Inflammatory Markers and Poor Outcome after Stroke: A Prospective Cohort Study and Systematic Review of Interleukin-6
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{"title"=>"Inflammatory markers and poor outcome after stroke: A prospective cohort study and systematic review of interleukin-6", "type"=>"journal", "authors"=>[{"first_name"=>"William", "last_name"=>"Whiteley", "scopus_author_id"=>"6603833551"}, {"first_name"=>"Caroline", "last_name"=>"Jackson", "scopus_author_id"=>"55057753300"}, {"first_name"=>"Steff", "last_name"=>"Lewis", "scopus_author_id"=>"7404041358"}, {"first_name"=>"Gordon", "last_name"=>"Lowe", "scopus_author_id"=>"56678958000"}, {"first_name"=>"Ann", "last_name"=>"Rumley", "scopus_author_id"=>"7006433197"}, {"first_name"=>"Peter", "last_name"=>"Sandercock", "scopus_author_id"=>"7102712686"}, {"first_name"=>"Joanna", "last_name"=>"Wardlaw", "scopus_author_id"=>"35417533500"}, {"first_name"=>"Martin", "last_name"=>"Dennis", "scopus_author_id"=>"7202799006"}, {"first_name"=>"Cathie", "last_name"=>"Sudlow", "scopus_author_id"=>"7004552277"}], "year"=>2009, "source"=>"PLoS Medicine", "identifiers"=>{"pmid"=>"19901973", "doi"=>"10.1371/journal.pmed.1000145", "sgr"=>"70349636710", "isbn"=>"1549-1676", "scopus"=>"2-s2.0-70349636710", "issn"=>"15491277", "pui"=>"355369599"}, "id"=>"6fe2371b-637c-311c-9d04-5f796d947951", "abstract"=>"BACKGROUND: The objective of this study was to determine whether: (a) markers of acute inflammation (white cell count, glucose, interleukin-6, C-reactive protein, and fibrinogen) are associated with poor outcome after stroke and (b) the addition of markers to previously validated prognostic models improves prediction of poor outcome.\\n\\nMETHODS AND FINDINGS: We prospectively recruited patients between 2002 and 2005. Clinicians assessed patients and drew blood for inflammatory markers. Patients were followed up by postal questionnaire for poor outcome (a score of>2 on the modified Rankin Scale) and death through the General Register Office (Scotland) at 6 mo. We performed a systematic review of the literature and meta-analysis of the association between interleukin-6 and poor outcome after stroke to place our study in the context of previous research. We recruited 844 patients; mortality data were available in 844 (100%) and functional outcome in 750 (89%). After appropriate adjustment, the odds ratios for the association of markers and poor outcome (comparing the upper and the lower third) were interleukin-6, 3.1 (95% CI: 1.9-5.0); C-reactive protein, 1.9 (95% CI: 1.2-3.1); fibrinogen, 1.5 (95% CI: 1.0-2.36); white cell count, 2.1 (95% CI: 1.3-3.4); and glucose 1.3 (95% CI: 0.8-2.1). The results for interleukin-6 were similar to other studies. However, the addition of inflammatory marker levels to validated prognostic models did not materially improve model discrimination, calibration, or reclassification for prediction of poor outcome after stroke.\\n\\nCONCLUSIONS: Raised levels of markers of the acute inflammatory response after stroke are associated with poor outcomes. However, the addition of these markers to a previously validated stroke prognostic model did not improve the prediction of poor outcome. Whether inflammatory markers are useful in prediction of recurrent stroke or other vascular events is a separate question, which requires further study. Please see later in the article for the Editors' Summary.", "link"=>"http://www.mendeley.com/research/inflammatory-markers-poor-outcome-after-stroke-prospective-cohort-study-systematic-review-interleuki-10", "reader_count"=>47, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>3, "Researcher"=>9, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>5, "Other"=>9, "Student > Master"=>7, "Student > Bachelor"=>4, "Lecturer"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>3, "Researcher"=>9, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>5, "Other"=>9, "Student > Master"=>7, "Student > Bachelor"=>4, "Lecturer"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Nursing and Health Professions"=>1, "Mathematics"=>2, "Medicine and Dentistry"=>25, "Agricultural and Biological Sciences"=>9, "Neuroscience"=>4, "Psychology"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>25}, "Neuroscience"=>{"Neuroscience"=>4}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>4}}, "reader_count_by_country"=>{"Japan"=>1, "United Kingdom"=>3, "Germany"=>1}, "group_count"=>5}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/885038"], "description"=>"<p>OR for death or poor outcome is presented per unit increase in marker levels. Sizes of squares are proportional to the number of patients in each study. Summary estimates are calculated by fixed effects meta-analysis. The <i>p</i> values show statistical significance of summary estimate of effect, and I<sup>2</sup> is reported as a measure of heterogeneity between studies used to calculate the summary OR. + = adjusted for age or stroke severity; ++ = adjusted for age and stroke severity; +++ = adjusted for age, stroke severity, and other factors.</p>", "links"=>[], "tags"=>["meta-analysis", "studies", "il-6"], "article_id"=>555489, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.g004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Systematic_review_and_meta_analysis_of_studies_of_IL_6_with_available_data_/555489", "title"=>"Systematic review and meta-analysis of studies of IL-6 with available data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-09-08 01:31:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/885204"], "description"=>"<p>All studies were prospective, inpatient-based studies of patients with ischaemic stroke and drew blood soon after stroke. No previous study examined unselected admissions of patients with stroke.