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NCT07274995
Machine Learning-Based Prediction of Postoperative Pain After Pediatric Ambulatory Surgery
trial in Pain, Acute Post-Operative in 90 participants. Participants enrolled and being followed up; not accepting new ones.
30 November 2026
Quick facts
| Lead sponsor | Başakşehir Çam & Sakura City Hospital |
|---|---|
| Status | Active, enrolled |
| Study type | OBSERVATIONAL |
| Enrollment | 90 |
| Start date | 1 August 2025 |
| Primary completion | 30 November 2026 |
| Estimated completion | 30 November 2026 |
| Sites | 1 location across Turkey (Türkiye) |
Conditions studied
- Pain, Acute Post-Operative — all drugs for Pain, Acute Post-Operative →
- Ambulatory Surgical Procedures — all drugs for Ambulatory Surgical Procedures →
- Pediatric Pain — all drugs for Pediatric Pain →
- Pediatric Patient (1m-21y) — all drugs for Pediatric Patient (1m-21y) →
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:
- PubMed search for NCT07274995
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Other Başakşehir Çam & Sakura City Hospital trials
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT07274995 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Başakşehir Çam & Sakura City Hospital
- Last refreshed: 31 December 2025
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.
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