Background: Medical management of acute aortic dissection (AAD) is poorly understood and based mainly on personal experience, expert opinion and observational studies. Society guidelines reaffirm this lack of evidence. We sought to determine the association of specific medications on outcomes in AAD patients. Methods: Prior analyses from the International Registry of Acute Aortic Dissection (IRAD) suggest beta blockers (BB) are associated with lower long-term mortality after AAD, and calcium channel blockers (CCB) are associated with lower long-term mortality after type B AAD. For this abstract, we analyzed factors associated with in-hospital mortality and aortic growth at follow-up, including medication use, using IRAD. We also looked at medication use and long-term survival in AAD patients with Marfan Syndrome (MFS). Results: Among 817 patients with type B AAD, improved in-hospital survival was associated with BB use (OR 23.09, 95% CI 6.62-80.58, p<0.001), absence of mesenteric ischemia (OR 10.53, 95% CI, 1.31-84.7, p=0.03) and absence of hypotension/shock (OR 7.55, 95% CI, 1.15-49.4, p=0.04). No benefit was associated with use of angiotensin converting enzyme inhibitor (ACE). On follow-up, CCB were associated with slower aortic growth in medically treated type B patients (p=0.013), and CCB use during the first two years after AAD is associated with negative growth of the aorta ( -0.07mm/yr for patients on CCB vs. 0.42mm/yr for those not, p=0.008). Analysis of 68 MFS patients showed improved long-term survival in type A patients receiving BB (p=0.01); ACE were associated with increased mortality after 30 months (p=0.008). Conclusions: This analysis suggests BB are associated with improved in-hospital survival in AAD patients. CCB in Type B patients are associated with improved survival and slower descending aortic growth. MFS patients also benefited from BB use. RAS inhibitors were not associated with improved in-hospital or long-term survival in patients (including MFS patients) with AAD. Whether these observed associations between treatment and outcome are due to cause-and effect cannot be determined. Optimal management needs to be confirmed in randomized controlled trials.
Background: Stroke is one of the most dreaded complications of type A acute aortic dissection (TA-AAD). However, few data exist on its incidence and association with prognosis. Methods: We evaluated 2202 TA-AAD patients [pts, mean age 61.9 ± 14.4, 1487 (67.5%) male] from the International Registry of Acute Aortic Dissection (IRAD) to determine the incidence and prognostic influence of stroke in TA-AAD. Results: Stroke was present at arrival in 132 (6.0%) TA-AAD pts. Stroke pts were older (65±12 vs. 62±15 yrs; p=.002) and more likely to have hypertension (86% vs. 71%; p=.001) or atherosclerosis (29% vs. 22%; p=.042). While chest pain at arrival was less common (70% vs. 82%; p<.001), stroke pts presented more often with syncope (44% vs. 15%; p<.001), shock (14% vs. 7%; p=.005) or pulse deficit (51% vs. 29%; p=<.001). Arch vessels involvement was more frequent among the stroke pts (68% vs. 37%; p<.001). Stroke pts were treated less frequently by surgery (74% vs. 85%; p<.001). Hospital stay was significantly longer in patients presenting with stroke (median 17.9 versus 13.3 days, p<0.001). Stroke patients demonstrated more frequent in-hospital complications (Table) and higher mortality (adjusted OR 1.62, 95% CI .99-2.65, p=.055) Among hospital survivors, mortality at follow-up was similar in pts with and without stroke (adjusted HR 1.15, 95% CI 0.46-2.89, p=.761). Conclusions: Stroke occurred in greater than 1 of 20 pts with TA-AAD and was associated with increased morbidity and in-hospital, but not long-term mortality. Whether aggressive early intervention will reduce morbidity and improve mortality remains to be evaluated in future studies.
Background: The effects of sleep deprivation are vast, ranging from increased stress responses, to lowered immunity and delayed wound healing. However, sleep disruptions are common in the inpatient setting. This study sought to quantify the number and frequency of inpatient sleep disturbances and analyze post-discharge outcomes (emergency department visit, readmission, death) among congestive heart failure (CHF) patients. Methods: Data were collected retrospectively from 30 randomly selected patients admitted for CHF and referred to a cardiac transitional care clinic from 2014 to 2017. Each night over the course of the hospitalization was broken into 12 one-hour intervals (1900-0659 hours), and the electronic health record was examined for 20 variables indicative of sleep disruption (e.g. vitals taken, medications dispensed, wound care) (Figure 1). Demographics and outcomes were compared between high (above median) and low (below median) groups for average number of nightly interval interruptions and average longest uninterrupted sleep interval (LUSI). Results: On average, patients had a length of admission of 5.4 nights, a LUSI of 2.9 hours (range: 1-4), and 6.3 disruptions between 1900-0659 hours (range: 3-8). The readmission rates for the total population were 23% at 30 days and 63% at 180 days. No significant differences were seen in demographics or outcomes up to 180 days post-discharge when comparing high and low patient groups in either average nightly interval interruptions or average LUSI. Conclusion: Although no differences were seen between groups, the majority of patients had poor outcomes (23% were readmitted at 30 days; 63% at 180 days) as well as poor sleep during their admission. The lack of sleep across the entire patient population may be contributing to the poor outcomes observed. Many of the variables reviewed (e.g. vitals taken, medications dispensed, etc.) had potentially elective timing, which suggests actionable changes to the inpatient process may be possible to improve sleep quantity and quality. This was an exploratory pilot study to determine the ability to use electronic health record data for this purpose. As such, the sample size was too small to detect differences. A larger sample size is needed to better understand the extent to which sleep disruptions impact patient outcomes.
