Abstract
BACKGROUND
Recent data are inconclusive regarding the risk of arrhythmias among young cannabis users. Furthermore, many young adults use both cannabis and tobacco, which could add a residual confounding effect on outcomes. So, we studied young men who have cannabis use disorder (CUD) excluding tobacco use disorder (TUD) to understand their independent association with atrial fibrillation (AF) and related outcomes.
AIM
To study the association of CUD with AF and related outcomes.
METHODS
We used weighted discharge records from National Inpatient Sample (2019) to assess the baseline characteristics and mortality rates for AF-related hospitalizations in young (18-44 years) men in 1:1 propensity-matched CUD + vs CUD- cohorts without TUD.
RESULTS
Propensity matched CUD + and CUD- cohorts consisted of 108495 young men in each arm. Our analysis showed an increased incidence of AF in black population with CUD. In addition, the CUD + cohort had lower rates of hyperlipidemia (6.4% vs 6.9%), hypertension (5.3% vs 6.3%), obesity (9.1% vs 10.9%), alcohol abuse (15.5% vs 16.9%), but had higher rates of anxiety (24.3% vs 18.4%) and chronic obstructive pulmonary disease (COPD) (9.8% vs 9.4%) compared to CUD-cohort. After adjustment with covariates including other substance abuse, a non-significant association was found between CUD + cohort and AF related hospitalizations (odd ratio: 1.27, 95% confidence interval: 0.91-1.78, P = 0.15).
CONCLUSION
Among hospitalized young men, the CUD + cohort had a higher prevalence of anxiety and COPD, and slightly higher proportion of black patients. Although there were higher odds of AF hospitalizations in CUD + cohort without TUD, the association was statistically non-significant. The subgroup analysis showed higher rates of AF in black patients. Large-scale prospective studies are required to evaluate long-term effects of CUD on AF risk and prognosis without TUD and concomitant substance abuse.
Keywords: Cannabis, Marijuana, Atrial fibrillation, Tobacco use disorder, Original research, Smoking
Core Tip: Among young hospitalized men, the cohort with Cannabis use disorder had a higher prevalence of anxiety and chronic obstructive pulmonary disease. Earlier studies have shown higher arrhythmia burden with cannabis use; however, this study population without concomitant tobacco use disorder was not associated with higher risk of atrial fibrillation when other sociodemographic and comorbid confounding variables were controlled. On subgroup analysis, blacks showed higher atrial fibrillation rates in the cannabis use disorder + arm.
INTRODUCTION
Atrial fibrillation (AF) is the most frequently encountered cardiac arrhythmia in clinical practice. Current literature suggests that AF will affect 6-12 million people in the United States by 2050 and 17.9 million people in Europe by 2060[1]. In addition, AF is associated with significant morbidity and mortality, with a significant cost of health care burden[2]. On the other hand, the association of AF with substance use disorder has shown a significant higher burden in the young population with higher substance use, including cannabis use disorder (CUD)[3]. On a worldwide scale, cannabis is one of the most highly used recreational substances, which has detrimental effects on cardiovascular health, including an established association with various types of arrhythmias, acute myocardial infarction, and stroke[4-7]. Often, CUD is associated with other substance use, and it is difficult to solely find the effect of CUD on incidence or association with AF. Considering the increasing burden of AF in society, it is mandatory to search for preventable causes of AF, which is why we sought to find an association between CUD and AF hospitalizations in young men without concomitant tobacco use disorder (TUD), which might work as a confounder if we consider its association with AF in the literature[8].
MATERIALS AND METHODS
Study data, design and population
The study utilized data from the National Inpatient Sample (2019) to identify hospital admissions of young men (age 18-44 years) in the United States with AF. The NIS dataset, which is a component of the Healthcare Cost and Utilization Project includes 35 million in-hospital encounters that occur annually across more than 1000 nonfederal acute care hospitals in 48 states[9]. Since patient identifiers were not included, Institutional Review Board approval was not necessary for this study. We identified hospitalizations of young men (age 18-44 years), with and without CUD after excluding the records with known TUD and then divided the main cohort into CUD + and CUD- arms using International Classification of Diseases, tenth revision, clinical modification (ICD-10-CM). Using the codes (F17.2) and (O99.33), tobacco smoking status was determined. Cardiovascular and extracardiac comorbidities were identified using Elixhauser Comorbidity Indices and predefined comorbidity criteria in the existing database based on ICD-10 codes. The identification of CUD + was accomplished by utilizing the diagnostic codes F12.1x and F12.2x from the ICD-10-CM. It is important to note that the code F12.21, which pertains to dependence in remission, was excluded from the cohort. Since the NIS contains deidentified data, IRB approval was not required.
