scholarly journals 29120 Classification of Individuals Across the Spectrum of Problematic Opioid Use: Clinical Correlates and Longitudinal Associations with Mortality

Author(s):  
Victoria Powell ◽  
Colin MacLeod ◽  
Lewei A. Lin ◽  
Amy S.B. Bohnert ◽  
Pooja Lagisetty
Author(s):  
Neill Y. Li ◽  
Alexander S. Kuczmarski ◽  
Andrew M. Hresko ◽  
Avi D. Goodman ◽  
Joseph A. Gil ◽  
...  

Abstract Introduction This article compares opioid use patterns following four-corner arthrodesis (FCA) and proximal row carpectomy (PRC) and identifies risk factors and complications associated with prolonged opioid consumption. Materials and Methods The PearlDiver Research Program was used to identify patients undergoing primary FCA (Current Procedural Terminology [CPT] codes 25820, 25825) or PRC (CPT 25215) from 2007 to 2017. Patient demographics, comorbidities, perioperative opioid use, and postoperative complications were assessed. Opioids were identified through generic drug codes while complications were defined by International Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification codes. Multivariable logistic regressions were performed with p < 0.05 considered statistically significant. Results A total of 888 patients underwent FCA and 835 underwent PRC. Three months postoperatively, more FCA patients (18.0%) continued to use opioids than PRC patients (14.7%) (p = 0.033). Preoperative opioid use was the strongest risk factor for prolonged opioid use for both FCA (odds ratio [OR]: 4.91; p < 0.001) and PRC (OR: 6.33; p < 0.001). Prolonged opioid use was associated with an increased risk of implant complications (OR: 4.96; p < 0.001) and conversion to total wrist arthrodesis (OR: 3.55; p < 0.001) following FCA. Conclusion Prolonged postoperative opioid use is more frequent in patients undergoing FCA than PRC. Understanding the prevalence, risk factors, and complications associated with prolonged postoperative opioid use after these procedures may help physicians counsel patients and implement opioid minimization strategies preoperatively.


2019 ◽  
Vol 7 (7_suppl5) ◽  
pp. 2325967119S0025
Author(s):  
Anita G. Rao ◽  
Heather A. Prentice ◽  
Priscilla Hannah Chan ◽  
Liz W. Paxton ◽  
Tadashi Ted Funahashi ◽  
...  

Objectives: The misuse of opioid medication has contributed to a significant national crisis affecting public health, as well as patient morbidity and medical costs. We sought to determine baseline opioid utilization in patients undergoing ACLR and examine demographic, patient characteristics, and medical factors associated with postoperative opioid utilization. Methods: Primary elective ACLR were identified using an integrated healthcare system’s ACLR registry (January 2005-January 2015). Patients with cancer or those who had other knee surgery in the preceding year were excluded. We studied the effect of preoperative and intraoperative risks factors on number of dispensed opioid medication prescriptions (Rx) in the early (0-90 days) and late (91-360 days) postoperative periods using logit regression. Risk factors studied included: number of opioid Rx in preceding year, age, gender, race, American Society of Anesthesiologists (ASA) classification, body mass index (BMI), activity at the time of injury, time from injury to ACLR, concomitant procedure or injury, medical comorbidities, and opioid-use comorbidities. Results: Of 21202 ACLR from 20813 patients, 25.5% used at least 1 opioid Rx in the one-year preoperative period. 17.7% and 2.7% used ≥2 opioid Rx in the early and late recovery periods, respectively. The risk factors associated with greater opioid Rx in both the early and late periods included: preoperative opioid use, age >20 years, ASA classification of ≥3, other activity at the time of injury, repaired cartilage injury, chronic pulmonary disease, and substance abuse. Risk factors associated with opioid Rx use during the early period only included: other race, acute ACL injury, repaired meniscal injury, multi-ligament injury, and dementia/psychoses. Risk factors associated with greater opioid Rx during the late period included: female gender, BMI >25 kg/m2, motor vehicle accident as the mechanism of injury, and hypertension. Conclusion: We identified several risk factors for postoperative opioid usage after ACLR. The strongest predictors of postoperative prescription opioid usage after ACLR included preoperative opioid use, increasing age, ASA classification of 3 or more, other activity at the time of injury, repaired meniscal injury, cartilage repair, chronic pulmonary disease, and substance abuse. Awareness of risk factors for postoperative opioid usage may encourage more targeted utilization of opioids in pain management. Surgeons may consider additional support or referral to a pain specialist for patients with these risk factors. [Figure: see text]


2020 ◽  
Vol 55 (7) ◽  
pp. 1054-1058
Author(s):  
R. Kathryn McHugh ◽  
Amy C. Janes ◽  
Margaret L. Griffin ◽  
Nadine Taghian ◽  
Shelly F. Greenfield ◽  
...  

