Effects of Kidney Stone Prevention After ER intervention: Does rurality or comorbid conditions affect outcomes?

Effects of Kidney Stone Prevention After ER intervention: Does rurality or comorbid conditions affect outcomes? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of Kidney Stone Prevention After ER intervention: Does rurality or comorbid conditions affect outcomes? Stephen Summers, Zachary Pfeifer, Joshua Stern, Joshua John Horn This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4909679/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction and Objective: The incidence of kidney stones is rising, particularly among diabetic and obese populations. Limited access to urologic care in rural US areas may predispose these patients to increased kidney stone-related visits. This study aims to determine if rural residency and comorbid conditions affect kidney stone-related healthcare visits and the effectiveness of medical prophylaxis. Methods: Using Merative Marketscan data from 2008 to 2017, patients diagnosed with kidney or ureteral stones who underwent surgical intervention in emergency settings were identified. Patients were categorized by comorbidities, demographics, and rural vs. urban residency. Preventative treatments, including medication and 24-hour urine testing, were noted. All patients were followed for 365 days post initial encounter to track subsequent stone disease management and prevention encounters. Results: Out of 1,030,512 patients, 17% were rural residents. Post-initial stone events, 19% engaged in medical treatment. Treatment engagement led to a 16% reduction in stone-related ED visits the following year. Diabetic and obese patients not engaged in treatment had an 11% and 20% increased risk of subsequent stone-related ED visits, respectively. Engagement reduced the risk of subsequent stone events by 34% in diabetic patients and 24.5% in obese patients compared to their unengaged counterparts. Conclusions: Medical treatment engagement slightly reduced overall stone-related encounters and return rates in the general population, with a minor decrease in urban compared to rural populations. However, treatment engagement significantly lowered stone-related event rates in diabetic and obese patients, highlighting the need for focused and aggressive preventive medical treatment in these groups. Figures Figure 1 INTRODUCTION Nephrolithiasis is a common diagnosis which is increasing in incidence. Lifetime prevalence is estimated at 10–12% in men and 5–6% in women. 1, 2 Recent studies have shown relative increases in incidence as much as 36% in a 5 year period, 3 and other studies have also demonstrated an upward trend in incidence in several populations. 4, 5 Kidney stone disease results in increasing costs to the healthcare system through many routes including chronic kidney disease, repeated interventions for stone removal, and financial loss resulting from lost work days. Reports have estimated this cost to be $ 2.1 billion in 2000 6 which have likely only risen with increasing treatment costs and incidence. 7 Obesity and Diabetes are well established risk factors for stone formation 8 both with increasing incidence, 9 and may account for some of the increases previously mentioned. As the obesity epidemic continues, patients with metabolic syndrome will continue to be a rising proportion of our urologic practice. There is increased recognition that the metabolic syndrome and specifically diabetes can increase one’s risk of urolithiasis. There is abundant evidence that disparities in health care access and quality are present across the medical field. 20 In the US there have been discrepancies found between medical care between urban and rural patient populations 21 as well as in kidney stone care by race and ethnicity. 22–25 Data also show increased use of imaging for suspected nephrolithiasis in higher income ZIP codes, 26 however differences based upon patient rurality have not been well established. As such we hypothesized that urban patients and those without DM or obesity would use the health care system less than similar rural patients. We also sought to examine if kidney stone patients engaged in stone care (defined as having completed a 24 hour urine, having been prescribed a thiazide like medication, or alkali therapy) would use the health system less than the non engaged population. METHODS Using the Merative Marketscan commercial claims database we identified a cohort of patient undergoing kidney stone surgery after presenting to an emergency department (n = 1239611). 42168 patients were excluded because their enrollment ended within 30 days of their index event and could not be adequately followed. 175347 patients were excluded because they lacked drug coverage, making tracking of medical therapy impossible. This resulted in a cohort of 1030512 patients. Following their initial kidney stone event, we determined whether each patient could be considered ‘engaged in treatment.’ Patients were considered to be engaged if they received any stone prevention medication (HCTZ, potassium citrate, sodium bicarbonate, chlorthalidone, or allopurinol) as defined by national drug codes or received a 24-hour urine test defined by CPT coding within 365 days of their event. All other patients were considered unengaged. We followed patients for 365 days after their initial kidney stone event and evaluated subsequent healthcare encounters. Types of healthcare encounters considered were kidney stones or ureteral stones associated with an ED or surgical visit, UTI, nausea, hematuria, stent placement or removal, nephrostomy placement, KUB, abdominal CT, cystoscopy, laser, or percutaneous drain. We ran a series of poison regressions of the number of healthcare encounters against age, sex, rurality (defined as residence within a metropolitan statistical area), comorbidities, and whether the patient was considered engaged in treatment. In all models patient-days was included as an offset. We also included an interaction between engagement and DM2 and between engagement and obesity. RESULTS DEMOGRAPHICS AND COMORBIDITIES A total of 1,030,512 patients were identified that had an initial stone event, had drug coverage and could be followed for 1 year. Table 1 summarizes the demographic breakdown of the cohort based on treatment engagement. The majority of patients were urban (83.15%) and male (54.58%). Overall, 19.3% of patients were engaged in some sort of secondary prevention (medications or having completed