Video Abstract

Video Abstract

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BACKGROUND

Increasing legalization and widespread misinformation about the dangers of cannabis use have contributed to the rising prevalence of cannabis use disorder (CUD) among adolescents. Our objective was to determine the prevalence of CUD in adolescent surgical patients and evaluate its association with postoperative complications.

METHODS

We performed a retrospective, 1:1 propensity-matched cohort study of adolescents (aged 10–17 years) with and without CUD who underwent inpatient operations at US hospitals participating in the Pediatric Health Information System from 2009 to 2022. The primary outcome was the trend in prevalence of CUD. Secondary outcomes included postoperative complications. Using a Bonferroni correction, we considered a P value < .008 to be significant.

RESULTS

Of 558 721 adolescents undergoing inpatient surgery from 2009 to 2022, 2604 (0.5%) were diagnosed with CUD (2483 were propensity matched). The prevalence of CUD increased from 0.4% in 2009 to 0.6% in 2022 (P < .001). The adjusted odds of respiratory complications, ICU admission, mechanical ventilation, and extended hospital stay were significantly higher in adolescents with CUD (respiratory complications: odds ratio [OR], 1.52; 95% confidence interval [CI], 1.16–2.00; P = .002; ICU admission: OR, 1.78; 95% CI, 1.61–1.98; P < .001; mechanical ventilation: OR, 2.41; 95% CI, 2.10–2.77; P < .001; extended hospital stay: OR, 1.96; 95% CI, 1.74–2.20; P < .001). The propensity score-adjusted odds of postoperative mortality or stroke for adolescents with CUD were not significantly increased (mortality: OR, 1.40; 95% CI, 0.87–2.25; P = .168; stroke: OR, 2.46; 95% CI, 1.13–5.36; P = .024).

CONCLUSIONS

CUD is increasing among adolescents scheduled for surgery. Given its association with postoperative complications, it is crucial to screen adolescents for cannabis use to allow timely counseling and perioperative risk mitigation.

What’s Known on This Subject:

Increasing legalization and widespread misinformation about cannabis have contributed to the rising prevalence of cannabis use among adolescents in the United States. Whether cannabis use disorder increases postoperative complications among adolescents has not been studied.

What This Study Adds:

The prevalence of comorbid cannabis use disorder in adolescents presenting for surgery is increasing, and this diagnosis is associated with increased risk of postoperative complications.

In 2022, an estimated 209 million individuals worldwide used cannabis in the past year, an increase of 23% over the previous decade.1  Much of this increase can be attributed to sensational claims of the natural health benefits of cannabis.2 ,3  An epidemiologic concern is the growing trend of adolescents being introduced to cannabis. The movement to legalize recreational cannabis use has created an overwhelming perception of cannabis safety among adolescents—only 14% of high school seniors believe cannabis use is harmful.4 ,5  According to the Centers for Disease Control and Prevention, ∼40% of high school students have reported using cannabis, with 1 in 5 having used cannabis in the previous month.6  The prevalence of cannabis use among American adolescents, likely amplified by increased societal acceptance, legalization, and ready drug availability, is a cause for concern.

Acute and chronic cannabis use have important implications for the cardiovascular, cerebrovascular, respiratory, thermoregulatory, and coagulation systems.7  Furthermore, cannabis can interact with anesthetic and analgesic medications.7 ,8  Given the multisystemic effects of cannabis and the increasing frequency of cannabis use among adolescents, it is imperative to evaluate the association of cannabis use with surgical outcomes. A recent retrospective cohort study among adult inpatient surgical patients demonstrated a modest increase in the rate of postoperative morbidity and mortality among patients with comorbid cannabis use disorder (CUD).9  Comparable data among the adolescent surgical population are unavailable.

In this report, we evaluated changes in the prevalence of comorbid CUD among adolescents who underwent surgical procedures between 2009 and 2022 in the United States. We also investigated the association of comorbid CUD with postoperative complications in the same cohort. We hypothesized that adolescents with comorbid CUD would have a higher risk of postoperative complications and mortality compared with adolescents without comorbid CUD.

We identified adolescents aged 10 to 17 years who underwent inpatient surgery between 2009 and 2022 using the Pediatric Health Information System (PHIS) dataset. The PHIS is an administrative database managed by the Children’s Hospital Association that provides detailed information on resource utilization and clinical data across different pediatric care settings, including inpatient, emergency department, and ambulatory care. The PHIS collects deidentified patient-level data from 50 not-for-profit pediatric hospitals in the United States. It includes demographic information, payer details, and diagnostic codes. The database is used for quality improvement and research. Our study protocol was approved by the institutional review board, with a waiver of written informed consent. We adhered to Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines for cohort studies.