</p><p>IL-18, interleukin-18; TNF, tumour necrosis factor alpha; GABA, gamma-amino-butyric acid; SBP, systolic blood pressure; HBP, high blood pressure; CSS, Canadian stroke scale; SSS, Scandinavian stroke scale.</p>", "links"=>[], "tags"=>["studies", "included", "systematic"], "article_id"=>555657, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.t005", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Table_of_studies_included_in_the_systematic_review_/555657", "title"=>"Table of studies included in the systematic review.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-09-08 01:34:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/884695"], "description"=>"<p><sup>a</sup>Results are incomplete for glucose and white cell count, as for outpatients these results were sometimes reported to the general practice rather than the central results database.</p>", "links"=>[], "tags"=>["evidence-based healthcare/clinical decision-making", "neurological disorders/cerebrovascular disease"], "article_id"=>555146, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.g001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flowchart_of_data_available_in_the_study_/555146", "title"=>"Flowchart of data available in the study.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-09-08 01:25:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/884950"], "description"=>"<p>Each OR is adjusted for the six simple variables (age, living alone, independent of activities of daily living prior to stroke, normal verbal GCS, able to lift arms from bed, able to walk), and the estimate for the whole cohort is given by the vertical dashed line. OR of>1 indicates that increased levels of marker are associated with poorer outcome in that category of patient. The <i>p</i> values are derived from tests for heterogeneity. LACS, lacunar stroke syndrome; PACS, partial anterior strokesyndrome; POCS, posterior circulation stroke syndrome; TACS,total anterior stroke syndrome.</p>", "links"=>[], "tags"=>["il-6"], "article_id"=>555403, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.g003", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_upper_third_and_lower_third_of_IL_6_by_subgroups_/555403", "title"=>"Association between upper third and lower third of IL-6 by subgroups.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-09-08 01:30:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/438502"], "description"=>"<div><h3>Background</h3><p>The objective of this study was to determine whether: (a) markers of acute inflammation (white cell count, glucose, interleukin-6, C-reactive protein, and fibrinogen) are associated with poor outcome after stroke and (b) the addition of markers to previously validated prognostic models improves prediction of poor outcome.</p><h3>Methods and Findings</h3><p>We prospectively recruited patients between 2002 and 2005. Clinicians assessed patients and drew blood for inflammatory markers. Patients were followed up by postal questionnaire for poor outcome (a score of>2 on the modified Rankin Scale) and death through the General Register Office (Scotland) at 6 mo. We performed a systematic review of the literature and meta-analysis of the association between interleukin-6 and poor outcome after stroke to place our study in the context of previous research. We recruited 844 patients; mortality data were available in 844 (100%) and functional outcome in 750 (89%). After appropriate adjustment, the odds ratios for the association of markers and poor outcome (comparing the upper and the lower third) were interleukin-6, 3.1 (95% CI: 1.9–5.0); C-reactive protein, 1.9 (95% CI: 1.2–3.1); fibrinogen, 1.5 (95% CI: 1.0–2.36); white cell count, 2.1 (95% CI: 1.3–3.4); and glucose 1.3 (95% CI: 0.8–2.1). The results for interleukin-6 were similar to other studies. However, the addition of inflammatory marker levels to validated prognostic models did not materially improve model discrimination, calibration, or reclassification for prediction of poor outcome after stroke.</p><h3>Conclusions</h3><p>Raised levels of markers of the acute inflammatory response after stroke are associated with poor outcomes. However, the addition of these markers to a previously validated stroke prognostic model did not improve the prediction of poor outcome. Whether inflammatory markers are useful in prediction of recurrent stroke or other vascular events is a separate question, which requires further study.</p><h3></h3><p><em>Please see later in the article for the Editors' Summary</em></p></div>", "links"=>[], "tags"=>["inflammatory", "markers", "prospective", "cohort", "systematic", "interleukin-6"], "article_id"=>146460, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145", "stats"=>{"downloads"=>21, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Inflammatory_Markers_and_Poor_Outcome_after_Stroke_A_Prospective_Cohort_Study_and_Systematic_Review_of_Interleukin_6/146460", "title"=>"Inflammatory Markers and Poor Outcome after Stroke: A Prospective Cohort Study and Systematic Review of Interleukin-6", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-09-08 01:47:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/884808"], "description"=>"<p>Expressed as ratio of odds in middle and top thirds of marker distribution, versus the referent lower third. Dotted line indicates OR = 1 (i.e., same odds as lower third). ORs are reported unadjusted and adjusted for six simple variables (age, living alone, independent of activities of daily living prior to stroke, normal verbal Glasgow coma scale, able to lift arms from bed, able to walk). Tertiles of IL-6: 2.8 and 5.5 pg/l; CRP: 1.9 and 7.1 mg/l; fibrinogen: 4.1 and 5.1 g/l; white cell count: 7.0 and 9.1×10<sup>9</sup> cells/l; and glucose: 5.2 and 6.3 mmol/l.