Develop a Risk Prediction Model for Phthalate-ester-induced Diseases

This exploratory study collected basic demographic and laboratory data from the Taiwan Biobank using artificial intelligence algorithms and applied data mining to identify the correlations between phthalate esters [di(2-ethylhexyl) phthalate, DEHP], lifestyle, and disease.

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Key information

Conditions

Plasticizers

Sex eligibility

All sexes

Study type

Observational

Primary location

Cheng Hsin General Hospital, Taipei, Taiwan

About this study

This study was designed as exploratory research. The Institutional Review Board and the Taiwan Biobank approved the study before it was conducted (Approval Number: TWBR11007-06). The data set included information from participants between 30 and 70 years old who were tested for PAEs between 2016 and 2022 (1337 cases). The data set includes (1) questionnaire responses, such as basic personal information, individual health behaviors, and female health issues; (2) physical examination results, such as body mass index (BMI), body fat percentage, waist circumference, hip circumference, waist-to-hip ratio, blood pressure, heart rate, pulmonary function, and bone mineral density; (3) blood and urine analyses results from blood tests, serology tests, hepatobiliary function tests, renal function tests, and urinalysis; and (4) data on PAE content of urine

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

inclusion:

The target subjects of this study are individuals aged 30 to 70 years old
who were tested for PAEs from January 1, 2016 to December 31, 2020.

exclusion:

1who have not been tested for plasticizers

Treatment and study plan

Primary outcomes

Risk assessment analysis of disease and PAEs

Time frame: 2022

(1) questionnaire responses, such as basic personal information, individual health behaviors, and female health issues; (2) physical examination results, such as body mass index (BMI), body fat percentage, waist circumference, hip circumference, waist-to-hip ratio, blood pressure, heart rate, pulmonary function, and bone mineral density; (3) blood and urine analyses results from blood tests, serology tests, hepatobiliary function tests, renal function tests, and urinalysis; and (4) data on PAE content of urine.
Artificial intelligence prediction model for diseases and PAEs

Time frame: 2022

to apply machine learning to establish the correlations between the environmental hormone PAE and high disease risk and suggest assessment items for nursing intervention.

Sponsors and collaborators

Lead sponsor

National Taipei University of Nursing and Health Sciences

Other

Registry information

Official study title

Using Machine Learning Algorithms to Develop a Risk Prediction Model for Phthalate-ester-induced Diseases and Suggestions for Improved Nursing Assessment

Important dates

Study start: 2021
Primary completion: 2022
Study completion: 2022
First posted: Jun 7, 2023
Registry last updated: Jun 7, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.