The primary exposure was comorbid CUD. We identified patients with comorbid CUD using International Classification of Diseases (ICD-9 and ICD-10) codes.9  These codes are included in Supplemental Table 2.

The primary outcome was the annual prevalence and trend of comorbid CUD. The secondary outcomes included postoperative mortality and morbidity (stroke, cardiac, and respiratory complications). Consistent with a previous study, respiratory complications were operationalized as a composite variable including pneumonia and respiratory failure.10  We also assessed measures of postoperative resource utilization, including ICU admission, need for mechanical ventilation, and extended hospital length of stay. Length of stay was operationalized as a binary variable, with extended hospital stay defined as ≥75th percentile for the study cohort.

The standardized difference was used to compare baseline characteristics between adolescents with and without comorbid CUD. We described categorical variables as numbers and percentages, and continuous variables as median and interquartile range. To minimize confounding, we performed a 1:1 propensity score matching without replacement. We estimated the propensity of having comorbid CUD using a multivariable logistic regression model that included age, sex, race and ethnicity, admission priority, year of surgery, presence of preoperative complex chronic condition, and procedural group. Procedural group was derived from the PHIS service line data element, which was created by mapping the All-Patient Refined Diagnosis Related Groups (DRGs), Centers for Medicare and Medicaid Services DRGs, and Medicare Severity DRGs. DRGs are used to classify patients into homogeneous groups based on severity of illness, procedure complexity, and resource utilization.11  We analyzed race and ethnicity, which are based on perceived physical or cultural distinctiveness as social constructs.12  Race and ethnicity were defined according to PHIS data characteristics and were reported by parents or caregivers. Race and ethnicity were included as covariates because of known association with both the exposure and outcome variables.13 ,14  We defined postmatching covariate-specific imbalances by an absolute standardized difference ≥10%.15 ,16  We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for mortality, morbidity, and resource utilization comparing patients with and without comorbid CUD by using logistic regression models with general estimating equations in the matched sample. We adjusted our analyses for the presence of alcohol use disorder and tobacco use disorder, recognizing that individuals with CUD often suffer from other psychoactive substance disorders. We adjusted the P values by applying Bonferroni correction by the number of multiple comparisons. Therefore, we considered P < .05/6 (.008) as statistically significant. We used Stata 16 (StataCorp LP, College Station, TX) for all statistical analyses.

Between 2009 and 2022, 558 721 adolescents underwent inpatient surgery at 50 PHIS-participating hospitals. Of these, 2604 had a diagnosis of comorbid CUD, for a prevalence rate of 0.5%. Before propensity matching, adolescents with comorbid CUD differed in several ways from those without CUD (Table 1). Adolescents with comorbid CUD were older than those without CUD (aged 16 vs 14 years), they were more likely to be male, Black, and come from the lower income ZIP codes. Adolescents with CUD were more likely to be alcohol and/or smoking dependent and were less likely to have elective operations. Propensity score matching yielded a well-balanced distribution of covariates between adolescents with comorbid CUD and those without. The matched cohorts contained 2483 adolescents, with a standardized difference <10% for all covariates.

TABLE 1

Characteristics of Adolescents Undergoing Inpatient Surgery at PHIS-Participating Hospitals Between 2009 and 2022, Before and After Propensity Matching

