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. 2024 Nov 27;53(11):afae261. doi: 10.1093/ageing/afae261

Adverse events caused by cannabinoids in middle aged and older adults for all indications: a meta-analysis of incidence rate difference

Latha Velayudhan 1, Sara Pisani 2, Marta Dugonjic 3, Katie McGoohan 4, Sagnik Bhattacharyya 5,✉
PMCID: PMC11601816  PMID: 39602500

Abstract

Background

Cannabinoid-based medicines (CBMs) are being used widely in older people. However, information on the incidence of adverse events (AEs) is limited.

Objective

To quantify the incidence rate difference (IRD) of AEs in middle aged and older adults of age ≥50 years receiving CBMs and also examine associations with weekly doses.

Design

Systematic review and meta-analysis.

Data sources

MEDLINE, PubMed, EMBASE, CINAHL, PsychInfo, Cochrane Library and ClinicalTrials.gov (1st Jan 1990–12th June 2023).

Methods

We included randomised clinical trials (RCTs) using CBMs with mean participant age ≥50 years for medicinal purposes for all clinical indications. Paired reviewers independently screened studies, extracted data and appraised risk of bias. We estimated pooled effect-sizes IRD under the random-effects model.

Results

Data from 58 RCTs (37 moderate-high quality studies, pooled n = 6611, mean age range 50–87 years, 50% male, n = 3450 receiving CBMs) showed that compared with controls, the incidence of all-cause and treatment-related AEs attributable to delta-9-tetrahydrocannabinol (THC)-containing CBMs were: THC alone [IRD:18.83(95% Confidence Interval [CI], 1.47–55.79) and 16.35(95% CI, 1.25–48.56)] respectively; THC:cannabidiol (CBD) combination [IRD:19.37(95% CI, 4.24–45.47) and 11.36(95% CI, 2.55–26.48)] respectively. IRDs of serious AEs, withdrawals and deaths were not significantly greater for CBMs containing THC with or without CBD. THC dose-dependently increased the incidence of dry mouth, dizziness/lightheadedness, mobility/balance/coordination difficulties, dissociative/thinking/perception problems and somnolence/drowsiness. The interaction of weekly THC:CBD doses played a role in mostly neurological, psychiatric and cardiac side-effects.

Conclusions

Although CBMs in general are safe and acceptable in middle aged and older adults, one needs to be mindful of certain common dose-dependent side-effects of THC-containing CBMs.

Keywords: cannabinoid-based medication, delta-9-tetrahydrocannabinol (THC), cannabidiol, adverse events, middle aged and older adults, systematic review, older people

Key Points

  • There is a particular need to quantify risk of various adverse events (AEs) with use of cannabinoid-based medicines (CBMs) in older people.

  • We examined incidence rate differences of AEs in middle aged and older adults receiving CBMs for all conditions.

  • Delta-9-tetrahydrocannabinol (THC) containing CBMs were associated with gastrointestinal, neurological and psychiatric side-effects in a dose-related manner.

  • Cumulative weekly doses of delta-9-THC and CBDs played a role in mostly neurological, psychiatric and cardiac side-effects.

  • We present age-specific safety/tolerability information about cannabinoids that is critical to prescribing in older people.

Introduction

Cannabinoid-based medicines (CBMs) are increasingly being used in the older people, a fast-growing segment of the population [1, 2]. The term cannabinoid generally refers to chemicals that have a certain (terpenophenolic) structure, which are naturally present in the extract of the cannabis plant (when they are also known as phytocannabinoids) or may have a synthetic origin. Out of 150 cannabinoids in the cannabis plant, delta-9-tetrahydorcannabinol (THC) and cannabidiol (CBD) are commonly used for medicinal purposes with a range of reported benefits [3–6].

For any novel treatment, safety and tolerability must be weighed up against clinical benefits to inform their use in different contexts. This is of particular importance in middle aged and older adults, who often have various comorbid health conditions requiring treatments that may interact with any additional treatment being prescribed. They are also more sensitive to side-effects of medications than many other demographic groups. With growing usage of CBMs, there is a particular need therefore to quantify the risk of various adverse events (AEs) associated with CBM use, so as to enable informed risk–benefit analysis during clinical use. However, to the best of our knowledge there is limited evidence in this regard. Although, a number of randomised clinical trials (RCTs) of CBMs have been carried out, the sample sizes of these RCTs on their own are underpowered to systematically and meaningfully estimate the risk of individual AEs. Against this background and in the absence of large-scale population level pharmaco-vigilance data which will only accrue over time, meta-analytic pooling of incidence rate data of individual AEs across placebo-controlled RCTs allows the best estimate of risk associated with CBM treatments based on available evidence. By estimating difference in the incidence rate between the CBM and control intervention arms, such evidence can help understand the additional risk of AEs associated with CBM use. A number of previous reviews [7–10] have examined whether CBMs are associated with greater risk (either as odds or risk ratios or incident rate ratios) of side-effects and reported them as ratios. However, estimates of relative effect such as these do not lend themselves as easily to use in a clinical context unless the risk in the control group is readily known. Incident rate difference (IRD), which in this context refers to the additional risk of AEs estimated as the number of events per person-years of exposure associated with CBM use over and above a control intervention may be more easily understood but has not been systematically examined before. Another gap in current evidence relates to understanding about how the risk of AEs relate to the range of doses or ratio of doses used in formulations containing single or multiple cannabinoids respectively being used in the clinical settings. With limited number of studies being available, there is a paucity of data for any clinical indication-specific dose–response relationships with regard to AEs (that may exist) to become easily apparent. Meta-analytic pooling of data therefore will allow for an estimation of the likelihood of such risks at different doses across clinical indications to inform clinicians and researchers. Such a detailed assessment may help inform use of CBM in older people, in whom certain side-effects may be more directly related to morbidity and even mortality. For example, dizziness, which may contribute to risk for falls in older people, can in turn result in serious injuries such as fractures, head injuries or accidental deaths [11, 12]. Furthermore, certain AEs and dose–response relationships may be systematically different between THC and THC:CBD formulations [8]. Therefore, the overarching objective of the present endeavour was to address these gaps in knowledge by conducting a search of evidence from placebo-controlled RCTs and systematically report the incidence rate of all individual AEs attributable to the use of different types of CBMs. Specifically, we aimed to quantify the IRDs of AEs in people receiving THC only and THC-CBD combination treatment in middle aged and older adults with mean age of 50 years and older. We also aimed to examine the association of AEs with the weekly doses of THC and CBD.

Methods

Search strategy and selection criteria

The review was undertaken according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines [13] and registered with PROSPERO (CRD42019148869). A detailed description of the bibliographic search strategy, as previously published, is presented in Supplementary Methods [8]. We identified studies published from 1 January 1990 up to 12 June 2023, from several electronic databases. Studies were independently assessed by pair of researchers (LV, KM, SP, MD) and disagreements resolved through consensus or discussions with senior researcher.

As described in our previous meta-analysis [8], studies were included if [1] published from 1990 onwards; [2] included middle aged and older adults (defined as mean age ≥50 years) or reported a distinct subgroup of middle aged and older adults and provided separate results for this subgroup; and [3] provided data on the safety and tolerability of medical cannabinoids administered by any route, at any dose, for any duration and for any indication. Studies were excluded if they [1] included exclusively younger subjects (≤50 years); [2] studied effects of cannabinoids for recreational purposes or failed to provide the dosage of cannabinoids and [3] were not reported in English language. Here we focus on results from RCTs.

Data analysis

All relevant available data for examination of the safety and tolerability of different CBMs (THC:CBD combination or THC alone) was collected from eligible studies, complemented with information from www.ClinicalTrials.gov and we also contacted study authors to supplement information. Data were extracted for study design, participant characteristics, indication, dosage and duration of intervention, all cause and treatment-related AEs and serious AEs (SAEs), AE-related withdrawals and deaths. AEs and SAEs were coded according to the Medical Dictionary for Regulatory Activities (MedDRA) ‘system organ classes’ (SOC). Data were extracted for the top five (as reported by each study) AEs for each SOC, where available. Withdrawals and deaths outcomes were extracted as reported in the studies from the text and tables for each treatment arm. Data extraction and coding was verified by a medically qualified researcher and discrepancies resolved following discussions with senior researcher. The disease conditions investigated were classified into broader subgroups for analysis purpose [8]. Overall quality of evidence was assessed using recommended criteria [14] and summarised to reflect confidence in estimates [15].

Pooled effect-sizes were estimated (as square root transformed incident rate difference; IRSD) if there were two or more RCTs within each group or sub-group under the random-effects model using the restricted maximum-likelihood estimator because of anticipated heterogeneity. For reporting purposes, IRSDs have been converted to IRDs for ease of understanding, unless otherwise specified. However, for dose–response relationships (as in Tables 2 and 4), we have reported the IRSD values to allow an interested reader to estimate the expected IRD for a particular dose of CBM and shown an example calculation in table footnotes. Doses of both THC and CBD were included separately, as well as their interaction as predictors, in the same regression model for studies using THC:CBD combinations (Table 4). For each category of intervention, analyses combined both parallel-arm and crossover RCTs, with the latter treated as parallel-arm design [16] for pooled analyses. We also report results by RCT design. In studies with more than one active treatment arm, each active arm was considered as a different study. Throughout the manuscript, results are reported for analyses treating all studies as independent. We investigated heterogeneity using forest-plots and the QE statistic (and its significance; QEp) and publication bias using Egger’s regression test [17] and the ‘Trim and fill’ method [18]. Data for all clinical conditions were combined. We also examined the effect of treatment, design, clinical condition and weekly dose of THC and CBD and their interaction in THC:CBD combination studies using meta-regression except for the route of administration which was oral for all the included studies. Statistical analyses were performed using the metafor package in R (version 3.6.3) [19].

