scholarly journals Opiate and Benzodiazepine Use during Hospitalization for Hematopoietic Stem Cell Transplantation (HSCT) Is Associated with Adverse Health Related Outcomes

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5873-5873
Author(s):  
Madiha Iqbal ◽  
Aaron C. Spaulding ◽  
Salman Ahmed ◽  
Prachi Jani ◽  
Chanel Wood ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Length Of Stay ◽  
Hematological Malignancies ◽  
Hospitalized Patients ◽  
Opioid Use ◽  
Allogeneic Transplant ◽  
Autologous Transplants ◽  
Health Related ◽  
Benzodiazepine Use ◽  
Opioid Users

Abstract INTRODUCTION: Significant burden of pain syndromes are reported in patients with hematological malignancies undergoing HSCT mostly due to underlying disease and associated treatments. Opioid analgesics and benzodiazepines are routinely used for symptomatic management in this patient population. The use of narcotic analgesics and benzodiazepines in non-transplant hospitalized patients has been shown to adversely affect health related outcomes such as length-of-stay (LOS), falls and other complications. However, there is a significant knowledge gap regarding the patterns of opioid and benzodiazepine use and their impact on health outcomes in HSCT patients. METHODS: We identified 275 patients from the year 2015-2018 who underwent HSCT (allogeneic and autologous transplants) at our center for a variety of hematological malignancies. Opioid exposure was defined in three groups of patients 1) Opioid naïve: those did not report prior use of opioid at admission and who were not prescribed opioid during hospitalization, 2) Previous Opioid users: those who reported active use of opioid at admission and continued during hospitalization 3) New Opioid users: Patients who did not report opioid use at admission but were prescribed opioid during hospitalization. Multivariable analysis was performed to identify differences in opioid status, opioid use, benzodiazepine use, disease diagnosis, Karnofsky score, gender, age, race, and marital status with associated complications (Poisson regression), emergency department visits (Logistic Regression) and length of stay (Ordinal Logistic Regression) Figure 1 and Figure 2. RESULTS: The median age of patients was 59 (range: 25-74 ) years with slight male predominance (57%). Patients undergoing autologous transplants for multiple myeloma (MM) comprised 48% of the population. The majority (72 %) were exposed to opioid during hospitalization. Ninety two percent of the opioid naïve population (28% of the total population) underwent autologous transplant. Conversely, 36% of patients undergoing autologous transplants never received opiates during hospitalization as compared to 7% of those who received an allogeneic transplant. Median morphine milligram equivalent daily dose was 3.1 mg. Median diazepam equivalent daily dosage in patients that were opiate exposed was 2.07 milligram. Of the total transplant population, 55% received benzodiazepine concurrently with opiates during hospitalization. 76 % of the population was exposed to both opioid and benzodiazepine. Twenty five percent of those who were exposed to opioid did not receive benzodiazepines. Sixty four percent of the MM patients were exposed to opioid of which majority (59%) were previous opioid users. Of the non-MM patients undergoing HSCT, 80% were exposed to opioid of which 36% were previous opioid users and 64% were new users. A wide range of complications from neutropenic fever to death, were seen in 89% of all patients (opioid users and non-users) but all the falls occurred in patients who were on opioid medications. Autologous transplant recipients had higher odds of having a greater number of complications compared to Allogeneic transplant patients (OR 1.25, 95% CI: 1.01 - 1.55, p=0.04), as well as a reduced odds of having a medium or high length of stay (OR 0.03, 95% CI: 0.02 - 0.07). Of the opioid naïve patients, 6% presented to the ED within 30 days of discharge versus 15% of those that were exposed to opiates during hospitalization. Benzodiazepine use at admission for HSCT was associated with greater odd of presenting to ED within 30 days of discharge (OR 3.94, 95% CI: 1.55-10.04) and this was more significant in patients with MM (OR 4.08, 95% CI: 1.01-16.44). Finally, we also saw a trend towards longer stay in patients who were exposed to opioids as compared to opioid naïve (40% vs. 17%). CONCLUSION: Our study, albeit limited due to its retrospective design, is among the first to report the patterns of use and the impact of opioids and benzodiazepines in patients undergoing HSCT. Our results indicate that the use of these medications is frequent in this population and as in the non-transplant hospitalized patients and is associated with more emergency room visits post discharge, along with other potentially adverse outcomes. Disclosures Kharfan-Dabaja: Incyte Corp: Speakers Bureau; Seattle Genetics: Speakers Bureau; Alexion Pharmaceuticals: Speakers Bureau. Ailawadhi:Amgen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy; Janssen: Consultancy.

