Sex differences in quality of life in stroke survivors. Data from the Tinzaparin in Acute Ischaemic Stroke Trial (TAIST)

Introduction: Female sex is predictive of poor functional outcome in stroke, even after correction for prognostic factors. Poor quality of life (QoL) is observed in stroke survivors, with lower scores seen in the most disabled patients. We used data from the TAIST trial to assess the relationship between sex and QoL after ischaemic stroke. Methods: TAIST was a randomised controlled trial assessing the safety and efficacy of tinzaparin versus aspirin in 1,484 patients with acute ischaemic stroke. QoL was measured at 180 days post randomisation using the short-form 36 health survey which assesses QoL across eight domains. The relationship between sex and each domain was assessed using ordinal regression, both unadjusted and adjusted for key prognostics factors. Results: Of the 1,484 patients randomised into TAIST, 216 had died at 180 days post randomisation. 1,268 survivors were included in this analysis, 694 males (55%), 574 females (45%). Females tended to score lower than males across all QoL domains (apart from general health); statistically significant lower scores were seen for physical functioning (odds ratio (OR) 0.58, 95% confidence interval (CI) 0.47-0.72), vitality (OR 0.79, 95% CI 0.64-0.98) and mental health (OR 0.75, 95% CI 0.61-0.93). The results for physical functioning and mental health remained significant after adjustment for prognostic variables (OR 0.73, 95% CI 0.58-0.92; OR 0.76, 95% CI 0.60-0.95 respectively). Conclusions: QoL, in particular physical function and mental health domains, is lower in female patients after stroke. This difference persists even after correction for known prognostic factors such as age and stroke severity.

Compression stockings and the prevention of symptomatic venous thromboembolism: data from the Tinzaparin in Acute Ischaemic Stroke Trial

Background: Venous thromboembolism (VTE) is a well recognised and preventable complication of acute stroke. While graduated compression stockings reduce the risk of VTE in surgical patients their benefit in acute stroke remains uncertain. Methods: The relationship between symptomatic VTE and use of stockings using observational data from the ‘Tinzaparin in Acute Ischaemic Stroke Trial’, which compared 10 days of treatment with tinzaparin (175 IU.kg-1 or 100 IU.kg-1) with, aspirin (300 mg od), was assessed using logistic regression adjusted for known VTE risk factors and treatment. Results: Symptomatic VTE occurred in 28 patients (1.9%, DVT 18, PE 13) within 15 days of enrolment in 1,479 patients. Patients wearing one or two stockings for any period of time during the first 10 days (n=803) had a non-significant increase (odds ratio, OR 2.45, 95% confidence interval, CI 0.95 - 6.32) in the risk of symptomatic VTE. In contrast, those wearing bilateral stockings for 10 days (n=374) had a non-significant reduction in the odds of symptomatic VTE as compared to those who wore no stockings or wore them for less than 10 days (OR 0.65, 95% CI 0.26-1.65). Mild stroke and treatment with tinzaparin were associated with a reduced risk of VTE. Conclusions: Bilateral graduated compression stockings may reduce the incidence of VTE by one-third in patients with acute ischaemic stroke. However, the uncertainty in this finding, low frequency of symptomatic VTE, potential for stockings to cause harm, and cost of stockings highlight the need for a large randomised-controlled trial to examine the safety and efficacy of stockings in acute stroke.

Relationship between hyperacute blood pressure and outcome after ischemic stroke: data from the VISTA Collaboration

Background and Purpose—High blood pressure (BP) is associated independently with poor outcome after acute ischemic stroke, although in most analyses “baseline” BP was measured 24 hours or more postictus, and not during the hyperacute period. Methods—Analyses included 1722 patients in hyperacute trials (recruitment 8 hours) from the Virtual Stroke International Stroke Trial Archive (VISTA) Collaboration. Data on BP at enrolment and after 1, 2, 16, 24, 48, and 72 hours, neurological impairment at 7 days (NIHSS), and functional outcome at 90 days (modified Rankin scale) were assessed using logistic regression models, adjusted for confounding variables; results are for 10-mm Hg change in BP. Results—Mean time to enrolment was 3.7 hours (range 1.0 to 7.9). High systolic BP (SBP) was significantly associated with increased neurological impairment (odds ratio, OR 1.06, 95% confidence interval, 95% CI 1.01 to 1.12), and poor functional outcome; odds ratios for both increased with later BP measurements made at up to 24 hours poststroke. Smaller (versus larger) declines in SBP over the first 24 hours were significantly associated with poor NIHSS scores (OR 1.16, 95% CI 1.05 to 1.27) and functional outcome (OR 1.23, 95% CI 1.13 to 1.34). A large variability in SBP was also associated with poor functional outcome. Conclusions—High SBP and large variability in SBP in the hyperacute stages of ischemic stroke are associated with increased neurological impairment and poor functional outcome, as are small falls in SBP over the first 24 hours.

Parcellation of fMRI datasets with ICA and PLS: a data driven approach

Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.