CClinicalTrials.gg
CompletedNCT06903624CannabisUpdated Apr 3, 2025

Cannabis in Postoperative Pain Management

An observational study in Postoperative Pain, sponsored by Assuta Medical Center. Completed. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-04-03.

Sponsored by Assuta Medical Center · Observational

Study type
Observational
Model
Cohort
Time perspective
Retrospective
Enrollment
70,000
Ages
18 Years and older
Sex
All
01

Study summary

Postoperative pain management is critical for surgical recovery, affecting patient outcomes, hospitalization duration, and quality of life. Variability in pain perception and medication needs among surgical patients poses a challenge in clinical practice. Identifying predictive factors for pain severity and analgesic use could enhance personalized pain management strategies.

Cannabis, containing cannabinoids with analgesic and anti-inflammatory properties, has garnered attention as a potential pain management option for surgical patients. The effectiveness of cannabis varies, depending on surgery type, severity, and individual pain tolerance. Some studies suggest cannabis users may experience heightened pain sensitivity and require more analgesics, while others highlight its potential to reduce opioid use. Despite growing interest, the use of cannabis in surgery remains controversial due to a lack of large-scale clinical trials evaluating its safety and efficacy in this setting.

Some research indicates cannabis use could lower pain levels post-surgery and reduce opioid needs. However, other studies raise safety concerns, and conflicting findings have yet to establish its role conclusively. Given these uncertainties, healthcare professionals must carefully monitor cannabis use in surgical patients. Patients should inform providers of any cannabis use before surgery to ensure appropriate pain management and minimize risks.

This study aims to analyze pain intensity and analgesic usage patterns across various surgeries using real-world medical data. Machine learning models will predict high analgesic needs, focusing on cannabis users. This research seeks to optimize postoperative pain treatment and personalize clinical strategies.

Read the detailed description

Study Design This retrospective cohort study analyzes anonymized medical records of surgical patients who underwent surgery between January 2017 and January 2025 at the Assuta hospitals network.

Data Source Electronic health records from a hospital database, including postoperative pain scores, analgesic administration, and patient demographics. Pain levels will be assessed during hospitalization for up to one-week post-surgery. In the cannabis use research group, participants will be asked to report their daily use for at least the past six months. The study will utilize MDClone, a healthcare data analytics platform, to extract and analyze anonymized electronic health records. MDClone enables the generation of synthetic, privacy-preserving patient data, ensuring compliance with ethical and regulatory standards while allowing for robust statistical analysis.

Variables for Analysis

  • Demographics: Age, sex, BMI, Hospital stay, Operation duration, type of anesthesia, region of residence, marital status.
  • Medical History: Comorbidities, history of trauma, psychiatric conditions, prior surgeries.
  • Surgical Data: Type of procedure, intraoperative factors, postoperative complications.
  • Pain Management: Pain scores (e.g., VAS), opioid and non-opioid analgesic doses, use of regional anesthesia.
  • Psychosocial Factors: psychiatric medication use (e.g., antidepressants).
  • Hospital Course: Length of stay, ICU admissions

The study population The expected number of participants is 70,000 participants from the five medical canters in the Assuta network.

Statistical analysis include:

  1. Descriptive Analysis - Baseline characteristics will be summarized using means, medians, and proportions.
  2. Comparative Analysis - Pain levels and analgesic use across different surgical types, comorbidities and between cannabis users vs. non-users will be compared using t-tests, chi-square tests, or non-parametric equivalents.
  3. Machine Learning Models - Supervised learning algorithms (e.g., logistic regression, random forests, gradient boosting) will be employed to predict high analgesic requirements based on preoperative and intraoperative variables.
  4. Validation \& Model Performance - ROC-AUC, sensitivity, and specificity will be used to assess model accuracy.
02

Conditions studied

  • Postoperative Pain

Browse trials for

Keywords

  • Cannabis
  • Postoperative pain
  • Analgesics
  • Opioids
03

In context

Pain, Postoperative

5,093 studies on the registry are indexed under Pain, Postoperative; 1,140 are open to participants now.

This study's enrollment of 70,000 is above the median of 102 across 608 observational studies indexed under Pain, Postoperative.

Browse Pain, Postoperative studies →

Lead sponsor

Assuta Medical Center is the lead sponsor of 41 studies on the registry; 1 is open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

All patients that underwent painfull surgical procedures will be cosidered in the study.

Inclusion criteria

  • Patients aged 18 and over.
  • Patients who underwent surgery under general anesthesia.

Exclusion criteria

Exclusion Criteria:

  • Minimally painful surgical procedures, including wrist and ankle tendon surgeries, minor rectal surgeries (e.g., fistula repair, rectal polyp removal), and minor gynecological procedures (e.g., vaginal procedures, transvaginal tape [TVT] insertion and transurethral procedures).
  • Surgeries associated with potential neurological complications, such as craniotomy.
  • Procedures involving percutaneous stent placement, including ureteral stent insertion.
  • Incomplete pain assessment records
  • Patients with severe cognitive impairments, affecting their ability to accurately report pain levels.
  • Patients unable to express VAS scale.
05

Study design

Observational model
Cohort
Time perspective
Retrospective
Enrollment
70,000 participants (actual)
Patient registry
No

Groups and cohorts

  • Non cannabis users

    Patients that underwent surgical procedures

  • Chronic cannabis users

    Patients that use cannabis due to medical conditions causing chronic pain and underwent surgical procedure.

06

What researchers measure

Primary outcomes

  1. Pain Intensity

    To assess the impact of cannabis use on postoperative pain intensity (measured using the To assess the impact of cannabis use on postoperative pain intensity (measured using the Visual Analog Scale, VAS in a scale from 0 -no pain- to 10 -worst pain possible-)

    Time frame: 7 days

Secondary outcomes

  1. Analgesic Consumption

    total amount of analgesics required during the postoperative period including opioids

    Time frame: 7 days

07

Study locations

No study locations are listed for this record.

08

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Apr 3, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
09

Registry details

Key details

Study ID
NCT06903624
Lead sponsor
Assuta Medical Center
Responsible party
Sergio Gabriel Susmallian (Medicine Doctor, Assuta Medical Center) — Principal investigator
First posted
Mar 31, 2025
Start date
Jan 1, 2016
Primary completion
Feb 25, 2025
Completion
Mar 24, 2025
Last update
Apr 3, 2025

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Mar 2025. You cannot join it, but the record below documents what was studied.

Follow this study

Get an email when the registry record changes — status, dates, results — or when someone posts here.

Sign in to follow

Discussion

Questions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.

Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.

Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.

Start the discussion