a 24h urine test). A large portion of our patient population were identified as having the diagnosis of type 2 diabetes (21.89%) or Obesity (28.36%). Table 1 identifies the portions of our cohort with comorbid conditions in relation to engagement. OUTCOMES 54.54% of the patients identified in our cohort had subsequent visits for stone disease in the following year, 39% of the cohort returning to the ER with a kidney stone related visit as defined previously. Table 2 summarizes the model outputs for all ER or stone related surgical return visits for kidney stone related causes. Treatment engaged patients had lower incident of ER utilization of 0.840 (P < 0.001), while obese and diabetic patients had increased utilization (IRR 1.2 and 1.1 respectively, P < 0.001). To our surprise, the IRR in relation to rurality was found to be clinically interesting, but of questionable importance (3–4 out of 100), even though it was statistically significant (IRR 0.967, p < 0.001). Table 3 summarizes the interaction model outputs for all kidney stone related healthcare following initial kidney stone treatment. Similarly to stone related visits, engagement lead to less utilization (IRR 0.866, p < 0.001) while Obesity and DM lead to more utilization (IRR 1.16 and 1.2 respectively, p < 0.001). Hospital utilization stratified by rurality was not a significant factor (IRR 0.99, p = 0.116). Of interest when we evaluated the effect of engagement on stone related ED visits, engaged DM and Obese patients had significantly less utilization 0.769, P < 0.001 while the IRR for engaged obese patients was 0.96, P = 0.005. Figure 1 shows the predicted average number of overall hospital visits and stone related ER visits in the following year after initial stone treatment. Predictions are separated between treatment engaged and unengaged patients as well as evaluated with and without DM and Obesity. The graph demonstrates the benefit that engagement can have on kidney stone patient health care utilization, particularly in the obese and DM populations. DISCUSSION The prevalence of urinary stone disease has increased significantly in the United States in the last two decades. With the increasing obesity and diabetes epidemics predicting even higher rates of stone disease, we sought to determine factors that could influence hospital utilization. Using Merative marketscan we identified a large cohort of patients with an initial stone event treated surgically and followed for 1 year. Overall, stone related return rates were increased as expected in the comorbid patient population. Patients that engaged in treatment had a 16% reduction in emergent stone follow up within 1 year. RURALITY AFFECTING OUTCOMES In the US there have been discrepancies found between medical care between urban and rural patient populations. 21 Using this large data set we stratified for rurality in assessing rates of ER visits following initial stone treatment. Overall ER visits after initial stone treatment were not found to be significantly different, but stone related ER visits were found to be decreased by 3.3% in the urban population. 27 These results suggest that if there is a difference in stone care between the urban and rural populations, it is minimal at best, and there does not appear to be a large disparity in outcomes between the populations. However, we are limited by the cohort identified within the study. ENGAGEMENT OUTCOMES AND COMORBIDITIES Obesity and Diabetes are well established risk factors for stone formation 8 which are known to be rising in the US. 9 Our data further adds to the clinical burden of Obesity and DM among stone formers, suggesting increased incident use of hospital utilization after stone surgery. Strategies to decrease system utilization with stone disease is are needed, especially in the comorbid population. Engagement in the DM and obese populations respectively had 23% and 4% less incident ER visits after surgery than in the general population. Even when compared with unengaged non-comorbid patients, their incidence of subsequent stone related care is decreased or equivalent but when compared to unengaged comorbid patients this effect is compounded. Engagement can be easily achieved and warrants further studies. Based upon these values, Fig. 1 exemplifies the drastic decrease in predicted annual ER visits that is achieved by engagement in these patient populations. LIMITATIONS This is a retrospective study and inherent bias may have altered the results. The large patient population examined using this method makes the outcomes generalizable. Retrospective database research is inherently limited by the coding utilized for capturing patients into the cohort as well as their subsequent presentations for outcomes evaluation. Defining engagement by prescription of medication assumes that prescriptions were taken as indicated, however, patient non-compliance is a well-known factor that may have affected outcomes. CONCLUSIONS In conclusion, our data suggests that there is a minimal difference in outcomes between the urban and rural patient populations. Our data affirms that diabetic and obese patients present as high-risk patient populations where treatment engagement may have a much greater effect on subsequent stone related outcomes. We suggest that patients with diabetes and or obesity have the greatest benefit when engaged in stone prevention treatments. Clinicians could partner with these patients to increase potential opportunities for engagement. Declarations Author Contribution Z.P. and J.S. wrote the main manuscript text. S.S. Reviewed the manuscript, wrote portions of the final manuscript, and edited for content J.H. Provided statistical analysis and helped prepare the figures and tablesAll authors reviewed the final manuscript. Data Availability Data is provided within the manuscript or supplementary information files. References Edvardsson VO, Indridason OS, Haraldsson G, Kjartansson O, Palsson R. Temporal trends in the incidence of kidney stone disease. Kidney International. 2013;83(1):146-52. doi: https://doi.org/10.1038/ki.2012.320. Hiatt RA, Dales LG, Friedman GD, Hunkeler EM. FREQUENCY OF UROLITHIASIS IN A PREPAID MEDICAL CARE PROGRAM. American Journal of Epidemiology. 1982;115(2):255-65. doi: 10.1093/oxfordjournals.aje.a113297. Stamatelou KK, Francis ME, Jones CA, Nyberg LM, Curhan GC. Time trends in reported prevalence of kidney stones in the United States: 1976–199411.See Editorial by Goldfarb, p. 1951. Kidney International. 