Combined Value of Red Blood Cell Distribution Width and Global Registry of Acute Coronary Events Risk Score for Predicting Cardiovascular Events in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention
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{"title"=>"Combined value of red blood cell distribution width and global registry of acute coronary events risk score for predicting cardiovascular events in patients with acute coronary syndrome undergoing percutaneous coronary intervention", "type"=>"journal", "authors"=>[{"first_name"=>"Na", "last_name"=>"Zhao", "scopus_author_id"=>"16687220100"}, {"first_name"=>"Lan", "last_name"=>"Mi", "scopus_author_id"=>"56783796500"}, {"first_name"=>"Xiaojun", "last_name"=>"Liu", "scopus_author_id"=>"55313332000"}, {"first_name"=>"Shuo", "last_name"=>"Pan", "scopus_author_id"=>"55577476900"}, {"first_name"=>"Jiaojiao", "last_name"=>"Xu", "scopus_author_id"=>"57191056336"}, {"first_name"=>"Dongyu", "last_name"=>"Xia", "scopus_author_id"=>"56988549400"}, {"first_name"=>"Zhongwei", "last_name"=>"Liu", "scopus_author_id"=>"55802089100"}, {"first_name"=>"Yong", "last_name"=>"Zhang", "scopus_author_id"=>"56719403500"}, {"first_name"=>"Yu", "last_name"=>"Xiang", "scopus_author_id"=>"57198411509"}, {"first_name"=>"Zuyi", "last_name"=>"Yuan", "scopus_author_id"=>"7401477144"}, {"first_name"=>"Gongchang", "last_name"=>"Guan", "scopus_author_id"=>"56464757300"}, {"first_name"=>"Junkui", "last_name"=>"Wang", "scopus_author_id"=>"55991384100"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"doi"=>"10.1371/journal.pone.0140532", "issn"=>"19326203", "pui"=>"607111660", "pmid"=>"26468876", "sgr"=>"84948947768", "scopus"=>"2-s2.0-84948947768"}, "id"=>"56770570-6db0-3e9c-9037-01d71e7dc22a", "abstract"=>"Global Registry of Acute Coronary Events (GRACE) risk score and red blood cell distribution width (RDW) content can both independently predict major adverse cardiac events (MACEs) in patients with acute coronary syndrome (ACS). We investigated the combined predictive value of RDW and GRACE risk score for cardiovascular events in patients with ACS undergoing percutaneous coronary intervention (PCI) for the first time. We enrolled 480 ACS patients. During a median follow-up time of 37.2 months, 70 (14.58%) patients experienced MACEs. Patients were divided into tertiles according to the baseline RDW content (11.30-12.90, 13.00-13.50, 13.60-16.40). GRACE score was positively correlated with RDW content. Multivariate Cox analysis showed that both GRACE score and RDW content were independent predictors of MACEs (hazard ratio 1.039; 95% confidence interval [CI] 1.024-1.055; p < 0.001; 1.699; 1.294-2.232; p < 0.001; respectively). Furthermore, Kaplan-Meier analysis demonstrated that the risk of MACEs increased with increasing RDW content (p < 0.001). For GRACE score alone, the area under the receiver operating characteristic (ROC) curve for MACEs was 0.749 (95% CI: 0.707-0.787). The area under the ROC curve for MACEs increased to 0.805 (0.766-0.839, p = 0.034) after adding RDW content. The incremental predictive value of combining RDW content and GRACE risk score was significantly improved, also shown by the net reclassification improvement (NRI = 0.352, p < 0.001) and integrated discrimination improvement (IDI = 0.023, p = 0.002). Combining the predictive value of RDW and GRACE risk score yielded a more accurate predictive value for long-term cardiovascular events in ACS patients who underwent PCI as compared to each measure alone.", "link"=>"http://www.mendeley.com/research/combined-value-red-blood-cell-distribution-width-global-registry-acute-coronary-events-risk-score-pr-1", "reader_count"=>2, "reader_count_by_academic_status"=>{"Student > Ph. D. Student"=>1, "Student > Bachelor"=>1}, "reader_count_by_user_role"=>{"Student > Ph. D. Student"=>1, "Student > Bachelor"=>1}, "reader_count_by_subject_area"=>{"Medicine and Dentistry"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2361475"], "description"=>"<p>The 480 patients of 70 had a MACE were divided by tertiles based on the RDW (tertile 1: 11.30–12.90, tertile 2: 13.00–13.50, and tertile 3: 13.60–16.40). The risk of MACE increased along with increasing RDW (p < 0.001).</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576917, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.g001", "stats"=>{"downloads"=>1, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kaplan_8211_Meier_analysis_of_major_adverse_cardiac_events_based_on_red_blood_cell_distribution_width_/1576917", "title"=>"Kaplan–Meier analysis of major adverse cardiac events based on red blood cell distribution width.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-10-15 03:22:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/2361477"], "description"=>"<p>For GRACE score alone, the area under the curve (AUC) was 0.749 (95% CI: 0.707–0.787). When RDW was added to GRACE score, the AUC was 0.805 (95% CI: 0.766–0.839, p = 0.034).</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576919, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.g002", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Receiver_operating_characteristic_ROC_curve_analysis_for_predicting_cardiovascular_events_/1576919", "title"=>"Receiver operating characteristic (ROC) curve analysis for predicting cardiovascular events.