Table 2.

Effect of cumulative THC dose per week across THC studies expressed as square root transformed incidence rate difference (IRSD, i.e. summary estimate) for each single adverse event. Summary estimates are reported here for intercept and THC dose per week (i.e. regression coefficient), followed by 95% confidence intervals and associated P value.

MedDRA high-level grouping Individual AE MODEL Summary estimate 95% CI (lower, upper) P value N QE QEp
Gastrointestinal Nausea Intercept 0.013 −0.010, 0.036 0.268 22 28.800 0.092
THC 0.000 −0.000, 0.000 0.373 22
Vomiting Intercept 0.016 −0.005, 0.037 0.139 18 9.686 0.883
THC 0.000 0.000, 0.000 0.252 18
Dry mouth Intercept 0.075 0.050, 0.100 <0.001 20 27.136 0.076
THC −0.00005 −0.00001, 0.00003 <0.001 20
Nervous System Dizziness/Lightheaded Intercept 0.055 0.038, 0.071 <0.001 25 49.357 0.001
THC −0.00001 −0.00003, −0.00001 0.001 25
Mobility/Balance/Coordination Intercept 0.025 0.009, 0.041 0.002 17 16.338 0.360
THC −0.000005 −0.00001, −0.000001 0.027 17
Muscle weakness Intercept 0.003 −0.015, 0.020 0.744 18 5.049 0.996
THC 0.000 0.000, 0.000 0.961 18
Headache/migraine Intercept 0.004 −0.095, 0.104 0.936 8 7.667 0.264
THC 0.002 0.000, 0.004 0.094 8
Sedation Intercept 0.260 0.023, 0.498 0.032 2 0.000 1.000
THC −0.013 −0.032, 0.006 0.173 2
Psychiatric Sleep problems/Insomnia Intercept 0.039 −0.024, 0.102 0.222 16 8.723 0.848
THC 0.000 −0.001, 0.000 0.338 16
Dissociative/Thinking/Perception Intercept 0.002 −0.013, 0.018 0.761 17 9.988 0.820
THC 0.00001 0.000002, 0.00001 0.006 17
Somnolence/Drowsiness Intercept 0.064 0.030, 0.097 <0.001 20 47.142 <0.001
THC −0.0003 −0.00001, −0.001 0.009 20
Anxiety/Depression Intercept −0.002 −0.020, 0.016 0.824 13 2.377 0.997
THC 0.000 0.000, 0.000 0.565 13
Concentration/attention problem Intercept 0.119 0.006, 0.232 0.039 5 1.004 0.800
THC −0.001 −0.004, 0.001 0.285 5
Euphoria Intercept 0.098 −0.030, 0.226 0.135 6 3.169 0.530
THC 0.000 −0.003, 0.002 0.967 6
Cardiac Dyspnoea Intercept 0.004 −0.021, 0.029 0.744 16 1.256 1.000
THC 0.000 0.000, 0.000 0.788 16
Palpitation Intercept 0.000 −0.001, 0.001 0.973 15 1.434 1.000
THC 0.000 0.000, 0.000 0.968 15
Chest pain Intercept −0.002 −0.029, 0.025 0.886 16 3.706 0.997
THC 0.000 0.000, 0.000 0.904 16
Vascular Hypotension Intercept 0.001 −0.026, 0.027 0.963 16 3.998 0.995
THC 0.000 0.000, 0.000 0.969 16
Infections Unspecified Intercept −0.006 −0.024, 0.011 0.470 16 2.312 1.000
THC 0.000 0.000, 0.000 0.514 16
UTI Intercept 0.001 −0.017, 0.018 0.929 16 0.006 1.000
THC 0.000 0.000, 0.000 0.651 16
RTI Intercept 0.008 −0.018, 0.035 0.534 15 7.858 0.853
THC 0.000 0.000, 0.000 0.601 15
General Pain: non-specific Intercept −0.009 −0.034, 0.016 0.490 16 2.554 1.000
THC 0.000 0.000, 0.000 0.416 16
Fatigue/tiredness Intercept 0.005 −0.012, 0.022 0.584 21 4.812 1.000
THC 0.000 0.000, 0.000 0.702 21 1.000
Weakness/reduced mobility Intercept 0.015 −0.012, 0.042 0.271 16 0.451 1.000
THC 0.000 0.000, 0.000 0.117 16
Blood/Lymphatic System Anaemia Intercept 0.004 −0.021, 0.029 0.761 16 2.042 1.000
THC 0.000 0.000, 0.000 0.802 16
Ear & Labyrinth Vertigo Intercept 0.002 −0.024, 0.029 0.871 15 3.974 0.991
THC 0.000 0.000, 0.000 0.892 15
Eye Disorders Visual impairment/disturbances Intercept 0.010 −0.016, 0.037 0.451 15 1.182 1.000
THC 0.000 0.000, 0.000 0.891 15
Injury/Poisoning Falls & injuries Intercept 0.007 −0.011, 0.025 0.436 14 1.845 1.000
THC 0.000 0.000, 0.000 0.486 14
Investigations Raised gamma GT Intercept 0.004 −0.023, 0.030 0.792 16 3.322 0.998
THC 0.000 0.000, 0.000 0.828 16
Metabolism/Nutritional Fluid retention Intercept −0.002 −0.024, 0.020 0.864 16 2.112 1.000
THC 0.000 0.000, 0.000 0.895 16
Decreased appetite Intercept 0.003 −0.023, 0.029 0.801 16 5.367 0.980
THC 0.000 0.000, 0.000 0.841 16
Increased appetite Intercept 0.002 −0.024, 0.029 0.863 16 1.970 1.000
THC 0.000 0.000, 0.000 0.888 16
Musculoskeletal Spasm stiffness Intercept 0.001 −0.016, 0.019 0.894 17 1.993 1.000
THC 0.000 0.000, 0.000 0.945 17
Joint disorders Intercept 0.001 −0.017, 0.018 0.947 16 0.003 1.000
THC 0.000 0.000, 0.000 0.737 16
Musculoskeletal pain Intercept 0.007 −0.010, 0.025 0.396 18 10.692 0.828
THC 0.000 0.000, 0.000 0.091 18
Reproductive system Male impotence Intercept −0.020 −0.042, 0.002 0.072 15 6.188 0.939
THC 0.000 0.000, 0.000 0.161 15 0.939
Respiratory/Thoracic Nose tenderness Intercept 0.003 −0.024, 0.030 0.822 15 1.949 1.000
THC 0.000 0.000, 0.000 0.850 15
Skin/Subcutaneous Other skin problem Intercept 0.005 −0.021, 0.032 0.694 15 1.961 1.000
THC 0.000 0.000, 0.000 0.231 15
Rash Intercept 0.005 −0.021, 0.032 0.692 15 1.856 1.000
THC 0.000 0.000, 0.000 0.738 15
Pressure sore Intercept 0.002 −0.024, 0.029 0.864 15 0.007 1.000
THC 0.000 0.000, 0.000 0.270 15
Renal and Urinary Bladder symptoms Intercept 0.001 −0.025, 0.028 0.915 15 0.004 1.000
THC 0.000 0.000, 0.000 0.898 15
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N = number of studies included in analysis. QE = test statistic for the test of heterogeneity. QEp = P value for the test of heterogeneity. NA = not applicable. Statistically significant results are presented in bold.

A summary estimate of the intercept model represents the square root transformed incidence rate difference (IRSD) of a given AE when the dose of THC treatment (per week) is 0. The summary estimate for THC refers to the additional increase in incidence rate per milligramme of increase in weekly THC dose per person-year, over and above the corresponding summary estimate of the intercept. Reported here need to be converted into incidence rate difference to be meaningfully interpreted as shown in the example below. For example, the square root transformed incident rate difference of developing dizziness/lightheadedness for a person taking 100 mg of THC per week over 1 year may be estimated using the formula [IRSD = intercept + summary estimate * (THC dose per week)] as IRSD = 0.055 + (−0.00001)*100,= 0.056. To convert IRSD per person-year into incidence rate difference (IRD) per 1000 person-years (i.e. incidence rate difference associated with cumulative exposure at the specified dose over 1 year for 1000 individuals) one would need to use the formula (IRSD2 * 1000). Using this formula, the additional incidence (IRD) of dizziness/lightheadedness attributable to THC exposure of 100 mg/week in 1000 people over 1 year amounts to 3.136 per 1000 person-years. Therefore, in a sample of 1000 individuals taking100 mg of THC per week over a 1-year period, 3.136 additional individuals will experience dizziness/lightheadedness attributable to their THC treatment.

Table 4.

Effect of cumulative THC and CBD doses per week and THC*CBD dose interaction across THC:CBD combination studies expressed as square root transformed incidence rate difference (IRSD, i.e. summary estimate) for each single adverse event. Summary estimates (i.e. regression coefficient) are reported here for intercept and THC and CBD doses as well as their interaction, followed by 95% confidence intervals and associated P value.

