Comprehensive analysis of cannabis use and dependence in the setting of total abdominal hysterectomy

Comprehensive analysis of cannabis use and dependence in the setting of total abdominal hysterectomy | 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 Comprehensive analysis of cannabis use and dependence in the setting of total abdominal hysterectomy Dr. Dalia Rahmon, Diana Mansour, Megan Guiles, Emilia Rodriguez Espinoza, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9058918/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Widespread legalization of cannabis has been associated with an increased prevalence of cannabis use and dependence (CUD) among surgical patients. This study examines the demographic characteristics, comorbidities, and inpatient outcomes of patients with CUD undergoing total abdominal hysterectomy (TAH). Methods retrospective cohort study utilized the National Inpatient Sample (2016–2021) to identify patients undergoing TAH. Patients were stratified into CUD and non-CUD cohorts. Demographics, comorbidities, in-hospital complications, and economic outcomes were compared using t -tests and chi-square analyses. Propensity score matching was performed to assess postoperative complications. Results Among 557,055 TAH procedures, 0.50% involved patients with CUD. Compared with non-CUD patients, those with CUD were younger (49 vs. 53 years), more often Black (38.7% vs. 23.8%) or Native American (0.5% vs. 0.4%), and more frequently insured by Medicaid (43.1% vs. 15.2%). Patients with CUD experienced longer hospitalizations (4.6 vs. 3.5 days) and higher total charges ( $ 72,078 vs. $ 62,610). They also had higher rates of comorbid substance use, including alcoholism (7.3% vs. 0.5%), opioid use disorder (3.4% vs. 0.2%), and tobacco use disorder (50.8% vs. 9.7%), as well as anxiety (23.9% vs. 11.5%), depression (16.6% vs. 8.8%). After propensity score matching, CUD was not associated with increased risk of postoperative complications. Conclusion As cannabis use rises, understanding the demographic and clinical profile of surgical patients with CUD is increasingly important. Recognition of CUD in patients undergoing hysterectomy may support more individualized perioperative planning, equitable screening practices, and optimized pain management strategies. cannabis use substance use total abdominal hysterectomy Introduction Approximately 22% of the United States population uses cannabis, making it the most commonly used illicit drug in the country and worldwide. 1 , 2 Widespread legalization for recreational and medical use has contributed to increasing rates of cannabis use and dependence (CUD), particularly among surgical patients, in whom a threefold increase has been observed in recent years. 3 Cannabis contains multiple active compounds, most notably delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), which exert physiologic effects through the endocannabinoid system. 4 These compounds have demonstrated potential in modulating nociceptive and inflammatory pathways, 5 and are therefore frequently used in pain management. However, the interaction between cannabis use and postoperative pain control remains incompletely understood, with existing studies yielding conflicting results. Emerging evidence suggests that CUD may be associated with higher postoperative pain scores and increased opioid requirements following major surgery 6 – 9 , though data specific to gynecologic surgery are limited. Hysterectomy is among the most frequently performed surgical procedures worldwide, with common indications including abnormal uterine bleeding, leiomyomata, adenomyosis, endometriosis, and gynecologic malignancy. 10 It may be performed using abdominal or minimally invasive approaches, and its prevalence has been associated with increasing age, higher body mass index, Black race, and tobacco use. 11 As cannabis decriminalization and social acceptance have increased patient disclosure, understanding the impact of CUD on postoperative outcomes following hysterectomy has become increasingly important. While prior studies have broadly examined substance use in surgical populations, large-scale, population-based research focused specifically on CUD in gynecologic surgery remains limited. Therefore, this study aims to evaluate epidemiologic trends, demographic characteristics, comorbidities, and immediate clinical and economic outcomes among patients with CUD undergoing total abdominal hysterectomy (TAH). Methods This retrospective cohort study utilized discharge data from the National Inpatient Sample (NIS), the largest publicly available all-payer inpatient database in the United States. The NIS, developed by the Healthcare Cost and Utilization Project (HCUP), provides nationally representative estimates of inpatient utilization, costs, and outcomes. 12 All analyses were evaluated in accordance with recommendations from the Agency for Healthcare Research and Quality (AHRQ). 13 Patients who underwent TAH between 2016 and 2021 were identified using ICD-10 procedure codes. The study population was divided into patients with and without CUD. CUD was defined using ICD-10-CM codes F12.1, F12.2, and F12.9, representing cannabis abuse, dependence, and unspecified use. Comorbidities and in-hospital complications were identified using corresponding ICD-10 codes. Patients younger than 40 years were excluded to minimize inclusion of atypical indications for hysterectomy and to improve cohort homogeneity. Patients who underwent laparoscopic hysterectomy were also excluded. Continuous variables were compared using t -tests, whereas categorical variables were analyzed using Rao-Scott chi-square tests. Propensity score matching based on age and medical comorbidities was performed to assess postoperative complications. 14 Statistical significance was set at P < 0.05. All analyses accounted for the complex survey design of the NIS and were conducted using SAS version 9.4. This study used publicly available, de-identified data from the NIS and was determined to be not human subject research according to institutional policy; therefore, IRB review was not required under 45 CFR 46.104(d)(4). Results Trends in CU by Year From 2016 to 2021, an estimated 557,055 patients underwent TAH, of whom 0.50% were identified with CUD. Although the total number of TAH procedures decreased by 33.7% during the study period, no significant association was observed between CUD prevalence and year ( P = 0.906). Annual CUD prevalence remained stable, ranging from 0.51% to 0.53% (Table 1 ). Table 1 Trends in CUD rate per year Year CUD (%Rate) (n = 2,805) Non-CUD (%Rate) (n = 554,250) P -value 2016 615 (0.53%) 114,500 0.906 2017 540 (0.51%) 104,400 2018 495 (0.52%) 95,305 2019 415 (0.46%) 90,270 2020 350 (0.47%) 73,875 2021 390 (0.51%) 75,900 Demographic Factors