Study variables and co-morbidities
We studied baseline characteristics including mean age, race, median household income and various comorbidities. We compared both CUD + and CUD- groups with different comorbidities to evaluate its effect on AF related hospitalizations.
Study outcomes
Our primary outcome was the frequency and odds of AF related hospitalizations in young men without concomitant TUD with and without CUD by multivariable logistic regression analysis adjusted for sociodemographic and comorbid confounding variables. We also evaluated AF admission rates stratified by race, median household income (lowermost income quartile vs highest income quartile) and hospital region (Northeast, Midwest, South, and West).
Statistical analysis
For analyzing and identifying any categorical associations, we employed the Pearson χ2 test, and the Mann-Whitney U test was utilized for continuous variables that had a non-normal distribution. To ensure significance, we set a P value threshold of 0.05. In accordance with the privacy guidelines of the Healthcare Cost and Utilization Project (HCUP), any cell sizes below 11 were not disclosed to uphold patient confidentiality. We performed a 1:1 propensity score-matched analysis focusing on baseline characteristics and relevant comorbidities (age at admission, race, median household income quartile, hospital location/teaching status, region, alcohol abuse and other concomitant substance abuse) employing the near-neighbor method and 0.01 caliper width. Multivariable logistic regression was performed to evaluate the odds of outcomes, adjusting for potential patient and hospital-level covariates and preexisting comorbidities relevant to the studied patient population. We utilized the weighted data and complex survey modules in IBM SPSS Statistics v25.0 to accurately account for the sampling design and generate national estimates.
RESULTS
Our initial analysis included 1388130 young men hospitalization with AF in total without TUD with and without CUD. Before matching, CUD + cohort experienced lower rate of AF-related hospitalizations compared to CUD- cohort 0.3% (395/1202400) vs 0.6% (7305/1267890); P < 0.001.
We performed 1:1 propensity-score matched analysis to obtain CUD + arm and CUD- arm with 108495 patients in each arm. post-matching the CUD + arm demonstrated higher rates of AF admissions vs CUD- arm (0.4% vs 0.3%, P = 0.023). On subgroup analysis, whites and Hispanics had comparable AF admission rates between CUD + vs CUD- arms, whereas blacks showed higher AF rates in the CUD + arm (0.3% vs 0.1%, P = 0.001). On income-based stratification, individuals from lowermost income quartiles have a slightly higher AF admission rate for CUD + arm compared to CUD- arm (0.4% vs 0.3%, P = 0.023). Conversely, individuals from the highest income quartile exhibited a slightly lower admission rate for CUD + arm compared to CUD- arm (0.2% vs 0.3%, P = 0.020). Southern region hospitals showed a higher rate of AF admission among CUD + cohort compared to CUD- cohort (0.4% vs 0.3%, P = 0.03) whereas admissions in young men in hospitals from the other region demonstrated comparable rates of AF (P > 0.05).
As shown in Table 1, Both CUD + and CUD- cohorts among young men without TUD had median age of 30 (24-37). It was evident that the CUD + more often had black patients in comparison to CUD- cohort (25.70% vs 25.50%). There was no significant difference in median household income in both arms. In both the arms highest number of patients were covered by Medicaid (40.40% vs 40.40%) and self-pay was higher in CUD + arm (15.70% vs 13.60%, P < 0.0001). CUD + cohort had higher association with chronic pulmonary disease (9.80% vs 9.40%, P = 0.01) and depression (12.20% vs 11.80%, P = 0.007) in compared to CUD- cohort. Surprisingly, CUD + patients had significantly low associated comorbidities including complicated hypertension (5.30% vs 6.30%), hyperlipidemia (6.40% vs 6.90%), obesity (9.10% vs 10.90%), peripheral vascular disease (0.90% vs 1.40%), alcohol abuse (15.50% vs 16.90%), diabetes with complications (6.40% vs 6.80%), prior myocardial infarction (1.00% vs 1.10%), prior stroke (1.10% vs 1.40%), prior venous thromboembolism (1.80% vs 3.20%), and cancer (1.60% vs 2.80%) when compared to CUD- patients.
Table 1.
Baseline characteristics of young men hospitalizations without concomitant tobacco use disorder with vs without cannabis use disorder, 2019, n (%)
|
Variable
|
Cannabis use disorder
|
P value
|
||
|
No (n = 108495)
|
Yes (n = 108495)
|
|||
| Age (years) at admission | Median (IQR) | 30 | 30 | < 0.001 |
| Race | < 0.001 | |||
| White | 53525 (49.30) | 53365 (49.20) | ||
| Black | 27670 (25.50) | 27830 (25.70) | ||
| Hispanic | 19480 (18.00) | 19465 (17.90) | ||
| Asian or Pacific Islander | 1605 (1.50) | 1840 (1.70) | ||
| Native American | 1200 (1.10) | 1190 (1.10) | ||
| Median household income national quartile for patient ZIP code | 0.100 | |||
| 0-25th | 38785 (35.70) | 38400 (35.40) | ||
| 26-50th | 26595 (24.50) | 26730 (24.60) | ||
| 51-75th | 24615 (22.70) | 24500 (22.60) | ||
| 76-100th | 18500 (17.10) | 18865 (17.40) | ||
| Primary payer | < 0.001 | |||
| Medicare | 10325 (9.50) | 9365 (8.70) | ||
| Medicaid | 43715 (40.40) | 43730 (40.40) | ||
| Private insurance | 32395 (29.90) | 31465 (29.10) | ||
| Self-pay | 14675 (13.60) | 17045 (15.70) | ||
| No charges | 1385 (1.30) | 1455 (1.30) | ||
| Other | 5750 (5.30) | 5180 (4.80) | ||
| Hypertension, complicated | 6835 (6.30) | 5700 (5.30) | < 0.001 | |
| Hypertension, uncomplicated | 16735 (15.40) | 16335 (15.10) | 0.010 | |
| Hyperlipidemia | 7445 (6.90) | 6900 (6.40) | < 0.001 | |
| Obesity | 11780 (10.90) | 9920 (9.10) | < 0.001 | |
| Peripheral vascular disease | 1510 (1.40) | 970 (0.90) | < 0.001 | |
| Chronic pulmonary disease | 10235 (9.40) | 10590 (9.80) | 0.010 | |
| Alcohol abuse | 18325 (16.90) | 16770 (15.50) | < 0.001 | |
| Drug abuse | 55370 (51.00) | 55380 (51.00) | 0.960 | |
| Diabetes with chronic complications | 7375 (6.80) | 6890 (6.40) | < 0.001 | |
| Diabetes without chronic complications | 3735 (3.40) | 2950 (2.70) | < 0.001 | |
| Prior myocardial infarction | 1170 (1.10) | 1070 (1.00) | 0.030 | |
| Prior transient ischemic attack/stroke | 1570 (1.40) | 1165 (1.10) | < 0.001 | |
| Depression | 12800 (11.80) | 13210 (12.20) | 0.007 | |
| Prior VTE | 3475 (3.20) | 1910 (1.80) | < 0.001 | |
| Cancer | 3030 (2.80) | 1745 (1.60) | < 0.001 | |
P < 0.05 indicates statistical significance. IQR: Interquartile range, VTE: Venous thromboembolism.
Unadjusted odds of AF in the CUD + cohort without concomitant TUD were 1.19 with a 95% confidence interval (95%CI) of 0.85 to 1.66 and failed to reach a statistical significance; P = 0.313. Furthermore, when adjusted for confounders, the odds of AF hospitalizations in CUD + cohort without TUD were non-significant (Odd ratio: 1.27, 95%CI: 0.91-1.78, P = 0.15) (Table 2).
Table 2.