MedDRA high-level grouping Individual AE Model Summary estimate 95% CI (lower, upper) P value N QE QEp
Blood/Lymphatic System Anaemia Intercept −0.007 −0.089, 0.075 0.871 14 0.773 1.000
THC 0.000 −0.001, 0.000 0.890 14
CBD 0.000 −0.001, 0.001 0.889 14
THC*CBD interaction 0.000 0.000, 0.000 0.815 14
Cardiac Dyspnoea Intercept 0.067 −0.073, 0.208 0.346 11 0.047 1.000
THC 0.000 −0.002, 0.001 0.422 11
CBD −0.001 −0.007, 0.005 0.730 11
THC*CBD interaction 0.000 0.000, 0.000 0.724 11
Palpitation Intercept 0.437 −0.132, 1.005 0.132 10 1.919 0.927
THC −0.004 −0.008, 0.000 0.053 10
CBD −0.008118 −0.016085, −0.000151 0.046 10
THC*CBD interaction 0.000066 0.000008, 0.000124 0.026 10
Ear & Labyrinth Vertigo Intercept 0.024 −0.295, 0.344 0.881 11 5.204 0.635
THC −0.001 −0.002, 0.001 0.535 11
CBD 0.001 −0.001, 0.002 0.352 11
THC*CBD interaction 0.000 0.000, 0.000 0.920 11
Eye Disorders Visual impairment/disturbances Intercept 0.018 −1.309, 1.345 0.979 9 6.621 0.250
THC 0.000 −0.012, 0.011 0.941 9
CBD 0.000 −0.028, 0.028 0.999 9
THC*CBD interaction 0.000 0.000, 0.000 0.966 9
Gastrointestinal Nausea Intercept 0.023 −0.054, 0.100 0.555 21 14.301 0.646
THC 0.000 −0.001, 0.000 0.112 21
CBD 0.000 0.000, 0.001 0.202 21
THC*CBD interaction 0.000 0.000, 0.000 0.925 21
Vomiting Intercept −0.027 −0.159, 0.105 0.687 19 13.342 0.576
THC 0.000 −0.001, 0.001 0.848 19
CBD 0.000 −0.001, 0.001 0.410 19
THC*CBD interaction 0.000 0.000, 0.000 0.930 19
Dry Mouth Intercept 0.020 −0.121, 0.162 0.777 17 49.346 <0.001
THC 0.000 −0.001, 0.001 0.561 17
CBD 0.001 0.000, 0.002 0.323 17
THC*CBD interaction 0.000 0.000, 0.000 0.643 17
General Pain: non-specific Intercept 0.029 −0.053, 0.111 0.493 14 18.617 0.045
THC 0.000 −0.001, 0.000 0.698 14
CBD 0.000 −0.002, 0.001 0.475 14
THC*CBD interaction 0.000 0.000, 0.000 0.316 14
Fatigue/tiredness Intercept 0.024 −0.054, 0.102 0.544 19 24.526 0.057
THC 0.000 −0.001, 0.000 0.266 19
CBD 0.000 0.000, 0.001 0.543 19
THC*CBD interaction 0.000 0.000,0.000 0.714 19
Weakness/reduced mobility Intercept −0.041 −0.202, 0.121 0.623 14 5.009 0.891
THC 0.000 −0.001, 0.001 0.801 14
CBD 0.001 −0.001, 0.002 0.399 14
THC*CBD interaction 0.000 0.000, 0.000 0.450 14
Infections Unspecified Intercept −0.007 −1.334, 1.321 0.992 8 0.014 1.000
THC 0.000 −0.011, 0.011 0.994 8
CBD 0.000 −0.028, 0.028 0.991 8
THC*CBD interaction 0.000 0.000, 0.000 0.991 8
UTI Intercept −0.063 −0.867, 0.742 0.879 11 0.534 0.999
THC 0.001 −0.006, 0.007 0.876 11
CBD 0.001 −0.014, 0.016 0.859 11
THC*CBD interaction 0.000 0.000, 0.000 0.865 11
RTI Intercept 0.078 −0.279, 0.435 0.668 11 0.476 1.000
THC 0.000 −0.002, 0.002 0.674 11
CBD −0.002 −0.005, 0.001 0.242 11
THC*CBD interaction 0.000 0.000, 0.000 0.238 11
Injury/Poisoning Falls & injuries Intercept −0.251 −0.820, 0.317 0.386 10 1.252 0.974
THC 0.002 −0.002, 0.007 0.286 10
CBD 0.005 −0.003, 0.013 0.183 10
THC*CBD interaction 0.000 0.000, 0.000 0.172 10
Investigations Raised Gamma GT Intercept 0.077 −0.434, 0.587 0.768 10 0.015 1.000
THC −0.001 −0.004, 0.003 0.699 10
CBD −0.002 −0.010, 0.007 0.707 10
THC*CBD interaction 0.000 0.000,0.000 0.671 10
Metabolism/Nutritional Decreased Appetite Intercept 0.053 −0.031, 0.137 0.216 16 4.443 0.974
THC 0.000 −0.001,0.000 0.296 16
CBD 0.000 0.000,0.000 0.080 16
THC*CBD interaction 0.000 0.000,0.000 0.263 16
Increased Appetite Intercept −0.071 −0.571, 0.428 0.779 10 2.657 0.850
THC 0.000 −0.003, 0.003 0.884 10
CBD 0.002 −0.006, 0.011 0.616 10
THC*CBD interaction 0.000 0.000,0.000 0.697 10
Anorexia Intercept −0.103 −0.249, 0.043 0.167 14 10.513 0.397
THC 0.000 0.000, 0.001 0.272 14
CBD 0.001 0.000, 0.002 0.158 14
THC*CBD interaction 0.000 0.000,0.000 0.229 14
Musculoskeletal Back pain Intercept 0.084 −1.168, 1.335 0.896 10 0.138 1.000
THC −0.001 −0.011, 0.010 0.898 10
CBD −0.002 −0.028, 0.024 0.887 10
THC*CBD interaction 0.000 0.000, 0.000 0.891 10
Spasm stiffness Intercept 0.300 −0.952, 1.551 0.639 10 4.242 0.644
THC −0.003 −0.014,0.008 0.578 10
CBD −0.006 −0.032,0.020 0.659 10
THC*CBD interaction 0.000 0.000,0.000 0.617 10
Musculoskeletal pain Intercept −0.173 −1.500, 1.154 0.799 9 0.026 1.000
THC 0.001 −0.010, 0.012 0.859 9
CBD 0.002 −0.026, 0.029 0.915 9
THC*CBD interaction 0.000 0.000,0.000 0.929 9
Neoplasms Neoplasms progression Intercept 0.120 −0.040, 0.279 0.142 16 6.544 0.886
THC −0.001 −0.001,0.000 0.123 16
CBD −0.001 −0.002, 0.001 0.340 16
THC*CBD interaction 0.000 0.000,0.000 0.283 16
Nervous system Altered taste Intercept −0.077 −0.226, 0.072 0.311 13 8.557 0.479
THC 0.000 −0.001,0.001 0.759 13
CBD 0.001 0.000,0.002 0.024 13
THC*CBD interaction 0.000 0.000,0.000 0.141 13
Dizziness/Lightheaded Intercept −0.018 −0.077,0.041 0.549 24 60.352 <0.001
THC 0.000498 0.000080, 0.000916 0.020 24
CBD 0.000 0.000,0.000 0.628 24
THC*CBD interaction 0.000 0.000,0.000 0.602 24
Headache/migraine Intercept 0.087 −0.055,0.228 0.229 18 14.376 0.422
THC −0.001 −0.001,0.000 0.102 18
CBD 0.000 −0.001,0.001 0.816 18
THC*CBD interaction 0.000 0.000,0.000 0.651 18
Numbness/paraesthesia Intercept −0.016 −1.343, 1.311 0.981 9 0.106 1.000
THC 0.000 −0.011, 0.011 0.985 9
CBD 0.000 −0.027, 0.028 0.977 9
THC*CBD interaction 0.000 0.000,0.000 0.979 9
Psychiatric Sleep problems Intercept 0.045 −0.117,0.206 0.587 12 12.044 0.149
THC 0.000 −0.001,0.001 0.973 12
CBD −0.001 −0.002,0.001 0.311 12
THC*CBD interaction 0.000 0.000,0.000 0.459 12
Dissociative/Thinking/Perception Intercept 0.026 −0.135, 0.188 0.751 12 9.068 0.337
THC 0.000 −0.001, 0.001 0.718 12
CBD −0.001 −0.003,0.000 0.162 12
THC*CBD interaction 0.000 0.000,0.000 0.294 12
Somnolence/Drowsiness Intercept 0.066 −0.067, 0.199 0.332 19 11.992 0.680
THC −0.001 −0.001,0.000 0.063 19
CBD 0.000 −0.001,0.001 0.500 19
THC*CBD interaction 0.000 0.000,0.000 0.465 19
Anxiety/Depression Intercept −0.027 −0.515, 0.461 0.915 11 16.508 0.021
THC 0.000 −0.003,0.003 0.887 11
CBD 0.002 −0.006,0.010 0.580 11
THC*CBD interaction 0.000 0.000,0.000 0.733 11
Concentration/attention problem Intercept 0.502257 0.145686, 0.858829 0.006 11 1.154 0.992
THC −0.003128 −0.005162, −0.001094 0.003 11
CBD −0.003718 −0.006809, −0.000628 0.018 11
THC*CBD interaction 0.000024 0.000007, 0.000041 0.006 11
Disorientation Intercept 0.103 −0.045, 0.251 0.173 15 8.917 0.630
THC −0.001014 −0.001833, −0.000194 0.015 15
CBD 0.001 −0.001,0.002 0.315 15
THC*CBD interaction 0.000 0.000,0.000 0.386 15
Renal and Urinary Renal & urinary symptoms Intercept 0.490 −0.314, 1.295 0.233 10 1.199 0.977
THC −0.004 −0.011,0.003 0.237 10
CBD −0.011 −0.026,0.004 0.154 10
THC*CBD interaction 0.000 0.000,0.000 0.178 10
Respiratory/Thoracic Nose Tenderness Intercept 0.024 −0.475, 0.523 0.925 10 0.001 1.000
THC 0.000 −0.003,0.003 0.895 10
CBD −0.001 −0.009,0.008 0.906 10
THC*CBD interaction 0.000 0.000,0.000 0.888 10
Skin/Subcutaneous Other skin problem Intercept 0.049 −1.277, 1.376 0.942 9 2.369 0.796
THC 0.000 −0.011, 0.012 0.972 9
CBD −0.002 −0.030, 0.026 0.883 9
THC*CBD interaction 0.000 0.000,0.000 0.952 9
Rash Intercept 0.012 −0.488, 0.511 0.964 10 0.000 1.000
THC 0.000 −0.003,0.003 0.949 10
CBD 0.000 −0.009,0.008 0.955 10
THC*CBD interaction 0.000 0.000,0.000 0.946 10
Pressure Sore Intercept −0.041 −1.368, 1.286 0.952 9 0.568 0.989
THC 0.000 −0.011, 0.012 0.961 9
CBD 0.001 −0.027, 0.029 0.941 9
THC*CBD interaction 0.000 0.000,0.000 0.946 9
Vascular Hypotension Intercept 0.328 −0.182, 0.839 0.207 10 0.276 1.000
THC −0.003 −0.006, 0.001 0.099 10
CBD −0.007 −0.016,0.002 0.109 10
THC*CBD interaction 0.000 0.000,0.000 0.070 10
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Statistically significant results are presented in bold. A summary estimate of the intercept model represents the square root transformed incidence rate difference (IRSD) of a given AE when the doses of THC and CBD dose per week are 0. The incidence rate at a particular dose combination of THC and CBD formulation may be estimated using the formula: IRSD = intercept + summary estimate * (THC dose per week) + summary estimate * (CBD dose per week) + summary estimate * (THC dose per week)* (CBD dose per week)]. For example, the square root transformed incident rate difference (IRSD) of developing disorientation if a patient is taking a THC:CBD combination formulation containing 10 mg of THC per week and 10 mg of CBD per week will be IRSD = 0.103 + (−0.001014)*10 + (0.001)*10 + (0.000)*10*10 = 0.10286. To convert IRSD per person-year into incidence rate difference (IRD) per 1000 person-years (i.e. incidence rate difference associated with cumulative exposure at the specified doses of THC and CBD in combination over 1 year for 1000 individuals) one would need to use the formula (IRSD2 * 1000). Using this formula, the additional incidence (IRD) of disorientation attributable to THC:CBD combination exposure of 10 mg/week of THC and 10 mg/week of CBD in 1000 people over 1 year amounts to 10.58 per 1000 person-years. Therefore, in a sample of 1000 individuals taking a THC: CBD combination treatment containing 10 mg of THC and 10 mg of CBD per week over a 1-year period, 10.58 additional individuals will experience dizziness/lightheadedness attributable to their THC:CBD combination treatment.