2003;63(5):1817-23. doi: https://doi.org/10.1046/j.1523-1755.2003.00917.x. Romero V, Akpinar H, Assimos DG. Kidney stones: a global picture of prevalence, incidence, and associated risk factors. Rev Urol. 2010;12(2-3):e86-96. PubMed PMID: 20811557; PMCID: PMC2931286. Wang W, Fan J, Huang G, Li J, Zhu X, Tian Y, Su L. Prevalence of kidney stones in mainland China: A systematic review. Sci Rep. 2017;7:41630. Epub 20170131. doi: 10.1038/srep41630. PubMed PMID: 28139722; PMCID: PMC5282506. Lotan Y. Economics and cost of care of stone disease. Adv Chronic Kidney Dis. 2009;16(1):5-10. doi: 10.1053/j.ackd.2008.10.002. PubMed PMID: 19095200. Canales BK, Sharma N, Yuzhakov SV, Bozorgmehri S, Otto BJ, Bird VG. Long-term Recurrence Rates in Uric Acid Stone Formers With or Without Medical Management. Urology. 2019;131:46-52. Epub 20190531. doi: 10.1016/j.urology.2019.05.023. PubMed PMID: 31158354. Taylor EN, Stampfer MJ, Curhan GC. Obesity, weight gain, and the risk of kidney stones. Jama. 2005;293(4):455-62. Scales Jr CD, Smith AC, Hanley JM, Saigal CS, Project UDiA. Prevalence of kidney stones in the United States. European urology. 2012;62(1):160-5. Dietary and Pharmacologic Management to Prevent Recurrent Nephrolithiasis in Adults: A Clinical Practice Guideline From the American College of Physicians. Annals of Internal Medicine. 2014;161(9):659-67. doi: 10.7326/m13-2908 %m 25364887. Pearle MS, Goldfarb DS, Assimos DG, Curhan G, Denu-Ciocca CJ, Matlaga BR, Monga M, Penniston KL, Preminger GM, Turk TM. Medical management of kidney stones: AUA guideline. The Journal of urology. 2014;192(2):316-24. Hsi RS, Yan PL, Crivelli JJ, Goldfarb DS, Shahinian V, Hollingsworth JM. Comparison of Selective vs Empiric Pharmacologic Preventive Therapy of Kidney Stone Recurrence With High-Risk Features. Urology. 2022;164:74-9. Epub 20220217. doi: 10.1016/j.urology.2021.12.037. PubMed PMID: 35182586; PMCID: PMC9232879. LÆRUM E, LARSEN S. Thiazide prophylaxis of urolithiasis: A double‐blind study in general practice. Acta medica Scandinavica. 1984;215(4):383-9. Scholz D, Schwille PO, Sigel A. Double-blind study with thiazide in recurrent calcium lithiasis. The Journal of urology. 1982;128(5):903-7. Borghi L, Meschi T, Guerra A, Novarini A. Randomized prospective study of a nonthiazide diuretic, indapamide, in preventing calcium stone recurrences. Journal of cardiovascular pharmacology. 1993;22:78-86. Ettinger B, Pak CY, Citron JT, Thomas C, Adams-Huet B, Vangessel A. Potassium-magnesium citrate is an effective prophylaxis against recurrent calcium oxalate nephrolithiasis. The Journal of urology. 1997;158(6):2069-73. Barcelo P, Wuhl O, Servitge E, Rousaud A, Pak C. Randomized double-blind study of potassium citrate in idiopathic hypocitraturic calcium nephrolithiasis. The Journal of urology. 1993;150(6):1761-4. Ettinger B, Tang A, Citron JT, Livermore B, Williams T. Randomized trial of allopurinol in the prevention of calcium oxalate calculi. New England Journal of Medicine. 1986;315(22):1386-9. Hsi RS, Yan PL, Crivelli JJ, Goldfarb DS, Shahinian V, Hollingsworth JM. Comparison of Empiric Preventative Pharmacologic Therapies on Stone Recurrence Among Patients with Kidney Stone Disease. Urology. 2022;166:111-7. Epub 20220508. doi: 10.1016/j.urology.2022.04.031. PubMed PMID: 35545149; PMCID: PMC9356981. Dhayat NA, Bonny O, Roth B, Christe A, Ritter A, Mohebbi N, Faller N, Pellegrini L, Bedino G, Venzin RM, Grosse P, Hüsler C, Koneth I, Bucher C, Del Giorno R, Gabutti L, Mayr M, Odermatt U, Buchkremer F, Ernandez T, Stoermann-Chopard C, Teta D, Vogt B, Roumet M, Tamò L, Cereghetti GM, Trelle S, Fuster DG. Hydrochlorothiazide and Prevention of Kidney-Stone Recurrence. N Engl J Med. 2023;388(9):781-91. doi: 10.1056/NEJMoa2209275. PubMed PMID: 36856614. Chen X, Orom H, Hay JL, Waters EA, Schofield E, Li Y, Kiviniemi MT. Differences in Rural and Urban Health Information Access and Use. J Rural Health. 2019;35(3):405-17. Epub 20181116. doi: 10.1111/jrh.12335. PubMed PMID: 30444935; PMCID: PMC6522336. Berger AJ, Wang Y, Rowe C, Chung B, Chang S, Haleblian G. Racial disparities in analgesic use amongst patients presenting to the emergency department for kidney stones in the United States. The American Journal of Emergency Medicine. 2021;39:71-4. Seklehner S, Laudano MA, Jamzadeh A, Del Pizzo JJ, Chughtai B, Lee RK. Trends and inequalities in the surgical management of ureteric calculi in the USA. BJU international. 2014;113(3):476-83. Kirshenbaum EJ, Doshi C, Dornbier R, Blackwell RH, Bajic P, Gupta GN, Gorbonos A, Turk TM, Flanigan RC, Baldea KG. Socioeconomic disparities in the acute management of stone disease in the United States. Journal of Endourology. 2019;33(2):167-72. Schoenfeld D, Mohn L, Agalliu I, Stern JM. Disparities in care among patients presenting to the emergency department for urinary stone disease. Urolithiasis. 2020;48(3):217-25. Epub 20190425. doi: 10.1007/s00240-019-01136-y. PubMed PMID: 31025079. Balthazar P, Sadigh G, Hughes D, Rosenkrantz AB, Hanna T, Duszak Jr R. Increasing use, geographic variation, and disparities in emergency department CT for suspected urolithiasis. Journal of the American College of Radiology. 2019;16(11):1547-53. Stolzenbach LF, Deuker M, Collà-Ruvolo C, Nocera L, Tian Z, Maurer T, Tilki D, Briganti A, Saad F, Mirone V, Chun FKH, Graefen M, Karakiewicz PI. Differences between rural and urban prostate cancer patients. World J Urol. 2021;39(7):2507-14. Epub 20201105. doi: 10.1007/s00345-020-03483-7. PubMed PMID: 33155063; PMCID: PMC8332582. Tables Table 1. Demographic breakdown of cohort. Continuous variables presented as median (with inter-quartile range). Categorical variables presented as number of patients (with percentage of group). Percentages in ‘Total’ row denote percentage of full cohort; percentages in all other rows denote percentage of column group. Variable No Engagement Both Engagement Medication Engagement 24h Urine Engagement Full cohort P value Total 831690 (80.71%) 26457 (2.57%) 42300 (4.1%) 130065 (12.62%) 1030512 Age 46 (34-57) 53 (43-60) 56 (47-64) 50 (39-58) 47 (35-58) < 0.001 Male 448489 (53.93%) 15802 (59.73%) 28392 (67.12%) 69778 (53.65%) 562461 (54.58%) < 0.001 Urban 689192 (82.87%) 22352 (84.48%) 34486 (81.53%) 110839 (85.22%) 856869 (83.15%) < 0.001 Comorbidities Type 2 Diabetes 149986 (18.03%) 10745 (40.61%) 15934 (37.67%) 48921 (37.61%) 225586 (21.89%) < 0.001 Inflammatory Bowel Disease 28233 (3.39%) 1127 (4.26%) 2042 (4.83%) 4854 (3.73%) 36256 (3.52%) < 0.001 History of Gastric Bypass 16991 (2.04%) 