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Ensemble Machine Learning Models for Cost-Saving Prediction of Adverse Drug Reaction in Hospitalized Elderly patients with Type 2 Diabetes: A Multi-center Development, Validation and Economic Evaluation Study

Ensemble Machine Learning Models for Cost-Saving Prediction of Adverse Drug Reaction in Hospitalized Elderly patients with Type 2 Diabetes: A Multi-center Development, Validation and Economic Evaluation Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500109366
Enrollment
Unknown
Registered
2025-09-17
Start date
2025-09-30
Completion date
Unknown
Last updated
2025-09-22

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

Conditions

Type 2 Diabetes

Interventions

Retrospective study:None

Sponsors

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
60 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. Age >=60 years old; 2. Elderly inpatients initially diagnosed with T2DM.

Exclusion criteria

Exclusion criteria: Cases in the perioperative period, with a hospital stay of less than 24 hours, or incomplete laboratory records.

Design outcomes

Primary

MeasureTime frame
Economic Benefits;AUROC;—

Secondary

MeasureTime frame
Accuracy;Precision;Recall;F1-Score;—

Countries

China

Contacts

Public ContactWu Xingwei

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital

wuxingwei@med.uestc.edu.cn+86 151 9615 5259

Outcome results

None listed

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