Patients with CUD were significantly younger than those without (mean age 49.4 vs. 53.0 years, P < 0.001). While White patients constituted the largest racial group in both cohorts, patients with CUD were more likely to be Black (38.7% vs. 23.8%, P < 0.001) or Native American (0.5% vs. 0.4%, P < 0.001). CUD patients were also more frequently insured by Medicaid (43.1% vs. 15.2%, P < 0.001) or self-pay (8.2% vs. 3.6%, P < 0.001) (Table 2 ). Table 2 Demographic factors, stratified by CUD vs. non-CUD Variable CUD (n = 2,805) Non-CUD (n = 554,250) P -value Average age of patient (years) Mean (standard error) 49.4 (0.34) 53.0 (0.06) < 0.001 Race* White 45.10% 51.19% < 0.001 Black 38.68% 23.75% Hispanic 9.63% 13.78% Asian/Pacific Islander 0.36% 4.54% Native American 0.53% 0.43% Other 1.96% 3.55% Primary Payor Medicare 13.01% 18.36% < 0.001 Medicaid 43.14% 15.24% Private Insurance/HMO 31.91% 59.43% Self-Pay 8.20% 3.56% Other 3.74% 3.41% *Race was reported as documented in administrative records and may be subject to misclassification. Comorbidities Stratified by CUD Patients with CUD had substantially higher rates of polysubstance use, including alcohol use disorder (7.3% vs. 0.5%, P < 0.001), opioid use disorder (3.4% vs. 0.2%, P < 0.001), and tobacco use disorder (50.8% vs. 9.7%, P < 0.001). They also demonstrated increased prevalence of anxiety (23.9% vs. 11.5%, P < 0.001), depression (16.6% vs. 8.8%, P < 0.001), COPD (7.5% vs. 2.6%, P < 0.001), hepatitis (2.3% vs. 0.5%, P < 0.001), and obesity (26.6% vs. 22.7%, P = 0.032). Conversely, CUD was associated with lower prevalence of atrial fibrillation (0.9% vs. 2.2%, P = 0.037), diabetes (9.5% vs. 13.3%, P = 0.008), and endometrial hyperplasia (3.7% vs. 6.4%, P = 0.01), likely reflecting the younger age of this cohort (Table 3 ). Table 3 Comorbidities, stratified by CUD vs. non-CUD Variables CUD (n = 2,805) Non-CUD (n = 554,250) P- value Abnormal uterine bleeding 13.90% 12.41% 0.283 Atrial fibrillation 0.89% 2.18% 0.037 Alcoholism 7.31% 0.47% < 0.001 Anxiety 23.89% 11.48% < 0.001 Chronic obstructive pulmonary disease 7.49% 2.61% < 0.001 Depression 16.58% 8.82% < 0.001 Diabetes mellitus (Type 1 or 2) 9.45% 13.29% 0.008 Endometrial hyperplasia 3.74% 6.39% 0.01 Endometriosis 10.16% 11.71% 0.266 Fibroids 59.00% 57.19% 0.387 Hepatitis 2.32% 0.46% < 0.001 Hypertension 36.72% 34.71% 0.315 Obesity 26.56% 22.70% 0.032 Opioid use disorder 3.39% 0.24% < 0.001 Renal disease 3.21% 2.66% 0.413 Tobacco use disorder 50.80% 9.73% < 0.001 Complications, Economic, and Discharge Dispositions Unadjusted analyses showed higher rates of blood transfusion and respiratory complications among patients with CUD; however, these differences were not sustained after propensity score matching (Table 4 ). Patients with CUD experienced significantly longer hospitalizations (4.6 vs. 3.5 days, P < 0.001) and higher total hospital charges ( $ 72,078 vs. $ 62,610, P < 0.003). Although discharge disposition differed statistically, the majority of patients in both cohorts were discharged home. Table 4 Complications, economic, and disposition outcomes CUD (n = 2,805) Non-CUD (n = 554,250) P -value Blood transfusion* 7.66% 7.29% 0.823 Cardiac complications* 1.63% 2.66% 0.207 Genitourinary complications* 2.70% 4.42% 0.117 Ileus / small bowel obstruction* 4.16% 5.43% 0.282 Respiratory complications* 3.12% 4.76% 0.72 Venous thrombotic embolism (VTE)* 0.82% 0.77% 0.915 Length of stay (days) 4.6 3.5 0.001 Total charges ( $ ) $ 72,078 $ 62,610 0.003 Discharge disposition Home 90.37% 90.43% 0.006 Rehab 0.53% 0.14% Other facility 1.60% 2.67% Home health 6.95% 6.50% AMA 0.36% 0.06% Deceased 0.18% 0.19% *Represents weighted analysis Discussion This study provides a large, nationally representative assessment of CUD among patients undergoing TAH in the United States. Prior research has examined cannabis use in surgical populations, particularly in major abdominal and arthroplasty procedures. 3 , 15 – 18 However, to our knowledge, no prior studies have specifically evaluated inpatient trends among gynecologic surgical patients with CUD. Despite an approximately 33% decline in the overall volume of TAH during the study period, no significant association was observed between CUD prevalence and year. The decline in abdominal hysterectomy volume is consistent with national trends reflecting increased adoption of minimally invasive and robotic-assisted approaches. 19 – 22 Notably, although national surveys report increasing cannabis use in the general population and among gynecologic patients specifically 23 , the prevalence of CUD in this patient cohort remained stable at approximately 0.5%, comparable to rates reported in other inpatient studies. 15 , 16 This discrepancy may reflect underrecognition or underdocumentation of cannabis use by medical providers 24 , highlighting the need for improved screening and documentation practices in surgical populations. Demographic analyses demonstrated that patients with CUD were significantly younger than those without CUD, consistent with population-based data showing higher rates of cannabis use among younger adults. 25 – 29 This pattern likely reflects generational differences in social acceptance, evolving legalization policies, and shifting perceptions of risks associated with cannabis use With respect to race and ethnicity, although White patients comprised the largest proportion of both cohorts, patients with CUD were more likely to be Black or Native American. This finding aligns with prior literature documenting racial and ethnic disparities in substance use diagnoses and documentation. 29 – 31 One study reported the highest prevalence of CUD among Black and Native American populations, attributing this to higher rates of daily cannabis use 29 , which may increase susceptibility to developing dependence. However, these findings should be interpreted with caution, as CUD diagnosis and reporting may be influenced by clinician implicit bias and variability in documentation practices. Such factors may contribute to the apparent overrepresentation of certain racial groups, rather than reflecting true differences in disease prevalence. Several factors may contribute to these disparities, including socioeconomic inequities, differential access to healthcare, structural racism, and clinician bias in screening and coding practices. Prior studies suggest that substance use disorders may be more frequently documented among minority populations despite similar prevalence across racial groups, underscoring the need for equitable and standardized screening practices. 24 Additionally, clinician bias may influence not only the diagnosis and documentation, but also access to treatment. For example, despite higher prevalence of CUD among Black patients, this population has been shown to receive treatment less frequently and to report greater unmet treatment needs compared to White patients. 