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E-147 Factors affecting aspects changes in patients transferred from referral hospitals to a stroke center for possible intervention
  1. P Hinckley1,
  2. A DeHavenon2,
  3. M Alexander1
  1. 1Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT
  2. 2Neurology, University of Utah, Salt Lake City, UT


Introduction/purpose Proper identification of patients suitable for treatment from a referring hospital (RH) to a comprehensive stroke center (CSC) can be difficult. Protocols should maximize access to interventions while limiting futile transfers of patients with no chance for benefit. This conundrum is often compounded by poor access to advanced imaging at low-volume RHs.

Materials and methods Patients with a discharge diagnosis of acute ischemic stroke at a CSC from 2016–2017 were identified, selecting those patients who had been transferred from a RH. According to CSC protocols, only patients meeting criteria for treatment were transferred from RHs. Patients eligible for this study had a non-contrast CT at the RH, repeat non-contrast CT at the CSC, and a CT angiogram of the head and neck at the CSC. All imaging was evaluated by two radiologists, assessing ASPECTS at the RH and CSC, as well as collaterals, which were rated according to techniques described by Maas et al. Ratings were compared with weighted kappa. Two dichotomous primary outcomes were assessed: ASPECTS decline—any negative change in ASPECTS after transfer—and ASPECTS decay—initial ASPECTS≥8 that declined to <8 after transfer). Univariate logistic regression analysis was performed with one-tailed chi-square tests to evaluate baseline patient characteristics predictive of primary outcomes. A multivariate model was then constructed from factors with p<0.2 in univariate analysis, assessing area under the Receiver Operating Curve (AUC).

Results Ninety-five patients met inclusion criteria. Baseline characteristics are shown in Table 1, along with univariate analysis results. Weighted kappa between the raters was 0.72 for RH ASPECTS and 0.85 for CSC ASPECTS. Mean ASPECTS were 9.5 and 8.8 at RHs and CSC, respectively. Mean decrease in ASPECTS was 0.8 with ASPECTS decline identified in 37 (39%) patients and decay in 16 (16.8%). The best multivariate model to predict ASPECTS decline included poor collaterals, large vessel occlusion, non-Caucasian race, current use of >3 alcoholic beverages/day and history of coronary artery disease, yielding AUC of 0.833. The best multivariate model to predict ASPECTS decay included poor collaterals, large vessel occlusion, NIH Stroke scale >5, RH-CSC transport time >240 min, air transport, and female gender, yielding AUC of 0.922.

Conclusion These results support a strategy for transfer between RHs and CSCs that favors inclusivity and minimizes transfer times between sites. As rapid CT angiography becomes more widely available at RHs, presence of large vessel occlusion and identification of poor collaterals may limit futile transfers. Further standardized, large-cohort analysis is needed to refine transfer protocols.

Disclosures P. Hinckley: None. A. DeHavenon: None. M. Alexander: None.

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