Chantelle Chapman1, Prue Morgan1, Dominique A Cadilhac2,3, Tara Purvis2, Nadine E Andrew2,4. 1. a Department of Physiotherapy , Monash University , Melbourne , Australia. 2. b Stroke & Ageing Research, School of Clinical Sciences at Monash Health , Monash University , Clayton , Australia. 3. c Florey Institute of Neurosciences and Mental Health , Heidelberg , Australia. 4. d Peninsula Clinical School , Monash University , Clayton , Australia.
Abstract
BACKGROUND: Chest infections occur in approximately one-third of patients following acute stroke, and are associated with poor outcomes. Limitations in previous reviews restricted the accuracy of results. OBJECTIVES: To perform a systematic review to reliably identify modifiable risk factors for chest infections following acute stroke. METHODS: Ovid Medline, CINAHL, Cochrane, EMBASE and AMED were searched from 1946 to April 2017 for observational studies where risk factors for chest infections in patients hospitalized with acute stroke were reported. Key words used to identify included chest infection or pneumonia. Included studies were evaluated based on methodological criteria and scientific quality. Results were collated and separate meta-analyses were performed for risk factors examined in three or more studies where quality and homogeneity criteria were met. RESULTS: 3172 studies were identified, 15 were eligible for inclusion. Data collection methods included primary data collection, medical record audit and registry data. Chest infections were diagnosed 2-30 days following acute stroke in ten studies. Of the 39 risk factors identified, four were included in the meta-analysis. These were mechanical ventilation: 4 studies, OR: 3.83, 95%CI: 3.21, 4.57; diabetes: 4 studies, OR: 1.06, 95%CI: 1.04, 1.08; pre-existing respiratory conditions: 3 studies, OR: 1.48, 95%CI 1.21, 1.81 and atrial fibrillation: 3 studies, OR: 1.21, 95%CI: 1.17, 1.24. Common risk factors not eligible for meta-analysis were dysphagia and cardiac comorbidities. CONCLUSION: Evidence has been comprehensively synthesized to provide reliable estimates of the association between important risk factors and chest infection. Monitoring patients meeting these criteria may promote early identification and treatment to improve long-term outcomes.
BACKGROUND:Chest infections occur in approximately one-third of patients following acute stroke, and are associated with poor outcomes. Limitations in previous reviews restricted the accuracy of results. OBJECTIVES: To perform a systematic review to reliably identify modifiable risk factors for chest infections following acute stroke. METHODS: Ovid Medline, CINAHL, Cochrane, EMBASE and AMED were searched from 1946 to April 2017 for observational studies where risk factors for chest infections in patients hospitalized with acute stroke were reported. Key words used to identify included chest infection or pneumonia. Included studies were evaluated based on methodological criteria and scientific quality. Results were collated and separate meta-analyses were performed for risk factors examined in three or more studies where quality and homogeneity criteria were met. RESULTS: 3172 studies were identified, 15 were eligible for inclusion. Data collection methods included primary data collection, medical record audit and registry data. Chest infections were diagnosed 2-30 days following acute stroke in ten studies. Of the 39 risk factors identified, four were included in the meta-analysis. These were mechanical ventilation: 4 studies, OR: 3.83, 95%CI: 3.21, 4.57; diabetes: 4 studies, OR: 1.06, 95%CI: 1.04, 1.08; pre-existing respiratory conditions: 3 studies, OR: 1.48, 95%CI 1.21, 1.81 and atrial fibrillation: 3 studies, OR: 1.21, 95%CI: 1.17, 1.24. Common risk factors not eligible for meta-analysis were dysphagia and cardiac comorbidities. CONCLUSION: Evidence has been comprehensively synthesized to provide reliable estimates of the association between important risk factors and chest infection. Monitoring patients meeting these criteria may promote early identification and treatment to improve long-term outcomes.
Authors: Shu Wen Wen; Raymond Shim; Luke Ho; Brooke J Wanrooy; Yogitha N Srikhanta; Kathryn Prame Kumar; Alyce J Nicholls; S J Shen; Tara Sepehrizadeh; Michael de Veer; Velandai K Srikanth; Henry Ma; Thanh G Phan; Dena Lyras; Connie H Y Wong Journal: Aging Cell Date: 2019-06-14 Impact factor: 9.304
Authors: Fabrizio Racca; Andrea Vianello; Tiziana Mongini; Paolo Ruggeri; Antonio Versaci; Gian Luca Vita; Giuseppe Vita Journal: Neurol Sci Date: 2019-12-02 Impact factor: 3.307