scholarly journals Hospitalization and Combined Use of Opioids, Benzodiazepines, and Muscle Relaxants in the United States

2019 ◽  
Vol 55 (5) ◽  
pp. 286-291
Author(s):  
Jonathan H. Watanabe ◽  
Jincheng Yang
Keyword(s):  
United States ◽  
Logistic Regression ◽  
Longitudinal Analysis ◽  
Muscle Relaxant ◽  
The United States ◽  
Muscle Relaxants ◽  
Medical Expenditure ◽  
Benzodiazepine Use ◽  
Opioid Users ◽  
Triple Threat

Introduction: Concurrent opioid and benzodiazepine use (“double-threat”) and double-threat and muscle relaxant use (“triple-threat”) are postulated to increase morbidity versus opioids alone. Study objectives were to measure association between double- and triple-threat exposure and hospitalizations in a validated, nationally representative database of the United States. Methods: A retrospective cohort study was conducted using the 2013 and 2014 Medical Expenditure Panel Survey (MEPS) longitudinal dataset and affiliated Prescribed Medicines Files. Association between 2013 and 2014 double- and triple-threat exposures and outcome of hospitalizations compared to nonusers, opioid users, and all combinations were assessed via logistic regression. The cohort surveyed in MEPS has been weighted to be reflective of the actual US population in the years 2013 and 2014. Logistic regression applying the subject-level MEPS survey weights was performed to measure association via odds ratios (ORs) of medication exposures with the outcome of all-cause hospitalization. Study subjects were categorized into exposure groups as nonusers (nonuse of opioids, benzodiazepines, or muscle relaxants), opioid users, benzodiazepine users, muscle relaxant users, “double-threat” users, and “triple-threat” users. Analyses were conducted using RStudio® 1.1.5 (Boston, MA) with α level = 0.05 for all comparisons. Results: Opioids, benzodiazepines, and muscle relaxants were used in 11.9% (38.4 million), 4.2% (13.5 million), and 3.4% (10.9 million) lives of the United States in 2013, respectively. Double-threat prevalence rose from 1.6% to 1.9% from 2013 to 2014. Triple-threat prevalence remained unchanged at 0.53%. Compared to nonusers, triple-threat patients increased hospitalization probability with ORs of 8.52 (95% confidence interval [CI]: 8.50-8.55) in 2013, 5.06 (95% CI: 5.04-5.08) in 2014, and 4.61 (95% CI: 4.59-4.63) in the 2013-2014 longitudinal analysis. Compared to nonusers, double-threat patients increased hospitalization probability with ORs of 5.71 (95% CI: 5.69-5.72) in 2013, 11.47 (95% CI: 11.44-11.49) in 2014, and 5.59 (95% CI: 5.57-5.60) in the longitudinal analysis. Conclusion: Concurrent opioid and benzodiazepine use and opioid, benzodiazepine, and muscle relaxant use were associated with increased hospitalization likelihood. Amplified efforts in surveillance, prescribing, monitoring, and deprescribing for concurrent opioid, benzodiazepine, and muscle relaxant use are needed to reduce this public health concern.

scholarly journals Variation Among Hospitals in the Continuity of Care for Older Hospitalized Patients: a Cross-sectional Cohort Study

2021 ◽  
Author(s):  
James S. Goodwin ◽  
Shuang Li ◽  
Jie Zhou ◽  
Yong-Fang Kuo ◽  
Ann Nattinger
Keyword(s):  
Logistic Regression ◽  
Length Of Stay ◽  
Regression Model ◽  
Continuity Of Care ◽  
Logistic Regression Model ◽  
Large Degree ◽  
Patient Characteristics ◽  
Hospitalized Patients ◽  
Cross Sectional ◽  
The Impact

