This article is the last in a series of 3 examining the methodological issues in measuring rates of TIA and strokeassociated dementia. The 2 previous articles have shown that widely used baseline selection criteria and selective attrition from face-to-face follow-up result in TIA and stroke cohorts that are unrepresentative of the whole with those at highest risk of dementia being excluded. 10,11 This third article examines the third and final major potential source of bias in assessing cognitive outcomes after TIA and stroke: the applicability of cognitive tests. Previous studies in noncerebrovascular populations have shown that sensory impairments and more severe cognitive impairment impact on the applicability of such tests [12][13][14] and that cognitive impairment associates with frailty. 15 We therefore hypothesized that risk factors for dementia including nonstroke characteristics such as older age and sensory deficits as well as more severe cerebrovascular events, would be associated with untestability in TIA and stroke but there are few data from inclusive cohorts with long-term follow-up. Background and Purpose-Cognitive assessment is recommended after stroke but there are few data on the applicability of short cognitive tests to the full spectrum of patients. We therefore determined the rates, causes, and associates of untestability in a population-based study of all transient ischemic attack (TIA) and stroke. Methods-Patients with TIA or stroke prospectively recruited (2002)(2003)(2004)(2005)(2006)(2007)
Background Cohorts of severely ill patients with COVID-19 have been described in several countries around the globe, but to date there have been few published reports from the United Kingdom (UK). Understanding the characteristics of the affected population admitted to intensive care units (ICUs) in the UK is crucial to inform clinical decision making, research and planning for future waves of infection. Methods We conducted a prospective observational cohort study of all patients with COVID-19 admitted to a large UK ICU from March to May 2020 with follow-up to June 2020. Data were collected from health records using a standardised template. We used multivariable logistic regression to analyse the factors associated with ICU survival. Results Of the 156 patients included, 112 (72%) were male, 89 (57%) were overweight or obese, 68 (44%) were from ethnic minorities, and 89 (57%) were aged over 60 years of age. 136 (87%) received mechanical ventilation, 77 (57% of those intubated) were placed in the prone position and 95 (70% of those intubated) received neuromuscular blockade. 154 (99%) patients required cardiovascular support and 44 (28%) required renal replacement therapy. Of the 130 patients with completed ICU episodes, 38 (29%) died and 92 (71%) were discharged alive from ICU. In multivariable models, age (OR 1.13 [95% CI 1.07–1.21]), obesity (OR 3.06 [95% CI 1.16–8.74]), lowest P/F ratio on the first day of admission (OR 0.82 [95% CI 0.67–0.98]) and PaCO2 (OR 1.52 [95% CI 1.01–2.39]) were independently associated with ICU death. Conclusions Age, obesity and severity of respiratory failure were key determinants of survival in this cohort. Multiorgan failure was prevalent. These findings are important for guiding future research and should be taken into consideration during future healthcare planning in the UK.
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