (4) respiratory rate >20. Severe SIRS was defined as meeting all four criteria. The primary endpoint was 6-month all-cause mortality (60 deaths occurred by 6 months). Inverse probability weighting (IPW) was performed on 44 baseline and procedural variables to minimise confounding.

Results: Severe SIRS developed in 6% of TAVR patients and 11% of SAVR patients (p=0.02). Six-month mortality tended to be higher in those with severe SIRS (15.5%) versus those without (7.4%) (p=0.07). After adjustment, severe SIRS was associated with higher 6-month mortality (IPW adjusted HR 2.77, 95% CI 2.04 to 3.76, p<0.001). Moreover, severe SIRS was more strongly associated with increased mortality in diabetic (IPW adjusted HR 4.12, 95% CI 2.69 to 6.31, p<0.001) than non-diabetic patients (IPW adjusted HR 1.74, 95% CI 1.10 to 2.73, p=0.02) (interaction p=0.007). The adverse effect of severe SIRS on mortality was similar after TAVR and SAVR.

Conclusions: Severe SIRS was associated with a higher mortality after SAVR or TAVR. It occurred more commonly after SAVR and had a greater effect on mortality in diabetic patients. These findings may have implications for treatment decisions in patients with AS, may help explain differences in outcomes between different AVR approaches and identify diabetic patients as a high-risk subgroup to target in clinical trials with therapies to attenuate SIRS.

Figure 1. Covariate balancing between those with and without severe SIRS

Covariate balancing is shown between those with versus without severe SIRS (4 criteria met) before and after inverse propensity weighting (IPW).

Figure 2. SIRS and mortality after aortic valve replacement

Time-to-event curves are shown based on inverse propensity weighting Kaplan-Meier estimates. Hazard ratios are shown for Cox proportional hazards models utilizing inverse propensity weighting. Comparison between those with and without severe SIRS is shown (a) as well as for those with and without severe SIRS and diabetes (b).