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-10-15 03:22:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/2361478"], "description"=>"<p>Data are presented as mean ± SD or n (%). ACEI, angiotensin-converting enzyme inhibitor; ACS, acute coronary syndrome; ARB, angiotensin-receptor blocker; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FBG, fasting blood glucose; HbA1c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol; HGB, hemoglobin; LDL-C, low-density lipoprotein cholesterol; LPA, lipoprotein(a); LVEF, left ventricular ejection fraction; MCV, mean corpuscular volume; MCHC, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; NSTEMI, non-ST elevation myocardial infarction; NT-proBNP, N-terminal pro–B-type natriuretic peptide; PLT, platelets; RBC, red blood cell count; STEMI, ST elevation myocardial infarction; TC, total cholesterol; TG, triglycerides; WBC, white blood cell count.</p><p>Baseline characteristics of 480 patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) according to the RDW content tertiles.</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576920, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.t001", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Baseline_characteristics_of_480_patients_with_acute_coronary_syndrome_ACS_undergoing_percutaneous_coronary_intervention_PCI_according_to_the_RDW_content_tertiles_/1576920", "title"=>"Baseline characteristics of 480 patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI) according to the RDW content tertiles.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-10-15 03:22:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/2361479"], "description"=>"<p>Data are expressed as mean ± SD or n (%). GRACE, Global Registry of Acute Coronary Events, RDW, red blood cell distribution width.</p><p>Characteristics of acute coronary syndrome patients undergoing percutaneous intervention (PCI) with or without a major adverse cardiac event (MACE).</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576921, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.t002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_acute_coronary_syndrome_patients_undergoing_percutaneous_intervention_PCI_with_or_without_a_major_adverse_cardiac_event_MACE_/1576921", "title"=>"Characteristics of acute coronary syndrome patients undergoing percutaneous intervention (PCI) with or without a major adverse cardiac event (MACE).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-10-15 03:22:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/2361480"], "description"=>"<p>HR, hazard ratio; CI, confidence interval.</p><p>Univariate Cox analysis for major adverse cardiovascular events.</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576922, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.t003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Univariate_Cox_analysis_for_major_adverse_cardiovascular_events_/1576922", "title"=>"Univariate Cox analysis for major adverse cardiovascular events.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-10-15 03:22:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/2361481"], "description"=>"<p>Multivariate Cox analysis for major adverse cardiovascular events.</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576923, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.t004", "stats"=>{"downloads"=>8, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Multivariate_Cox_analysis_for_major_adverse_cardiovascular_events_/1576923", "title"=>"Multivariate Cox analysis for major adverse cardiovascular events.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-10-15 03:22:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/2361483"], "description"=>"<p>NRI, Net Reclassification Improvement; IDI, Integrated Discrimination Improvement</p><p>Discrimination of model in predicting major adverse cardiovascular events (MACE).</p>", "links"=>[], "tags"=>["480 ACS patients", "GRACE score", "multivariate Cox analysis", "blood cell distribution width", "pci", "roc", "Red Blood Cell Distribution Width", "mace", "Acute Coronary Events", "idi", "ci", "GRACE risk score", "Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention Global Registry", "RDW content", "Acute Coronary Events Risk", "nri"], "article_id"=>1576925, "categories"=>["Biological Sciences"], "users"=>["Na Zhao", "Lan Mi", "Xiaojun Liu", "Shuo Pan", "Jiaojiao Xu", "Dongyu Xia", "Zhongwei Liu", "Yong Zhang", "Yu Xiang", "Zuyi Yuan", "Gongchang Guan", "Junkui Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0140532.t005", "stats"=>{"downloads"=>1, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Discrimination_of_model_in_predicting_major_adverse_cardiovascular_events_MACE_/1576925", "title"=>"Discrimination of model in predicting major adverse cardiovascular events (MACE).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-10-15 03:22:05"}

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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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