Fadar Oliver Otite1, Smit Patel2, Richa Sharma2, Pushti Khandwala2, Devashish Desai2, Julius Gene Latorre2, Emmanuel Oladele Akano2, Nnabuchi Anikpezie2, Saef Izzy2, Amer M Malik2, Dileep Yavagal2, Priyank Khandelwal2, Seemant Chaturvedi2. 1. From the Department of Neurology (F.O.O., J.G.L.), State University of New York Upstate Medical University, Syracuse; Department of Neurology (S.P.), University of Connecticut, Hartford; Department of Neurology (R.S.), Yale University, New Haven, CT; Department of Internal Medicine (P. Khandwala, D.D.), Crozier Chester Medical Center, Chester, PA; Molecular Neuropharmacology Unit (E.O.A.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Department of Healthcare Transformation Initiative (N.A.), University of Texas Health Science Center at Houston; Department of Neurology (S.I.), Brigham and Women's Hospital/Harvard Medical School, Boston, MA; Department of Neurology (A.M.M., D.Y.), University of Miami Miller School of Medicine, FL; Department of Neurology (P. Khandelwal), Rutgers New Jersey Medical School, Newark; and Department of Neurology (S.C.), University of Maryland, Baltimore. otitef@upstate.edu. 2. From the Department of Neurology (F.O.O., J.G.L.), State University of New York Upstate Medical University, Syracuse; Department of Neurology (S.P.), University of Connecticut, Hartford; Department of Neurology (R.S.), Yale University, New Haven, CT; Department of Internal Medicine (P. Khandwala, D.D.), Crozier Chester Medical Center, Chester, PA; Molecular Neuropharmacology Unit (E.O.A.), National Institute of Neurological Disorders and Stroke, Bethesda, MD; Department of Healthcare Transformation Initiative (N.A.), University of Texas Health Science Center at Houston; Department of Neurology (S.I.), Brigham and Women's Hospital/Harvard Medical School, Boston, MA; Department of Neurology (A.M.M., D.Y.), University of Miami Miller School of Medicine, FL; Department of Neurology (P. Khandelwal), Rutgers New Jersey Medical School, Newark; and Department of Neurology (S.C.), University of Maryland, Baltimore.
Abstract
OBJECTIVE: To test the hypothesis that race-, age-, and sex-specific incidence of cerebral venous thrombosis (CVT) has increased in the United States over the last decade. METHODS: In this retrospective cohort study, validated ICD codes were used to identify all new cases of CVT (n = 5,567) in the State Inpatients Databases (SIDs) of New York and Florida (2006-2016). A new CVT case was defined as first hospitalization for CVT in the SID without prior CVT hospitalization. CVT counts were combined with annual Census data to compute incidence. Joinpoint regression was used to evaluate trends in incidence over time. RESULTS: From 2006 to 2016, annual age- and sex-standardized incidence of CVT in cases per 1 million population ranged from 13.9 to 20.2, but incidence varied significantly by sex (women 20.3-26.9, men 6.8-16.8) and by age/sex (women 18-44 years of age 24.0-32.6, men 18-44 years of age 5.3-12.8). Incidence also differed by race (Blacks: 18.6-27.2; Whites: 14.3-18.5; Asians: 5.1-13.8). On joinpoint regression, incidence increased across 2006 to 2016, but most of this increase was driven by an increase in all age groups of men (combined annualized percentage change [APC] 9.2%, p < 0.001), women 45 to 64 years of age (APC 7.8%, p < 0.001), and women ≥65 years of age (APC 7.4%, p < 0.001). Incidence in women 18 to 44 years of age remained unchanged over time. CONCLUSION: CVT incidence is disproportionately higher in Blacks compared to other races. New CVT hospitalizations increased significantly over the last decade mainly in men and older women. Further studies are needed to determine whether this increase represents a true increase from changing risk factors or an artifactual increase from improved detection.
OBJECTIVE: To test the hypothesis that race-, age-, and sex-specific incidence of cerebral venous thrombosis (CVT) has increased in the United States over the last decade. METHODS: In this retrospective cohort study, validated ICD codes were used to identify all new cases of CVT (n = 5,567) in the State Inpatients Databases (SIDs) of New York and Florida (2006-2016). A new CVT case was defined as first hospitalization for CVT in the SID without prior CVT hospitalization. CVT counts were combined with annual Census data to compute incidence. Joinpoint regression was used to evaluate trends in incidence over time. RESULTS: From 2006 to 2016, annual age- and sex-standardized incidence of CVT in cases per 1 million population ranged from 13.9 to 20.2, but incidence varied significantly by sex (women 20.3-26.9, men 6.8-16.8) and by age/sex (women 18-44 years of age 24.0-32.6, men 18-44 years of age 5.3-12.8). Incidence also differed by race (Blacks: 18.6-27.2; Whites: 14.3-18.5; Asians: 5.1-13.8). On joinpoint regression, incidence increased across 2006 to 2016, but most of this increase was driven by an increase in all age groups of men (combined annualized percentage change [APC] 9.2%, p < 0.001), women 45 to 64 years of age (APC 7.8%, p < 0.001), and women ≥65 years of age (APC 7.4%, p < 0.001). Incidence in women 18 to 44 years of age remained unchanged over time. CONCLUSION: CVT incidence is disproportionately higher in Blacks compared to other races. New CVT hospitalizations increased significantly over the last decade mainly in men and older women. Further studies are needed to determine whether this increase represents a true increase from changing risk factors or an artifactual increase from improved detection.
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