Results

A total of 58 RCTs (n = 6611 participants; 1655.84 person-years of cannabinoid exposure) from 47 published articles were included (see Fig. 1, PRISMA flow chart for summary of study selection procedure and Supplementary Table 1a-b in the Supplementary Material for main study characteristics).

Figure 1.

Figure 1

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PRISMA flow diagram. In total, 58 studies were obtained from 47 papers, as in studies with more than one active treatment arm, each active arm was considered as a different study.

Supplementary Figures 1-7 (THC studies) and Figs 8–14 (THC: CBD combination studies) show the forest-plots and results stratified according to study design, for all cause and treatment-related AEs and SAEs, withdrawals, deaths, respectively.

Overall study quality (Grading of Recommendations Assessment, Development and Evaluation, GRADE) [15] is reported in Supplementary Table 1a and 1b. Risk of bias estimates are reported in Supplementary Figs 15(a,b) and 16(a,b). Sub-group meta-analysis at SOC level was done for systems with three or more AEs for THC (Supplementary Table 2a) and THC-CBD combination treatment (Supplementary Table 2b).

THC studies

In total, 31 RCTs (15 crossover and 16 parallel-arm) from 29 articles [20–48] (see Supplementary Table 1a in the Supplementary Material), reported on 1473 patients (analysed 1429; 1255.82 person-years; mean ± SD: 40.51 ± 181.32 person-years) on active and 1265 (analysed 1224) on control intervention, with mean reported ages across studies ranging from 50–87 years (males: 0–100%). All except four studies used placebo as control [20, 23, 32, 43].

Pooled IRDs for all cause (k = 21) and treatment-related AEs (k = 9) from all RCTs were 18.83 (95% Confidence Interval [CI], 1.47–55.79) and 16.35 (95% CI, 1.25–48.56) AEs per 1000 person-years, respectively. Pooled IRDs of the most commonly reported AEs (Table 1) suggested significantly higher incidence rate of dizziness/lightheadedness, somnolence/drowsiness, impaired mobility/balance/coordination, sedation, headache, dissociative/thinking/perception disorders, euphoria and dry mouth, amounting on average to an additional incidence of 0.819 (95% CI 0.489–1.232), 0.684 (95% CI 0.055–2.014), 0.078 (95% CI 0.006–0.234), 11.103 (95% CI 0.596–34.721), 5.287 (95% CI 0.191–17.324), 0.510 (95% CI 0.260–0.844), 9.117 (95% CI 0.765–26.669) and 1.059 (95% CI 0.346–2.161) per 1000 person-years respectively in active compared to control arms.

Table 1.

Effect of cumulative THC treatment across studies expressed as incidence rate difference (IRD, indicated by the summary estimate) followed by 95% confidence intervals and associated P value for each type of adverse event.

MedDRA high-level grouping Individual AE Summary estimate 95% CI (lower, upper) P value N Q Qp
Blood/Lymphatic System Anaemia 0.002 0.162, 0.230 0.863 16 2.105 1.000
Cardiac Dyspnoea 0.002 0.159, 0.233 0.852 16 1.329 1.000
Palpitation 0.000 0.000, 0.000 0.992 15 1.436 1.000
Chest pain 0.000 0.219, 0.187 0.938 16 3.720 0.999
Ear & Labyrinth Vertigo 0.000 0.185, 0.222 0.929 15 3.992 0.996
Eye Disorders Visual impairment/disturbances 0.141 0.006, 0.681 0.103 15 1.201 1.000
Gastrointestinal Nausea 0.021 0.082, 0.330 0.511 22 29.595 0.100
Vomiting 0.040 0.047, 0.378 0.348 18 10.998 0.857
Dry Mouth 1.059 0.346, 2.161 <0.001 20 43.062 0.001
General Pain: non-specific 0.000 0.178, 0.209 0.937 17 3.552 0.999
Fatigue/tiredness 0.003 0.024, 0.067 0.615 21 4.958 1.000
Weakness/reduced mobility 0.009 0.125, 0.299 0.674 16 2.911 1.000
Infections Unspecified 0.001 0.030, 0.058 0.754 16 2.738 1.000
UTI 0.009 0.013, 0.091 0.378 16 0.210 1.000
RTI 0.001 0.178, 0.226 0.908 16 14.231 0.508
Injury/Poisoning Falls & injuries 0.001 0.029, 0.060 0.723 15 2.330 1.000
Investigations Raised Gamma GT 0.001 0.171, 0.232 0.881 16 3.370 0.999
Metabolism/Nutritional Fluid retention 0.001 0.157, 0.196 0.913 16 2.129 1.000
Decreased appetite 0.001 0.169, 0.232 0.877 16 5.407 0.988
Increased appetite 0.001 0.182, 0.223 0.920 16 1.990 1.000
Musculoskeletal Spasm stiffness 0.000 0.035, 0.052 0.852 17 1.998 1.000
Joint disorders 0.005 0.019, 0.077 0.513 16 0.116 1.000
Musculoskeletal pain 0.039 0.000, 0.163, 0.062 18 13.544 0.699
Nervous System Sedation 11.103 0.596, 34.721 0.011 2 1.855 0.173
Dizziness/Lightheaded 0.819 0.489, 1.232 <0.001 25 61.099 <0.001
Mobility/Balance/Coordination 0.078 0.006, 0.234 0.007 17 21.216 0.170
Muscle weakness 0.006 0.016, 0.082 0.453 18 5.052 0.998
Headache/migraine 5.287 0.191, 17.324 0.016 8 10.475 0.163
Psychiatric Sleep problems/Insomnia 0.110 0.158, 1.125 0.373 17 9.656 0.884
Dissociative/Thinking/Perception 0.510 0.260, 0.844 <0.001 17 17.454 0.357
Somnolence/Drowsiness 0.684 0.055, 2.014 0.006 20 53.934 <0.001
Anxiety/Depression 0.008 0.014, 0.089 0.399 13 2.708 0.997
Concentration/attention problem 6.361 0.051, 27.778 0.072 5 2.146 0.709
Euphoria 9.117 0.765, 26.669 0.006 6 3.171 0.674
Renal and Urinary Bladder symptoms 0.009 0.128, 0.295 0.686 15 0.020 1.000
Reproductive system Male impotence 0.058 0.438, 0.032 0.260 15 8.150 0.881
Respiratory/Thoracic Nose tenderness 0.001 0.178, 0.229 0.902 15 1.985 1.000
Skin/Subcutaneous Other skin problem 0.072 0.515, 0.033 0.244 15 3.397 0.998
Rash 0.002 0.161, 0.249 0.831 15 1.968 1.000
Pressure sore 0.108 0.606, 0.015 0.153 15 1.225 1.000
Vascular Hypotension 0.000 0.195, 0.205 0.980 16 3.999 0.998
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I2 = percent of total variability (heterogeneity plus sampling variability) attributed to heterogeneity amongst the true effects. N = number of studies included in analysis. QE = test statistic for the test of heterogeneity. QEp = P value for the test of heterogeneity. UTI, Urinary tract infection. RTI, Respiratory tract infection. NA = not applicable. Statistically significant results are presented in bold.