Odds of atrial fibrillation related admissions in young men without concomitant tobacco use disorder with vs without cannabis use disorder by logistic regression
|
Item
|
OR
|
95%CI lower limit
|
95%CI upper limit
|
P value
|
| Unadjusted | 1.19 | 0.85 | 1.66 | 0.313 |
| Adjusted for age, race, income quartile, hospital location/teaching status, and regions | 1.19 | 0.85 | 1.67 | 0.300 |
| Adjusted for all baseline patient level and hospital level sociodemographic characteristics and pre-existing comorbidities | 1.27 | 0.91 | 1.78 | 0.158 |
P < 0.05 indicates statistical significance. Multivariable regression models were adjusted for age at admission, race, median household income national quartile for patient ZIP Code, location/teaching status of the hospital, region of the hospital, alcohol abuse, other drug abuse, depression, complicated hypertension, diabetes with chronic complications, hyperlipidemia, obesity, peripheral vascular disease, prior myocardial infarction, chronic pulmonary disease, prior venous thromboembolism, and cancer. 95%CI: 95% confidence interval; OR: Odds ratio.
DISCUSSION
This study observed a relative increase in AF-related hospitalizations, anxiety, and chronic obstructive pulmonary disease (COPD) rates among the propensity matched CUD + subgroup compared to CUD- group even in absence of concomitant TUD in young, hospitalized men. After adjusting for demographic factors and comorbidities, the odds of AF-related hospitalization were 27% higher in the CUD + cohort compared to the CUD-cohort, though this difference was not statistically significant.
The mechanisms linking CUD to AF may involve direct toxic effects on the myocardium and autonomic nervous system, causing arrhythmogenic effects. Theoretically, THC stimulation increases the content of catecholamines and adrenaline in cardiac tissue, which may promote arrhythmias. Moreover, it is evident that cannabis increased action potential and decreased the rapid delayed rectifier potassium currents, the slow delayed rectifier potassium currents, and the transient outward rectifier potassium currents, which promote arrhythmias[10,11]. The CUD + group also had higher anxiety and stress, possibly contributing to arrhythmogenic triggers. Of note, the prevalence of co-diagnosed CUD and AF has risen substantially in recent years, which is concerning given the ongoing expansion of cannabis legalization[12]. In addition, a recent scientific statement from the American Heart Association suggests potential cardiovascular side effects of CUD by stimulating CB1R, causing sympathetic activation, myocyte hypertrophy, reduced mobility, and chronic endothelial dysfunction, leading to direct effects such as cardiomyopathy, acute myocardial infarction, and arrhythmias[13].
Importantly, this study highlights CUD as a potential contributor to racial and socio-economic disparities in AF outcomes[14]. The higher burden of CUD and related AF admissions in blacks warrants greater attention, as this could compound their underlying thromboembolic risk due to prothrombotic milieu, hyperactivation of adrenergic drive, and can potentiate conversion from paroxysmal to persistent AF[12]. Considering the younger age group of CUD + patients and the progression from paroxysmal to permanent AF with a low burden of hypertension, hyperlipidemia, diabetes, obesity, and alcohol use disorder, progressing from paroxysmal to persistent AF can escalate subsequent cardioembolic complications in higher-risk groups. Southern region hospitals reported a higher rate of AF admission among the CUD + cohort compared to the CUD-cohort, highlighting potential geographical factors contributing to variations in the cannabis-cardiovascular risk relationship. Regional differences could be due to existing differences in state-wise cannabis policies and decriminalization laws. Furthermore, it is important to consider the potential impact of different cannabis strains and potency levels, as these factors can vary across regions. Additionally, variations in healthcare access and quality between different regions may have influenced the rates of AF admission among individuals with CUD. Efforts to reduce the burden of CUD and AF among Black individuals should focus on addressing the root causes of these disparities, including socioeconomic disadvantage, limited access to healthcare, and exposure to environmental stressors[8]. Interventions that promote health equity, such as community-based education programs and policies that reduce barriers to healthcare access, may be particularly effective in mitigating the adverse cardiovascular effects of cannabis use in vulnerable populations[15].
The co-diagnosis of CUD and AF has risen substantially from 2008 to 2018, with over a 3-fold relative increase and a nearly 5-fold absolute increase[12]. However, previous studies have not considered the confounding effect of TUD, which has profound cardiac adverse effects[12]. Moreover, smoking is associated with a 2-fold increased risk of AF attributed to current smoking and a trend towards a lower incidence of AF amongst smokers who quit[16]. With the legalization of cannabis across many states, this trend is expected to increase and have a growing impact on inpatient healthcare utilization and costs[12]. However, the cost of care for these CUD patients with AF was substantially higher in this study, suggesting a pathologic interaction that results in more severe AF requiring intensive treatment. As these younger patients with CUD and AF age, they may develop risk factors like hypertension and coronary disease that promote AF progression and complications like stroke.