32 Patients with CUD undergoing TAH were also more likely to have Medicaid coverage or be self-pay. This finding is consistent with prior studies demonstrating higher prevalence of cannabis use among lower-income populations and may partially reflect the younger age of the CUD cohort, as fewer patients qualified for Medicare coverage. 25 , 33 In addition, cannabis retailers are disproportionately concentrated in lower-income communities, where retailer density has been reported to be up to 2.5 times higher than in higher-income areas. 34 , 35 Taken together, these findings highlight the importance of targeted public health strategies aimed at improving screening, intervention, and access to treatment resources for socioeconomically disadvantaged populations. With respect to comorbidity profile, patients with CUD demonstrated higher rates of psychiatric illness, polysubstance use, and select chronic medical conditions. The increased prevalence of anxiety and depression is consistent with extensive literature describing a bidirectional relationship between cannabis use and mental health disorders. 36 , 37 Cannabis is frequently used as a coping strategy for psychiatric symptoms, a pattern consistently observed in epidemiologic studies of CUD populations. 38 , 39 Elevated rates of alcohol, opioid, and tobacco use disorders likely reflect shared behavioral and neurobiological risk factors 37 , 40 , including impaired inhibitory control and overlapping reward pathways, as well as broader socioeconomic vulnerabilities. Higher rates of chronic obstructive pulmonary disease and hepatitis among CUD patients may reflect increased inhalational and substance-related exposures 41 , whereas lower prevalence of atrial fibrillation, diabetes, and endometrial hyperplasia likely reflects the younger age of the CUD cohort. These comorbidities are clinically relevant in the perioperative setting, as psychiatric illness, substance use, and physiologic stress have each been associated with impaired postoperative recovery, increased pain, and delayed wound healing. 42 – 46 This is particularly relevant for patients undergoing hysterectomy, a procedure that can be accompanied by heightened psychological stress, hormonal changes, and shifts in reproductive or gender identity, potentially amplifying vulnerability in patients with preexisting CUD and psychiatric comorbidity. Although unadjusted analyses demonstrated higher rates of blood transfusion and respiratory complications among patients with CUD, these associations were not sustained after propensity score matching, suggesting that baseline demographic and comorbidity differences accounted for the observed findings. These findings are consistent with prior studies in abdominal surgery populations showing that cannabis use is not independently associated with increased postoperative complication rates. 18 , 46 – 48 However, prior work has suggested that while complication incidence may be similar, complication severity may be greater among cannabis users 46 , highlighting an important distinction that warrants further investigation. Future studies should explore how cannabis dosage, chronicity, and patterns of use influence postoperative outcomes across surgical populations. Despite similar postoperative complication rates, patients with CUD experienced significantly longer hospital stays and higher total hospital charges. While existing literature on length of stay remains mixed, there is consistent evidence linking CUD to increased healthcare utilization and hospital costs. 15 , 16 , 49 These differences may reflect higher perioperative resource use, particularly related to pain management, as patients with CUD have been shown to report higher postoperative pain scores 8 , 50 , 51 and require greater opioid doses. 6 , 52 However, one must also recognize hospital charges may not accurately reflect true healthcare costs or reimbursements, as they are influenced by institutional billing practices, regional variation, negotiated payer rates, and accounting practices, rather than actuarial resources utilized during hospitalization. Clinically, these findings highlight the importance of recognizing CUD as a factor influencing perioperative resource needs, individualized pain management strategies, and discharge planning. Although a statistically significant difference in discharge disposition was observed, it is unlikely to be clinically meaningful, as the majority of patients in both cohorts were discharged home. This study has limitations inherent to large registry-based analyses. The NIS relies on administrative coding, which is subject to misclassification, underreporting, and inconsistent documentation. 53 , 54 The database also lacks granular clinical details, including cannabis use patterns, laboratory data, and post-discharge outcomes, limiting assessment to immediate inpatient events. As such, this precludes the assessment of post-discharge complications, readmissions, or long-term recovery. Additionally, the analysis was restricted to patients undergoing TAH for benign indications, excluding minimally invasive approaches and malignancy-related procedures, which may limit generalizability to contemporary hysterectomy populations and outpatient surgical settings. Despite these limitations, this study has notable strengths in both design and scope. To the authors’ knowledge, it represents the largest national analysis examining demographic and epidemiologic characteristics of patients with CUD undergoing TAH. The large sample size, extended study period, procedure-specific focus, and use of survey-weighted analyses and propensity score matching strengthen the validity of the findings. Moreover, the use of survey-weighted analyses and propensity score matching allowed for adjustment across a broad range of demographic factors and medical comorbidities, improving the accuracy of postoperative complication comparisons and reducing confounding. 12 , 14 Collectively, these results may help gynecologists, perioperative teams, and public health professionals better understand the implications of CUD in gynecologic surgery and inform risk stratification, resource allocation, and perioperative care planning. Abbreviations CUD cannabis use and dependence TAH total abdominal hysterectomy NIS National Inpatient Sample Declarations Ethics approval and consent to participate: Not applicable. IRB review was not required under 45 CFR 46.104(d)(4). Consent for publication: Not applicable Availability of data and materials: The datasets generated and analyzed during the current study are available through the National Inpatient Sample (NIS), which is a publicly available inpatient database in the United States. The database can be obtained through the following website: https://hcup-us.ahrq.gov/db/nation/nis/nisdbdocumentation.jsp. Competing interests: The authors declare that they have no competing interests. Funding: No funding was received for this project. Authors’ contributions: DR conceived the study, developed and executed the study design, and drafted the manuscript. DM managed the data and contributed to manuscript writing and revisions. MG and ERE contributed to writing the manuscript. LC provided substantial edits and critical revisions to the manuscript. IHH served as the principal investigator, oversaw the study design, and provided manuscript revisions. All authors reviewed the manuscript. 