Last reviewed · How we verify

NCT07274995

Machine Learning-Based Prediction of Postoperative Pain After Pediatric Ambulatory Surgery

Active, enrolled Last updated 31 December 2025
What this trial tests

trial in Pain, Acute Post-Operative in 90 participants. Participants enrolled and being followed up; not accepting new ones.

Timeline
1 August 2025
Primary endpoint
30 November 2026
30 November 2026

Quick facts

Lead sponsorBaşakşehir Çam & Sakura City Hospital
StatusActive, enrolled
Study typeOBSERVATIONAL
Enrollment90
Start date1 August 2025
Primary completion30 November 2026
Estimated completion30 November 2026
Sites1 location across Turkey (Türkiye)

Conditions studied

Sponsor

Başakşehir Çam & Sakura City Hospital

Who can join

Adults 1 to 3, any sex, with Pain, Acute Post-Operative or Ambulatory Surgical Procedures. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

This study aims to predict pain after surgery in children of ages 1 to 3 years by using computer programming (machine learning). Participant children will be observed before, during, and after surgery. Before surgery, the investigators will record each child's age, sex, weight, and the parent's level of anxiety using a short questionnaire (STAI: State Trait Anxiety Inventory). During surgery, the investigators will note the type of the surgery, how long it takes, and the medication given for pain relief. After surgery, the child's pain will be checked using the FLACC (Face, Legs, Activity, Cry, Consolability) scale, which assesses the child's face, legs, activity, crying, and how easy they are to comfort. For each assesment the children will be given points from 0 to 2. Pain will be measured 2 times. Firstly when the child reaches to the postoperative recovery room after they are monitorized. Secondly after 30 minutes spending in recovery room. At both times the pain scores and vital signs (pulse pressure and saturation) will be noted. No additional medication or intervention will be done throughout the study. All information will be stored without names or personal details. A computer model will study 80% of the data and then test itself on the remaining 20% of the collected data to see how well it can predict pain.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

Verify or expand the search:

Other recruiting trials for Pain, Acute Post-Operative

Currently open trials in the same condition.

Other Başakşehir Çam & Sakura City Hospital trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07274995.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing