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

NCT07274995 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 90

Last updated 2025-12-31

No results posted yet for this study

Summary

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.

Conditions

  • Pain, Acute Post-Operative
  • Ambulatory Surgical Procedures
  • Pediatric Pain
  • Pediatric Patient (1m-21y)

Sponsors & Collaborators

  • Başakşehir Çam & Sakura City Hospital

    lead OTHER_GOV

Eligibility

Min Age
1 Year
Max Age
3 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-08-01
Primary Completion
2026-11-30
Completion
2026-11-30

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07274995 on ClinicalTrials.gov