Meta-regression analyses suggested a significant association between cumulative THC dose per week across THC studies and incidence rate (expressed as IRSD) of some of the AEs (Table 2) such as dry mouth, dizziness/lightheadedness, mobility/balance/coordination difficulties, dissociative/thinking perception and somnolence/drowsiness. However, these estimates need to be interpreted with caution due to heterogeneity across the studies reporting the AEs.

Pooled IRDs for all cause (k = 28) and treatment-related (k = 24) SAEs from all RCTs were 0.002 (95% CI, 0.117–0.188) and 0.908 (95% CI, 0.05–4.54) SAEs per 1000 person years respectively. Pooled IRDs for all cause (k = 14) and treatment-related withdrawals (k = 28) from all RCTs were 0.052 (95% CI, 0.43–0.04) and 0.517 (95% CI, 0.01–2.34) withdrawals per 1000 person years respectively. IRDs for all cause deaths (k = 31) from all RCTs were 0.023 (95% CI, 0.002–0.012) deaths per 1000 person-years.

Neither Egger’s test nor ‘Trim and fill’ method indicated publication or other selection bias for any of the other outcomes except for all cause AEs (Supplementary Figs 17a-f, 18a-f, 19a-e, 20a-c). For all cause AEs for all RCTs as outcome, Egger’s test was p = 0.0265, and Trim and fill method indicated one missing study. Meta-regression analyses indicated effects of clinical condition on estimated effect of THC treatment on all cause AEs, which seemed to be mainly related to a significantly lower estimated effect in crossover studies investigating neurodegenerative disorder (p = 0.005) patients compared to other conditions.

THC: CBD combination

A total of 27 studies (five crossover and 22 were parallel-arm; see Supplementary Table 1b in the Supplementary Material for additional details) from 22 articles [24, 26, 27, 31, 42, 49–64] reported on 1977 patients (analysed 1952; 400.02 person-years; mean ± SD: 14.82 ± 27.71 person-years) on active and 1896 (analysed 1872) on placebo, with mean reported ages across studies ranging from 51 to 67 years (males: 0–80%). All studies used placebo as control.

Pooled IRDs for all cause (k = 16) and treatment-related (k = 10) AEs from all RCTs was 19.37 (95% CI, 4.24–45.47) and 11.36 (95% CI, 2.55–26.48) respectively. Pooled IRDs of AEs (Table 3) from cumulative THC: CBD combination treatment across all studies per 1000 person-years for each single AE suggested significantly higher incidence rate of nausea, vomiting, dry mouth, fatigue/tiredness, dizziness/lightheadedness, somnolence/drowsiness and disorientation, amounting on average to an additional incidence of 0.674 (95% CI 0.100–1.7 54), 0.214 (95% CI 0.000–0.837), 1.227 (95% CI 0.093–3.650), 0.439 (95% CI 0.025–1.361), 2.467 (95% CI 0.519–5.862), 1.650 (95% CI 0.361–3.875) and 2.536 (95% CI 0.458–6.290)per 1000 person-years respectively in active compared to control arms.

Table 3.

Effect of cumulative THC:CBD combination treatment across THC:CBD studies expressed as incidence rate difference (IRD, indicated by the summary estimate, followed by 95% confidence intervals and associated P value).

MedDRA high-level grouping Individual AE Summary estimate 95% CI (lower, upper) P value N Q Qp
Blood/Lymphatic System Anaemia 0.003 0.115, 0.204 0.780 14 2.248 1.000
Cardiac Dyspnoea 0.004 0.112, 0.212 0.757 11 1.349 0.999
Palpitation 0.002 0.153, 0.227 0.847 10 8.871 0.449
Ear & Labyrinth Vertigo 1.602 0.001, 6.579 0.056 11 24.747 0.006
Eye Disorders Visual impairment/disturbances 0.354 0.107, 2.305 0.206 9 7.400 0.494
Gastrointestinal Nausea 0.674 0.100, 1.754 0.001 21 24.371 0.227
Vomiting 0.214 0.000, 0.837 0.045 19 23.852 0.160
Dry mouth 1.227 0.093, 3.650 0.007 17 52.664 <0.001
General Pain: non-specific 0.005 0.276, 0.444 0.818 14 20.025 0.095
Fatigue/tiredness 0.439 0.025, 1.361 0.010 19 29.920 0.038
Weakness/reduced mobility 0.008 0.107, 0.258 0.670 14 5.839 0.952
Infections Unspecified 0.002 0.159, 0.230 0.858 8 0.015 1.000
UTI 0.005 0.111, 0.219 0.740 11 0.580 1.000
RTI 0.000 0.142, 0.176 0.916 11 2.693 0.988
Injury/Poisoning Falls & injuries 0.136 0.004, 0.644 0.096 10 4.121 0.903
Investigations Raised Gamma GT 0.000 0.177, 0.201 0.951 10 0.323 1.000
Metabolism/Nutritional Decreased appetite 0.011 0.076, 0.237 0.585 16 8.888 0.883
Increased appetite 0.067 0.065, 0.600 0.323 10 6.947 0.643
Anorexia 0.010 0.078, 0.228 0.606 14 13.756 0.391
Musculoskeletal Back pain 0.000 0.187, 0.194 0.984 10 0.169 1.000
Spasm stiffness 0.002 0.153, 0.232 0.839 10 5.902 0.750
Musculoskeletal pain 0.000 0.178, 0.205 0.946 9 0.682 1.000
Neoplasms Neoplasms progression 0.009 0.074, 0.217 0.606 16 9.477 0.851
Nervous System Altered taste 0.237 0.039, 1.367 0.163 13 16.906 0.153
Dizziness/Lightheaded 2.467 0.519, 5.862 <0.001 24 75.465 <0.001
Headache/migraine 0.024 0.037, 0.250 0.385 18 19.517 0.300
Numbness/paraesthesia 0.009 0.284, 0.117 0.668 9 0.111 1.000
Psychiatric Sleep problems 0.001 0.148, 0.190 0.904 12 13.621 0.255
Dissociative/Thinking/Perception 0.010 0.098, 0.258 0.640 12 12.317 0.340
Somnolence/Drowsiness 1.650 0.361, 3.875 <0.001 19 32.569 0.019
Anxiety/Depression 0.716 0.085, 3.933 0.145 11 30.209 0.001
Concentration/attention problem 0.277 0.060, 1.685 0.181 11 15.614 0.111
Disorientation 2.536 0.458, 6.290 0.001 15 40.301 <0.001
Renal and Urinary Renal & urinary symptoms 0.001 0.161, 0.214 0.890 10 5.094 0.826
Respiratory/Thoracic Nose Tenderness 0.001 0.136, 0.192 0.867 10 0.165 1.000
Skin/Subcutaneous Other skin problem 0.029 0.072, 0.367 0.448 9 5.806 0.669
Rash 0.000 0.150, 0.177 0.935 10 0.038 1.000
Pressure Sore 0.059 0.037, 0.463 0.274 9 0.605 1.000
Vascular Hypotension 0.003 0.141, 0.243 0.792 10 5.880 0.752
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N = number of studies included in analysis. QE = test statistic for the test of heterogeneity. QEp = p value for the test of heterogeneity. NA = not applicable. Statistically significant results are presented in bold.

Meta-regression analyses suggested a significant association between individual AEs and weekly doses of THC and CBD and their interaction expressed as IRSD (Table 4) for some of the AEs such as palpitations (CBD and THC*CBD interaction), altered taste (CBD), dizziness and lightheadedness (THC), concentration and attention problems (THC, CBD, THC*CBD interaction) and disorientation (THC).

Pooled IRDs for all cause (k = 26) and treatment-related (k = 22) SAEs from all RCTs was 0.056 (95% CI, 0.02–0.39) and 0.058 (95% CI, 0.08–0.59) respectively. Pooled IRDs for all cause (k = 22) and treatment related (k = 27) withdrawals from all RCTs was 0.036 (95% CI, 0.44–0.08) and 0.489 (95% CI, 0.05–1.37) respectively. IRDs for all cause deaths (k = 27) from all RCTs were 0.010 (95% CI, 0.04–0.17).