Abstract Background: Little is known about how continuity of care for hospitalized patients varies among hospitals. We describe the number of different general internal medicine physicians seeing hospitalized patients during a medical admission and how that varies by hospital. Methods: We conducted a retrospective study of a national 20% sample of Medicare inpatients from 01/01/16 to 12/31/18. In patients with routine medical admissions (length of stay of 3-6 days, no Intensive Care Unit stay, and seen by only one generalist per day), we assessed odds of receiving all generalist care from one generalist. We calculated rates for each hospital, adjusting for patient and hospital characteristics in a multi-level logistic regression model. Results: Among routine medical admissions with 3- to 6-day stays, only 43.1% received all their generalist care from the same physician. In those with a 3-day stay, 50.1% had one generalist providing care vs. 30.8% in those with a 6-day stay. In a two-level (admission and hospital) logistic regression model controlling for patient characteristics and length of stay, the odds of seeing just one generalist did not vary greatly by patient characteristics such as age, race/ethnicity, comorbidity or reason for admission. There were large variations in continuity of care among different hospitals and geographic areas. In the highest decile of hospitals, the adjusted mean percentage of patients receiving all generalist care from one physician was >84.1%, vs. <24.1% in the lowest decile. This large degree of variation persisted when hospitals were stratified by size, ownership, location or teaching status. Conclusions: Continuity of care provided by generalist physicians to medical inpatients varies widely among hospitals. The impact of this variation on quality of care is unknown.

Pre-operative opioid use in gynecologic oncology: a common comorbidity relevant to the peri-operative period

2019 ◽  
Vol 29 (9) ◽  
pp. 1411-1416
Author(s):  
Megan Elizabeth Ross ◽  
Lindsay J Wheeler ◽  
Dina M Flink ◽  
Carolyn Lefkowits
Keyword(s):  
Length Of Stay ◽  
Gynecologic Oncology ◽  
Oral Morphine ◽  
Opioid Use ◽  
Oncology Patients ◽  
Opioid Prescription ◽  
Operative Outcomes ◽  
Operative Planning ◽  
Opioid Users ◽  
The Relationship

ObjectivesPre-operative opioid use is common and should be considered a comorbidity among surgical candidates. Our objective was to describe the rate of pre-operative opioid use and patterns of post-operative outpatient opioid prescribing in a cohort of gynecologic oncology patients.MethodsA retrospective cohort study was conducted with 448 gynecologic oncology surgical patients undergoing surgery for a suspected or known cancer diagnosis from January 2016 to December 2016. Pre-operative opioid users (n=97) were identified. Patient and surgical characteristics were abstracted, as was post-operative opioid prescription (type of opioid, oral morphine equivalents amount) and length of stay. For pre-operative opioid users, the type of opioid prescribed post-operatively was compared with the type of pre-operative opioid. Pre-operative opioid users were compared with non-users, stratified by surgery type. Descriptive statistics were analyzed using χ2 statistic, and medians were compared using a Mann-Whitney U statistic.ResultsPre-operative opioid prescriptions were noted in 21% of patients, and 24% of these had two or more opioid prescriptions before surgery. The majority of pre-operative opioid users (51%) were maintained on the same agent post-operatively at the time of discharge, but 36% were switched to a different opioid and 7% were prescribed an additional opioid. Overall and in laparotomies, pre-operative opioid users received higher volume post-operative prescriptions than non-users. There was no difference in post-operative prescription volume for minimally invasive surgeries or in length of stay between pre-operative users and non-users.ConclusionsPre-operative opioid use is common in gynecologic oncology patients and should be considered during pre-operative planning. Pre-operative opioid use was associated with a higher volume and wider range of post-operative prescription. Over 40% of opioid users were discharged with either an additional opioid or a new opioid, highlighting a potential missed opportunity to optimize opioid safety. Further research is needed to characterize the relationship between pre-operative opioid use and peri-operative outcomes and to develop strategies to manage pain effectively in this population without compromising opioid safety.

scholarly journals Effect of Preoperative Opioid Use on Adverse Outcomes, Medical Spending, and Persistent Opioid Use Following Elective Total Joint Arthroplasty in the United States: A Large Retrospective Cohort Study of Administrative Claims Data

Pain Medicine ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 521-531 ◽  
Author(s):  
Meridith Blevins Peratikos ◽  
Hannah L Weeks ◽  
Andrew J B Pisansky ◽  
R Jason Yong ◽  
Elizabeth Ann Stringer
Keyword(s):  
Length Of Stay ◽  
Claims Data ◽  
The United States ◽  
Adverse Outcomes ◽  
Unplanned Readmission ◽  
Administrative Claims ◽  
Opioid Use ◽  
Opioid Prescription ◽  
Opioid Dose ◽  
Opioid Users

