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Mims MM, Parikh AC, Sandhu Z, DeMoss N, Mhawej R, Queimado L. Surgery-Related Considerations in Treating People Who Use Cannabis: A Review. JAMA Otolaryngol Head Neck Surg 2024:2822893. [PMID: 39172477 DOI: 10.1001/jamaoto.2024.2545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2024]
Abstract
Importance Cannabis use has experienced substantial growth. Many patients treated by otolaryngologists are using cannabis in various forms, often without the knowledge of the treating surgeon. These cannabinoid substances have various systemic effects, and it is critical for otolaryngologists to recognize how cannabis use may contribute to a patient's care. Observations Cannabis use has effects that contribute to every phase of a surgeon's care. Preoperative counseling for tapering use may prevent increased rates of adverse effects. Care with anesthesia must be observed due to increased rates of myocardial ischemia, higher tolerance to standard doses, and prolonged sedation. Although results of studies are mixed, there may be an association with cannabis use and postoperative pain, nausea, and vomiting. Postoperative wound healing may be improved through the use of topical cannabinoids. Significant drug-drug interactions exist with cannabis, most notably with several common anticoagulant medications. Care should be exercised when managing medications for people who use cannabis. While many people who use cannabis consume it infrequently, a substantial population has developed cannabis use disorder, which is associated with increased morbidity and mortality postoperatively. Screening for cannabis use disorder is important and can be done through short screening tools. Conclusions and Relevance Patients who use cannabis may require special attention regarding preoperative counseling and workup, intraoperative anesthesia, postoperative pain management, nausea, wound healing, and drug-drug interactions. As patient use continues to increase, otolaryngologists will find an increasing need to remain up to date on how cannabis use contributes to patient care.
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Affiliation(s)
- Mark M Mims
- Department of Otolaryngology-Head and Neck Surgery, University of Oklahoma Health Sciences Center, Oklahoma City
| | - Aniruddha C Parikh
- Department of Otolaryngology-Head and Neck Surgery, University of Oklahoma Health Sciences Center, Oklahoma City
| | - Zainab Sandhu
- University of Oklahoma Medical School, Oklahoma City
| | - Noah DeMoss
- University of Oklahoma Medical School, Oklahoma City
| | - Rachad Mhawej
- Department of Otolaryngology-Head and Neck Surgery, University of Oklahoma Health Sciences Center, Oklahoma City
| | - Lurdes Queimado
- Department of Otolaryngology-Head and Neck Surgery, University of Oklahoma Health Sciences Center, Oklahoma City
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Maskal S, Foreman JM, Ellis RC, Phillips S, Messer N, Melland-Smith M, Beffa LRA, Petro CC, Prabhu AS, Rosen MJ, Miller BT. Cannabis smoking and abdominal wall reconstruction outcomes: a propensity score-matched analysis. Hernia 2024; 28:847-855. [PMID: 38386125 PMCID: PMC11249614 DOI: 10.1007/s10029-024-02976-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/25/2024] [Indexed: 02/23/2024]
Abstract
PURPOSE Despite increasing use of cannabis, literature on perioperative effects is lagging. We compared active cannabis-smokers versus non-smokers and postoperative wound morbidity and reoperations following open abdominal wall reconstruction (AWR). METHODS Patients who underwent open, clean, AWR with transversus abdominis release and retromuscular synthetic mesh placement at our institution between January 2014 and May 2022 were identified using the Abdominal Core Health Quality Collaborative database. Active cannabis-smokers were 1:3 propensity matched to non-smokers based on demographics and comorbidities. Wound complications, 30 day morbidity, pain (PROMIS 3a-Pain Intensity), and hernia-specific quality of life (HerQles) were compared. RESULTS Seventy-two cannabis-smokers were matched to 216 non-smokers. SSO (18% vs 17% p = 0.86), SSI (11.1% vs 9.3%, p = 0.65), SSOPI (12% vs 12%, p = 0.92), and all postoperative complications (46% vs 43%, p = 0.63) were similar between cannabis-smokers and non-smokers. Reoperations were more common in the cannabis-smoker group (8.3% vs 2.8%, p = 0.041), driven by major wound complications (6.9% vs 3.2%, p = 0.004). No mesh excisions occurred. HerQles scores were similar at baseline (22 [11, 41] vs 35 [14, 55], p = 0.06), and were worse for cannabis-smokers compared to non-smokers at 30 days (30 [12, 50] vs 38 [20, 67], p = 0.032), but not significantly different at 1 year postoperatively (72 [53, 90] vs 78 [57, 92], p = 0.39). Pain scores were worse for cannabis-smokers compared to non-smokers at 30 days postoperatively (52 [46, 58] vs 49 [44, 54], p = 0.01), but there were no differences at 6 months or 1 year postoperatively (p > 0.05 for all). CONCLUSION Cannabis smokers will likely experience similar complication rates after clean, open AWR, but should be counseled that despite similar wound complication rates, the severity of their wound complications may be greater than non-smokers.