Neither Egger’s test nor ‘Trim and fill’ method indicated significant effect of publication or other selection bias for any of the outcomes except for all cause AEs (Supplementary Figs 21a-d, 22a-f, 23a-e, 24a-c). For all cause AEs for all RCTs as outcome, Egger’s test was p = 0.0332, and ‘Trim and fill’ method indicated two missing studies. Meta-regression analysis indicated that there was a significant effect of neurodegenerative disorder on effect-size for all cause withdrawals (p = 0.044) compared to other conditions. Except these, moderators such as study design or type of intervention did not significantly influence estimated effects of THC:CBD combination treatment on any of the outcomes assessed.

Discussion

In this systematic review and meta-analysis, we estimated the additional risk of organ-specific and total AEs attributable to exposure with medicinal cannabinoids in middle aged and older adults by assessing incidence rate differences of AEs. For medications containing THC-alone, on average this amounted to an additional incidence of ~19 all-cause and ~16 treatment-related AEs, whilst for THC:CBD combination treatments, there was an additional incidence of ~19 all-cause and ~11 treatment-related AEs per 1000 person-years of exposure.

Importantly, in this meta-analysis, we identified specific AEs associated with THC in THC alone or THC: CBD combination treatments. We found that THC significantly increased the incidence of dizziness/lightheadedness, somnolence/drowsiness, impaired mobility/balance/coordination, sedation, headache, dissociative/thinking/perception disorders, euphoria and dry mouth amounting on average to an additional incidence from ˂1 to ~11 per 1000 person-years, respectively. Further, there was a dose-dependent increase in the additional incidence of the aforementioned AEs as well as dry mouth and dissociative/thinking/perception problems, such that the higher the weekly dose of THC the higher was the additional attributable incidence of these specific AEs. These individual AEs are worth noting, as they not only impair quality of life but may also contribute to risk of falls in this age group [11, 65, 66], a leading cause of fatal and nonfatal injuries amongst older people [66, 67]. Incidence of psychotic-like experiences such as dissociative/thinking/perception abnormalities was significantly increased in THC alone studies and associated with higher THC doses as noted in our previous observation [9] and can be distressing to patients and their carers.

In addition, further analysis showed that THC and CBD in combination significantly increased the incidence of nausea, vomiting, dry mouth, fatigue/tiredness, dizziness/lightheadedness, somnolence/drowsiness and disorientation, amounting on average to an additional incidence of ˂1 to ~3 per 1000 person-years, respectively. This highlights the need to be mindful of higher weekly doses of THC and CBD in the older population, who are also on other medications for multiple co-morbidities. Furthermore, there was a dose-dependent relationship of weekly CBD doses with palpitation, altered taste and problems of inattention and concentration. Some of these effects are consistent with another meta-analysis, though they also reported abnormal liver function tests, decreased appetite, diarrhoea, pneumonia [10]. However, most of the studies were in those with childhood epilepsies and authors conjectured that this may have been due to interaction of CBD with other medications such as clobazam and/or sodium valproate and excluding these studies showed only diarrhoea as an adverse event for CBD [10]. It is interesting to note that these side-effects were not found in our analysis for middle aged and older adults, although interaction with other medications was not examined.

This report, which includes data from 58 RCTs is an update of our previous meta-analysis summarising 46 RCTs, and confirms that whilst middle aged and older adults are at greater risk of both treatment-related and all cause AEs from CBMs containing THC, they are not associated with SAEs, withdrawals or death [8]. Critically, we extend previous literature by providing the first pooled estimate of incidence of AEs attributable to CBMs. As described before, previous reviews of AEs with CBMs have either been qualitative, did not specifically focus on middle aged and older adults, or did not consider the effects of THC, CBD, or their combination separately [8] or focused on specific clinical indications [7, 68–71]. They have sometimes reported conflicting findings in terms of AEs, likely contributed partly by varying pooled sample sizes, as well as the quality of included studies (details in Supplementary Discussion). In general, those with larger number of pooled participants tend to show a modest but significant increase in risk of AEs as we have reported here, though results vary in terms of specific individual AEs reported [68–71]. By pooling data across all indications, here, we extend previous evidence to provide a more comprehensive and robust CBM-specific summary of the plethora of AEs associated with CBM use in adults over the age of 50. We also provide dose–response relationship estimates that have not been reported before to the best of our knowledge, which may help clinicians and researchers in dosage decisions in different contexts [72]. Further, across different meta-analyses, AEs have commonly been reported in terms of risk ratios, odds ratios or incidence rate ratios. Whilst these metrics are useful to convey whether there are significant additional risks associated with CBMs, they do not lend themselves as easily to everyday use. One needs to be aware of the baseline risk in the control (or placebo) group, which often remains unclear, to estimate the additional incidence associated with exposure to the CBM over a period of time. By estimating the additional incidence rate of all AEs as well as specific AEs associated with CBM use, we hope that results reported here will allow easier use of this information in the clinical and research contexts, especially in terms of estimating and communicating additional risk.

Limitations

Our review has some limitations. Using GRADE Framework, we found evidence of moderate to high quality evidence in ~64% of studies and low to very low quality in 36% of studies. Some of the trials had inadequate information about randomisation, allocation concealment, selective outcome reporting and objective outcomes which restricts interpretation of results (see supplementary material for full details of bias). However, we included double-blind studies to increase the methodological rigour of the contributing evidence. Therefore, these results need to be considered in light of potential selective reporting of side-effects, often relatively short duration of treatment in included RCTs and imprecision in the estimated IRD values. Notwithstanding this, we provide estimates from a larger pool of patients with indication that publication or other selection biases are unlikely to have influenced the pooled estimates reported here [8]. Further, our dose–response relationship tables may also aid dosage and formulation decisions in clinicians and researchers using CBMs by allowing them to compute ball-park estimates of incidence of AEs at different dose ranges (see footnotes for Tables 2 and 4 for guidance on calculations).

Unlike in other recent meta-analyses, which reported summary effects separately based on indications [7, 68–71], we pooled safety and tolerability data in middle aged and older adults across a broad range of indications. Whilst this may have added to the heterogeneity of the data synthesised, it allowed us to comprehensively estimate separately the tolerability of the two broad categories of cannabinoid-based interventions i.e. THC only and THC:CBD combination, something that has not been done before. This is a key strength of the present approach, given the reported opposite effects of different cannabinoids [3, 73]. Another important strength of the present report relates to the analysis of the effects of moderators to examine the extent to which they may have influenced results, in particular relationship with cannabinoid weekly doses used and interaction.

There is growing evidence that THC and CBD may have opposing acute effects on autonomic arousal, brain [73] and cardiovascular function [74] and CBD may mitigate some of the harmful effects of THC on cognition and behaviour [73, 75, 76], consistent with their opposing effects on some of their molecular targets [3]. The suggestion that THC and CBD may have distinct tolerability profiles, with certain side-effects noticeable in those taking THC-only formulations whilst adverse effects may even be mitigated in those taking THC and CBD in combination, underscored the importance of examining their safety and tolerability separately as well as dose–response relationships as we have done here. Our findings of AEs are consistent with other meta-analyses but in addition show the association of weekly doses with some of the adverse effects of THC and CBD. Few studies have examined the drug–drug interaction of CBMs given their effect on cytochrome p450 enzymes [77], an important likely determinant of tolerability and dose adjustment in older people, and therefore worthy of investigation in future studies.

Conclusions

Results of the present study suggest that THC-containing CBMs are associated with certain gastrointestinal, neurological and psychiatric side-effects in a dose-related manner, both for THC only and for THC: CBD combinations some of which can be mitigated by CBD. Efficacy should additionally consider dose–response relationships with regard to tolerability whilst prescribing CBMs, particularly in older people.

Supplementary Material

aa-24-0836-File002_afae261
aa-24-0836-file002_afae261.docx (15.7MB, docx)

Contributor Information

Latha Velayudhan, Division of Academic Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK.

Sara Pisani, Division of Academic Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK.

Marta Dugonjic, Division of Academic Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK.

Katie McGoohan, Division of Academic Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK.

Sagnik Bhattacharyya, Division of Academic Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK.

Declaration of Conflicts of Interest

SB has participated in advisory boards for or received honoraria as a speaker from Reckitt Benckiser, EmpowerPharm/SanteCannabis and Britannia Pharmaceuticals. All of these honoraria were received as contributions towards research support through King’s College London, and not personally. SB and LV have collaborated with Beckley Canopy Therapeutics/Canopy Growth (investigator-initiated research) wherein they supplied study drug for free for charity (Parkinson’s UK) and NIHR (BRC) funded research.

Declaration of Sources of Funding

SB and LV have received grants from Parkinson’s UK, Psychiatry Research trust, Rosetrees Trust, Alzheimer's Research UK and National Institute of Health Research. SP PhD studentship is funded by Parkinson’s UK. The funding sources had no involvement in this research.

