Late infection or recurrence of the AEF and associated mortality rates are high when TEVAR is used as a sole therapeutic strategy. Prolonged antibiotic treatment has a strong negative association with mortality. A strategy of a temporizing endovascular procedure to stabilize the patient in extremis, and upon recovery, an open surgical esophageal repair with or without stent graft explantation is advocated.
Long-term survival remains poor after aneurysm repair and adverse cardiovascular events are common relative to the wider population. Further research is required to characterise and optimise cardiovascular risk prevention in patients with aortic aneurysms.
BackgroundImproved critical care, pre-operative optimization, and the advent of endovascular surgery (EVAR) have improved 30 day mortality for elective abdominal aortic aneurysm (AAA) repair. It remains unknown whether this has translated into improvements in long-term survival, particularly because these factors have also encouraged the treatment of older patients with greater comorbidity. The aim of this study was to quantify how 5 year survival after elective AAA repair has changed over time.MethodsA systematic review was performed identifying studies reporting 5 year survival after elective infrarenal AAA repair. An electronic search of the Embase and Medline databases was conducted to January 2014. Thirty-six studies, 60 study arms, and 107,814 patients were identified. Meta-analyses were conducted to determine 5 year survival and to report whether 5 year survival changed over time.ResultsFive-year survival was 69% (95% CI 67 to 71%, I2 = 87%). Meta-regression on study midpoint showed no improvement in 5 year survival over the period 1969–2011 (log OR −0.001, 95% CI −0.014–0.012). Larger average aneurysm diameter was associated with poorer 5 year survival (adjusted log OR −0.058, 95% CI −0.095 to −0.021, I2 = 85%). Older average patient age at surgery was associated with poorer 5 year survival (adjusted log OR −0.118, 95% CI −0.142 to −0.094, I2 = 70%). After adjusting for average patient age, an improvement in 5 year survival over the period that these data spanned was obtained (adjusted log OR 0.027, 95% CI 0.012 to 0.042).ConclusionFive-year survival remains poor after elective AAA repair despite advances in short-term outcomes and is associated with AAA diameter and patient age at the time of surgery. Age-adjusted survival appears to have improved; however, this cohort as a whole continues to have poor long-term survival. Research in this field should attempt to improve the life expectancy of patients with repaired AAA and to optimise patient selection.
Appropriate risk factor modification could significantly reduce long-term mortality in patients with AAA. In the UK, up to 30 per cent of patients are not currently receiving these medications.
Deterioration in renal function has been described after endovascular repair of abdominal aortic aneurysms (EVR). The aetiology is multifactorial and represents an important therapeutic target. A need exists to quantitatively summarise incidence and severity of renal dysfunction after EVR to allow better-informed attempts to preserve renal function and improve life expectancy. A systematic search was performed using Medline and Embase for renal function after EVR applying PRISMA statements. Univariate and multivariate random effects meta-analyses were performed to estimate pooled post-operative changes in serum creatinine and creatinine clearance at four time points after EVR: 0-7 days, 30 days/1 month, 1 month-1year and ≥1year. Clinically relevant deterioration in renal function was also estimated at ≥1year after EVR. 23 papers were identified for analysis. Pooled probability of clinically-relevant deterioration in renal function ≥1year was 18% (95% CI=14-23%,I²=82.5%). From univariate meta-analyses, serum creatinine increased after EVR by of 0.05mg/dL at 30 days/1month, 0.09mg/dL at 1 month to 1 year and 0.11mg/dL at ≥ 1 year (all p<0.05). Creatinine clearance reduced after EVR by 5.65 ml/min at 1 month-1 year and 6.58 ml/min at ≥1 year (both p<0.05). Renal failure after EVR is underreported and reporting standards are poorly followed. Clinically relevant deterioration in renal function is common and merits focussed attention to attenuate impact on long-term mortality.
BackgroundLifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques.MethodsPatients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk.Results761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p<0.001)ConclusionThis study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.
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