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Perioperative cannabis use: a longitudinal study of associated clinical characteristics and surgical outcomes. Reg Anesth Pain Med. 2021;46(2):137–44. 10.1136/rapm-2020-101812 . Shah S, Schwenk ES, Sondekoppam RV, et al. ASRA Pain Medicine consensus guidelines on the management of the perioperative patient on cannabis and cannabinoids. Reg Anesth Pain Med. 2023;48(3):97–117. 10.1136/rapm-2022-104013 . Khera R, Krumholz HM. With Great Power Comes Great Responsibility: Big Data Research from the National Inpatient Sample. Circ Cardiovasc Qual Outcomes. 2017;10(7). 10.1161/CIRCOUTCOMES.117.003846 . Pass HI. Medical registries: Continued attempts for robust quality data. Journal of Thoracic Oncology . 2010;5(6 SUPPL. 2). 10.1097/JTO.0b013e3181dcf957 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 30 Apr, 2026 Reviewers invited by journal 16 Mar, 2026 Editor assigned by journal 15 Mar, 2026 Submission checks completed at journal 15 Mar, 2026 First submitted to journal 07 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9058918","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607108513,"identity":"f0204c49-1e2e-4012-88ad-a50bc9f6b031","order_by":0,"name":"Dr. Dalia Rahmon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDCCAwxsIIqHX4LxGWlaZCRnMJuRpsXG4AaxWvhuH3726EbFHR7j281sD38w2OTLOxDQInkuzdw458wzHrM7h9mNeRjSLDceIKDF4AyDmXRu22Eesxv5x6QZGA4bGDYQ1ML+DazFeEYym+QP4rTwQGwxkEhmk+ABapEnoINB8gxPmXTOmcM8EjeS2aR5DNIMDAhp4TvDvk06p+KwPT/YYRU2BvKEHIbuTiA6QJoWICDVllEwCkbBKBj+AADUYDruHhxl0gAAAABJRU5ErkJggg==","orcid":"","institution":"Henry Ford Hospital","correspondingAuthor":true,"prefix":"Dr.","firstName":"Dalia","middleName":"","lastName":"Rahmon","suffix":""},{"id":607108514,"identity":"0e246611-b7ec-4bb5-8da6-19dc09411bb5","order_by":1,"name":"Diana Mansour","email":"","orcid":"","institution":"Oakland University","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"","lastName":"Mansour","suffix":""},{"id":607108515,"identity":"04aff114-6fce-4969-9389-11cfc3df363e","order_by":2,"name":"Megan Guiles","email":"","orcid":"","institution":"Oakland University","correspondingAuthor":false,"prefix":"","firstName":"Megan","middleName":"","lastName":"Guiles","suffix":""},{"id":607108516,"identity":"8db80a57-3ea9-4e61-8f44-4d2fb3d85098","order_by":3,"name":"Emilia Rodriguez Espinoza","email":"","orcid":"","institution":"Oakland University","correspondingAuthor":false,"prefix":"","firstName":"Emilia","middleName":"Rodriguez","lastName":"Espinoza","suffix":""},{"id":607108519,"identity":"3bf4b926-8919-43b6-ab76-bfa71dd52f9f","order_by":4,"name":"Dr. Inaya Hajj Hussein","email":"","orcid":"","institution":"Oakland University","correspondingAuthor":false,"prefix":"Dr.","firstName":"Inaya","middleName":"Hajj","lastName":"Hussein","suffix":""},{"id":607108524,"identity":"7c9283b6-85d5-4f8f-af8d-b975bbc4417c","order_by":5,"name":"Dr. Lena Carr","email":"","orcid":"","institution":"Henry Ford Hospital","correspondingAuthor":false,"prefix":"Dr.","firstName":"Lena","middleName":"","lastName":"Carr","suffix":""}],"badges":[],"createdAt":"2026-03-07 13:54:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9058918/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9058918/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105034575,"identity":"d2572e95-f8b2-48f5-bf48-25cd91eae870","added_by":"auto","created_at":"2026-03-20 07:23:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":668203,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9058918/v1/a43c0e74-7df5-4606-a5d8-6ff4f4f4fb9c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive analysis of cannabis use and dependence in the setting of total abdominal hysterectomy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eApproximately 22% of the United States population uses cannabis, making it the most commonly used illicit drug in the country and worldwide.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Widespread legalization for recreational and medical use has contributed to increasing rates of cannabis use and dependence (CUD), particularly among surgical patients, in whom a threefold increase has been observed in recent years.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eCannabis contains multiple active compounds, most notably delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), which exert physiologic effects through the endocannabinoid system.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e These compounds have demonstrated potential in modulating nociceptive and inflammatory pathways,\u003csup\u003e5\u003c/sup\u003e and are therefore frequently used in pain management. However, the interaction between cannabis use and postoperative pain control remains incompletely understood, with existing studies yielding conflicting results. Emerging evidence suggests that CUD may be associated with higher postoperative pain scores and increased opioid requirements following major surgery\u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, though data specific to gynecologic surgery are limited.\u003c/p\u003e \u003cp\u003eHysterectomy is among the most frequently performed surgical procedures worldwide, with common indications including abnormal uterine bleeding, leiomyomata, adenomyosis, endometriosis, and gynecologic malignancy.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e It may be performed using abdominal or minimally invasive approaches, and its prevalence has been associated with increasing age, higher body mass index, Black race, and tobacco use.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs cannabis decriminalization and social acceptance have increased patient disclosure, understanding the impact of CUD on postoperative outcomes following hysterectomy has become increasingly important. While prior studies have broadly examined substance use in surgical populations, large-scale, population-based research focused specifically on CUD in gynecologic surgery remains limited. Therefore, this study aims to evaluate epidemiologic trends, demographic characteristics, comorbidities, and immediate clinical and economic outcomes among patients with CUD undergoing total abdominal hysterectomy (TAH).