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Perioperative Hypoxemia in Pediatrics

Development and Validation of Perioperative Hypoxemia Using Clinical Big Data and Deep Learning Technique in Pediatric Patients

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04723017
Enrollment
17000
Registered
2021-01-25
Start date
2021-01-21
Completion date
2021-12-31
Last updated
2021-01-25

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hypoxemia

Brief summary

The primary aim was to develop and validation of perioperative hypoxemia using clinical big data and deep learning technique in pediatric patients

Interventions

OTHERRetrospective analysis cohort

We analyze pre-existing data base and develop machine-learning-based system that predicts the risk of hypoxemia

OTHERProspective validation cohort

We validate our model to predict the risk of hypoxemia to prospective cohort

Sponsors

Seoul National University Hospital
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
No minimum to 19 Years
Healthy volunteers
No

Inclusion criteria

* Pediatric patients undergoing general or spinal anesthesia and monitored anesthesia care

Exclusion criteria

* none

Design outcomes

Primary

MeasureTime frameDescription
hypoxemiafrom induction of anesthesia to end of operation, about 3 hourspulse oximetry desaturation below 95%

Countries

South Korea

Contacts

Primary ContactHee-Soo Kim, professor
dami0605@snu.ac.kr+82-2-2072-3664

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026