A prognostic nomogram incorporating red cell distribution width for patients with intracerebral hemorrhage.

Szczegóły
Abstrakt

Tytuł:: A prognostic nomogram incorporating red cell distribution width for patients with intracerebral hemorrhage.
Autorzy:: Cui Z; Division of Hematology and Transfusion Medicine, Department of Laboratory Medicine, Tianjin Baodi Hospital, Tianjin Baodi Affiliated Hospital of Tianjin Medical University, Baodi District, Tianjin.
Liu C; Division of Hematology and Transfusion Medicine, Department of Laboratory Medicine, Tianjin Baodi Hospital, Tianjin Baodi Affiliated Hospital of Tianjin Medical University, Baodi District, Tianjin.
Sun G; Division of Hematology and Transfusion Medicine, Department of Laboratory Medicine, Tianjin Baodi Hospital, Tianjin Baodi Affiliated Hospital of Tianjin Medical University, Baodi District, Tianjin.
Huang L; Department of Oncology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province.
Zhou W; Department of Emergency Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Yuexiu District, Guangzhou, China.
Źródło:: Medicine [Medicine (Baltimore)] 2020 Dec 11; Vol. 99 (50), pp. e23557.
Typ publikacji:: Journal Article
Język:: English
Imprint Name(s):: Original Publication: Hagerstown, Md : Lippincott Williams & Wilkins
MeSH Terms:: Erythrocyte Indices*
Nomograms*
Cerebral Hemorrhage/*diagnosis
Erythrocytes/*pathology
Aged ; Biomarkers/blood ; Cerebral Hemorrhage/mortality ; Cerebral Hemorrhage/pathology ; Female ; Glasgow Coma Scale ; Humans ; Male ; Middle Aged ; Prognosis ; ROC Curve ; Retrospective Studies ; Survival Analysis
References:: Ann Clin Biochem. 2017 Nov;54(6):696-701. (PMID: 27932670)
J Clin Neurosci. 2014 Jan;21(1):91-4. (PMID: 24090518)
J Trauma. 2003 Apr;54(4):671-8; discussion 678-80. (PMID: 12707528)
J Thromb Haemost. 2012 Apr;10(4):596-605. (PMID: 22257107)
Arch Pathol Lab Med. 2009 Apr;133(4):628-32. (PMID: 19391664)
Coron Artery Dis. 2011 May;22(3):138-44. (PMID: 21233710)
Stroke. 2001 Apr;32(4):891-7. (PMID: 11283388)
Stroke. 2005 Jun;36(6):1120-2. (PMID: 15879325)
Thromb Haemost. 2012 Aug;108(2):349-56. (PMID: 22739700)
Stroke. 2010 May;41(5):992-5. (PMID: 20360551)
J Am Coll Cardiol. 2007 Jul 3;50(1):40-7. (PMID: 17601544)
J Thromb Thrombolysis. 2017 Apr;43(3):394-400. (PMID: 27838806)
Gut Liver. 2011 Dec;5(4):460-7. (PMID: 22195244)
Stroke. 1993 Jul;24(7):987-93. (PMID: 8322400)
AJNR Am J Neuroradiol. 2004 Feb;25(2):257-60. (PMID: 14970027)
Continuum (Minneap Minn). 2018 Dec;24(6):1603-1622. (PMID: 30516598)
Medicine (Baltimore). 2016 Jun;95(24):e3692. (PMID: 27310948)
Stroke. 2015 Jul;46(7):2032-60. (PMID: 26022637)
Arterioscler Thromb Vasc Biol. 2006 Apr;26(4):697-705. (PMID: 16424350)
Thromb Haemost. 2014 Feb;111(2):300-7. (PMID: 24173039)
J Neurol. 2004 Dec;251(12):1443-50. (PMID: 15645342)
Stroke. 2007 May;38(5):1641-4. (PMID: 17379820)
Blood. 2004 Oct 15;104(8):2565-73. (PMID: 15205258)
J Card Fail. 2010 Mar;16(3):230-8. (PMID: 20206898)
PLoS One. 2014 Jul 16;9(7):e102326. (PMID: 25029592)
Curr Atheroscler Rep. 2012 Aug;14(4):300-6. (PMID: 22538431)
Stroke. 2013 Jul;44(7):1840-5. (PMID: 23686981)
Nature. 2008 Jul 24;454(7203):436-44. (PMID: 18650914)
Turk Neurosurg. 2017;27(3):368-373. (PMID: 27593780)
Clin Hemorheol Microcirc. 2012;51(4):243-54. (PMID: 22277951)
J Neurosurg Anesthesiol. 2018 Oct;30(4):319-327. (PMID: 28991058)
Expert Rev Neurother. 2019 Jul;19(7):679-694. (PMID: 31188036)
Ann Emerg Med. 2011 Nov;58(5):427-30. (PMID: 21803447)
Crit Care. 2013 Dec 09;17(6):R282. (PMID: 24321201)
Sci Rep. 2017 Jun 2;7(1):2709. (PMID: 28578411)
Ecology. 2014 Mar;95(3):631-6. (PMID: 24804445)
Stroke. 2019 Mar;50(3):588-594. (PMID: 30732556)
Neurology. 2005 Feb 22;64(4):725-7. (PMID: 15728302)
Crit Care. 2011 Aug 11;15(4):R194. (PMID: 21835005)
Clin Chem Lab Med. 2009;47(3):353-7. (PMID: 19676148)
Crit Rev Clin Lab Sci. 2014 Oct;51(5):263-79. (PMID: 24918900)
Adv Exp Med Biol. 2013;765:211-216. (PMID: 22879035)
Stroke. 2008 Aug;39(8):2304-9. (PMID: 18556582)
PLoS One. 2013 Nov 11;8(11):e80240. (PMID: 24244659)
Crit Rev Clin Lab Sci. 2015;52(2):86-105. (PMID: 25535770)
Clin Appl Thromb Hemost. 2015 May;21(4):354-8. (PMID: 24085745)
Substance Nomenclature:: 0 (Biomarkers)
Entry Date(s):: Date Created: 20201217 Date Completed: 20210107 Latest Revision: 20221005
Update Code:: 20240105
PubMed Central ID:: PMC7738053
DOI:: 10.1097/MD.0000000000023557
PMID:: 33327308
: Czasopismo naukowe

