Does the Magnitude of the Electrocardiogram QT Interval Dispersion Predict Stroke Outcome?

BACKGROUND: QT dispersion, maximal interlead difference in QT interval on 12-lead electrocardiogram (ECG), measures cardiac repolarization abnormalities. Data are conflicting whether QT dispersion predicts adverse outcome in acute ischemic stroke (AIS) patients. Our objective is to determine if QT dispersion predicts: (1) short-term clinical outcome in AIS, and (2) stroke location (insular versus noninsular cortex). METHODS: Admission ECGs from 412 consecutive patients with acute stroke symptoms from 2 university-based stroke centers were reviewed. QT dispersion was measured. A neuroradiologist reviewed brain imaging for insular cortex involvement. Favorable clinical outcomes at discharge were modified Rankin Scale (mRS) score of 0-1, discharge National Institutes of Health Stroke Scale (NIHSS) score less than 2, and discharge to home. Multiple logistic regressions were performed for each outcome measure and to determine the association between insular infarct and QT dispersion. RESULTS: Of 145 subjects in the final analysis, median age was 65 years (interquartile range [IQR] 56-75), male patients were 38%, black patients were 68%, median QT dispersion was 78 milliseconds (IQR 59-98), and median admission NIHSS score was 4 (IQR 2-6). QT dispersion did not predict short-term clinical outcome for mRS score (odds ratio [OR] = 1.001, 95% confidence interval [CI] .99-1.01, P = .85), NIHSS at discharge (OR = .994, 95% CI .98-1.01, P = .30), or discharge disposition (OR = 1.001, 95% CI .99-1.01, P = .81). Insular cortex involvement did not correlate with QT dispersion magnitude (OR = 1.009, 95% CI .99-1.02, P = .45). CONCLUSIONS: We could not demonstrate that QT dispersion is useful in predicting short-term clinical outcome at discharge in AIS. Further, the magnitude of QT dispersion did not predict insular cortical stroke location.

To Treat or Not to Treat?

Background and Purpose- The 2015 updated US Food and Drug Administration alteplase package insert altered several contraindications. We thus explored clinical factors influencing alteplase treatment decisions for patients with minor stroke. Methods- An expert panel selected 7 factors to build a series of survey vignettes: National Institutes of Health Stroke Scale (NIHSS), NIHSS area of primary deficit, baseline functional status, previous ischemic stroke, previous intracerebral hemorrhage, recent anticoagulation, and temporal pattern of symptoms in first hour of care. We used a fractional factorial design (150 vignettes) to provide unconfounded estimates of the effect of all 7 main factors, plus first-order interactions for NIHSS. Surveys were emailed to national organizations of neurologists, emergency physicians, and colleagues. Physicians were randomized to 1 of 10 sets of 15 vignettes, presented randomly. Physicians reported the subjective likelihood of giving alteplase on a 0 to 5 scale; scale categories were anchored to 6 probabilities from 0% to 100%. A conjoint statistical analysis was applied. Results- Responses from 194 US physicians yielded 156 with complete vignette data: 74% male, mean age 46, 80% neurologists. Treatment mean probabilities for individual vignettes ranged from 6% to 95%. Treatment probability increased from 24% for NIHSS score =1 to 41% for NIHSS score =5. The conjoint model accounted for 25% of total observed response variance. In contrast, a model accounting for all possible interactions accounted for 30% variance. Four of the 7 factors accounted jointly for 58% of total relative importance within the conjoint model: previous intracerebral hemorrhage (18%), recent anticoagulation (17%), NIHSS (13%), and previous ischemic stroke (10%). Conclusions- Four main variables jointly account for only a small fraction (<15%) of the total variance related to deciding to treat with intravenous alteplase, reflecting high variability and complexity. Future studies should consider other variables, including physician characteristics.