</p>", "links"=>[], "tags"=>["levels", "inflammatory"], "article_id"=>555260, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_levels_of_inflammatory_marker_versus_poor_outcome_mRS_gt_2_or_death_/555260", "title"=>"Association between levels of inflammatory marker versus poor outcome (mRS>2 or death).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-09-08 01:27:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/885255"], "description"=>"<p>Risk stratification tables to assess the clinical significance of added predictive value of IL-6 to the six simple variable model.</p>", "links"=>[], "tags"=>["stratification", "tables", "predictive", "il-6"], "article_id"=>555702, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.t004", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Risk_stratification_tables_to_assess_the_clinical_significance_of_added_predictive_value_of_IL_6_to_the_six_simple_variable_model_/555702", "title"=>"Risk stratification tables to assess the clinical significance of added predictive value of IL-6 to the six simple variable model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-09-08 01:35:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/885365"], "description"=>"a<p>Previous diabetes, history of cardiovascular disease, history of peripheral vascular disease, history of cardiac failure, history of hypertension, current or history of atrial fibrillation.</p>", "links"=>[], "tags"=>["levels"], "article_id"=>555817, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.t002", "stats"=>{"downloads"=>6, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_association_between_marker_levels_and_poor_outcome_after_stroke_/555817", "title"=>"The association between marker levels and poor outcome after stroke.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-09-08 01:36:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/885322"], "description"=>"<p>Performance of six simple variables model (age, living alone, independent of activities of daily living prior to stroke, normal verbal GCS, able to lift arms from bed, able to walk) and addition of IL-6, CRP, and white cell count as continuous variables.</p>a<p>The likelihood ratio test compares a goodness of fit between models with and without biomarker data. <i>p</i><0.05 indicates that the model with biomarkers gives a significantly better fit of the data.</p>b<p>The Hosmer Lemeshow test compares the observed number of people with events to that predicted by the model. <i>p</i>>0.05 indicates that the model is well calibrated.</p>c<p>AUC = 1 indicates perfect discrimination of a model between patients with good and bad outcomes. <i>p</i><0.05 indicates that the model containing biomarkers has a significantly higher AUC than one without.</p>", "links"=>[], "tags"=>["models"], "article_id"=>555772, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.t003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_models_to_predict_poor_outcome_after_stroke_/555772", "title"=>"Performance of models to predict poor outcome after stroke.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-09-08 01:36:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/885290"], "description"=>"a<p><i>t</i>-test.</p>b<p>χ<sup>2</sup> test.</p>c<p>National Institute of Health Stroke Scale.</p>d<p>482 good outcome and 224 poor outcome strokes.</p>e<p>Wilcoxon rank sum test.</p>f<p>496 good outcome and 233 poor outcome strokes.</p>g<p>471 good outcome and 218 poor outcome strokes.</p>h<p>The sixth variable in this model is age.</p>", "links"=>[], "tags"=>["characteristics", "biomarker", "cohort"], "article_id"=>555741, "categories"=>["Neuroscience", "Medicine"], "users"=>["William Whiteley", "Caroline Jackson", "Steff Lewis", "Gordon Lowe", "Ann Rumley", "Peter Sandercock", "Joanna Wardlaw", "Martin Dennis", "Cathie Sudlow"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1000145.t001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Baseline_characteristics_of_biomarker_cohort_and_their_association_with_death_and_poor_outcome_/555741", "title"=>"Baseline characteristics of biomarker cohort and their association with death and poor outcome.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2009-09-08 01:35:41"}

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  • {"unique-ip"=>"11", "full-text"=>"13", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
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  • {"unique-ip"=>"11", "full-text"=>"12", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
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  • {"unique-ip"=>"19", "full-text"=>"21", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"21", "full-text"=>"22", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"18", "full-text"=>"21", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
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  • {"unique-ip"=>"18", "full-text"=>"23", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
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  • {"unique-ip"=>"25", "full-text"=>"40", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"22", "full-text"=>"25", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"13", "full-text"=>"12", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"18", "full-text"=>"17", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
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Relative Metric

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