Identifying Delirium Early after Stroke: A New Prediction Tool for the Intensive Care Unit.

BACKGROUND: Delirium is common after stroke and associated with poor functional outcomes and mortality. It is unknown whether delirium is a modifiable risk factor, or simply an indicator of prognosis, but in order to intervene successfully, those at greatest risk must be identified early. We created a tool to predict the development of delirium in patients admitted to the intensive care unit for stroke, focusing on factors present on hospital admission. METHODS: Charts of 102 patients admitted to the ICU or IMC after ischemic stroke or intracranial hemorrhage with symptom onset within 72 hours were reviewed. Delirium was identified using the Confusion Assessment Method for the ICU (CAM-ICU). Factors significantly associated with delirium were included in a multivariable logistic regression analysis to create a predictive model. The model was validated in a unique inpatient cohort. RESULTS: In regression analyses, the variables present on admission most strongly associated with the development of delirium after stroke included: age greater than 64 years; intraventricular hemorrhage; intubation; presence of either cognitive dysfunction, aphasia, or neglect; and acute kidney injury. Using these variables in our predictive model, an ROC analysis resulted in an area under the curve of 0.90, and 0.82 in our validation cohort. CONCLUSIONS: Factors available on admission can be used to accurately predict risk of delirium following stroke. Our model can be used to implement more rigorous screening paradigms, allowing for earlier detection and timely treatment. Futures studies will focus on determining if prevention can mitigate the poor outcomes with which delirium is associated.

Psychological well-being and regional brain amyloid and tau in mild cognitive impairment.

OBJECTIVES: To determine whether psychological well-being in people with mild cognitive impairment (MCI), a risk state for Alzheimer disease (AD), is associated with in vivo measures of brain pathology. METHODS: Cross-sectional clinical assessments and positron emission tomography (PET) scans after intravenous injections of 2-(1-{6-[(2-[F18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile (FDDNP), a molecule that binds to plaques and tangles, were performed on middle-aged and older adults at a university research institute. Volunteers were aged 40-85 years with MCI (N = 35) or normal cognition (N = 29) without depression or anxiety. Statistical analyses included general linear models, using regional FDDNP-PET binding values as dependent variables and the Vigor-Activity subscale of the Profile of Mood States (POMS) as the independent variable, covarying for age. The POMS is a self-rated inventory of 65 adjectives that describe positive and negative feelings. RESULTS: Scores on the POMS Vigor-Activity subscale were inversely associated with degree of FDDNP binding in the posterior cingulate cortex (r = -0.35, p = 0.04) in the MCI group but not in the control group. CONCLUSION: Psychological well-being, as indicated by self-reports of greater vigor and activity, is associated with lower FDDNP-PET binding in the posterior cingulate cortex, a region involved in emotional regulation, in individuals with MCI but not in those with normal cognition. These findings are consistent with previous work indicating that deposition of brain amyloid plaques and tau tangles may result in noncognitive and cognitive symptoms in persons at risk for AD.

Association Between Ischemic Stroke Subtype and Stroke Severity: The Atherosclerosis Risk in Communities Study.

BACKGROUND AND OBJECTIVES: Disability after stroke occurs across ischemic stroke subtypes, with a suggestion that embolic strokes are more devastating. Whether this difference is as a result of differences in comorbidities or differences in severity at the time of the stroke event is not known. The primary hypothesis was that participants with embolic stroke would have more severe stroke at the time of admission and a higher risk of mortality, compared with thrombotic stroke participants even with consideration of confounders over time, with a secondary hypothesis that this association would differ by race and sex. METHODS: Atherosclerosis Risk in Communities (ARIC) study participants with incident adjudicated ischemic stroke, stroke severity and mortality data, and complete covariates were included. Multinomial logistic regression models determined the association between stroke subtype (embolic vs thrombotic) and admission NIH Stroke Scale (NIHSS) category (minor [≤5], mild [6-10], moderate [11-15], severe [16-20], and very severe [>20]) adjusted for covariates from visits most proximal to the stroke. Separate ordinal logistic models evaluated for interaction by race and sex. Adjusted Cox proportional hazard models estimated the association between stroke subtype and all-cause mortality (through December 31, 2019). RESULTS: Participants (N = 940) were mean age 71 years (SD = 9) at incident stroke, 51% female, and 38% Black. Using adjusted multinomial logistic regression, the risk of having a more severe stroke (reference NIHSS ≤5) was higher among embolic stroke vs thrombotic stroke patients, with a step-wise increase for embolic stroke patients when moving from mild (odds ratio [OR] 1.95, 95% CI 1.14-3.35) to very severe strokes (OR 4.95, 95% CI 2.34-10.48). After adjusting for atrial fibrillation, there was still a higher risk of having a worse NIHSS among embolic vs thrombotic strokes but with attenuation of effect (very severe stroke OR 3.91, 95% CI 1.76-8.67). Sex modified the association between stroke subtype and severity (embolic vs thrombotic stroke, p interaction = 0.03, per severity category, females OR 2.38, 95% CI 1.55-3.66; males OR 1.75, 95% CI 1.09-2.82). The risk of death (median follow-up 5 years, interquartile range 1-12) was also increased for embolic vs thrombotic stroke patients (hazard ratio 1.66, 95% CI 1.41-1.97). DISCUSSION: Embolic stroke was associated with greater stroke severity at the time of the event and a higher risk of death vs thrombotic stroke, even after careful adjustment for patient-level differences.