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Affiliation(s)
- S Maskal
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA.
| | - J M Foreman
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - R C Ellis
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - S Phillips
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - N Messer
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - M Melland-Smith
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - L R A Beffa
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - C C Petro
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - A S Prabhu
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - M J Rosen
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
| | - B T Miller
- General Surgery, Cleveland Clinic, 2049 E 100th St, Desk A-100, Cleveland, OH, 44106, USA
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Arina P, Kaczorek MR, Hofmaenner DA, Pisciotta W, Refinetti P, Singer M, Mazomenos EB, Whittle J. Prediction of Complications and Prognostication in Perioperative Medicine: A Systematic Review and PROBAST Assessment of Machine Learning Tools. Anesthesiology 2024; 140:85-101. [PMID: 37944114 PMCID: PMC11146190 DOI: 10.1097/aln.0000000000004764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND The utilization of artificial intelligence and machine learning as diagnostic and predictive tools in perioperative medicine holds great promise. Indeed, many studies have been performed in recent years to explore the potential. The purpose of this systematic review is to assess the current state of machine learning in perioperative medicine, its utility in prediction of complications and prognostication, and limitations related to bias and validation. METHODS A multidisciplinary team of clinicians and engineers conducted a systematic review using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Multiple databases were searched, including Scopus, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Library, PubMed, Medline, Embase, and Web of Science. The systematic review focused on study design, type of machine learning model used, validation techniques applied, and reported model performance on prediction of complications and prognostication. This review further classified outcomes and machine learning applications using an ad hoc classification system. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was used to assess risk of bias and applicability of the studies. RESULTS A total of 103 studies were identified. The models reported in the literature were primarily based on single-center validations (75%), with only 13% being externally validated across multiple centers. Most of the mortality models demonstrated a limited ability to discriminate and classify effectively. The PROBAST assessment indicated a high risk of systematic errors in predicted outcomes and artificial intelligence or machine learning applications. CONCLUSIONS The findings indicate that the development of this field is still in its early stages. This systematic review indicates that application of machine learning in perioperative medicine is still at an early stage. While many studies suggest potential utility, several key challenges must be first overcome before their introduction into clinical practice. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Pietro Arina
- Bloomsbury Institute of Intensive Care Medicine and Human Physiology and Performance Laboratory, Centre for Perioperative Medicine, Department of Targeted Intervention, University College London, London, United Kingdom
| | - Maciej R. Kaczorek
- Wellcome/EPSRC Centre of Interventional and Surgical Sciences and Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Daniel A. Hofmaenner
- Bloomsbury Institute of Intensive Care Medicine, University College London, London, United Kingdom; and Institute of Intensive Care Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Walter Pisciotta
- Bloomsbury Institute of Intensive Care Medicine, University College London, London, United Kingdom
| | - Patricia Refinetti
- Human Physiology and Performance Laboratory, Centre for Perioperative Medicine, Department of Targeted Intervention, University College London, London, United Kingdom
| | - Mervyn Singer
- Bloomsbury Institute of Intensive Care Medicine, University College London, London, United Kingdom
| | - Evangelos B. Mazomenos
- Wellcome/EPSRC Centre of Interventional and Surgical Sciences and Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - John Whittle
- Human Physiology and Performance Laboratory, Centre for Perioperative Medicine, Department of Targeted Intervention, University College London, London, United Kingdom