841 (3.18%) 1085 (2.57%) 3594 (2.76%) 22511 (2.18%) < 0.001 Obesity 218987 (26.33%) 11073 (41.85%) 17289 (40.87%) 44879 (34.51%) 292228 (28.36%) < 0.001 Outcomes All ER visits 413752 (49.75%) 22729 (85.91%) 27478 (64.96%) 98097 (75.42%) 562056 (54.54%) < 0.001 Kidney or Ureteral Stone 284488 (34.21%) 20386 (77.05%) 21025 (49.7%) 79360 (61.02%) 405259 (39.33%) < 0.001 Table 2. Model outputs for kidney/ureteral stone-related visits associated with ED or surgery. Results presented as incident rate ratios with 95% confidence intervals and p-values. P-values of 0 indicate less than 0.001. Effect of population density relative to rural; effect of engagement realtive to people not engaged in treatment; effect of age represents increase of one year; effect of comorbidities relative to patients without. Variable IRR Low95 High95 p Intercept 0.002 0.002 0.002 0 Population density (urban) 0.967 0.955 0.979 0 Engaged in treatment (yes) 0.840 0.828 0.852 0 Age 1.007 1.007 1.008 0 Sex (female) 1.025 1.015 1.035 0 DM2 1.112 1.100 1.125 0 Inflamatory bowel 1.078 1.053 1.104 0 Gastric bypass history 1.108 1.076 1.140 0 Obesity 1.197 1.184 1.209 0 Variable IRR Engagement * DM2 0.769 (0.746-0.792) p=0 Engagement * Obesity 0.959 (0.932-0.988) p=0.005 Table 3; Model outputs for all healthcare visits. Results presented as incident rate ratios with 95% confidence intervals and p-values. P-values of 0 indicate less than 0.001. Effect of population density relative to rural; effect of engagement realtive to people not engaged in treatment; effect of age represents increase of one year; effect of comorbidities relative to patients without. Variable IRR Low95 High95 p Intercept 0.003 0.003 0.003 0.000 Population density (urban) 0.992 0.982 1.002 0.116 Engaged in treatment (yes) 0.866 0.856 0.875 0.000 Age 1.009 1.009 1.009 0.000 Sex (female) 1.226 1.217 1.236 0.000 DM2 1.200 1.189 1.211 0.000 Inflamatory bowel 1.492 1.468 1.516 0.000 Gastric bypass history 1.195 1.169 1.221 0.000 Obesity 1.167 1.157 1.177 0.000 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4909679","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":344599339,"identity":"b72f2780-05af-424e-bd46-173cbc8e7d1b","order_by":0,"name":"Stephen Summers","email":"data:image/png;base64,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","orcid":"","institution":"University of Utah","correspondingAuthor":true,"prefix":"","firstName":"Stephen","middleName":"","lastName":"Summers","suffix":""},{"id":344599340,"identity":"8de6a966-5f36-4d1c-93ac-c36dfb325ee4","order_by":1,"name":"Zachary Pfeifer","email":"","orcid":"","institution":"University of Utah","correspondingAuthor":false,"prefix":"","firstName":"Zachary","middleName":"","lastName":"Pfeifer","suffix":""},{"id":344599341,"identity":"83ef6472-7b86-4a2c-b899-930b4ce6c89e","order_by":2,"name":"Joshua Stern","email":"","orcid":"","institution":"Intermountain Healthcare","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Stern","suffix":""},{"id":344599342,"identity":"42a56c20-50e4-4747-a8a2-5f71719eff1a","order_by":3,"name":"Joshua John Horn","email":"","orcid":"","institution":"University of Utah","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"John","lastName":"Horn","suffix":""}],"badges":[],"createdAt":"2024-08-13 23:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4909679/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4909679/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66543260,"identity":"fe4addf3-e219-4654-9a07-081e9c1f8d09","added_by":"auto","created_at":"2024-10-14 07:57:41","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":244280,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted numbers of visits in one year based on engagement and comorbidities.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4909679/v1/fdd20f34540539c41be361f4.jpeg"},{"id":66544535,"identity":"f4b451e3-b227-4214-a53b-81763cb227f4","added_by":"auto","created_at":"2024-10-14 08:13:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":623921,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4909679/v1/38513868-3587-490e-88d5-4a1e2d1b9288.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of Kidney Stone Prevention After ER intervention: Does rurality or comorbid conditions affect outcomes?","fulltext":[{"header":"INTRODUCTION ","content":"\u003cp\u003eNephrolithiasis is a common diagnosis which is increasing in incidence. Lifetime prevalence is estimated at 10\u0026ndash;12% in men and 5\u0026ndash;6% in women.\u003csup\u003e1, 2\u003c/sup\u003eRecent studies have shown relative increases in incidence as much as 36% in a 5 year period,\u003csup\u003e3\u003c/sup\u003e and other studies have also demonstrated an upward trend in incidence in several populations.\u003csup\u003e4, 5\u003c/sup\u003e Kidney stone disease results in increasing costs to the healthcare system through many routes including chronic kidney disease, repeated interventions for stone removal, and financial loss resulting from lost work days. Reports have estimated this cost to be \u003cspan\u003e$\u003c/span\u003e2.1\u0026nbsp;billion in 2000\u003csup\u003e6\u003c/sup\u003e which have likely only risen with increasing treatment costs and incidence.\u003csup\u003e7\u003c/sup\u003e Obesity and Diabetes are well established risk factors for stone formation\u003csup\u003e8\u003c/sup\u003e both with increasing incidence,\u003csup\u003e9\u003c/sup\u003e and may account for some of the increases previously mentioned. As the obesity epidemic continues, patients with metabolic syndrome will continue to be a rising proportion of our urologic practice. There is increased recognition that the metabolic syndrome and specifically diabetes can increase one\u0026rsquo;s risk of urolithiasis.\u003c/p\u003e \u003cp\u003eThere is abundant evidence that disparities in health care access and quality are present across the medical field.\u003csup\u003e20\u003c/sup\u003e In the US there have been discrepancies found between medical care between urban and rural patient populations\u003csup\u003e21\u003c/sup\u003e as well as in kidney stone care by race and ethnicity.\u003csup\u003e22\u0026ndash;25\u003c/sup\u003e Data also show increased use of imaging for suspected nephrolithiasis in higher income ZIP codes,\u003csup\u003e26\u003c/sup\u003e however differences based upon patient rurality have not been well established.