Author(s):  
Thien C. Pham ◽  
Courtney Kominek ◽  
Abigail Brooks ◽  
Jeffrey Fudin

Chronic pain management employing opioids is divided into subtopics, including: risk–benefit balance; a review of the mode of action of opioid analgesics (Chap. 8); the suitability of synthetic opioids for neuropathic pain; endocrinopathy proceeding from opioid use; the use of the morphine-equivalent daily dose as a conversion tool for managing multiple opioids; the place of extended-release and long-acting opioids; current technology in abuse deterrence; and an overview of the challenges entailed in prescribing. This last section details the complex components of a decision to prescribe opioids for chronic pain. A table is provided of the classification of common opioid analgesics and their duration of activity. A text box gives the table of contents of Appendix B, supportive tables and figures therein for this chapter; there is also a text box listing additional resources.


Author(s):  
Jennifer D. Ellis ◽  
Jami L. Mayo ◽  
Patrick H. Finan ◽  
Charlene E. Gamaldo ◽  
Andrew S. Huhn

Heart ◽  
2020 ◽  
pp. heartjnl-2020-317618
Author(s):  
Josef Madrigal ◽  
Yas Sanaiha ◽  
Joseph Hadaya ◽  
Puneet Dhawan ◽  
Peyman Benharash

ObjectiveWhile opioid use disorder (OUD) has been previously associated with increased morbidity and resource use in cardiac operations, its impact on readmissions is understudied.MethodsPatients undergoing coronary artery bypass grafting and valve repair or replacement, excluding infective endocarditis, were identified in the 2010–16 Nationwide Readmissions Database. Using International Classification of Diseases 9/10, we tabulated OUD and other characteristics. Multivariable regression was used to adjust for differences.ResultsOf an estimated 1 978 276 patients who had cardiac surgery, 5707 (0.3%) had OUD. During the study period, the prevalence of OUD increased threefold (0.15% in 2010 vs 0.53% in 2016, parametric trend<0.001). Patients with OUD were more likely to be younger (54.0 vs 66.0 years, p<0.001), insured by Medicaid (28.2 vs 6.2%, p<0.001) and of the lowest income quartile (33.6 vs 27.1%, p<0.001). After multivariable adjustment, OUD was associated with decreased mortality (1.5 vs 2.7%, p=0.001). Although these patients had similar rates of overall complications (36.1 vs 35.1%, p=0.363), they had increased thromboembolic (1.3 vs 0.8%, p<0.001) and infectious (4.1 vs 2.8%, p<0.001) events, as well as readmission at 30 days (19.0 vs 13.2%, p<0.001). While patients with OUD had similar hospitalisation costs ($50 766 vs $50 759, p=0.994), they did have longer hospitalisations (11.4 vs 10.3 days, p<0.001).ConclusionThe prevalence of OUD among cardiac surgical patients has steeply increased over the past decade. Although the presence of OUD was not associated with excess mortality at index hospitalisation, it was predictive of 30-day readmission. Increased attention to predischarge interventions and care coordination may improve outcomes in this population.


2017 ◽  
Vol 41 (S1) ◽  
pp. S115-S116
Author(s):  
J. García-Jiménez ◽  
A. Porras-Segovia ◽  
J.M. Gota-Garcés ◽  
J.E. Muñoz-Negro ◽  
L. Gutiérrez-Rojas

IntroductionType I and type II classification of bipolar disorder (BD) may not provide useful information to the clinician regarding epidemiological and clinical correlates.New classifications have recently been proposed, such as the Predominant Polarity (PP) classification, which is based on the tendency of the patient to relapse in the manic (Manic Predominant Polarity [MPP]) or the depressive (Depressive Predominant Polarity [DPP]) poles along the course of the disease.ObjectivesTo explore the epidemiological and clinical correlates of PP.MethodsWe performed a search of the PubMed and Web of Science databases up to June 1st 2016, using the keywords “bipolar disorder”, “polarity” and “predominant polarity”.ResultsThe initial search identified 1598 articles. Only 17 articles met inclusion criteria. Factors associated with MPP are manic onset, history of drug abuse and a better response to atypical antipsychotics and mood stabilizers. Meanwhile DPP is associated with depressive onset, more relapses, longer acute episodes, and a higher risk of suicide. Moreover, delay until diagnosis, mixed episodes and comorbid anxiety disorders are more prevalent in DPP patients, whose treatment often involves quetiapine and lamotrigine.LimitationsFew prospective studies. Variability of results.ConclusionsPP classification may be useful for the clinical management of BD. Further research in this field is needed. Future research should use standardized definitions and more comparable methods.Disclosure of interestThe authors have not supplied their declaration of competing interest.


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