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis retrospective cohort study utilized discharge data from the National Inpatient Sample (NIS), the largest publicly available all-payer inpatient database in the United States. The NIS, developed by the Healthcare Cost and Utilization Project (HCUP), provides nationally representative estimates of inpatient utilization, costs, and outcomes.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e All analyses were evaluated in accordance with recommendations from the Agency for Healthcare Research and Quality (AHRQ).\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePatients who underwent TAH between 2016 and 2021 were identified using ICD-10 procedure codes. The study population was divided into patients with and without CUD. CUD was defined using ICD-10-CM codes F12.1, F12.2, and F12.9, representing cannabis abuse, dependence, and unspecified use. Comorbidities and in-hospital complications were identified using corresponding ICD-10 codes. Patients younger than 40 years were excluded to minimize inclusion of atypical indications for hysterectomy and to improve cohort homogeneity. Patients who underwent laparoscopic hysterectomy were also excluded.\u003c/p\u003e \u003cp\u003eContinuous variables were compared using \u003cem\u003et\u003c/em\u003e-tests, whereas categorical variables were analyzed using Rao-Scott chi-square tests. Propensity score matching based on age and medical comorbidities was performed to assess postoperative complications.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses accounted for the complex survey design of the NIS and were conducted using SAS version 9.4. This study used publicly available, de-identified data from the NIS and was determined to be not human subject research according to institutional policy; therefore, IRB review was not required under 45 CFR 46.104(d)(4).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTrends in CU by Year\u003c/h2\u003e \u003cp\u003eFrom 2016 to 2021, an estimated 557,055 patients underwent TAH, of whom 0.50% were identified with CUD. Although the total number of TAH procedures decreased by 33.7% during the study period, no significant association was observed between CUD prevalence and year (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.906). Annual CUD prevalence remained stable, ranging from 0.51% to 0.53% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTrends in CUD rate per year\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCUD (%Rate)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,805)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-CUD (%Rate)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;554,250)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e615 (0.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114,500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e540 (0.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104,400\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e495 (0.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95,305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e415 (0.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90,270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e350 (0.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73,875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e390 (0.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75,900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDemographic Factors\u003c/h3\u003e\n\u003cp\u003ePatients with CUD were significantly younger than those without (mean age 49.4 vs. 53.0 years, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). While White patients constituted the largest racial group in both cohorts, patients with CUD were more likely to be Black (38.7% vs. 23.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or Native American (0.5% vs. 0.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). CUD patients were also more frequently insured by Medicaid (43.1% vs. 15.2%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or self-pay (8.2% vs. 3.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic factors, stratified by CUD vs. non-CUD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCUD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,805)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-CUD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;554,250)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAverage age of patient (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (standard error)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.4 (0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.0 (0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eRace*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian/Pacific Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.54%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNative American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.55%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePrimary Payor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedicare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedicaid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate Insurance/HMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-Pay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.56%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.74%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Race was reported as documented in administrative records and may be subject to misclassification.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eComorbidities Stratified by CUD\u003c/h3\u003e\n\u003cp\u003ePatients with CUD had substantially higher rates of polysubstance use, including alcohol use disorder (7.3% vs. 0.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), opioid use disorder (3.4% vs. 0.2%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and tobacco use disorder (50.8% vs. 9.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). They also demonstrated increased prevalence of anxiety (23.9% vs. 11.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), depression (16.6% vs. 8.8%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), COPD (7.5% vs. 2.6%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hepatitis (2.3% vs. 0.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and obesity (26.6% vs. 22.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032). Conversely, CUD was associated with lower prevalence of atrial fibrillation (0.9% vs. 2.2%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037), diabetes (9.5% vs. 13.