Methods for stroke severity assessment by chart review in the Atherosclerosis Risk in Communities study.

Stroke severity is the most important predictor of post-stroke outcome. Most longitudinal cohort studies do not include direct and validated measures of stroke severity, yet these indicators may provide valuable information about post-stroke outcomes, as well as risk factor associations. In the Atherosclerosis Risk in Communities (ARIC) study, stroke severity data were retrospectively collected, and this paper outlines the procedures used and shares them as a model for assessment of stroke severity in other large epidemiologic studies. Trained physician abstractors, who were blinded to other clinical events, reviewed hospital charts of all definite/probable stroke events occurring in ARIC. In this analysis we included 1,198 ischemic stroke events occurring from ARIC baseline (1987-1989) through December 31, 2009. Stroke severity was categorized according to the National Institutes of Health Stroke Scale (NIHSS) score and classified into 5 levels: NIHSS ≤ 5 (minor), NIHSS 6-10 (mild), NIHSS 11-15 (moderate), NIHSS 16-20 (severe), and NIHSS > 20 (very severe). We assessed interrater reliability in a subgroup of 180 stroke events, reviewed independently by the lead abstraction physician and one of the four secondary physician abstractors. Interrater correlation coefficients for continuous NIHSS score as well as percentage of absolute agreement and Cohen Kappa Statistic for NIHSS categories were presented. Determination of stroke severity by the NIHSS, based on data abstracted from hospital charts, was possible for 97% of all ischemic stroke events. Median (25%-75%) NIHSS score was 5 (2-8). The distribution of NIHSS category was NIHSS ≤ 5 = 58.3%, NIHSS 6-10 = 24.5%, NIHSS 11-15 = 8.9%, NIHSS 16-20 = 4.7%, NIHSS > 20 = 3.6%. Overall agreement in the classification of severity by NIHSS category was present in 145/180 events (80.56%). Cohen's simple Kappa statistic (95% CI) was 0.64 (0.55-0.74) and weighted Kappa was 0.79 (0.72-0.86). Mean (SD) NIHSS score was 5.84 (5.88), with a median score of 4 and range 0-31 for the lead reviewer (rater 1) and mean (SD) 6.16 (6.10), median 4.5 and range 0-36 in the second independent assessment (rater 2). There was a very high correlation between the scores reported in both assessments (Pearson r = 0.90). Based on our findings, we conclude that hospital chart-based retrospective assessment of stroke severity using the NIHSS is feasible and reliable.

The Maryland Acute Stroke Emergency Medical Services Routing Pilot: Expediting Access to Thrombectomy for Stroke.

Background: Mechanical thrombectomy (MT) is the standard of care for acute ischemic stroke caused by large vessel occlusion, but is not available at all stroke centers. Transfers between hospitals lead to treatment delays. Transport directly to a facility capable of MT based on a prehospital stroke severity scale score has been recommended, if transportation time is less than 30 min. Aims: We hypothesized that an Emergency Medical Services (EMS) routing algorithm for stroke, using the Los Angeles Motor Scale (LAMS) in the field, would improve time from last known well to MT, without causing patients to miss the IV Thrombolysis (IVT) window. Methods: An EMS algorithm in the Baltimore metro area using the LAMS was implemented. Patients suspected of having an acute stroke were assessed by EMS using the LAMS. Patients scoring 4 or higher and within 20 h from last known well, were transported directly to a Thrombectomy Center, if transport could be completed within 30 min. The algorithm was evaluated retrospectively with prospectively collected data at the Thrombectomy Centers. The primary outcome variables were proportion of patients with suspected stroke rerouted by EMS, proportion of rerouted ischemic stroke patients receiving MT, time to treatment, and whether the IVT window was missed. Results: A total of 303 patients were rerouted out of 2459 suspected stroke patients over a period of 6 months. Of diverted patients, 47% had acute ischemic stroke. Of these, 48% received an acute stroke treatment: 16.8% IVT, 17.5% MT, and 14% MT+IVT. Thrombectomy occurred 119 min earlier in diverted patients compared to patients transferred from other hospitals (P = 0.006). 55.3% of diverted patients undergoing MT and 38.2% of patients transferred from hospital to hospital were independent at 90 days (modified Rankin score 0-2) (P = 0.148). No patient missed the time window for IVT due to the extra travel time. Conclusions: In this retrospective analysis of prospectively acquired data, implementation of a pre-hospital clinical screening score to detect patients with suspected acute ischemic stroke due to large vessel occlusion was feasible. Rerouting patients directly to a Thrombectomy Center, based on the EMS algorithm, led to a shorter time to thrombectomy.