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Ripperger D, Atte A, Ritto F. Cannabis Users Require More Anesthetic Agents for General Anesthesia in Ambulatory Oral and Maxillofacial Surgery Procedures. J Oral Maxillofac Surg 2023; 81:1460-1465. [PMID: 37783364 DOI: 10.1016/j.joms.2023.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 09/10/2023] [Accepted: 09/10/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND The use of cannabis in the general population has steadily increased over recent years and there is limited literature regarding the anesthetic implications of chronic cannabis use, particularly in the setting of outpatient anesthesia. PURPOSE To determine whether chronic cannabis users undergoing deep sedation or general anesthesia during ambulatory procedures require more anesthetic agents than nonusers. STUDY DESIGN, SETTING, AND SAMPLE A retrospective cohort study of subjects undergoing deep sedation or general anesthesia at the Oklahoma University Oral and Maxillofacial Surgery Clinic from January to December 2022 was performed. The inclusion criteria were duration of anesthetic procedure between 15 to 40 minutes, use of propofol, fentanyl, ketamine, and midazolam, and extraction of at least 2 teeth. The exclusion criterion was patients undergoing adjunctive procedures other than extractions during sedation. PREDICTOR VARIABLE Cannabis use status was grouped as users and nonusers. A user was defined as a subject who self-reported any regular use of cannabis. OUTCOME VARIABLE The primary outcome variable was the amount of intravenous anesthetic agents administered. Secondary outcome variables included the length of the procedure and the number of teeth extracted. COVARIATES Age, sex, and the senior-most resident involved in the sedation. ANALYSES IBM SPSS was utilized to perform descriptive statistics, paired t-tests, ANOVA, and multivariate linear regression. A level of significance of 5% (P < .05) was used for all analyses. RESULTS Four hundred and ninety nine subjects were identified, 189 met the inclusion criteria, and 57 reported using cannabis. The mean age of nonusers was 28.2 ± 7.8 years and that of users was 26.6 ± 6.4 years (P = .09). Females represented 71.9% of nonusers and 72.7% of users. Cannabis users received significantly more propofol (117.5 mg ± 71.3 vs 152.5 mg ± 101.8; P = .004), midazolam (4.7 mg ± 1.0 vs 5.1 mg ± 1.5; P = .01), ketamine (40.2 mg ± 15.7 vs 46.1 mg ± 16.9; P = .01), and fentanyl (75.2 μg ± 26.3 vs 88.6 μg ± 32.8; P = .002) than nonusers, despite extracting a similar number of teeth (4.5 ± 3.1 vs 4.4 ± 3.5; P = .37) in a similar amount of time (25.5 ± 7.3 vs 27.3 ± 7.8; P = .06). CONCLUSION AND RELEVANCE Cannabis users required more propofol, midazolam, ketamine, and fentanyl than non-cannabis users during outpatient oral and maxillofacial surgery procedures.
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Affiliation(s)
- Daniel Ripperger
- Chief Resident, Department of Oral and Maxillofacial Surgery, University of Oklahoma, Oklahoma City, OK
| | - Antonio Atte
- Resident, Department of Oral and Maxillofacial Surgery, University of Oklahoma, Oklahoma City, OK
| | - Fabio Ritto
- Professor & Program Director, Department of Oral and Maxillofacial Surgery, University of Oklahoma, Oklahoma City, OK.
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Shah S, Schwenk ES, Sondekoppam RV, Clarke H, Zakowski M, Rzasa-Lynn RS, Yeung B, Nicholson K, Schwartz G, Hooten WM, Wallace M, Viscusi ER, Narouze S. ASRA Pain Medicine consensus guidelines on the management of the perioperative patient on cannabis and cannabinoids. Reg Anesth Pain Med 2023; 48:97-117. [PMID: 36596580 DOI: 10.1136/rapm-2022-104013] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 11/08/2022] [Indexed: 01/04/2023]
Abstract
BACKGROUND The past two decades have seen an increase in cannabis use due to both regulatory changes and an interest in potential therapeutic effects of the substance, yet many aspects of the substance and their health implications remain controversial or unclear. METHODS In November 2020, the American Society of Regional Anesthesia and Pain Medicine charged the Cannabis Working Group to develop guidelines for the perioperative use of cannabis. The Perioperative Use of Cannabis and Cannabinoids Guidelines Committee was charged with drafting responses to the nine key questions using a modified Delphi method with the overall goal of producing a document focused on the safe management of surgical patients using cannabinoids. A consensus recommendation required ≥75% agreement. RESULTS Nine questions were selected, with 100% consensus achieved on third-round voting. Topics addressed included perioperative screening, postponement of elective surgery, concomitant use of opioid and cannabis perioperatively, implications for parturients, adjustment in anesthetic and analgesics intraoperatively, postoperative monitoring, cannabis use disorder, and postoperative concerns. Surgical patients using cannabinoids are at potential increased risk for negative perioperative outcomes. CONCLUSIONS Specific clinical recommendations for perioperative management of cannabis and cannabinoids were successfully created.
