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PREDICTING MINS WITH FRAILTY AND BIOMARKERS IN GERIATRIC SURGERY

NCT07566013 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 600

Last updated 2026-05-04

No results posted yet for this study

Summary

The primary objective of this study is to develop and validate a machine learning model that integrates preoperative clinical data, biomarkers, and modified frailty indices (mFI-5) to accurately predict myocardial injury after non-cardiac surgery (MINS) in geriatric patients ($\\ge$65 years) undergoing major orthopedic surgery and requiring postoperative intensive care. The research aims to compare the predictive performance of advanced algorithms, such as XGBoost and Random Forest, against traditional clinical risk scores like the Revised Cardiac Risk Index (RCRI), while specifically evaluating the impact of frailty on the model's area under the curve (AUC). Furthermore, by identifying the most critical preoperative predictors, this study seeks to establish an objective clinical decision support mechanism to guide clinicians in the early risk stratification of high-risk geriatric patients.

Conditions

  • Geriatric Patients
  • Postoperative Complications
  • Frailty
  • Myocardial Ischemia
  • Hip Surgeries

Interventions

OTHER

Preoperative Risk Assessment and Machine Learning Modeling

Standard clinical care for major orthopedic surgery including preoperative assessment of biomarkers (hs-cTnT, NT-proBNP), frailty screening (mFI-5), and clinical data collection for the development of a machine learning-based MINS prediction model.

Sponsors & Collaborators

  • DİLEK KALAYCI

    lead OTHER

Principal Investigators

  • Dilek Kalaycı · Dr Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital

Eligibility

Min Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-04-01
Primary Completion
2026-06-01
Completion
2026-06-05

Countries

  • Turkey (Türkiye)

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07566013 on ClinicalTrials.gov