CharacteristicsBefore Propensity MatchingAfter Propensity Matching
Cannabis Use DisorderStandard DifferenceCannabis Use DisorderStandard Difference
NoYesNoYes
Study population 556 117 (99.5) 2604 (0.5)  2483 (50.0) 2483 (50.0)  
Age, median [interquartile range] 14 [12–15] 16 [15–17] 0.98 16 [15–17] 16 [15–17] 0.00 
Male sex 298 142 (53.6) 1659 (63.8) 0.21 1560 (62.8) 1581 (63.7) 0.02 
Race/ethnicity 
 Non-Hispanic white 300 066 (54) 1288 (49.5) 0.09 1300 (52.4) 1234 (49.7) 0.02 
 Non-Hispanic Black 77 582 (14) 582 (22.4) 0.22 526 (21.2) 548 (22.1) 0.02 
 Other 47 314 (8.5) 187 (7.2) 0.05 164 (6.6) 179 (7.2) 0.02 
 Hispanic 117 140 (21.1) 484 (18.6) 0.06 437 (17.6) 460 (18.5) 0.02 
 Unknown 14 015 (2.5) 63 (2.4) 0.01 56 (2.3) 62 (2.5) 0.03 
Income for ZIP code, $ 
 >63 000 95 931 (17.3) 336 (12.9) 0.12 291 (11.7) 319 (12.8) 0.01 
 39–63 000 236 215 (42.5) 1030 (39.6) 0.06 986 (39.7) 976 (39.3) 0.01 
 <39 000 223 971 (40.3) 1238 (47.5) 0.15 1206 (48.6) 1188 (47.8) 0.00 
Alcohol/smoking dependent 972 (0.2) 453 (17.4) 0.64 384 (15.5) 384 (15.5) 0.01 
Chronic complex condition 228 161 (41) 1119 (43) 0.04 1067 (43) 1077 (43.4) 0.01 
Elective surgery 273 761 (51.3) 793 (31.2) 0.42 790 (31.8) 783 (31.5) 0.01 
Procedural group 
 Cardiovascular 22 124 (4) 119 (4.6) 0.03 107 (4.3) 112 (4.5) 0.01 
 Digestive/metabolic 133 775 (24.1) 36 5(14) 0.26 351 (14.1) 357 (14.4) 0.02 
 Hematology/oncology 9691 (1.7) 51 (2) 0.02 42 (1.7) 47 (1.9) 0.01 
 Neurology 64 871 (11.7) 301 (11.6) 0.00 297 (12) 289 (11.6) 0.02 
 Orthopedics/joint disease 170 472 (30.7) 716 (27.5) 0.07 701 (28.2) 678 (27.3) 0.00 
 Other surgical 128 260 (23.1) 866 (33.3) 0.23 818 (32.9) 822 (33.1) 0.00 
 Respiratory 18 357 (3.3) 117 (4.5) 0.06 108 (4.3) 110 (4.4) 0.02 
 Transplant 8567 (1.5) 69 (2.6) 0.08 59 (2.4) 68 (2.7) 0.01 
CharacteristicsBefore Propensity MatchingAfter Propensity Matching
Cannabis Use DisorderStandard DifferenceCannabis Use DisorderStandard Difference
NoYesNoYes
Study population 556 117 (99.5) 2604 (0.5)  2483 (50.0) 2483 (50.0)  
Age, median [interquartile range] 14 [12–15] 16 [15–17] 0.98 16 [15–17] 16 [15–17] 0.00 
Male sex 298 142 (53.6) 1659 (63.8) 0.21 1560 (62.8) 1581 (63.7) 0.02 
Race/ethnicity 
 Non-Hispanic white 300 066 (54) 1288 (49.5) 0.09 1300 (52.4) 1234 (49.7) 0.02 
 Non-Hispanic Black 77 582 (14) 582 (22.4) 0.22 526 (21.2) 548 (22.1) 0.02 
 Other 47 314 (8.5) 187 (7.2) 0.05 164 (6.6) 179 (7.2) 0.02 
 Hispanic 117 140 (21.1) 484 (18.6) 0.06 437 (17.6) 460 (18.5) 0.02 
 Unknown 14 015 (2.5) 63 (2.4) 0.01 56 (2.3) 62 (2.5) 0.03 
Income for ZIP code, $ 
 >63 000 95 931 (17.3) 336 (12.9) 0.12 291 (11.7) 319 (12.8) 0.01 
 39–63 000 236 215 (42.5) 1030 (39.6) 0.06 986 (39.7) 976 (39.3) 0.01 
 <39 000 223 971 (40.3) 1238 (47.5) 0.15 1206 (48.6) 1188 (47.8) 0.00 
Alcohol/smoking dependent 972 (0.2) 453 (17.4) 0.64 384 (15.5) 384 (15.5) 0.01 
Chronic complex condition 228 161 (41) 1119 (43) 0.04 1067 (43) 1077 (43.4) 0.01 
Elective surgery 273 761 (51.3) 793 (31.2) 0.42 790 (31.8) 783 (31.5) 0.01 
Procedural group 
 Cardiovascular 22 124 (4) 119 (4.6) 0.03 107 (4.3) 112 (4.5) 0.01 
 Digestive/metabolic 133 775 (24.1) 36 5(14) 0.26 351 (14.1) 357 (14.4) 0.02 
 Hematology/oncology 9691 (1.7) 51 (2) 0.02 42 (1.7) 47 (1.9) 0.01 
 Neurology 64 871 (11.7) 301 (11.6) 0.00 297 (12) 289 (11.6) 0.02 
 Orthopedics/joint disease 170 472 (30.7) 716 (27.5) 0.07 701 (28.2) 678 (27.3) 0.00 
 Other surgical 128 260 (23.1) 866 (33.3) 0.23 818 (32.9) 822 (33.1) 0.00 
 Respiratory 18 357 (3.3) 117 (4.5) 0.06 108 (4.3) 110 (4.4) 0.02 
 Transplant 8567 (1.5) 69 (2.6) 0.08 59 (2.4) 68 (2.7) 0.01 