Abstract Objective Between 17% and 40% of patients undergoing elective arthroplasty are preoperative opioid users. This US study analyzed patients in this population to illustrate the relationship between preoperative opioid use and adverse surgical outcomes. Design Retrospective study of administrative medical and pharmaceutical claims data. Subjects Adults (aged 18+) who received elective total knee, hip, or shoulder replacement in 2014–2015. Methods A patient was a preoperative opioid user if opioid prescription fills occurred in two periods: 1–30 and 31–90 days presurgery. Zero-truncated Poisson (incidence rate ratio [IRR]), logistic (odds ratio [OR]), Cox (hazard ratio [HR]), and quantile regressions modeled the effects of preoperative opioid use and opioid dose, adjusted for demographics, comorbidities, and utilization. Results Among 34,792 patients (38% hip, 58% knee, 4% shoulder), 6,043 (17.4%) were preoperative opioid users with a median morphine equivalent daily dose of 32 mg. Preoperative opioid users had increased length of stay (IRR = 1.03, 95% CI = 1.02 to 1.05), nonhome discharge (OR = 1.10, 95% CI = 1.00 to 1.21), and 30-day unplanned readmission (OR = 1.43, 95% CI = 1.17 to 1.74); experienced 35% higher surgical site infection (HR = 1.35, 95% CI = 1.14 to 1.59) and 44% higher surgical revision (HR = 1.44, 95% CI = 1.21 to 1.71); had a median $1,084 (95% CI = $833 to $1334) increase in medical spend during the 365 days after discharge; and had a 64% lower rate of opioid cessation (HR = 0.34, 95% CI = 0.33 to 0.35) compared with patients not filling two or more prescriptions across periods. Conclusions Preoperative opioid users had longer length of stay, increased revision rates, higher spend, and persistent opioid use, which worsened with dose. Adverse outcomes after elective joint replacement may be reduced if preoperative opioid risk is managed through increased monitoring or opioid cessation.

scholarly journals Variation among hospitals in the continuity of care for older hospitalized patients: a cross-sectional cohort study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
James S. Goodwin ◽  
Shuang Li ◽  
Jie Zhou ◽  
Yong-Fang Kuo ◽  
Ann Nattinger
Keyword(s):  
Logistic Regression ◽  
Length Of Stay ◽  
Regression Model ◽  
Continuity Of Care ◽  
Logistic Regression Model ◽  
Large Degree ◽  
Patient Characteristics ◽  
Hospitalized Patients ◽  
Cross Sectional ◽  
The Impact

Abstract Background Little is known about how continuity of care for hospitalized patients varies among hospitals. We describe the number of different general internal medicine physicians seeing hospitalized patients during a medical admission and how that varies by hospital. Methods We conducted a retrospective study of a national 20% sample of Medicare inpatients from 01/01/16 to 12/31/18. In patients with routine medical admissions (length of stay of 3–6 days, no Intensive Care Unit stay, and seen by only one generalist per day), we assessed odds of receiving all generalist care from one generalist. We calculated rates for each hospital, adjusting for patient and hospital characteristics in a multi-level logistic regression model. Results Among routine medical admissions with 3- to 6-day stays, only 43.1% received all their generalist care from the same physician. In those with a 3-day stay, 50.1% had one generalist providing care vs. 30.8% in those with a 6-day stay. In a two-level (admission and hospital) logistic regression model controlling for patient characteristics and length of stay, the odds of seeing just one generalist did not vary greatly by patient characteristics such as age, race/ethnicity, comorbidity or reason for admission. There were large variations in continuity of care among different hospitals and geographic areas. In the highest decile of hospitals, the adjusted mean percentage of patients receiving all generalist care from one physician was > 84.1%, vs. < 24.1% in the lowest decile. This large degree of variation persisted when hospitals were stratified by size, ownership, location or teaching status. Conclusions Continuity of care provided by generalist physicians to medical inpatients varies widely among hospitals. The impact of this variation on quality of care is unknown.

scholarly journals Opioid Use in Fibromyalgia Is Associated with Negative Health Related Measures in a Prospective Cohort Study

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Mary-Ann Fitzcharles ◽  
Neda Faregh ◽  
Peter A. Ste-Marie ◽  
Yoram Shir
Keyword(s):  
Pain Relief ◽  
Occupational Status ◽  
Opioid Therapy ◽  
Favourable Outcome ◽  
Opioid Use ◽  
Health Related ◽  
Opioid Medications ◽  
Pharmacologic Treatments ◽  
Opioid Users ◽  
Cardinal Symptom