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Affiliation(s)
- Shalini Shah
- Dept of Anesthesiology & Perioperative Care, UC Irvine Health, Orange, California, USA
| | - Eric S Schwenk
- Anesthesiology and Perioperative Medicine, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | | | - Hance Clarke
- Anesthesiology and Pain Medicine, Univ Toronto, Toronto, Ontario, Canada
| | - Mark Zakowski
- Anesthesiology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | | | - Brent Yeung
- Anesthesiology and Perioperative Care, University of California Irvine, Irvine, California, USA
| | | | - Gary Schwartz
- AABP Integrative Pain Care, Melville, New York, USA.,Anesthesiology, Maimonides Medical Center, Brooklyn, New York, USA
| | | | - Mark Wallace
- Anesthesiology, Division of Pain Medicine, University of California San Diego, La Jolla, California, USA
| | - Eugene R Viscusi
- Anesthesiology and Perioperative Medicine, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Samer Narouze
- Center for Pain Medicine, Western Reserve Hospital, Cuyahoga Falls, Ohio, USA
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Worrest T, Malibiran CC, Welshans J, Dewey E, Husain F. Marijuana use does not affect weight loss or complication rate after bariatric surgery. Surg Endosc 2022; 36:6931-6936. [PMID: 35024935 DOI: 10.1007/s00464-022-09038-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 01/03/2022] [Indexed: 11/25/2022]
Abstract
INTRODUCTION Marijuana use has been legalized in several states. It is unclear if marijuana use affects weight loss outcomes or complication rates following bariatric surgery. The purpose of this study was to determine if patients who use marijuana had higher complication rates or lower weight loss compared with non-users. METHODS All patients at a single institution who underwent primary bariatric surgery between July 2015 and July 2020 at a single institution after the legalization of marijuana within the jurisdiction were included. Data regarding marijuana use, weight and complications were abstracted retrospectively. Differences between groups were evaluated with Wilcoxon Rank-Sum tests and Fisher Freeman Halton test. Trends for marijuana use over time was evaluated with simple linear regression on summary data. RESULTS 1107 patients met inclusion criteria. 798 (73.3%) were never users, 225 (19.4%) were previous users, and 84 (7.2%) were active users. The proportion of active users and previous users increased over time, with significantly more prior marijuana use reported in more recent years (p = 0.014). Active users had significantly higher pre-procedural BMIs than never users: 48.7 vs. 46.3 (p = 0.03). Any marijuana use (active and previous users) was associated with higher preoperative weight compared to never: 136.4 kg vs. 130.6 kg (p = 0.001). Overall complication rate was low in all groups, and there was no difference in the rates of any complications. Active and previous users tended to lose less weight than never users, but this was not statistically significant (p = 0.17). CONCLUSIONS Active and prior marijuana users tend to have higher BMIs on presentation, but use was not associated with complications or percent weight loss. The incidence of patient reported marijuana use is increasing in the study population. More studies on the effects of marijuana use in this patient population are warranted.
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Affiliation(s)
- Tarin Worrest
- Division of Bariatric Surgery, Department of Surgery, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - C Cole Malibiran
- Division of Bariatric Surgery, Department of Surgery, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Jill Welshans
- Division of Bariatric Surgery, Department of Surgery, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Elizabeth Dewey
- Division of Bariatric Surgery, Department of Surgery, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Farah Husain
- Division of Bariatric Surgery, Department of Surgery, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.