The prevalence of CUD in adolescents undergoing surgery increased from 0.4% in 2009 to 0.6% in 2022, representing an adjusted annual percent change of 0.05% (95% CI, 0.04–0.06; P < .001; Fig 1).

FIGURE 1

Adjusted trend in the prevalence of comorbid CUD in adolescents presenting for surgery between 2009 and 2022 at Pediatric Health Information System–participating hospitals. CUD, cannabis use disorder.

FIGURE 1

Adjusted trend in the prevalence of comorbid CUD in adolescents presenting for surgery between 2009 and 2022 at Pediatric Health Information System–participating hospitals. CUD, cannabis use disorder.

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The overall postoperative complication rate was 2.6%, whereas the postoperative mortality rate was 0.58%. Postoperative complications occurred more frequently among adolescents with CUD compared with those without CUD (5.9% vs 3.7%; P = .001).

The incidence of postoperative mortality was 1.5% in adolescents with comorbid CUD, compared with 0.6% in those without CUD. However, after propensity score matching, the adjusted odds of mortality was not significantly different between the cohorts (OR, 1.40; 95% CI, 0.87–2.25; P = .168). The incidence of stroke was 0.9% in the CUD cohort and 0.3% in the cohort without CUD, which did not differ significantly after matching (OR, 2.46; 95% CI, 1.13–5.36; P = .024). Postoperative respiratory complications occurred more frequently in adolescents with comorbid CUD (5.2%) compared with those without (2.4%). The propensity adjusted odds of postoperative respiratory complications was 52% greater for those with comorbid CUD (OR, 1.52; 95% CI, 1.16–2.00; P = .002). The incidence of ICU admission was higher in patients with comorbid CUD (40.9%) than for those without CUD (24.4%), with a propensity score adjusted OR of 1.78 (95% CI, 1.61–1.98; P < .001). The requirement for postoperative mechanical ventilation occurred more frequently for adolescents with comorbid CUD than in those without (25.4% vs 8.3%), with a propensity score adjusted OR of 2.41 (95% CI, 2.10–2.77; P < .001). Finally, adolescents with comorbid CUD had a greater incidence of extended hospital length of stay (LOS) (49.6%) compared with those without CUD (29.6%). The propensity adjusted odds of postoperative extended LOS was 1.96 for adolescents with CUD (95% CI, 1.74–2.20; P < .001). The median hospital LOS was 4 days in the cohort with CUD compared with 3 days in those without (Fig 2).

FIGURE 2

Propensity score-adjusted odds of mortality and morbidities comparing adolescents with comorbid cannabis use disorder to those without.

FIGURE 2

Propensity score-adjusted odds of mortality and morbidities comparing adolescents with comorbid cannabis use disorder to those without.

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Using a US pediatric administrative database, we documented a steady increase in the prevalence of comorbid CUD among adolescents who underwent inpatient surgery. We also observed higher rates of major postoperative complications among those with CUD compared with their peers without CUD. Given the growing availability, legalization, and public perception of cannabis as innocuous or even beneficial, these findings are particularly concerning.

Cannabis is the most widely used illicit drug among adolescents in the United States.17  With increasing legalization and availability coupled with rising public misinformation about its safety and health benefits, increasing prevalence of cannabis use is anticipated.18  Recent estimates indicate that about 6.3% of US 12th graders are daily users of cannabis,19  an alarming statistic because daily use is a precursor of CUD.20  CUD is a more severe consequence of cannabis use; thus, our finding of increasing prevalence of CUD among adolescent surgical patients is particularly concerning. CUD is likely underdiagnosed among adolescents because of poor patient disclosure and inconsistent provider screening and documentation.21  Our results underscore the urgent need for identifying adolescents with CUD preoperatively for counseling and other interventions aimed at mitigating the additional surgical risk they incur. The perioperative encounter may be a “teachable moment” for counseling about cannabis cessation as well as allowing for interventions aimed at decreasing substance abuse in general.22 ,23  Recently, the US Preventive Services Task Force recommended screening all adolescents and adults in primary care settings for substance use disorders, including CUD, if “services for accurate diagnosis, effective treatment, and appropriate care can be offered or referred.”24  For optimal screening, practitioners should use a validated, brief instrument completed by the patient, either as a standalone questionnaire or integrated into a comprehensive health survey. Testing for cannabis (tetrahydrocannabinol in body fluids such as urine, saliva, or blood) is inappropriate as a screening method for CUD; a positive test result only signifies recent cannabis use, not the presence of CUD.25 

