Samantha Danielle Minc1, Brian Hendricks2, Ranjita Misra3, Yue Ren4, Dylan Thibault4, Luke Marone4, Gordon Stephen Smith2. 1. Division of Vascular and Endovascular Surgery, West Virginia University School of Medicine, Morgantown, WV. Electronic address: samantha.minc@wvumedicine.org. 2. Department of Epidemiology, West Virginia University School of Public Health, Morgantown, WV. 3. Department of Social and Behavioral Sciences, West Virginia University School of Public Health, Morgantown, WV. 4. Division of Vascular and Endovascular Surgery, West Virginia University School of Medicine, Morgantown, WV.
Abstract
OBJECTIVE: Amputation is a devastating but preventable complication of diabetes and peripheral arterial disease (PAD). Multiple studies have focused on disparities in amputation rates based on race and socioeconomic status, but few focus on amputation trends in rural populations. The objective of this study was to identify the prevalence of major and minor amputation among patients admitted with diabetes and/or PAD in a rural, Appalachian state, and to identify geographic areas with higher than expected major and minor amputations using advanced spatial analysis while controlling for comorbidities and rurality. METHODS: Patient hospital admissions of West Virginia residents with diagnoses of diabetes and/or PAD and with or without an amputation procedure were identified from the West Virginia Health Care Authority State Inpatient Database from 2011 to 2016 using relevant International Classification of Diseases, 9th edition and 10the edition codes. Bayesian spatial hierarchical modeling was conducted to identify areas of high risk, while controlling for important confounders for amputation. RESULTS: Overall, there were 5557 amputations among 459,452 hospital admissions with diabetes and/or PAD from 2011 to 2016. The majority of the amputations were minor (61.7%; n = 3430), with a prevalence of 7.5 per 1000 and 40.4% (n = 2248) were major, with a prevalence of 4.9 per 1000. Geographic analysis found significant variation in risk for both major and minor amputation across the state, even after adjusting for the prevalence of risk factors. Analyses indicated an increased risk of amputation in the central and northeastern regions of West Virginia at the county level, although zip code-level patterns of amputation varied, with high-risk areas identified primarily in the northeastern and south central regions of the state. CONCLUSIONS: There is significant geographic variation in risk of amputation across West Virginia, even after adjusting for disease-related risk factors, suggesting priority areas for further investigation. The level of granularity obtained using advanced spatial analyses rather than traditional methods demonstrate the value of this approach, particularly when risk estimates are used to inform policy or public health intervention.
OBJECTIVE: Amputation is a devastating but preventable complication of diabetes and peripheral arterial disease (PAD). Multiple studies have focused on disparities in amputation rates based on race and socioeconomic status, but few focus on amputation trends in rural populations. The objective of this study was to identify the prevalence of major and minor amputation among patients admitted with diabetes and/or PAD in a rural, Appalachian state, and to identify geographic areas with higher than expected major and minor amputations using advanced spatial analysis while controlling for comorbidities and rurality. METHODS:Patient hospital admissions of West Virginia residents with diagnoses of diabetes and/or PAD and with or without an amputation procedure were identified from the West Virginia Health Care Authority State Inpatient Database from 2011 to 2016 using relevant International Classification of Diseases, 9th edition and 10the edition codes. Bayesian spatial hierarchical modeling was conducted to identify areas of high risk, while controlling for important confounders for amputation. RESULTS: Overall, there were 5557 amputations among 459,452 hospital admissions with diabetes and/or PAD from 2011 to 2016. The majority of the amputations were minor (61.7%; n = 3430), with a prevalence of 7.5 per 1000 and 40.4% (n = 2248) were major, with a prevalence of 4.9 per 1000. Geographic analysis found significant variation in risk for both major and minor amputation across the state, even after adjusting for the prevalence of risk factors. Analyses indicated an increased risk of amputation in the central and northeastern regions of West Virginia at the county level, although zip code-level patterns of amputation varied, with high-risk areas identified primarily in the northeastern and south central regions of the state. CONCLUSIONS: There is significant geographic variation in risk of amputation across West Virginia, even after adjusting for disease-related risk factors, suggesting priority areas for further investigation. The level of granularity obtained using advanced spatial analyses rather than traditional methods demonstrate the value of this approach, particularly when risk estimates are used to inform policy or public health intervention.
Authors: Jenine K Harris; Kate Beatty; J P Leider; Alana Knudson; Britta L Anderson; Michael Meit Journal: Annu Rev Public Health Date: 2016-01-06 Impact factor: 21.981
Authors: Chin-Lin Tseng; Drew Helmer; Mangala Rajan; Anjali Tiwari; Donald Miller; Stephen Crystal; Monika Safford; Jeffrey Greenberg; Leonard Pogach Journal: Int J Qual Health Care Date: 2007-10-18 Impact factor: 2.038
Authors: Carl D Stevens; David L Schriger; Brian Raffetto; Anna C Davis; David Zingmond; Dylan H Roby Journal: Health Aff (Millwood) Date: 2014-08 Impact factor: 6.301
Authors: Brian M Schmidt; James S Wrobel; Michael Munson; Gary Rothenberg; Crystal M Holmes Journal: Diabetes Res Clin Pract Date: 2017-02-21 Impact factor: 5.602
Authors: W Schuyler Jones; Manesh R Patel; David Dai; Sumeet Subherwal; Judith Stafford; Sarah Calhoun; Eric D Peterson Journal: J Am Coll Cardiol Date: 2012-10-24 Impact factor: 24.094
Authors: David J Margolis; Ole Hoffstad; Jeffrey Nafash; Charles E Leonard; Cristin P Freeman; Sean Hennessy; Douglas J Wiebe Journal: Diabetes Care Date: 2011-09-20 Impact factor: 19.112
Authors: Samantha Danielle Minc; Stevan Budi; Dylan Thibault; Ranjita Misra; David G Armstrong; Gordon Stephen Smith; Luke Marone Journal: Prev Med Rep Date: 2021-07-23
Authors: Abdulmajeed Altoijry; Hesham AlGhofili; Shahad N Alanazi; Dania A AlHindawi; Norah S AlAkeel; Bedoor S Julaidan; Musaad AlHamzah; Talal Altuwaijri Journal: Saudi Med J Date: 2021-01 Impact factor: 1.484
Authors: Brian Witrick; Corey A Kalbaugh; Lu Shi; Rachel Mayo; Brian Hendricks Journal: Int J Environ Res Public Health Date: 2021-12-28 Impact factor: 3.390
Authors: Jose M Pereira de Godoy; Germano Giroldo Tazinaffo; Barbara Lasmine Gomes Abreu Christo; Maria de Fátima Guerreiro Godoy Journal: Arch Med Sci Atheroscler Dis Date: 2021-12-07