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), and endometrial hyperplasia (3.7% vs. 6.4%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), likely reflecting the younger age of this cohort (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComorbidities, stratified by CUD vs. non-CUD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCUD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,805)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-CUD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;554,250)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal uterine bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus (Type 1 or 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrial hyperplasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.74%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometriosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.72%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOpioid use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTobacco use disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eComplications, Economic, and Discharge Dispositions\u003c/h3\u003e\n\u003cp\u003eUnadjusted analyses showed higher rates of blood transfusion and respiratory complications among patients with CUD; however, these differences were not sustained after propensity score matching (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Patients with CUD experienced significantly longer hospitalizations (4.6 vs. 3.5 days, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher total hospital charges (\u003cspan\u003e$\u003c/span\u003e72,078 vs. \u003cspan\u003e$\u003c/span\u003e62,610, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.003). Although discharge disposition differed statistically, the majority of patients in both cohorts were discharged home.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComplications, economic, and disposition outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCUD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,805)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-CUD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;554,250)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBlood transfusion*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.66%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.29%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCardiac complications*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGenitourinary complications*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIleus / small bowel obstruction*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eRespiratory complications*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.76%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVenous thrombotic embolism (VTE)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLength of stay (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal charges (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e72,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e62,610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eDischarge disposition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRehab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeceased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003e*Represents weighted analysis\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a large, nationally representative assessment of CUD among patients undergoing TAH in the United States. Prior research has examined cannabis use in surgical populations, particularly in major abdominal and arthroplasty procedures.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e However, to our knowledge, no prior studies have specifically evaluated inpatient trends among gynecologic surgical patients with CUD.\u003c/p\u003e \u003cp\u003eDespite an approximately 33% decline in the overall volume of TAH during the study period, no significant association was observed between CUD prevalence and year. The decline in abdominal hysterectomy volume is consistent with national trends reflecting increased adoption of minimally invasive and robotic-assisted approaches.\u003csup\u003e\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Notably, although national surveys report increasing cannabis use in the general population and among gynecologic patients specifically\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, the prevalence of CUD in this patient cohort remained stable at approximately 0.5%, comparable to rates reported in other inpatient studies.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e This discrepancy may reflect underrecognition or underdocumentation of cannabis use by medical providers\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, highlighting the need for improved screening and documentation practices in surgical populations.\u003c/p\u003e \u003cp\u003eDemographic analyses demonstrated that patients with CUD were significantly younger than those without CUD, consistent with population-based data showing higher rates of cannabis use among younger adults.\u003csup\u003e\u003cspan additionalcitationids=\"CR26 CR27 CR28\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e This pattern likely reflects generational differences in social acceptance, evolving legalization policies, and shifting perceptions of risks associated with cannabis use\u003c/p\u003e \u003cp\u003eWith respect to race and ethnicity, although White patients comprised the largest proportion of both cohorts, patients with CUD were more likely to be Black or Native American. This finding aligns with prior literature documenting racial and ethnic disparities in substance use diagnoses and documentation.\u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e One study reported the highest prevalence of CUD among Black and Native American populations, attributing this to higher rates of daily cannabis use\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, which may increase susceptibility to developing dependence. However, these findings should be interpreted with caution, as CUD diagnosis and reporting may be influenced by clinician implicit bias and variability in documentation practices. Such factors may contribute to the apparent overrepresentation of certain racial groups, rather than reflecting true differences in disease prevalence.\u003c/p\u003e \u003cp\u003eSeveral factors may contribute to these disparities, including socioeconomic inequities, differential access to healthcare, structural racism, and clinician bias in screening and coding practices. Prior studies suggest that substance use disorders may be more frequently documented among minority populations despite similar prevalence across racial groups, underscoring the need for equitable and standardized screening practices.