References

  • 1. Hazekamp A, Ware MA, Muller-Vahl KRet al. The medicinal use of cannabis and cannabinoids--an international cross-sectional survey on administration forms. J Psychoactive Drugs. 2013;45:199–210. [DOI] [PubMed] [Google Scholar]
  • 2. Kaskie B, Ayyagari P, Milavetz Get al. The increasing use of cannabis among older Americans: a public health crisis or viable policy alternative? Gerontologist. 2017;57:1166–72. [DOI] [PubMed] [Google Scholar]
  • 3. Pertwee RG. The diverse CB1 and CB2 receptor pharmacology of three plant cannabinoids: delta9-tetrahydrocannabinol, cannabidiol and delta9-tetrahydrocannabivarin. Br J Pharmacol. 2008;153:199–215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Burstein S. Cannabidiol (CBD) and its analogs: a review of their effects on inflammation. Bioorg Med Chem. 2015;23:1377–85. [DOI] [PubMed] [Google Scholar]
  • 5. Bhattacharyya S, Wilson R, Appiah-Kusi Eet al. Effect of Cannabidiol on medial temporal, midbrain, and striatal dysfunction in people at clinical high risk of psychosis: a randomized clinical trial. JAMA Psychiatry. 2018;75:1107–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Leweke FM, Mueller JK, Lange Bet al. Therapeutic potential of cannabinoids in psychosis. Biol Psychiatry. 2016;79:604–12. [DOI] [PubMed] [Google Scholar]
  • 7. Black N, Stockings E, Campbell Get al. Cannabinoids for the treatment of mental disorders and symptoms of mental disorders: a systematic review and meta-analysis. Lancet Psychiatry. 2019;6:995–1010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Velayudhan L, McGoohan K, Bhattacharyya S. Safety and tolerability of natural and synthetic cannabinoids in adults aged over 50 years: a systematic review and meta-analysis. PLoS Med. 2021;18:e1003524. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Velayudhan L, McGoohan KL, Bhattacharyya S. Evaluation of THC-related neuropsychiatric symptoms among adults aged 50 years and older: a systematic review and Metaregression analysis. JAMA Netw Open. 2021;4:e2035913. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Chesney E, Oliver D, Green Aet al. Adverse effects of cannabidiol: a systematic review and meta-analysis of randomized clinical trials. Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology. 2020;45:1799–806. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Deandrea S, Lucenteforte E, Bravi Fet al. Risk factors for falls in community-dwelling older people: a systematic review and meta-analysis. Epidemiology. 2010;21:658–68. [DOI] [PubMed] [Google Scholar]
  • 12. Alyono JC. Vertigo and dizziness: understanding and managing fall risk. Otolaryngol Clin North Am. 2018;51:725–40. [DOI] [PubMed] [Google Scholar]
  • 13. Moher D, Liberati A, Tetzlaff Jet al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Guyatt GH, Oxman AD, Vist GEet al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ (Clinical Research Ed). 2008;336:924–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Balshem H, Helfand M, Schünemann HJet al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol. 2011;64:401–6. [DOI] [PubMed] [Google Scholar]
  • 16. Elbourne DR, Altman DG, Higgins JPet al. Meta-analyses involving cross-over trials: methodological issues. Int J Epidemiol. 2002;31:140–9. [DOI] [PubMed] [Google Scholar]
  • 17. Egger M, Davey Smith G, Schneider Met al. Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical Research Ed). 1997;315:629–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Duval S, Tweedie R. A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J Am Stat Assoc. 2000;95:89–98. [Google Scholar]
  • 19. Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36:48. [Google Scholar]
  • 20. Lane M, Vogel CL, Ferguson Jet al. Dronabinol and prochlorperazine in combination for treatment of cancer chemotherapy-induced nausea and vomiting. J Pain Symptom Manage. 1991;6:352–9. [DOI] [PubMed] [Google Scholar]
  • 21. Volicer L, Stelly M, Morris Jet al. Effects of dronabinol on anorexia and disturbed behavior in patients with Alzheimer's disease. Int J Geriatr Psychiatry. 1997;12:913–9. [PubMed] [Google Scholar]
  • 22. Sieradzan KA, Fox SH, Hill Met al. Cannabinoids reduce levodopa-induced dyskinesia in Parkinson's disease: a pilot study. Neurology. 2001;57:2108–11. [DOI] [PubMed] [Google Scholar]
  • 23. Jatoi A, Windschitl HE, Loprinzi CLet al. Dronabinol versus megestrol acetate versus combination therapy for cancer-associated anorexia: a north central cancer treatment group study. J Clin Oncol Off J Am Soc Clin Oncol. 2002;20:567–73. [DOI] [PubMed] [Google Scholar]
  • 24. Zajicek J, Fox P, Sanders Het al. Cannabinoids for treatment of spasticity and other symptoms related to multiple sclerosis (CAMS study): multicentre randomised placebo-controlled trial. Lancet. 2003;362:1517–26. [DOI] [PubMed] [Google Scholar]
  • 25. Svendsen KB, Jensen TS, Bach FW. Does the cannabinoid dronabinol reduce central pain in multiple sclerosis? Randomised double blind placebo controlled crossover trial. BMJ (Clin Res Ed). 2004;329:253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Zajicek JP, Sanders HP, Wright DEet al. Cannabinoids in multiple sclerosis (CAMS) study: safety and efficacy data for 12 months follow up. J Neurol Neurosurg Psychiatry. 2005;76:1664–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Strasser F, Luftner D, Possinger Ket al. Comparison of orally administered cannabis extract and delta-9-tetrahydrocannabinol in treating patients with cancer-related anorexia-cachexia syndrome: a multicenter, phase III, randomized, double-blind, placebo-controlled clinical trial from the cannabis-In-cachexia-study-group. J Clin Oncol Off J Am Soc Clin Oncol. 2006;24:3394–400. [DOI] [PubMed] [Google Scholar]
  • 28. Tomida I, Azuara-Blanco A, House Het al. Effect of sublingual application of cannabinoids on intraocular pressure: a pilot study. J Glaucoma. 2006;15:349–53. [DOI] [PubMed] [Google Scholar]
  • 29. Meiri E, Jhangiani H, Vredenburgh JJet al. Efficacy of dronabinol alone and in combination with ondansetron versus ondansetron alone for delayed chemotherapy-induced nausea and vomiting. Curr Med Res Opin. 2007;23:533–43. [DOI] [PubMed] [Google Scholar]
  • 30. Curtis A, Mitchell I, Patel Set al. A pilot study using nabilone for symptomatic treatment in Huntington's disease. Movement Disorders: Off J Movement Disorder Soc. 2009;24:2254–9. [DOI] [PubMed] [Google Scholar]
  • 31. Johnson JR, Burnell-Nugent M, Lossignol Det al. Multicenter, double-blind, randomized, placebo-controlled, parallel-group study of the efficacy, safety, and tolerability of THC:CBD extract and THC extract in patients with intractable cancer-related pain. J Pain Symptom Manage. 2010;39:167–79. [DOI] [PubMed] [Google Scholar]
  • 32. Ware MA, Fitzcharles MA, Joseph Let al. The effects of nabilone on sleep in fibromyalgia: results of a randomized controlled trial. Anesth Analg. 2010;110:604–10. [DOI] [PubMed] [Google Scholar]
  • 33. Weber M, Goldman B, Truniger S. Tetrahydrocannabinol (THC) for cramps in amyotrophic lateral sclerosis: a randomised, double-blind crossover trial. J Neurol Neurosurg Psychiatry. 2010;81:1135–40. [DOI] [PubMed] [Google Scholar]
  • 34. Brisbois TD, Kock IH, Watanabe SMet al. Delta-9-tetrahydrocannabinol may palliate altered chemosensory perception in cancer patients: results of a randomized, double-blind, placebo-controlled pilot trial. Ann Oncol Off J Eur Soc Med Oncol. 2011;22:2086–93. [DOI] [PubMed] [Google Scholar]
  • 35. Walther S, Schupbach B, Seifritz Eet al. Randomized, controlled crossover trial of dronabinol, 2.5 mg, for agitation in 2 patients with dementia. J Clin Psychopharmacol. 2011;31:256–8. [DOI] [PubMed] [Google Scholar]
  • 36. Zadikoff C, Wadia PM, Miyasaki Jet al. Cannabinoid, CB1 agonists in cervical dystonia: failure in a phase IIa randomized controlled trial. Basal Ganglia. 2011;1:91–5. [Google Scholar]
  • 37. Toth C, Mawani S, Brady Set al. An enriched-enrolment, randomized withdrawal, flexible-dose, double-blind, placebo-controlled, parallel assignment efficacy study of nabilone as adjuvant in the treatment of diabetic peripheral neuropathic pain. Pain. 2012;153:2073–82. [DOI] [PubMed] [Google Scholar]
  • 38. Zajicek J, Ball S, Wright Det al. Effect of dronabinol on progression in progressive multiple sclerosis (CUPID): a randomised, placebo-controlled trial. Lancet Neurol. 2013;12:857–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Ahmed AI, Elsen GA, Colbers Aet al. Safety and pharmacokinetics of oral delta-9-tetrahydrocannabinol in healthy older subjects: a randomized controlled trial. Eur Neuropsychopharmacol J Eur College Neuropsychopharmacol. 2014;24:1475–82. [DOI] [PubMed] [Google Scholar]
