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      The Edinburgh CT and genetic diagnostic criteria for lobar intracerebral haemorrhage associated with cerebral amyloid angiopathy: model development and diagnostic test accuracy study

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          Summary

          Background

          Identification of lobar spontaneous intracerebral haemorrhage associated with cerebral amyloid angiopathy (CAA) is important because it is associated with a higher risk of recurrent intracerebral haemorrhage than arteriolosclerosis-associated intracerebral haemorrhage. We aimed to develop a prediction model for the identification of CAA-associated lobar intracerebral haemorrhage using CT features and genotype.

          Methods

          We identified adults with first-ever intracerebral haemorrhage diagnosed by CT, who died and underwent research autopsy as part of the Lothian IntraCerebral Haemorrhage, Pathology, Imaging and Neurological Outcome (LINCHPIN) study, a prospective, population-based, inception cohort. We determined APOE genotype and radiologists rated CT imaging appearances. Radiologists were not aware of clinical, genetic, and histopathological features. A neuropathologist rated brain tissue for small vessel diseases, including CAA, and was masked to clinical, radiographic, and genetic features. We used CT and APOE genotype data in a logistic regression model, which we internally validated using bootstrapping, to predict the risk of CAA-associated lobar intracerebral haemorrhage, derive diagnostic criteria, and estimate diagnostic accuracy.

          Findings

          Among 110 adults (median age 83 years [IQR 76–87], 49 [45%] men) included in the LINCHPIN study between June 1, 2010 and Feb 10, 2016, intracerebral haemorrhage was lobar in 62 (56%) participants, deep in 41 (37%), and infratentorial in seven (6%). Of the 62 participants with lobar intracerebral haemorrhage, 36 (58%) were associated with moderate or severe CAA compared with 26 (42%) that were associated with absent or mild CAA, and were independently associated with subarachnoid haemorrhage (32 [89%] of 36 vs 11 [42%] of 26; p=0·014), intracerebral haemorrhage with finger-like projections (14 [39%] of 36 vs 0; p=0·043), and APOE ɛ4 possession (18 [50%] of 36 vs 2 [8%] of 26; p=0·0020). A prediction model for CAA-associated lobar intracerebral haemorrhage using these three variables had excellent discrimination (c statistic 0·92, 95% CI 0·86–0·98), confirmed by internal validation. For the rule-out criteria, neither subarachnoid haemorrhage nor APOE ɛ4 possession had 100% sensitivity (95% CI 88–100). For the rule-in criteria, subarachnoid haemorrhage and either APOE ɛ4 possession or finger-like projections had 96% specificity (95% CI 78–100).

          Interpretation

          The CT and APOE genotype prediction model for CAA-associated lobar intracerebral haemorrhage shows excellent discrimination in this cohort, but requires external validation. The Edinburgh rule-in and rule-out diagnostic criteria might inform prognostic and therapeutic decisions that depend on identification of CAA-associated lobar intracerebral haemorrhage.

          Funding

          UK Medical Research Council, The Stroke Association, and The Wellcome Trust.

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          Most cited references16

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          Update on the Global Burden of Ischemic and Hemorrhagic Stroke in 1990-2013: The GBD 2013 Study

          Background: Global stroke epidemiology is changing rapidly. Although age-standardized rates of stroke mortality have decreased worldwide in the past 2 decades, the absolute numbers of people who have a stroke every year, and live with the consequences of stroke or die from their stroke, are increasing. Regular updates on the current level of stroke burden are important for advancing our knowledge on stroke epidemiology and facilitate organization and planning of evidence-based stroke care. Objectives: This study aims to estimate incidence, prevalence, mortality, disability-adjusted life years (DALYs) and years lived with disability (YLDs) and their trends for ischemic stroke (IS) and hemorrhagic stroke (HS) for 188 countries from 1990 to 2013. Methodology: Stroke incidence, prevalence, mortality, DALYs and YLDs were estimated using all available data on mortality and stroke incidence, prevalence and excess mortality. Statistical models and country-level covariate data were employed, and all rates were age-standardized to a global population. All estimates were produced with 95% uncertainty intervals (UIs). Results: In 2013, there were globally almost 25.7 million stroke survivors (71% with IS), 6.5 million deaths from stroke (51% died from IS), 113 million DALYs due to stroke (58% due to IS) and 10.3 million new strokes (67% IS). Over the 1990-2013 period, there was a significant increase in the absolute number of DALYs due to IS, and of deaths from IS and HS, survivors and incident events for both IS and HS. The preponderance of the burden of stroke continued to reside in developing countries, comprising 75.2% of deaths from stroke and 81.0% of stroke-related DALYs. Globally, the proportional contribution of stroke-related DALYs and deaths due to stroke compared to all diseases increased from 1990 (3.54% (95% UI 3.11-4.00) and 9.66% (95% UI 8.47-10.70), respectively) to 2013 (4.62% (95% UI 4.01-5.30) and 11.75% (95% UI 10.45-13.31), respectively), but there was a diverging trend in developed and developing countries with a significant increase in DALYs and deaths in developing countries, and no measurable change in the proportional contribution of DALYs and deaths from stroke in developed countries. Conclusion: Global stroke burden continues to increase globally. More efficient stroke prevention and management strategies are urgently needed to halt and eventually reverse the stroke pandemic, while universal access to organized stroke services should be a priority.
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            Refining clinical diagnosis with likelihood ratios.