\u003c/p\u003e \u003cp\u003eAs such we hypothesized that urban patients and those without DM or obesity would use the health care system less than similar rural patients. We also sought to examine if kidney stone patients engaged in stone care (defined as having completed a 24 hour urine, having been prescribed a thiazide like medication, or alkali therapy) would use the health system less than the non engaged population.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eUsing the Merative Marketscan commercial claims database we identified a cohort of patient undergoing kidney stone surgery after presenting to an emergency department (n\u0026thinsp;=\u0026thinsp;1239611). 42168 patients were excluded because their enrollment ended within 30 days of their index event and could not be adequately followed. 175347 patients were excluded because they lacked drug coverage, making tracking of medical therapy impossible. This resulted in a cohort of 1030512 patients.\u003c/p\u003e \u003cp\u003eFollowing their initial kidney stone event, we determined whether each patient could be considered \u0026lsquo;engaged in treatment.\u0026rsquo; Patients were considered to be engaged if they received any stone prevention medication (HCTZ, potassium citrate, sodium bicarbonate, chlorthalidone, or allopurinol) as defined by national drug codes or received a 24-hour urine test defined by CPT coding within 365 days of their event. All other patients were considered unengaged.\u003c/p\u003e \u003cp\u003eWe followed patients for 365 days after their initial kidney stone event and evaluated subsequent healthcare encounters. Types of healthcare encounters considered were kidney stones or ureteral stones associated with an ED or surgical visit, UTI, nausea, hematuria, stent placement or removal, nephrostomy placement, KUB, abdominal CT, cystoscopy, laser, or percutaneous drain. We ran a series of poison regressions of the number of healthcare encounters against age, sex, rurality (defined as residence within a metropolitan statistical area), comorbidities, and whether the patient was considered engaged in treatment. In all models patient-days was included as an offset. We also included an interaction between engagement and DM2 and between engagement and obesity.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDEMOGRAPHICS AND COMORBIDITIES\u003c/h2\u003e \u003cp\u003eA total of 1,030,512 patients were identified that had an initial stone event, had drug coverage and could be followed for 1 year. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the demographic breakdown of the cohort based on treatment engagement. The majority of patients were urban (83.15%) and male (54.58%). Overall, 19.3% of patients were engaged in some sort of secondary prevention (medications or having completed a 24h urine test). A large portion of our patient population were identified as having the diagnosis of type 2 diabetes (21.89%) or Obesity (28.36%).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e identifies the portions of our cohort with comorbid conditions in relation to engagement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOUTCOMES\u003c/h2\u003e \u003cp\u003e54.54% of the patients identified in our cohort had subsequent visits for stone disease in the following year, 39% of the cohort returning to the ER with a kidney stone related visit as defined previously. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the model outputs for all ER or stone related surgical return visits for kidney stone related causes. Treatment engaged patients had lower incident of ER utilization of 0.840 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while obese and diabetic patients had increased utilization (IRR 1.2 and 1.1 respectively, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). To our surprise, the IRR in relation to rurality was found to be clinically interesting, but of questionable importance (3\u0026ndash;4 out of 100), even though it was statistically significant (IRR 0.967, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the interaction model outputs for all kidney stone related healthcare following initial kidney stone treatment. Similarly to stone related visits, engagement lead to less utilization (IRR 0.866, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) while Obesity and DM lead to more utilization (IRR 1.16 and 1.2 respectively, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hospital utilization stratified by rurality was not a significant factor (IRR 0.99, p\u0026thinsp;=\u0026thinsp;0.116).\u003c/p\u003e \u003cp\u003eOf interest when we evaluated the effect of engagement on stone related ED visits, engaged DM and Obese patients had significantly less utilization 0.769, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 while the IRR for engaged obese patients was 0.96, P\u0026thinsp;=\u0026thinsp;0.005.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the predicted average number of overall hospital visits and stone related ER visits in the following year after initial stone treatment. Predictions are separated between treatment engaged and unengaged patients as well as evaluated with and without DM and Obesity. The graph demonstrates the benefit that engagement can have on kidney stone patient health care utilization, particularly in the obese and DM populations.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe prevalence of urinary stone disease has increased significantly in the United States in the last two decades. With the increasing obesity and diabetes epidemics predicting even higher rates of stone disease, we sought to determine factors that could influence hospital utilization. Using Merative marketscan we identified a large cohort of patients with an initial stone event treated surgically and followed for 1 year. Overall, stone related return rates were increased as expected in the comorbid patient population. Patients that engaged in treatment had a 16% reduction in emergent stone follow up within 1 year.\u003c/p\u003e\n\u003ch3\u003eRURALITY AFFECTING OUTCOMES\u003c/h3\u003e\n\u003cp\u003eIn the US there have been discrepancies found between medical care between urban and rural patient populations.\u003csup\u003e21\u003c/sup\u003e Using this large data set we stratified for rurality in assessing rates of ER visits following initial stone treatment. Overall ER visits after initial stone treatment were not found to be significantly different, but stone related ER visits were found to be decreased by 3.3% in the urban population. \u003csup\u003e27\u003c/sup\u003e These results suggest that if there is a difference in stone care between the urban and rural populations, it is minimal at best, and there does not appear to be a large disparity in outcomes between the populations. However, we are limited by the cohort identified within the study.