  • 40. Ahmed AI, Elsen GA, Colbers Aet al. Safety, pharmacodynamics, and pharmacokinetics of multiple oral doses of delta-9-tetrahydrocannabinol in older persons with dementia. Psychopharmacology (Berl). 2015;232:2587–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Elsen GA, Ahmed AI, Verkes RJet al. Tetrahydrocannabinol for neuropsychiatric symptoms in dementia: a randomized controlled trial. Neurology. 2015;84:2338–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Jadoon KA, Ratcliffe SH, Barrett DAet al. Efficacy and safety of Cannabidiol and Tetrahydrocannabivarin on Glycemic and lipid parameters in patients with type 2 diabetes: a randomized, double-blind, placebo-controlled. Parallel Group Pilot Study Diabetes Care. 2016;39:1777–86. [DOI] [PubMed] [Google Scholar]
  • 43. Vries M, Van Rijckevorsel DC, Vissers KCet al. Single dose delta-9-tetrahydrocannabinol in chronic pancreatitis patients: analgesic efficacy, pharmacokinetics and tolerability. Br J Clin Pharmacol. 2016;81:525–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Amerongen G, Kanhai K, Baakman ACet al. Effects on spasticity and neuropathic pain of an oral formulation of Delta9-tetrahydrocannabinol in patients WithProgressive multiple sclerosis. Clin Ther. 2018;40:1467–82. [DOI] [PubMed] [Google Scholar]
  • 45. Carley DW, Prasad B, Reid KJet al. Pharmacotherapy of Apnea by cannabimimetic enhancement, the PACE clinical trial: effects of Dronabinol in obstructive sleep Apnea. Sleep. 2018;41:1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Herrmann N, Ruthirakuhan M, Gallagher Det al. Randomized placebo-controlled trial of Nabilone for agitation in Alzheimer's disease. Am J Geriatric Psychiatry Off J Am Assoc Geriatric Psychiatry. 2019;27:1161–73. [DOI] [PubMed] [Google Scholar]
  • 47. Elsen GAH, Ahmed AIA, Verkes RJet al. Tetrahydrocannabinol in Behavioral disturbances in dementia: a crossover randomized controlled trial. Am J Geriatric Psychiatry Off J Am Assoc Geriatric Psychiatry. 2015;23:1214–24. [DOI] [PubMed] [Google Scholar]
  • 48. Peball M, Krismer F, Knaus HGet al. Non-motor symptoms in Parkinson's disease are reduced by Nabilone. Ann Neurol. 2020;88:712–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Carroll CB, Bain P, Teare Let al. Cannabis for dyskinesia in Parkison disease: a randomized double-blind crossover study. Neurology. 2004;63:1245–50. [DOI] [PubMed] [Google Scholar]
  • 50. Vaney C, Heinzel-Gutenbrunner M, Jobin Pet al. Efficacy, safety and tolerability of an orally administered cannabis extract in the treatment of spasticity in patients with multiple sclerosis: a randomized, double-blind, placebo-controlled, crossover study. Multiple Sclerosis (Houndmills, Basingstoke, England). 2004;10:417–24. [DOI] [PubMed] [Google Scholar]
  • 51. Wade DT, Makela P, Robson Pet al. Do cannabis-based medicinal extracts have general or specific effects on symptoms in multiple sclerosis? A double-blind, randomized, placebo-controlled study on 160 patients. Multiple Sclerosis (Houndmills, Basingstoke, England). 2004;10:434–41. [DOI] [PubMed] [Google Scholar]
  • 52. Blake DR, Robson P, Ho Met al. Preliminary assessment of the efficacy, tolerability and safety of a cannabis-based medicine (Sativex) in the treatment of pain caused by rheumatoid arthritis. Rheumatology (Oxford). 2006;45:50–2. [DOI] [PubMed] [Google Scholar]
  • 53. Nurmikko TJ, Serpell MG, Hoggart Bet al. Sativex successfully treats neuropathic pain characterised by allodynia: a randomised, double-blind, placebo-controlled clinical trial. Pain. 2007;133:210–20. [DOI] [PubMed] [Google Scholar]
  • 54. Duran M, Perez E, Abanades Set al. Preliminary efficacy and safety of an oromucosal standardized cannabis extract in chemotherapy-induced nausea and vomiting. Br J Clin Pharmacol. 2010;70:656–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Pickering EE, Semple SJ, Nazir MSet al. Cannabinoid effects on ventilation and breathlessness: a pilot study of efficacy and safety. Chron Respir Dis. 2011;8:109–18. [DOI] [PubMed] [Google Scholar]
  • 56. Notcutt W, Langford R, Davies Pet al. A placebo-controlled, parallel-group, randomized withdrawal study of subjects with symptoms of spasticity due to multiple sclerosis who are receiving long-term Sativex(R) (nabiximols). Multiple Sclerosis (Houndmills, Basingstoke, England). 2012;18:219–28. [DOI] [PubMed] [Google Scholar]
  • 57. Portenoy RK, Ganae-Motan ED, Allende Set al. Nabiximols for opioid-treated cancer patients with poorly-controlled chronic pain: a randomized, placebo-controlled, graded-dose trial. J Pain Off J Am Pain Soc. 2012;13:438–49. [DOI] [PubMed] [Google Scholar]
  • 58. Zajicek JP, Hobart JC, Slade Aet al. Multiple sclerosis and extract of cannabis: results of the MUSEC trial. J Neurol Neurosurg Psychiatry. 2012;83:1125–32. [DOI] [PubMed] [Google Scholar]
  • 59. Lynch ME, Cesar-Rittenberg P, Hohmann AG. A double-blind, placebo-controlled, crossover pilot trial with extension using an oral mucosal cannabinoid extract for treatment of chemotherapy-induced neuropathic pain. J Pain Symptom Manage. 2014;47:166–73. [DOI] [PubMed] [Google Scholar]
  • 60. Serpell M, Ratcliffe S, Hovorka Jet al. A double-blind, randomized, placebo-controlled, parallel group study of THC/CBD spray in peripheral neuropathic pain treatment. Eur J Pain. 2014;18:999–1012. [DOI] [PubMed] [Google Scholar]
  • 61. Fallon MT, Albert Lux E, McQuade Ret al. Sativex oromucosal spray as adjunctive therapy in advanced cancer patients with chronic pain unalleviated by optimized opioid therapy: two double-blind, randomized, placebo-controlled phase 3 studies. Br J Pain. 2017;11:119–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Lichtman AH, Lux EA, McQuade Ret al. Results of a double-blind, randomized, placebo-controlled study of Nabiximols Oromucosal spray as an adjunctive therapy in advanced cancer patients with chronic uncontrolled pain. J Pain Symptom Manage. 2018;55:179–88.e1. [DOI] [PubMed] [Google Scholar]
  • 63. Twelves C, Sabel M, Checketts Det al. A phase 1b randomised, placebo-controlled trial of nabiximols cannabinoid oromucosal spray with temozolomide in patients with recurrent glioblastoma. Br J Cancer. 2021;124:1379–87. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Riva N, Mora G, Sorarù Get al. Safety and efficacy of nabiximols on spasticity symptoms in patients with motor neuron disease (CANALS): a multicentre, double-blind, randomised, placebo-controlled, phase 2 trial. Lancet Neurol. 2019;18:155–64. [DOI] [PubMed] [Google Scholar]
  • 65. Lindell E, Kollén L, Johansson Met al. Dizziness and health-related quality of life among older adults in an urban population: a cross-sectional study. Health Qual Life Outcomes. 2021;19:231. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Cuevas-Trisan R. Balance problems and fall risks in the elderly. Clin Geriatr Med. 2019;35:173–83. [DOI] [PubMed] [Google Scholar]
  • 67. Xu Q, Ou X, Li J. The risk of falls among the aging population: a systematic review and meta-analysis. Front Public Health. 2022;10:902599. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68. Bosnjak Kuharic D, Markovic D, Brkovic Tet al. Cannabinoids for the treatment of dementia. Cochrane Database Syst Rev. 2021;9:Cd012820. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. Torres-Moreno MC, Papaseit E, Torrens Met al. Assessment of efficacy and tolerability of medicinal cannabinoids in patients with multiple sclerosis: a systematic review and meta-analysis. JAMA Netw Open. 2018;1:e183485. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70. Wang L, Hong PJ, May Cet al. Medical cannabis or cannabinoids for chronic non-cancer and cancer related pain: a systematic review and meta-analysis of randomised clinical trials. BMJ. 2021;374:n1034. [DOI] [PubMed] [Google Scholar]
  • 71. AminiLari M, Wang L, Neumark Set al. Medical cannabis and cannabinoids for impaired sleep: a systematic review and meta-analysis of randomized clinical trials. Sleep. 2022;45:1–11. [DOI] [PubMed] [Google Scholar]
  • 72. Kruger DJ, Gerlach J, Kruger JSet al. Physicians' attitudes and practices regarding cannabis and recommending medical cannabis use. Cannabis Cannabinoid Res. 2023;9:e1048–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73. Bhattacharyya S, Morrison PD, Fusar-Poli Pet al. Opposite effects of delta-9-tetrahydrocannabinol and cannabidiol on human brain function and psychopathology. Neuropsychopharmacology. 2010;35:764–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74. Jadoon KA, Tan GD, O'Sullivan SE. A single dose of cannabidiol reduces blood pressure in healthy volunteers in a randomized crossover study. JCI Insight. 2017;2:e93760. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75. Englund A, Morrison PD, Nottage Jet al. Cannabidiol inhibits THC-elicited paranoid symptoms and hippocampal-dependent memory impairment. J Psychopharmacol. 2013;27:19–27. [DOI] [PubMed] [Google Scholar]
  • 76. Hindocha C, Freeman TP, Schafer Get al. Acute effects of delta-9-tetrahydrocannabinol, cannabidiol and their combination on facial emotion recognition: a randomised, double-blind, placebo-controlled study in cannabis users. Eur Neuropsychopharmacol. 2015;25:325–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77. Mahvan TD, Hilaire ML, Mann Aet al. Marijuana use in the elderly: implications and considerations. Consult Pharm. 2017;32:341–51. [DOI] [PubMed] [Google Scholar]

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