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Additionally, clinician bias may influence not only the diagnosis and documentation, but also access to treatment. For example, despite higher prevalence of CUD among Black patients, this population has been shown to receive treatment less frequently and to report greater unmet treatment needs compared to White patients.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePatients with CUD undergoing TAH were also more likely to have Medicaid coverage or be self-pay. This finding is consistent with prior studies demonstrating higher prevalence of cannabis use among lower-income populations and may partially reflect the younger age of the CUD cohort, as fewer patients qualified for Medicare coverage.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e In addition, cannabis retailers are disproportionately concentrated in lower-income communities, where retailer density has been reported to be up to 2.5 times higher than in higher-income areas.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Taken together, these findings highlight the importance of targeted public health strategies aimed at improving screening, intervention, and access to treatment resources for socioeconomically disadvantaged populations.\u003c/p\u003e \u003cp\u003eWith respect to comorbidity profile, patients with CUD demonstrated higher rates of psychiatric illness, polysubstance use, and select chronic medical conditions. The increased prevalence of anxiety and depression is consistent with extensive literature describing a bidirectional relationship between cannabis use and mental health disorders.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Cannabis is frequently used as a coping strategy for psychiatric symptoms, a pattern consistently observed in epidemiologic studies of CUD populations.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Elevated rates of alcohol, opioid, and tobacco use disorders likely reflect shared behavioral and neurobiological risk factors\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, including impaired inhibitory control and overlapping reward pathways, as well as broader socioeconomic vulnerabilities.\u003c/p\u003e \u003cp\u003eHigher rates of chronic obstructive pulmonary disease and hepatitis among CUD patients may reflect increased inhalational and substance-related exposures\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, whereas lower prevalence of atrial fibrillation, diabetes, and endometrial hyperplasia likely reflects the younger age of the CUD cohort. These comorbidities are clinically relevant in the perioperative setting, as psychiatric illness, substance use, and physiologic stress have each been associated with impaired postoperative recovery, increased pain, and delayed wound healing.\u003csup\u003e\u003cspan additionalcitationids=\"CR43 CR44 CR45\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e This is particularly relevant for patients undergoing hysterectomy, a procedure that can be accompanied by heightened psychological stress, hormonal changes, and shifts in reproductive or gender identity, potentially amplifying vulnerability in patients with preexisting CUD and psychiatric comorbidity.\u003c/p\u003e \u003cp\u003eAlthough unadjusted analyses demonstrated higher rates of blood transfusion and respiratory complications among patients with CUD, these associations were not sustained after propensity score matching, suggesting that baseline demographic and comorbidity differences accounted for the observed findings. These findings are consistent with prior studies in abdominal surgery populations showing that cannabis use is not independently associated with increased postoperative complication rates.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e However, prior work has suggested that while complication incidence may be similar, complication severity may be greater among cannabis users\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, highlighting an important distinction that warrants further investigation. Future studies should explore how cannabis dosage, chronicity, and patterns of use influence postoperative outcomes across surgical populations.\u003c/p\u003e \u003cp\u003eDespite similar postoperative complication rates, patients with CUD experienced significantly longer hospital stays and higher total hospital charges. While existing literature on length of stay remains mixed, there is consistent evidence linking CUD to increased healthcare utilization and hospital costs.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e These differences may reflect higher perioperative resource use, particularly related to pain management, as patients with CUD have been shown to report higher postoperative pain scores\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e and require greater opioid doses.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e However, one must also recognize hospital charges may not accurately reflect true healthcare costs or reimbursements, as they are influenced by institutional billing practices, regional variation, negotiated payer rates, and accounting practices, rather than actuarial resources utilized during hospitalization. Clinically, these findings highlight the importance of recognizing CUD as a factor influencing perioperative resource needs, individualized pain management strategies, and discharge planning. Although a statistically significant difference in discharge disposition was observed, it is unlikely to be clinically meaningful, as the majority of patients in both cohorts were discharged home.\u003c/p\u003e \u003cp\u003eThis study has limitations inherent to large registry-based analyses. The NIS relies on administrative coding, which is subject to misclassification, underreporting, and inconsistent documentation.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e The database also lacks granular clinical details, including cannabis use patterns, laboratory data, and post-discharge outcomes, limiting assessment to immediate inpatient events. As such, this precludes the assessment of post-discharge complications, readmissions, or long-term recovery. Additionally, the analysis was restricted to patients undergoing TAH for benign indications, excluding minimally invasive approaches and malignancy-related procedures, which may limit generalizability to contemporary hysterectomy populations and outpatient surgical settings.\u003c/p\u003e \u003cp\u003eDespite these limitations, this study has notable strengths in both design and scope. To the authors\u0026rsquo; knowledge, it represents the largest national analysis examining demographic and epidemiologic characteristics of patients with CUD undergoing TAH. The large sample size, extended study period, procedure-specific focus, and use of survey-weighted analyses and propensity score matching strengthen the validity of the findings. Moreover, the use of survey-weighted analyses and propensity score matching allowed for adjustment across a broad range of demographic factors and medical comorbidities, improving the accuracy of postoperative complication comparisons and reducing confounding.