Predicting Pain After Ambulatory Gynaecological Laparoscopies

NCT ID: NCT07308444

Last Updated: 2025-12-29

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ENROLLING_BY_INVITATION

Total Enrollment

207 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-12-19

Study Completion Date

2026-07-31

Brief Summary

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As day surgery is increasingly preferred over in-hospital treatment due to feasibility and reduced economic costs, it is important to evaluate patient-related outcomes such as comfort and safety after discharge. Most previous studies on predictors for postoperative pain have not focused on postdischarge pain. In a previous study, we found that over 42% of the patients experienced severe postdischarge pain within the first 24 h after ambulatory gynaecologocal laparoscopic surgery, that is a pain score of 7-10 on the NRS. We identified four preoperative risk factors independently associated with severe postdischarge pain. We have developed a risk matrix to predict who will suffer from severe pain after surgery. The risk matrix needs to be validated in a new gynaecological patient sample. It has the potential to improve clinical practice by providing clinicians with a simple, evidence-based tool that can identify high-risk patients before surgery. The scoring takes less than one minute. Today, we do not have such an instrument at hand. The results from this project could influence current routines and treatments at Oslo University Hospital and may also apply to other patient populations and other hospitals.

The primary research objective is to validate a previously developed risk matrix for postdischarge pain in gynecological day-surgery patients.

Detailed Description

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Early identification of patients at high risk for severe pain can contribute to better and more targeted individual pain prevention and management, thereby reducing the incidence of unnecessary pain and discomfort after surgery. By identifying and treating patients who are particularly vulnerable to severe postoperative pain, we can also reduce the length of hospital stays, prevent unplanned admissions due to pain, decrease the number of outpatient inquiries related to pain, and expedite recovery and return to normal activities. This will contribute to reduced resource use, improved patient care, and hopefully increased patient satisfaction.

In this prospective observational cohort study, we will collect post-discharge pain data necessary to validate a previously developed risk matrix at two different time points: T1) preoperatively on the day of surgery, and T2) during a follow-up call on POD1. In addition, patients' postoperative pain will be assessed using the NRS during PACU stay.

According to the sample size calculation (n=188) + at least 10%, we will include at least 207 patients.

There is no risk connected to participation in the study. All patients will receive standard medical and surgical treatment throughout the study.

Conditions

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Pain

Keywords

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Risk matrix

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

1. Participant must be 18 years of age at the time of signing the informed consent.
2. Participant scheduled for ambulatory gynaecological laparoscopy.
3. Capable of giving written informed consent.
4. Must speak and read Norwegian.

Exclusion Criteria

1. Severe psychiatric disorder, severe cognitive dysfunction.
2. Intraoperative ketamine or lidocaine infusion or regional anaesthesia.
Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Oslo University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Marlin Comelon

Senior Physician, Anesthesiologist, PhD

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Oslo University Hospital

Oslo, , Norway

Site Status

Countries

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Norway

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

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939735

Identifier Type: -

Identifier Source: org_study_id