\u003c/p\u003e\n\u003ch3\u003eENGAGEMENT OUTCOMES AND COMORBIDITIES\u003c/h3\u003e\n\u003cp\u003eObesity and Diabetes are well established risk factors for stone formation\u003csup\u003e8\u003c/sup\u003e which are known to be rising in the US.\u003csup\u003e9\u003c/sup\u003e Our data further adds to the clinical burden of Obesity and DM among stone formers, suggesting increased incident use of hospital utilization after stone surgery. Strategies to decrease system utilization with stone disease is are needed, especially in the comorbid population. Engagement in the DM and obese populations respectively had 23% and 4% less incident ER visits after surgery than in the general population. Even when compared with unengaged non-comorbid patients, their incidence of subsequent stone related care is decreased or equivalent but when compared to unengaged comorbid patients this effect is compounded. Engagement can be easily achieved and warrants further studies. Based upon these values, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e exemplifies the drastic decrease in predicted annual ER visits that is achieved by engagement in these patient populations.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLIMITATIONS\u003c/h2\u003e \u003cp\u003eThis is a retrospective study and inherent bias may have altered the results. The large patient population examined using this method makes the outcomes generalizable. Retrospective database research is inherently limited by the coding utilized for capturing patients into the cohort as well as their subsequent presentations for outcomes evaluation. Defining engagement by prescription of medication assumes that prescriptions were taken as indicated, however, patient non-compliance is a well-known factor that may have affected outcomes.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, our data suggests that there is a minimal difference in outcomes between the urban and rural patient populations. Our data affirms that diabetic and obese patients present as high-risk patient populations where treatment engagement may have a much greater effect on subsequent stone related outcomes. We suggest that patients with diabetes and or obesity have the greatest benefit when engaged in stone prevention treatments. Clinicians could partner with these patients to increase potential opportunities for engagement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZ.P. and J.S. wrote the main manuscript text. S.S. Reviewed the manuscript, wrote portions of the final manuscript, and edited for content J.H. Provided statistical analysis and helped prepare the figures and tablesAll authors reviewed the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEdvardsson VO, Indridason OS, Haraldsson G, Kjartansson O, Palsson R. Temporal trends in the incidence of kidney stone disease. Kidney International. 2013;83(1):146-52. doi: https://doi.org/10.1038/ki.2012.320.\u003c/li\u003e\n\u003cli\u003eHiatt RA, Dales LG, Friedman GD, Hunkeler EM. FREQUENCY OF UROLITHIASIS IN A PREPAID MEDICAL CARE PROGRAM. American Journal of Epidemiology. 1982;115(2):255-65. doi: 10.1093/oxfordjournals.aje.a113297.\u003c/li\u003e\n\u003cli\u003eStamatelou KK, Francis ME, Jones CA, Nyberg LM, Curhan GC. Time trends in reported prevalence of kidney stones in the United States: 1976\u0026ndash;199411.See Editorial by Goldfarb, p. 1951. Kidney International. 2003;63(5):1817-23. doi: https://doi.org/10.1046/j.1523-1755.2003.00917.x.\u003c/li\u003e\n\u003cli\u003eRomero V, Akpinar H, Assimos DG. Kidney stones: a global picture of prevalence, incidence, and associated risk factors. Rev Urol. 2010;12(2-3):e86-96. PubMed PMID: 20811557; PMCID: PMC2931286.\u003c/li\u003e\n\u003cli\u003eWang W, Fan J, Huang G, Li J, Zhu X, Tian Y, Su L. Prevalence of kidney stones in mainland China: A systematic review. Sci Rep. 2017;7:41630. Epub 20170131. doi: 10.1038/srep41630. PubMed PMID: 28139722; PMCID: PMC5282506.\u003c/li\u003e\n\u003cli\u003eLotan Y. Economics and cost of care of stone disease. Adv Chronic Kidney Dis. 2009;16(1):5-10. doi: 10.1053/j.ackd.2008.10.002. PubMed PMID: 19095200.\u003c/li\u003e\n\u003cli\u003eCanales BK, Sharma N, Yuzhakov SV, Bozorgmehri S, Otto BJ, Bird VG. Long-term Recurrence Rates in Uric Acid Stone Formers With or Without Medical Management. Urology. 2019;131:46-52. Epub 20190531. doi: 10.1016/j.urology.2019.05.023. PubMed PMID: 31158354.\u003c/li\u003e\n\u003cli\u003eTaylor EN, Stampfer MJ, Curhan GC. Obesity, weight gain, and the risk of kidney stones. Jama. 2005;293(4):455-62.\u003c/li\u003e\n\u003cli\u003eScales Jr CD, Smith AC, Hanley JM, Saigal CS, Project UDiA. Prevalence of kidney stones in the United States. European urology. 2012;62(1):160-5.\u003c/li\u003e\n\u003cli\u003eDietary and Pharmacologic Management to Prevent Recurrent Nephrolithiasis in Adults: A Clinical Practice Guideline From the American College of Physicians. Annals of Internal Medicine. 2014;161(9):659-67. doi: 10.7326/m13-2908 %m 25364887.\u003c/li\u003e\n\u003cli\u003ePearle MS, Goldfarb DS, Assimos DG, Curhan G, Denu-Ciocca CJ, Matlaga BR, Monga M, Penniston KL, Preminger GM, Turk TM. Medical management of kidney stones: AUA guideline. The Journal of urology. 2014;192(2):316-24.\u003c/li\u003e\n\u003cli\u003eHsi RS, Yan PL, Crivelli JJ, Goldfarb DS, Shahinian V, Hollingsworth JM. Comparison of Selective vs Empiric Pharmacologic Preventive Therapy of Kidney Stone Recurrence With High-Risk Features. Urology. 2022;164:74-9. Epub 20220217. doi: 10.1016/j.urology.2021.12.037. PubMed PMID: 35182586; PMCID: PMC9232879.\u003c/li\u003e\n\u003cli\u003eL\u0026AElig;RUM E, LARSEN S. Thiazide prophylaxis of urolithiasis: A double‐blind study in general practice. Acta medica Scandinavica. 1984;215(4):383-9.\u003c/li\u003e\n\u003cli\u003eScholz D, Schwille PO, Sigel A. Double-blind study with thiazide in recurrent calcium lithiasis. The Journal of urology. 1982;128(5):903-7.\u003c/li\u003e\n\u003cli\u003eBorghi L, Meschi T, Guerra A, Novarini A. Randomized prospective study of a nonthiazide diuretic, indapamide, in preventing calcium stone recurrences. Journal of cardiovascular pharmacology. 1993;22:78-86.\u003c/li\u003e\n\u003cli\u003eEttinger B, Pak CY, Citron JT, Thomas C, Adams-Huet B, Vangessel A. Potassium-magnesium citrate is an effective prophylaxis against recurrent calcium oxalate nephrolithiasis. The Journal of urology. 