Further research is needed to characterize CUD patterns, mechanisms, and outcomes in AF patients. This includes a detailed assessment of cannabis use history, arrhythmia phenotype, longitudinal outcomes, and potential treatment implications such as cannabis cessation. A focus on evaluating women, Hispanics, and other minority populations will also expand the generalizability. Future research should aim to explore these regional differences in more detail in order to gain a comprehensive understanding of the complex relationship between cannabis use, cardiovascular health, and geographic factors. Further study of the CUD-AF relationship offers significant potential to understand and reduce population health burdens related to cannabis use and AF.
Additional research using longitudinal designs is needed to clarify the temporality and quantify the magnitude of the association between cannabis use and AF risk. Understanding these relationships has important public health implications, given rising rates of cannabis use and growing awareness of AF-related morbidity in young people. Future studies should employ geospatial analysis techniques to map the distribution of CUD and AF across different regions and to identify hotspots where targeted interventions may be most effective[17]. Collaborations between researchers, policymakers, and healthcare providers will be essential in developing region-specific strategies to address the CUD-AF relationship and to promote cardiovascular health in communities most affected by cannabis use[18].
In addition to AF, CUD is also associated with increased risk of anxiety and other mental health condition. Recent evidence presented at the 2023 Cannabis Clinical Outcomes Research Conference highlights the complex relationship between cannabis use and mental health outcomes. While some studies suggest potential therapeutic benefits of cannabis for certain mental health conditions, such as insomnia[18], others have found no significant improvement in pain, anxiety, or depression among adolescents and young adults[18]. These findings underscore the need for further research to elucidate the effects of cannabis on mental health and cognition across different populations and contexts.
Recent studies have also suggested a potential link between cannabis use and COPD exacerbations. In a study by Chatkin et al[19], patients with COPD who reported using cannabis had a higher risk of exacerbations compared to non-users. Similarly, Tan et al[20] found that heavy cannabis use was associated with an increased risk of COPD exacerbations in a population-based cohort. Our study found a relative incremental association between cannabis use and COPD exacerbation rates similar to the potential for increased risk reported in other studies[19,20].
This study has limitations, including reliance on administrative data lacking clinical granularity, diagnostic coding inconsistencies, and the inability to infer causation due to the cross-sectional design. Other unmeasured confounders may include healthcare access and substance use patterns. Nonetheless, these findings highlight CUD as an emerging risk factor for AF among young adults, particularly in minority populations at elevated risk of AF complications. Additional longitudinal research is warranted to elucidate the temporal associations and detailed mechanisms linking cannabis use and arrhythmogenesis across demographically diverse populations.
CONCLUSION
This nationwide study highlights the effects of CUD on AF hospitalizations in young men without confounding effects of TUD. There was no association with higher AF risk when other confounding variables were controlled. Young black patients with CUD had higher rates of AF-related admissions. Large-scale prospective studies are required to evaluate long-term effects of CUD on AF risk and prognosis without TUD and concomitant substance abuse and to help formulate preventive measures to reduce AF burden in the young population.
Footnotes
Institutional review board statement: Data is obtained from a publicly available data set, so patient identifiers are not used.
Informed consent statement: Informed consent statement was not needed because the study was carried out on a publicly available data set without patient identifiers.
Conflict-of-interest statement: The authors have no conflict of interest related to the manuscript.
Provenance and peer review: Invited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Cardiac and cardiovascular systems
Country of origin: United States
Peer-review report’s classification
Scientific Quality: Grade B
Novelty: Grade B
Creativity or Innovation: Grade B
Scientific Significance: Grade B
P-Reviewer: Mehta V S-Editor: Chen YL L-Editor: A P-Editor: Cai YX
Contributor Information
Bhavin Patel, Department of Internal Medicine, Trinity Health Oakland Hospital, Pontiac, MI 48341, United States.
Sumanth Khadke, Lahey Hospital and Medical Center, Division of Cardiovascular Medicine, Department of Medicine, Burlington, MA 01805, United States.