Previous investigations into the association of cannabis use with perioperative complications have produced conflicting results. For example, among a retrospective cohort of adult surgical patients, Goel et al observed no significant difference in composite postoperative complications between those with comorbid CUD and those without CUD.26  Conversely, Potnuru et al recently studied a matched cohort of adult surgical patients and demonstrated a modestly increased risk of major postoperative complications in patients with CUD.9  Similarly, studies of adults who underwent inpatient vascular operations documented higher rates of stroke and myocardial infarction among patients with CUD.27  Our findings are consistent with these adult studies. In demonstrating increased rates of major postoperative complications, as well as indicators of increased cost of surgical care (postoperative mechanical ventilation and prolonged hospital length of stay), we spotlight the inherent risks of comorbid CUD among a younger surgical cohort.

Mechanisms of increased perioperative risk with cannabis use are incompletely understood but may be related to increased vasomotor tone (with consequent risk of perioperative stroke and myocardial infarction), as well as pulmonary effects that increase the risk of perioperative respiratory complications.7  The pulmonary effects of cannabis use are especially relevant to adolescent perioperative care. Regular use of inhaled cannabis causes bronchial inflammation, cough, wheezing, asthma exacerbation, increased sputum production, and increased risk of pneumonia.28 ,29  Preoperative cannabis use is also associated with acute postoperative pharyngeal and uvula swelling.7  The resulting acute postoperative upper airway obstruction may prompt a need for postoperative reintubation, ICU admission, and postoperative mechanical ventilation. In patients with a history of cannabis use, meticulous attention should be given to optimizing the patient’s respiratory status before surgery and anticipating potential pulmonary complication in the perioperative period.

Several limitations should be considered when interpreting our findings. First is the inherent lack of granularity of using a large administrative database. For example, we were unable to differentiate between adolescents with mild, moderate, or severe CUD; increasingly severe CUD is associated with worse mental health and psychosocial outcomes.18  We do not have details on the circumstances leading up to death or the other postoperative complications, nor do we have granular information on patients’ medical conditions or their surgical and postoperative course. Second, we used ICD codes to identify patients with CUD. However, this method likely underestimates the prevalence of comorbid CUD, given the need for patient disclosure and/or provider recognition of the condition. Third, we were unable to ascertain route of cannabis ingestion (ie, smoking, oral ingestion, use of cannabinoids, or vaping), which can affect outcomes.9  For example, pulmonary symptoms (wheezing, coughing) are more prominent with inhalational ingestion, especially with vaping.30  Finally, overall CUD prevalence in our study was low, likely because of underdiagnosis. However, CUD is a more extreme spectrum of cannabis use. Indeed, our data are consistent with a previous report among adult surgical patients. These investigators observed an overall CUD rate of 0.8% in their sample of patients reported in the National Inpatient Sample (NIS).9 

In this retrospective, nationally representative study, we demonstrated an increasing trend of comorbid CUD in adolescents undergoing surgery, as well as an association of comorbid CUD with important postoperative complications. The increasing prevalence of cannabis use in children along with its surgical implications should provide the impetus to institute universal preoperative screening which may allow for teachable moments and deployment of mitigation strategies.

Dr Willer helped with interpretation of the data, critical review of literature, writing of the manuscript, and manuscript revision; Dr Mpody helped with idea conception, study design, statistical analysis, and manuscript preparation and revision; Dr Nafiu helped with idea conception, study design, critical review of the literature, data acquisition and analyses, and manuscript preparation and revision; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: Funding was provided from institutional and departmental sources only.

CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no potential conflicts of interest to disclose.

CI

confidence interval

CUD

cannabis use disorder

DRG

Diagnosis Related Groups

ICD

International Classification of Diseases

LOS

length of stay

OR

odds ratio

PHIS

Pediatric Health Information System

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Supplementary data