1997;158(6):2069-73.\u003c/li\u003e\n\u003cli\u003eBarcelo P, Wuhl O, Servitge E, Rousaud A, Pak C. Randomized double-blind study of potassium citrate in idiopathic hypocitraturic calcium nephrolithiasis. The Journal of urology. 1993;150(6):1761-4.\u003c/li\u003e\n\u003cli\u003eEttinger B, Tang A, Citron JT, Livermore B, Williams T. Randomized trial of allopurinol in the prevention of calcium oxalate calculi. New England Journal of Medicine. 1986;315(22):1386-9.\u003c/li\u003e\n\u003cli\u003eHsi RS, Yan PL, Crivelli JJ, Goldfarb DS, Shahinian V, Hollingsworth JM. Comparison of Empiric Preventative Pharmacologic Therapies on Stone Recurrence Among Patients with Kidney Stone Disease. Urology. 2022;166:111-7. Epub 20220508. doi: 10.1016/j.urology.2022.04.031. PubMed PMID: 35545149; PMCID: PMC9356981.\u003c/li\u003e\n\u003cli\u003eDhayat NA, Bonny O, Roth B, Christe A, Ritter A, Mohebbi N, Faller N, Pellegrini L, Bedino G, Venzin RM, Grosse P, H\u0026uuml;sler C, Koneth I, Bucher C, Del Giorno R, Gabutti L, Mayr M, Odermatt U, Buchkremer F, Ernandez T, Stoermann-Chopard C, Teta D, Vogt B, Roumet M, Tam\u0026ograve; L, Cereghetti GM, Trelle S, Fuster DG. Hydrochlorothiazide and Prevention of Kidney-Stone Recurrence. N Engl J Med. 2023;388(9):781-91. doi: 10.1056/NEJMoa2209275. PubMed PMID: 36856614.\u003c/li\u003e\n\u003cli\u003eChen X, Orom H, Hay JL, Waters EA, Schofield E, Li Y, Kiviniemi MT. Differences in Rural and Urban Health Information Access and Use. J Rural Health. 2019;35(3):405-17. Epub 20181116. doi: 10.1111/jrh.12335. PubMed PMID: 30444935; PMCID: PMC6522336.\u003c/li\u003e\n\u003cli\u003eBerger AJ, Wang Y, Rowe C, Chung B, Chang S, Haleblian G. Racial disparities in analgesic use amongst patients presenting to the emergency department for kidney stones in the United States. The American Journal of Emergency Medicine. 2021;39:71-4.\u003c/li\u003e\n\u003cli\u003eSeklehner S, Laudano MA, Jamzadeh A, Del Pizzo JJ, Chughtai B, Lee RK. Trends and inequalities in the surgical management of ureteric calculi in the USA. BJU international. 2014;113(3):476-83.\u003c/li\u003e\n\u003cli\u003eKirshenbaum EJ, Doshi C, Dornbier R, Blackwell RH, Bajic P, Gupta GN, Gorbonos A, Turk TM, Flanigan RC, Baldea KG. Socioeconomic disparities in the acute management of stone disease in the United States. Journal of Endourology. 2019;33(2):167-72.\u003c/li\u003e\n\u003cli\u003eSchoenfeld D, Mohn L, Agalliu I, Stern JM. Disparities in care among patients presenting to the emergency department for urinary stone disease. Urolithiasis. 2020;48(3):217-25. Epub 20190425. doi: 10.1007/s00240-019-01136-y. PubMed PMID: 31025079.\u003c/li\u003e\n\u003cli\u003eBalthazar P, Sadigh G, Hughes D, Rosenkrantz AB, Hanna T, Duszak Jr R. Increasing use, geographic variation, and disparities in emergency department CT for suspected urolithiasis. Journal of the American College of Radiology. 2019;16(11):1547-53.\u003c/li\u003e\n\u003cli\u003eStolzenbach LF, Deuker M, Coll\u0026agrave;-Ruvolo C, Nocera L, Tian Z, Maurer T, Tilki D, Briganti A, Saad F, Mirone V, Chun FKH, Graefen M, Karakiewicz PI. Differences between rural and urban prostate cancer patients. World J Urol. 2021;39(7):2507-14. Epub 20201105. doi: 10.1007/s00345-020-03483-7. PubMed PMID: 33155063; PMCID: PMC8332582.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographic breakdown of cohort. Continuous variables presented as median (with inter-quartile range). Categorical variables presented as number of patients (with percentage of group). Percentages in \u0026lsquo;Total\u0026rsquo; row denote percentage of full cohort; percentages in all other rows denote percentage of column group.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" style=\"margin-right: calc(-1%); width: 101%;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eNo Engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eBoth Engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eMedication Engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e24h Urine Engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eFull cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e831690 (80.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e26457 (2.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e42300 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e130065 (12.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e1030512\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e46 (34-57)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e53 (43-60)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e56 (47-64)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e50 (39-58)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e47 (35-58)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e448489 (53.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e15802 (59.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e28392 (67.12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e69778 (53.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e562461 (54.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e689192 (82.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e22352 (84.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e34486 (81.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e110839 (85.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e856869 (83.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eType 2 Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e149986 (18.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e10745 (40.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e15934 (37.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e48921 (37.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e225586 (21.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eInflammatory Bowel Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e28233 (3.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e1127 (4.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e2042 (4.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e4854 (3.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e36256 (3.52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eHistory of Gastric Bypass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e16991 (2.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e841 (3.18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e1085 (2.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e3594 (2.