Kshitij Mahajan, Department of Internal Medicine, Trinity Health Oakland/Wayne State University, Pontiac, MI 48341, United States.
Avleen Dhingra, Department of Medicine, Dayanand Medical College and Hospital, Ludhiana 141001, Punjab, India.
Rishika Trivedi, Department of Internal Medicine, DHR Health, Edinburg, TX 78539, United States.
Samrath Singh Brar, Department of Medicine, Government Medical College, Patiala 147001, Punjab, India.
Sakshi Dixit, Department of Medicine, Government Medical College, Patiala 147001, Punjab, India.
Vaibhav Periwal, Department of Medicine, Government Medical College, Patiala 147001, Punjab, India.
Shaylika Chauhan, Department of Internal Medicine, Geisinger Health System, Wikes-Barre, PA 18702, United States. drshaylikachauhan@gmail.com.
Rupak Desai, Independent Researcher, Outcomes Research, Atlanta, GA 30079, United States.
Data sharing statement
Technical appendix, statistical code, and dataset available from the corresponding author on request.
References
- 1.Lippi G, Sanchis-Gomar F, Cervellin G. Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge. Int J Stroke. 2021;16:217–221. doi: 10.1177/1747493019897870. [DOI] [PubMed] [Google Scholar]
- 2.Kim MH, Johnston SS, Chu BC, Dalal MR, Schulman KL. Estimation of total incremental health care costs in patients with atrial fibrillation in the United States. Circ Cardiovasc Qual Outcomes. 2011;4:313–320. doi: 10.1161/CIRCOUTCOMES.110.958165. [DOI] [PubMed] [Google Scholar]
- 3.Lin AL, Nah G, Tang JJ, Vittinghoff E, Dewland TA, Marcus GM. Cannabis, cocaine, methamphetamine, and opiates increase the risk of incident atrial fibrillation. Eur Heart J. 2022;43:4933–4942. doi: 10.1093/eurheartj/ehac558. [DOI] [PubMed] [Google Scholar]
- 4.Desai R, Thakkar S, Patel HP, Tan BE, Damarlapally N, Haque FA, Farheen N, DeWitt N, Savani S, Parisha FJ, Doshi R, Mansuri Z, Gangani K. Higher odds and rising trends in arrhythmia among young cannabis users with comorbid depression. Eur J Intern Med. 2020;80:24–28. doi: 10.1016/j.ejim.2020.04.048. [DOI] [PubMed] [Google Scholar]
- 5.Desai R, Patel U, Deshmukh A, Sachdeva R, Kumar G. Burden of arrhythmia in recreational marijuana users. Int J Cardiol. 2018;264:91–92. doi: 10.1016/j.ijcard.2018.03.113. [DOI] [PubMed] [Google Scholar]
- 6.Parekh T, Pemmasani S, Desai R. Marijuana Use Among Young Adults (18-44 Years of Age) and Risk of Stroke: A Behavioral Risk Factor Surveillance System Survey Analysis. Stroke. 2020;51:308–310. doi: 10.1161/STROKEAHA.119.027828. [DOI] [PubMed] [Google Scholar]
- 7.Desai R, Fong HK, Shah K, Kaur VP, Savani S, Gangani K, Damarlapally N, Goyal H. Rising Trends in Hospitalizations for Cardiovascular Events among Young Cannabis Users (18-39 Years) without Other Substance Abuse. Medicina (Kaunas) 2019;55 doi: 10.3390/medicina55080438. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Doshi R, Dave M, Majmundar M, Kumar A, Adalja D, Shariff M, Desai R, Ziaeian B, Vallabhajosyula S. National rates and trends of tobacco and substance use disorders among atrial fibrillation hospitalizations. Heart Lung. 2021;50:244–251. doi: 10.1016/j.hrtlng.2020.12.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Agency for Healthcare Research and Quality. HCUP-US NIS Overview. [cited 10 September 2023]. Available from: https://hcup-us.ahrq.gov/nisoverview.jsp .
