Innovative nomogram integrating bile acid metabolomics for early diagnosis of intrahepatic

128 pregnant individuals diagnosed with intrahepatic cholestasis of pregnancy (ICP) and matched healthy controls were recruited for a prospective cohort study. Bile acid profiles were quantified using liquid chromatography-tandem mass spectrometry to develop a predictive nomogram model. The model demonstrated excellent discrimination, with an AUC of 0.920 in the training cohort and 0.940 in the validation cohort.

Use Cases

• Developing predictive models for early intrahepatic cholestasis of pregnancy (ICP) based on bile acid metabolomics profiles.
• Comparing the diagnostic accuracy of novel metabolomic biomarkers against traditional total bile acid (TBA) tests.
• Assessing clinical utility of a nomogram-based risk prediction tool for maternal-fetal risk management.
• Validating LASSO regression for feature selection in clinical metabolomics studies.

Strengths

• Includes 128 pregnant individuals diagnosed with ICP and matched healthy controls.
• Model performance is quantified with specific AUC values (0.920 and 0.940) and confidence intervals.
• Data collection methodology is explicitly described, including LC-MS/MS quantification and a prospective cohort design from January 2019 to June 2024.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is from a single hospital (Zhejiang Provincial People’s Hospital), which may limit generalizability.

Provenance

Source

Shuyang Han via figshare.

Collection Method

Prospective cohort study with bile acid profiles quantified by LC-MS/MS and clinical variables collected.

Time Range

January 2019 to June 2024.

Freshness

Last updated 2026-05-21 02:06:33; freshness should be verified.

Geography

Likely Zhejiang Province, China, based on recruitment at Zhejiang Provincial People’s Hospital.