As pain is the cardinal symptom of fibromyalgia (FM), strategies directed towards pain relief are an integral component of treatment. Opioid medications comprise a category of pharmacologic treatments which have impact on pain in various conditions with best evidence for acute pain relief. Although opioid therapy other than tramadol has never been formally tested for treatment of pain in FM, these agents are commonly used by patients. We have examined the effect of opioid treatments in patients diagnosed with FM and followed longitudinally in a multidisciplinary pain center over a period of 2 years. In this first study reporting on health related measures and opioid use in FM, opioid users had poorer symptoms and functional and occupational status compared to nonusers. Although opioid users may originally have had more severe symptoms at the onset of disease, we have no evidence that these agents improved status beyond standard care and may even have contributed to a less favourable outcome. Only a formal study of opioid use in FM will clarify this issue, but until then physicians must be vigilant regarding the multiple adverse consequences of opioid therapy.

350 Opioid Use and Abuse are Associated with Use of Sedative Hypnotic Medications

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A140-A140
Author(s):  
Andrew Tubbs ◽  
Michelle Naps ◽  
Michael Grandner ◽  
Louis Rivera
Keyword(s):  
Mental Illness ◽  
Sleep Disturbance ◽  
Race Model ◽  
Prescription Opioid ◽  
Opioid Overdose ◽  
Opioid Use ◽  
Hypnotic Medication ◽  
Benzodiazepine Use ◽  
Illness Category ◽  
Opioid Users

Abstract Introduction The Department of Health and Human Services recently reported that 10.3 million people misused opioid drugs in 2018. Recent research attributed 21% of the deaths from opioid overdose to benzodiazepines. The overdose data and clinical experience show that opioid misusers commonly complain of insomnia and use hypnotic medications to self-medicate their sleep disturbance. At the same time, it remains unclear from a scientific perspective whether those who use/abuse opioids are more likely to use drugs in the sedative-hypnotic medication category. Consequently, the present study explores the relationship between comorbid use of opioids and sedative-hypnotic medications. Methods We extracted data from the 2015–2018 waves of the National Survey on Drug Use and Health (N=171,766). The primary outcome was the use of sedative-hypnotic medications, either in the z-class (zaleplon, zolpidem, eszopiclone) or sedating benzodiazepines (temazepam, flurazepam, triazolam). The primary exposures were prescription use of an opioid or abuse of an opioid (i.e., use of an illegal opioid such as heroin or misuse of a prescription opioid). Covariates included age, sex, race, income, education, and predicted mental illness category (none, mild, moderate, severe). Exposures were balanced on covariates using inverse probability of treatment weighting. Sequential binomial logistic regression estimated the association between opioid use/abuse and sedative-hypnotic use after adjusting for covariates. Results Opioid use and abuse varied by age, sex, race, education, and income (all p &lt; 0.001). When adjusted for age, sex, and race (Model 1), sedative benzodiazepine use was more common among opioid users (OR 4.4 [4.04–4.79] and opioid abusers (OR 11.9 [9.72–14.5]). The use of z-class drugs was also more prevalent in opioid users (OR 3.69 [3.48–3.89]) and abusers (OR 7.74 [6.97–8.60]). Further adjusting for income and education (Model 2) and mental illness category (Model 3) attenuated but did not eliminate these associations. Conclusion Individuals who use or abuse opioids are significantly more likely to receive a sedative-hypnotic medication, a finding that is of concern and one that also suggests that sleep disturbance is common in this population. Further research is needed to determine the underlying nature and prevalence of sleep continuity disturbances in this population. Support (if any) VA grant IK2CX000855 and I01 CX001957 (S.C.).

scholarly journals Geospatial Distribution and Predictors of Mortality in Hospitalized Patients With COVID-19: A Cohort Study

2020 ◽  
Vol 7 (10) ◽  
Author(s):  
◽  
S K Mallipattu ◽  
R Jawa ◽  
R Moffitt ◽  
J Hajagos ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Cohort Study ◽  
Length Of Stay ◽  
Regression Models ◽  
Kidney Injury ◽  
Hospital Length ◽  
Hospitalized Patients ◽  
Hospital Length Of Stay ◽  
Logistic Regression Models

