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Nano-LDI-MS-Driven Metabolic Fingerprinting: A Novel Tool for Ectopic Pregnancy Diagnosis and Risk Stratification

Nano-LDI-MS-Driven Metabolic Fingerprinting: A Novel Tool for Ectopic Pregnancy Diagnosis and Risk Stratification

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500106386
Enrollment
Unknown
Registered
2025-07-23
Start date
2025-04-23
Completion date
Unknown
Last updated
2025-08-18

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

Conditions

ectopic pregnancy

Interventions

Ultrasound combined with serum hCG
Index test:Using the Nano-LDI-MS system, a machine learning-based diagnostic model for ectopic pregnancy was constructed utilizing serum metabolic fingerprints

Sponsors

The international peace maternity and child health hospital
Lead Sponsor

Eligibility

Sex/Gender
Female

Inclusion criteria

Inclusion criteria: 1.Patients who visited our hospital between July 2024 and December 2024; 2.Gestational age <=12 weeks since last menstrual period; 3.Reproductive-aged women with clinically or pathologically confirmed diagnoses of either ectopic pregnancy or intrauterine pregnancy (Diagnostic criteria: Clinical evaluation combined with ultrasonography and serial serum ß-hCG measurements);

Exclusion criteria

Exclusion criteria: 1.Gestational age >12 weeks; 2.Missing clinical data or unclear pregnancy outcomes; 3.This pregnancy has received pharmacological treatment; 4.Patients with concurrent active pelvic inflammatory disease, malignancies, or other chronic medical conditions including but not limited to autoimmune diseases, rheumatic disorders, hyperlipidemia, or active liver diseases;

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy (AUC-ROC, sensitivity and specificity);

Secondary

MeasureTime frame
Differences in diagnostic performance across clinical subgroups (e.g., gestational weeks, high- vs. low-risk ruptured ectopic pregnancy groups);

Countries

China

Contacts

Public ContactShenglan Gu

The international peace maternity and child health hospital

gushenglan19920415@163.com+86 13162216071

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026