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Bellini V, Valente M, Bertorelli G, Pifferi B, Craca M, Mordonini M, Lombardo G, Bottani E, Del Rio P, Bignami E. Machine learning in perioperative medicine: a systematic review. JOURNAL OF ANESTHESIA, ANALGESIA AND CRITICAL CARE 2022; 2:2. [PMCID: PMC8761048 DOI: 10.1186/s44158-022-00033-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Background Risk stratification plays a central role in anesthetic evaluation. The use of Big Data and machine learning (ML) offers considerable advantages for collection and evaluation of large amounts of complex health-care data. We conducted a systematic review to understand the role of ML in the development of predictive post-surgical outcome models and risk stratification. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, we selected the period of the research for studies from 1 January 2015 up to 30 March 2021. A systematic search in Scopus, CINAHL, the Cochrane Library, PubMed, and MeSH databases was performed; the strings of research included different combinations of keywords: “risk prediction,” “surgery,” “machine learning,” “intensive care unit (ICU),” and “anesthesia” “perioperative.” We identified 36 eligible studies. This study evaluates the quality of reporting of prediction models using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist. Results The most considered outcomes were mortality risk, systemic complications (pulmonary, cardiovascular, acute kidney injury (AKI), etc.), ICU admission, anesthesiologic risk and prolonged length of hospital stay. Not all the study completely followed the TRIPOD checklist, but the quality was overall acceptable with 75% of studies (Rev #2, comm #minor issue) showing an adherence rate to TRIPOD more than 60%. The most frequently used algorithms were gradient boosting (n = 13), random forest (n = 10), logistic regression (LR; n = 7), artificial neural networks (ANNs; n = 6), and support vector machines (SVM; n = 6). Models with best performance were random forest and gradient boosting, with AUC > 0.90. Conclusions The application of ML in medicine appears to have a great potential. From our analysis, depending on the input features considered and on the specific prediction task, ML algorithms seem effective in outcomes prediction more accurately than validated prognostic scores and traditional statistics. Thus, our review encourages the healthcare domain and artificial intelligence (AI) developers to adopt an interdisciplinary and systemic approach to evaluate the overall impact of AI on perioperative risk assessment and on further health care settings as well.
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Affiliation(s)
- Valentina Bellini
- Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
| | - Marina Valente
- General Surgery Unit, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
| | - Giorgia Bertorelli
- Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
| | - Barbara Pifferi
- Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
| | - Michelangelo Craca
- Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
| | - Monica Mordonini
- Department of Engineering and Architecture, University of Parma, Viale G.P.Usberti 181/A, 43124 Parma, Italy
| | - Gianfranco Lombardo
- Department of Engineering and Architecture, University of Parma, Viale G.P.Usberti 181/A, 43124 Parma, Italy
| | - Eleonora Bottani
- Department of Engineering and Architecture, University of Parma, Viale G.P.Usberti 181/A, 43124 Parma, Italy
| | - Paolo Del Rio
- General Surgery Unit, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
| | - Elena Bignami
- Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
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Zhang BH, Saud H, Sengupta N, Chen M, Bakshi D, Richardson L, Wang L, Shanthanna H. Effect of preoperative cannabis use on perioperative outcomes: a retrospective cohort study. Reg Anesth Pain Med 2021; 46:650-655. [PMID: 33990440 DOI: 10.1136/rapm-2021-102479] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 04/01/2021] [Accepted: 04/04/2021] [Indexed: 11/04/2022]
Abstract
INTRODUCTION The reported use of cannabis within surgical population is increasing. Cannabis use is potentially associated with increased harms and varied effects on pain control. These have important implications to perioperative care. METHODS We conducted a retrospective cohort study comparing surgical patients reporting cannabis use preoperatively to control patients with no cannabis exposure, in a 1:2 ratio. To control for confounding, we used a propensity score-matched analysis to assess the adjusted association between cannabis use and study outcomes. Our primary outcome was a composite of (1) respiratory arrest or cardiac arrest, (2) intensive care admission, (3) stroke, (4) myocardial infarction and (5) mortality during this hospital stay. Secondarily, we assessed the effects on pain control, opioid usage, induction agent dose and nausea-vomiting. RESULTS Between January 2018 and March 2019, we captured 1818 patients consisting of cannabis users (606) and controls (1212). For propensity score-matched analyses, 524 cannabis patients were compared with 1152 control patients. No difference in the incidence of composite outcome was observed (OR 1.06, 95% CI 0.23 to 3.98). Although a higher incidence of arrhythmias (2.7% vs 1.6%) and decreased incidence of nausea-vomiting needing treatment (9.6% vs 12.6%) was observed with cannabis users vs controls, results were not statistically significant. No significant differences were observed with other secondary outcomes. CONCLUSION Our results do not demonstrate a convincing association between self-reported cannabis use and major surgical outcomes or pain management. Perioperative decisions should be made based on considerations of dose, duration, and indication.
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Affiliation(s)
- Betty Huiyu Zhang
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Haris Saud
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Neil Sengupta
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Max Chen
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Devyani Bakshi
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Liz Richardson
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Li Wang
- Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada.,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Harsha Shanthanna
- Department of Anesthesia, McMaster University, Hamilton, Ontario, Canada .,Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.,Research Institute of St Joes, Hamilton, Ontario, Canada.,Michael G. DeGroote Centre for Medicinal Cannabis Research, McMaster University, Hamilton, Ontario, Canada
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