Full Text Finder

Intracerebral hemorrhage (ICH) is the second most common subtype of stroke with higher mortality and morbidity, and it lacks effective prognostic markers. The aim of this research is to construct newly valuable prognostic nomogram incorporating red blood cell distribution width (RDW) for ICH patients.We retrospectively analyzed 953 adult patients with ICH. The impacts of RDW on short-term mortality and functional prognosis were calculated using Akaike information criterion (AIC), Bayesian information criteria (BIC) and the area under the curve (AUC) respectively, which could be used to compare with Glasgow coma scale (GCS) and ICH score. The independent factors of prognosis were identified by univariate and multivariate logistic regression analysis. A nomogram based on RDW for nerve functional prognosis was further constructed and validated. Its clinical value was subsequently explored utilizing decision curve analysis.Cumulative clinical results were retrieved for 235 inpatients from Jan 2012 to June 2017. In 30-day mortality sets, GCS and ICH score had better prognostic performance than RDW (AUC: 0.929 and 0.917 vs 0.764; AIC: 124.101 and 134.188 vs 221.372; BIC: 131.021 and 141.107 vs 228.291). In 30-day functional prognosis sets, the consequences of evaluation systems were inconsistent. GCS was the best parameter for predicting outcome using AIC (262.350 vs 276.392 and 264.756) and BIC (269.269 vs 283.311 and 271.675). However, RDW was higher than GCS and ICH score considering AUC (0.784 vs 0.759 and 0.722). Age, GCS, RDW, platelet distribution width, and surgery were independent prognostic factors by multivariate logistic regression analysis, and those coefficients were used to formulate a nomogram. This nomogram can provide accurate prediction with the concordance index of 0.880 (95% CI, 0.837-0.922) higher than Harrell's concordance index of GCS system 0.759 (95% CI, 0.698-0.819) and RDW 0.784 (95% CI, 0.721-0.847). The calibration plots showed optimal consistency between bootstrap-predicted and the actual observed values of 30-day unfavorable prognosis. Decision curve analysis showed an increased net benefit for utilizing the nomogram.High RDW values are associated with an unfavorable outcome after ICH. The established nomogram incorporating RDW should be considered for a 30-day functional prognosis.

Informacja