Abstract Background The global coronavirus disease 2019 (COVID-19) pandemic offers the opportunity to assess how hospitals manage the care of hospitalized patients with varying demographics and clinical presentations. The goal of this study was to demonstrate the impact of densely populated residential areas on hospitalization and to identify predictors of length of stay and mortality in hospitalized patients with COVID-19 in one of the hardest hit counties internationally. Methods This was a single-center cohort study of 1325 sequentially hospitalized patients with COVID-19 in New York between March 2, 2020, to May 11, 2020. Geospatial distribution of study patients’ residences relative to population density in the region were mapped, and data analysis included hospital length of stay, need and duration of invasive mechanical ventilation (IMV), and mortality. Logistic regression models were constructed to predict discharge dispositions in the remaining active study patients. Results The median age of the study cohort (interquartile range [IQR]) was 62 (49–75) years, and more than half were male (57%) with history of hypertension (60%), obesity (41%), and diabetes (42%). Geographic residence of the study patients was disproportionately associated with areas of higher population density (rs = 0.235; P = .004), with noted “hot spots” in the region. Study patients were predominantly hypertensive (MAP &gt; 90 mmHg; 670, 51%) on presentation with lymphopenia (590, 55%), hyponatremia (411, 31%), and kidney dysfunction (estimated glomerular filtration rate &lt; 60 mL/min/1.73 m2; 381, 29%). Of the patients with a disposition (1188/1325), 15% (182/1188) required IMV and 21% (250/1188) developed acute kidney injury. In patients on IMV, the median (IQR) hospital length of stay in survivors (22 [16.5–29.5] days) was significantly longer than that of nonsurvivors (15 [10–23.75] days), but this was not due to prolonged time on the ventilator. The overall mortality in all hospitalized patients was 15%, and in patients receiving IMV it was 48%, which is predicted to minimally rise from 48% to 49% based on logistic regression models constructed to project disposition in the remaining patients on ventilators. Acute kidney injury during hospitalization (odds ratioE, 3.23) was the strongest predictor of mortality in patients requiring IMV. Conclusions This is the first study to collectively utilize the demographics, clinical characteristics, and hospital course of COVID-19 patients to identify predictors of poor outcomes that can be used for resource allocation in future waves of the pandemic.

scholarly journals Preadmission Cannabis Use Is Positively Correlated With Inpatient Opioid Dose Exposure in Hospitalized Patients With Inflammatory Bowel Diseases

2020 ◽  
Author(s):  
Rahul S Dalal ◽  
Sonali Palchaudhuri ◽  
Christopher K Snider ◽  
James D Lewis ◽  
Shivan J Mehta ◽  
...  
Keyword(s):  
Linear Regression ◽  
Length Of Stay ◽  
Symptom Relief ◽  
Hospitalized Patients ◽  
Cannabis Use ◽  
Management Approach ◽  
Opioid Use ◽  
Patient Reported ◽  
Intravenous Morphine ◽  
Inflammatory Bowel

Abstract Background Opioid use is associated with excess mortality in patients with inflammatory bowel disease (IBD). Recent data have highlighted that inpatient opioid exposure is associated with postdischarge opioid use in this population. It is unknown if preadmission use of cannabis, which is commonly used for symptom relief among patients with IBD, increases the risk for inpatient opioid exposure when patients lack access to cannabis for symptom management. We sought to determine the association between preadmission cannabis use and inpatient opioid exposure while adjusting for relevant confounders. Methods We performed a retrospective cohort study of adult patients hospitalized for IBD within a large academic health system from March 1, 2017, to April 10, 2018. Opioid exposure was calculated by converting the sum of administered opioid doses to intravenous morphine milligram equivalents and dividing by length of stay. We used multivariable linear regression to assess the association between cannabis use and inpatient opioid exposure while adjusting for confounders including IBD severity and preadmission opioid use. Results Our study included 423 IBD patients. Linear regression analysis showed a significant positive correlation between inpatient opioid exposure (intravenous morphine milligram equivalents divided by length of stay) and preadmission cannabis use (coefficient = 12.1; 95% confidence interval [CI], 2.6-21.5). Other significantly associated variables were first patient-reported pain score (coefficient = 1.3; 95% CI, 0.6-2.0) and preadmission opioid use (coefficient = 22.3; 95% CI, 17.0-27.6). Conclusions Cannabis use is positively correlated with inpatient opioid exposure after controlling for confounders. A personalized pain management approach should be considered to limit inpatient and possibly future opioid exposure among hospitalized patients with IBD who use cannabis.

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