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Collectively, these results may help gynecologists, perioperative teams, and public health professionals better understand the implications of CUD in gynecologic surgery and inform risk stratification, resource allocation, and perioperative care planning.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCUD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecannabis use and dependence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTAH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etotal abdominal hysterectomy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Inpatient Sample\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Not applicable. IRB review was not required under 45 CFR 46.104(d)(4).\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The datasets generated and analyzed during the current study are available through the National Inpatient Sample (NIS), which is a publicly available inpatient database in the United States. The database can be obtained through the following website: https://hcup-us.ahrq.gov/db/nation/nis/nisdbdocumentation.jsp.\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding: No funding was received for this project. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions: DR conceived the study, developed and executed the study design, and drafted the manuscript. DM managed the data and contributed to manuscript writing and revisions. MG and ERE contributed to writing the manuscript. LC provided substantial edits and critical revisions to the manuscript. IHH served as the principal investigator, oversaw the study design, and provided manuscript revisions. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: We would like to acknowledge Jacob Keeley for his contributions to the statistical analysis of this project.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDegenhardt L, Ferrari AJ, Calabria B, et al. The Global Epidemiology and Contribution of Cannabis Use and Dependence to the Global Burden of Disease: Results from the GBD 2010 Study. 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Medical registries: Continued attempts for robust quality data. \u003cem\u003eJournal of Thoracic Oncology\u003c/em\u003e. 2010;5(6 SUPPL. 2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/JTO.0b013e3181dcf957\u003c/span\u003e\u003cspan address=\"10.1097/JTO.0b013e3181dcf957\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"journal-of-cannabis-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcan","sideBox":"Learn more about [Journal of Cannabis Research](https://jcannabisresearch.biomedcentral.com/)","snPcode":"42238","submissionUrl":"https://submission.springernature.com/new-submission/42238/3","title":"Journal of Cannabis Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"cannabis use, substance use, total abdominal hysterectomy","lastPublishedDoi":"10.21203/rs.3.rs-9058918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9058918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWidespread legalization of cannabis has been associated with an increased prevalence of cannabis use and dependence (CUD) among surgical patients. This study examines the demographic characteristics, comorbidities, and inpatient outcomes of patients with CUD undergoing total abdominal hysterectomy (TAH).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eretrospective cohort study utilized the National Inpatient Sample (2016\u0026ndash;2021) to identify patients undergoing TAH. Patients were stratified into CUD and non-CUD cohorts. Demographics, comorbidities, in-hospital complications, and economic outcomes were compared using \u003cem\u003et\u003c/em\u003e-tests and chi-square analyses. Propensity score matching was performed to assess postoperative complications.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 557,055 TAH procedures, 0.50% involved patients with CUD. Compared with non-CUD patients, those with CUD were younger (49 vs. 53 years), more often Black (38.7% vs. 23.8%) or Native American (0.5% vs. 0.4%), and more frequently insured by Medicaid (43.1% vs. 15.2%). Patients with CUD experienced longer hospitalizations (4.6 vs. 3.5 days) and higher total charges (\u003cspan\u003e$\u003c/span\u003e72,078 vs. \u003cspan\u003e$\u003c/span\u003e62,610). They also had higher rates of comorbid substance use, including alcoholism (7.3% vs. 0.5%), opioid use disorder (3.4% vs. 0.2%), and tobacco use disorder (50.8% vs. 9.7%), as well as anxiety (23.9% vs. 11.5%), depression (16.6% vs. 8.8%). After propensity score matching, CUD was not associated with increased risk of postoperative complications.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAs cannabis use rises, understanding the demographic and clinical profile of surgical patients with CUD is increasingly important. Recognition of CUD in patients undergoing hysterectomy may support more individualized perioperative planning, equitable screening practices, and optimized pain management strategies.\u003c/p\u003e","manuscriptTitle":"Comprehensive analysis of cannabis use and dependence in the setting of total abdominal hysterectomy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-18 15:06:18","doi":"10.21203/rs.3.rs-9058918/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"256619781954894383360807158149620325692","date":"2026-04-30T15:50:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-16T17:32:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T03:10:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-16T03:09:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cannabis Research","date":"2026-03-07T13:48:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cannabis-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcan","sideBox":"Learn more about [Journal of Cannabis Research](https://jcannabisresearch.biomedcentral.com/)","snPcode":"42238","submissionUrl":"https://submission.springernature.com/new-submission/42238/3","title":"Journal of Cannabis Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1253f425-94d1-4ee1-99ae-7944371e8a13","owner":[],"postedDate":"March 18th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"256619781954894383360807158149620325692","date":"2026-04-30T15:50:40+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T15:06:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-18 15:06:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9058918","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9058918","identity":"rs-9058918","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}