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Comorbidity and age in the modelling of stroke: are we still failing to consider the characteristics of stroke patients?
McCann, Sarah K; Lawrence, Catherine B.
Afiliação
  • McCann SK; QUEST - Center for Transforming Biomedical Research, Berlin Institute of Health (BIH), Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Lawrence CB; Division of Neuroscience and Experimental Psychology and Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.
BMJ Open Sci ; 4(1): e100013, 2020.
Article em En | MEDLINE | ID: mdl-35047684
Stroke is a significant cause of mortality and morbidity for which there are limited treatment options. Virtually all drug interventions that have been successful preclinically in experimental stroke have failed to translate to an effective treatment in the clinical setting. In this review, we examine one of the factors likely contributing to this lack of translation, the failure of preclinical studies to consider fully the advanced age and comorbidities (eg, hypertension or diabetes) present in most patients with stroke. Age and comorbidities affect the likelihood of suffering a stroke, disease progression and the response to treatment. Analysing data from preclinical systematic reviews of interventions for ischaemic stroke we show that only 11.4% of studies included an aged or comorbid model, with hypertension being the most frequent. The degree of protection (% reduction in infarct volume) varied depending on the comorbidity and the type of intervention. We consider reasons for the lack of attention to comorbid and aged animals in stroke research and discuss the value of testing a potential therapy in models representing a range of comorbidities that affect patients with stroke. These models can help establish any limits to a treatment's efficacy and inform the design of clinical trials in appropriate patient populations.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Revista: BMJ Open Sci Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Revista: BMJ Open Sci Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Alemanha País de publicação: Reino Unido