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

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

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05892029

Enrollment

1136

Registered

2023-06-07

Start date

2021-01-01

Completion date

2022-12-31

Last updated

2023-06-07

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

Conditions

Plasticizers

Brief summary

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.

Detailed description

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

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

CROSS_SECTIONAL

Eligibility

Sex/Gender

ALL

Healthy volunteers

Yes

Inclusion criteria

inclusion: 1. The target subjects of this study are individuals aged 30 to 70 years old 2. who were tested for PAEs from January 1, 2016 to December 31, 2020. exclusion: 1who have not been tested for plasticizers

Design outcomes

Primary

Measure	Time frame	Description
Risk assessment analysis of disease and PAEs	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	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.

Countries

Taiwan

Outcome results