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e22511 (2.18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e218987 (26.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e11073 (41.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e17289 (40.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e44879 (34.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e292228 (28.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eOutcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eAll ER visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e413752 (49.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e22729 (85.91%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e27478 (64.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e98097 (75.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e562056 (54.54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003eKidney or Ureteral Stone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e284488 (34.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e20386 (77.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e21025 (49.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e79360 (61.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.10459587955626%\" valign=\"top\"\u003e\n \u003cp\u003e405259 (39.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.37242472266244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. Model outputs for kidney/ureteral stone-related visits associated with ED or surgery. Results presented as incident rate ratios with 95% confidence intervals and p-values. P-values of 0 indicate less than 0.001. Effect of population density relative to rural; effect of engagement realtive to people not engaged in treatment; effect of age represents increase of one year; effect of comorbidities relative to patients without.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"350\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePopulation density (urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEngaged in treatment (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSex (female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInflamatory bowel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGastric bypass history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.803827751196174%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"51.196172248803826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIRR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.803827751196174%\"\u003e\n \u003cp\u003eEngagement * DM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"51.196172248803826%\"\u003e\n \u003cp\u003e0.769 (0.746-0.792) p=0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.803827751196174%\"\u003e\n \u003cp\u003eEngagement * Obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"51.196172248803826%\"\u003e\n \u003cp\u003e0.959 (0.932-0.988) p=0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3; Model outputs for all healthcare visits. Results presented as incident rate ratios with 95% confidence intervals and p-values. P-values of 0 indicate less than 0.001. Effect of population density relative to rural; effect of engagement realtive to people not engaged in treatment; effect of age represents increase of one year; effect of comorbidities relative to patients without.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePopulation density (urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEngaged in treatment (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSex (female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInflamatory bowel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGastric bypass history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4909679/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4909679/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction and Objective:\u003c/strong\u003e The incidence of kidney stones is rising, particularly among diabetic and obese populations. Limited access to urologic care in rural US areas may predispose these patients to increased kidney stone-related visits. This study aims to determine if rural residency and comorbid conditions affect kidney stone-related healthcare visits and the effectiveness of medical prophylaxis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Using Merative Marketscan data from 2008 to 2017, patients diagnosed with kidney or ureteral stones who underwent surgical intervention in emergency settings were identified. Patients were categorized by comorbidities, demographics, and rural vs. urban residency. Preventative treatments, including medication and 24-hour urine testing, were noted. All patients were followed for 365 days post initial encounter to track subsequent stone disease management and prevention encounters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOut of 1,030,512 patients, 17% were rural residents. Post-initial stone events, 19% engaged in medical treatment. Treatment engagement led to a 16% reduction in stone-related ED visits the following year. Diabetic and obese patients not engaged in treatment had an 11% and 20% increased risk of subsequent stone-related ED visits, respectively. Engagement reduced the risk of subsequent stone events by 34% in diabetic patients and 24.5% in obese patients compared to their unengaged counterparts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eMedical treatment engagement slightly reduced overall stone-related encounters and return rates in the general population, with a minor decrease in urban compared to rural populations. However, treatment engagement significantly lowered stone-related event rates in diabetic and obese patients, highlighting the need for focused and aggressive preventive medical treatment in these groups.\u003c/p\u003e","manuscriptTitle":"Effects of Kidney Stone Prevention After ER intervention: Does rurality or comorbid conditions affect outcomes?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-14 07:57:36","doi":"10.21203/rs.3.rs-4909679/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67b5581e-1e14-4e90-90bf-73ba8a4ada57","owner":[],"postedDate":"October 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-14T07:57:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-14 07:57:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4909679","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4909679","identity":"rs-4909679","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}