            Likelihood ratios can refine clinical diagnosis on the basis of signs and symptoms; however, they are underused for patients' care. A likelihood ratio is the percentage of ill people with a given test result divided by the percentage of well individuals with the same result. Ideally, abnormal test results should be much more typical in ill individuals than in those who are well (high likelihood ratio) and normal test results should be most frequent in well people than in sick people (low likelihood ratio). Likelihood ratios near unity have little effect on decision-making; by contrast, high or low ratios can greatly shift the clinician's estimate of the probability of disease. Likelihood ratios can be calculated not only for dichotomous (positive or negative) tests but also for tests with multiple levels of results, such as creatine kinase or ventilation-perfusion scans. When combined with an accurate clinical diagnosis, likelihood ratios from ancillary tests improve diagnostic accuracy in a synergistic manner.
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              Is Open Access

              Brain hemorrhage recurrence, small vessel disease type, and cerebral microbleeds

              Objective: We evaluated recurrent intracerebral hemorrhage (ICH) risk in ICH survivors, stratified by the presence, distribution, and number of cerebral microbleeds (CMBs) on MRI (i.e., the presumed causal underlying small vessel disease and its severity). Methods: This was a meta-analysis of prospective cohorts following ICH, with blood-sensitive brain MRI soon after ICH. We estimated annualized recurrent symptomatic ICH rates for each study and compared pooled odds ratios (ORs) of recurrent ICH by CMB presence/absence and presumed etiology based on CMB distribution (strictly lobar CMBs related to probable or possible cerebral amyloid angiopathy [CAA] vs non-CAA) and burden (1, 2–4, 5–10, and >10 CMBs), using random effects models. Results: We pooled data from 10 studies including 1,306 patients: 325 with CAA-related and 981 CAA-unrelated ICH. The annual recurrent ICH risk was higher in CAA-related ICH vs CAA-unrelated ICH (7.4%, 95% confidence interval [CI] 3.2–12.6 vs 1.1%, 95% CI 0.5–1.7 per year, respectively; p = 0.01). In CAA-related ICH, multiple baseline CMBs (versus none) were associated with ICH recurrence during follow-up (range 1–3 years): OR 3.1 (95% CI 1.4–6.8; p = 0.006), 4.3 (95% CI 1.8–10.3; p = 0.001), and 3.4 (95% CI 1.4–8.3; p = 0.007) for 2–4, 5–10, and >10 CMBs, respectively. In CAA-unrelated ICH, only >10 CMBs (versus none) were associated with recurrent ICH (OR 5.6, 95% CI 2.1–15; p = 0.001). The presence of 1 CMB (versus none) was not associated with recurrent ICH in CAA-related or CAA-unrelated cohorts. Conclusions: CMB burden and distribution on MRI identify subgroups of ICH survivors with higher ICH recurrence risk, which may help to predict ICH prognosis with relevance for clinical practice and treatment trials.
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                Author and article information

                Contributors
                Journal
                Lancet Neurol
                Lancet Neurol
                The Lancet. Neurology
                Lancet Pub. Group
                1474-4422
                1474-4465
                1 March 2018
                March 2018
                : 17
                : 3
                : 232-240
                Affiliations
                [a ]Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
                [b ]UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, UK
                [c ]Row Fogo Centre for Research into Ageing and the Brain, The University of Edinburgh, Edinburgh, UK
                [d ]Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Edinburgh, UK
                [e ]Department of Neurology, Altnagelvin Hospital, Londonderry, UK
                [f ]Institute of Neuroscience and Institute for Ageing, Newcastle University, Newcastle-upon-Tyne, UK
                [g ]Newcastle upon Tyne Hospitals National Health Services Foundation Trust, Newcastle-upon-Tyne, UK
                [h ]Clinical Neurosciences, Clinical and Experimental Sciences, University of Southampton, Southampton, UK
                [i ]Université Lille, Inserm U1171, Degenerative and Vascular Cognitive Disorders, CHU Lille, Department of Neurology, Lille, France
                Author notes
                [* ]Correspondence to: Prof Rustam Al-Shahi Salman, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UKCorrespondence to: Prof Rustam Al-Shahi Salman, Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghEH16 4SBUK rustam.al-shahi@ 123456ed.ac.uk
                Article
                S1474-4422(18)30006-1
                10.1016/S1474-4422(18)30006-1
                5818029
                29331631
                45ddd938-9f0c-44bb-a6c6-12ac34ee829b
                © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                Categories
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                Neurology
                Neurology

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