Development of Machine Learning Models for the Prediction of BMI and Complications After Bariatric Surgery (CABS-Study)

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05710913

Enrollment

10000

Registered

2023-02-02

Start date

2023-01-05

Completion date

2025-12-31

Last updated

2023-02-02

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

Conditions

Anastomosis, Leaking, Body Weight, Diabetes Mellitus, Type 2, GERD, Hiatal Hernia, Internal Hernia, Intussusception, Mesenteric Hernia, Post-Op Complication, Sleep Apnea, Obstructive

Keywords

Bariatric Surgery, Machine learning, Clinical prediction modelling, Artificial intelligence

Brief summary

This Study aims to develop machine learning models with the ability to predict patients' BMI and complications after Bariatric Surgery (CABS-Score). This Study also aims to develop machine learning models with the ability to predict diabetic (DM II)patients' remission rate after Bariatric Surgery. The service mentioned above will be publicly available as a web-based application

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Inclusion criteria

* Patients undergoing bariatric surgery * Patients \>18 years

Exclusion criteria

* Patients \<18 years * Patients who cannot be followed up on for more than 6 month after surgery * Patients who are unable to provide informed approval to participate according to each centre's rules will be excluded.

Design outcomes

Primary

Measure	Time frame
Body mass Index (KG/m2) after surgery	[Time Frame: From index surgery up to 1 year postoperatively]
Diabetes mellitus type II remission rate postoperatively	[Time Frame: From index surgery up to 2 year postoperatively]
Complication after surgery	[Time Frame: From index surgery up to 3 months postoperatively]

Countries

Switzerland

Contacts

Primary ContactAnas Taha, MD

anas.taha@unibas.ch0041612075402

Backup ContactBassey Enodien, MD

Bassey.enodien@gzo.ch

Outcome results