- 10.Topal L, Naveed M, Orvos P, Pászti B, Prorok J, Bajtel Á, Kiss T, Csupor-Löffler B, Csupor D, Baczkó I, Varró A, Virág L, Jost N. The electrophysiological effects of cannabidiol on action potentials and transmembrane potassium currents in rabbit and dog cardiac ventricular preparations. Arch Toxicol. 2021;95:2497–2505. doi: 10.1007/s00204-021-03086-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Chen M, Lu YL, Chen XF, Wang Z, Ma L. Association of cannabis use disorder with cardiovascular diseases: A two-sample Mendelian randomization study. Front Cardiovasc Med. 2022;9:966707. doi: 10.3389/fcvm.2022.966707. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Chouairi F, Miller PE, Guha A, Clarke JR, Reinhardt SW, Ahmad T, Freeman JV, Desai NR, Friedman DJ. Cannabis use disorder among atrial fibrillation admissions, 2008-2018. Pacing Clin Electrophysiol. 2021;44:1934–1938. doi: 10.1111/pace.14356. [DOI] [PubMed] [Google Scholar]
- 13.Page RL 2nd, Allen LA, Kloner RA, Carriker CR, Martel C, Morris AA, Piano MR, Rana JS, Saucedo JF American Heart Association Clinical Pharmacology Committee and Heart Failure and Transplantation Committee of the Council on Clinical Cardiology; Council on Basic Cardiovascular Sciences; Council on Cardiovascular and Stroke Nursing; Council on Epidemiology and Prevention; Council on Lifestyle and Cardiometabolic Health; and Council on Quality of Care and Outcomes Research. Medical Marijuana, Recreational Cannabis, and Cardiovascular Health: A Scientific Statement From the American Heart Association. Circulation. 2020;142:e131–e152. doi: 10.1161/CIR.0000000000000883. [DOI] [PubMed] [Google Scholar]
- 14.Jeffers AM, Glantz S, Byers A, Keyhani S. Sociodemographic Characteristics Associated With and Prevalence and Frequency of Cannabis Use Among Adults in the US. JAMA Netw Open. 2021;4:e2136571. doi: 10.1001/jamanetworkopen.2021.36571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Connor JP, Stjepanović D, Le Foll B, Hoch E, Budney AJ, Hall WD. Cannabis use and cannabis use disorder. Nat Rev Dis Primers. 2021;7:16. doi: 10.1038/s41572-021-00247-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Chamberlain AM, Agarwal SK, Folsom AR, Duval S, Soliman EZ, Ambrose M, Eberly LE, Alonso A. Smoking and incidence of atrial fibrillation: results from the Atherosclerosis Risk in Communities (ARIC) study. Heart Rhythm. 2011;8:1160–1166. doi: 10.1016/j.hrthm.2011.03.038. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Degenhardt L, Chiu WT, Sampson N, Kessler RC, Anthony JC, Angermeyer M, Bruffaerts R, de Girolamo G, Gureje O, Huang Y, Karam A, Kostyuchenko S, Lepine JP, Mora ME, Neumark Y, Ormel JH, Pinto-Meza A, Posada-Villa J, Stein DJ, Takeshima T, Wells JE. Toward a global view of alcohol, tobacco, cannabis, and cocaine use: findings from the WHO World Mental Health Surveys. PLoS Med. 2008;5:e141. doi: 10.1371/journal.pmed.0050141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Goodin AJ, Tran PT, McKee S, Sajdeya R, Jyot J, Cook RL, Wang Y, Winterstein AG. Proceedings of the 2023 Cannabis Clinical Outcomes Research Conference. Med Cannabis Cannabinoids. 2023;6:97–101. doi: 10.1159/000533943. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Chatkin JM, Zani-Silva L, Ferreira I, Zamel N. Cannabis-Associated Asthma and Allergies. Clin Rev Allergy Immunol. 2019;56:196–206. doi: 10.1007/s12016-017-8644-1. [DOI] [PubMed] [Google Scholar]
- 20.Tan WC, Bourbeau J, Aaron SD, Hogg JC, Maltais F, Hernandez P, Marciniuk DD, Chapman KR, To T, FitzGerald JM, Walker BL, Road J, Zheng L, Zhou G, Yau T, Benedetti A, O'Donnell D, Sin DD CanCOLD Collaborative Research Group; Members of the CanCOLD Collaborative Research Group not listed as authors: The effects of marijuana smoking on lung function in older people. Eur Respir J. 2019;54 doi: 10.1183/13993003.00826-2019. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Technical appendix, statistical code, and dataset available from the corresponding author on request.