ABSTRACT
Background: Transient global amnesia (TGA) is defined by an acute memory disturbance of unclear etiology for a period of less than 24 h. TGA occurs as a single event in most cases. Prevalence rates of recurrent TGA vary widely from 5.4 to 27.1%. This retrospective study aimed to determine predictors for TGA recurrence. Methods: Cardiovascular risk profile and magnetic resonance imaging (MRI) of 340 hospitalized TGA patients between 2011 and 2020 were retrospectively analyzed. The median follow-up period amounted to 4.5 ± 2.7 years. Comparisons were made between TGA patients with and without subsequent recurrence. Results: TGA patients with subsequent recurrence were significantly younger (recurrent vs. single episode, 63.6 ± 8.6 years vs. 67.3 ± 10.5 years, p = 0.032) and showed a lower degree of cerebral microangiopathy compared to TGA patients without recurrence. The mean latency to recurrence was 3.0 years ± 2.1 years after the first episode. In a subgroup analysis, patients with at least five years of follow-up (N = 160, median follow-up period 7.0 ± 1.4 years) had a recurrence rate of 11.3%. A 24.5% risk of subsequent TGA recurrence in the following five years was determined for TGA patients up to 70 years of age without microangiopathic changes on MRI (Fazekas' score 0). Conclusion: Younger TGA patients without significant microangiopathy do have an increased recurrence risk. In turn, pre-existing cerebrovascular pathology, in the form of chronic hypertension and cerebral microangiopathy, seems to counteract TGA recurrence.
ABSTRACT
Objective: Transient global amnesia (TGA) is defined by an acute memory disturbance of unclear etiology for a period of <24 h. Several studies showed differences in vascular risk factors between TGA compared to transient ischemic attack (TIA) or healthy controls with varying results. This retrospective and cross-sectional study compares the cardiovascular risk profile of TGA patients with that of acute stroke patients. Methods: Cardiovascular risk profile and MR imaging of 277 TGA patients was retrospectively analyzed and compared to 216 acute ischemic stroke patients (26% TIA). Results: TGA patients were significantly younger and predominantly female compared to stroke patients. A total of 90.6% of TGA patients underwent MRI, and 53% of those showed hippocampal diffusion-weighted imaging (DWI) lesions. Scores for cerebral microangiopathy were lower in TGA patients compared to stroke patients. After statistical correction for age, TGA patients had higher systolic and diastolic blood pressure, higher cholesterol levels, lower HbA1c, as well as blood glucose levels, and lower CHA2DS2-VASc scores. Stroke patients initially displayed higher CRP levels than TIA and TGA patients. TGA patients without DWI lesions were older and showed higher CHA2DS2-VASc scores compared to TGA patients with DWI lesions. Conclusion: This study revealed significant differences between TGA and stroke patients in regard to the cardiovascular risk profile. Our main findings show a strong association between acute hypertensive peaks and TGA in patients not adapted to chronic hypertension, indicating a vascular cause of the disease.
ABSTRACT
BACKGROUND: Detection of atrial fibrillation (AF) is one of the primary diagnostic goals for patients on a stroke unit. Physician-based manual analysis of continuous ECG monitoring is regarded as the gold standard for AF detection but requires considerable resources. Recently, automated computer-based analysis of RR intervals was established to simplify AF detection. The present prospective study analyzes both methods head to head regarding AF detection specificity, sensitivity, and overall effectiveness. METHODS: Consecutive stroke patients without history of AF or proof of AF in the admission ECG were enrolled over the period of 7 months. All patients received continuous ECG telemetry during the complete stay on the stroke unit. All ECGs underwent automated analysis by a commercially available program. Blinded to these results, all ECG tracings were also assessed manually. Sensitivity, specificity, time consumption, costs per day, and cost-effectiveness were compared. RESULTS: 216 consecutive patients were enrolled (70.7 ± 14.1 years, 56% male) and 555 analysis days compared. AF was detected by manual ECG analysis on 37 days (6.7%) and automatically on 57 days (10.3%). Specificity of the automated algorithm was 94.6% and sensitivity 78.4% (28 [5.0%] false positive and 8 [1.4%] false negative). Patients with AF were older and had more often arterial hypertension, higher NIHSS at admission, more often left atrial dilatation, and a higher CHA2DS2-VASc score. Automation significantly reduced human resources but was more expensive compared to manual analysis alone. CONCLUSION: Automatic AF detection is highly specific, but sensitivity is relatively low. Results of this study suggest that automated computer-based AF detection should be rather complementary to manual ECG analysis than replacing it.
