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OpenTrials
Completed

NCT Number: NCT07121309

With the Development of Research, New Algorithms and Technologies Have Emerged, One of Which is Machine Learning. Machine Learning Can Extract Key Factors From Vast Amounts of Data, Identify Underlying Patterns, and Predict Future Trends. In Recent Years, Machine Learning Has Been Widely Used in

The aim of this study is to construct a predictive model for postoperative delirium in elderly patients with hip fractures. The main question it answers is to construct a risk prediction model for hip fractures in the elderly through six machine learning methods, compare which method's model is better, and conduct external validation of the model's stability to provide a reference for the early clinical detection of postoperative delirium in elderly hip fracture patients.

The clinical data of elderly patients with hip fractures have been collected in clinical practice and the model has been constructed.

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Key information

Conditions

Delirium Confusion Femoral Fractures Fractures, Bone Hip Fractures Hip Injuries Leg Injuries Mental Disorders Nervous System Diseases Neurobehavioral Manifestations Neurocognitive Disorders Neurologic Manifestations Pathological Conditions, Signs and Symptoms Signs and Symptoms Wounds and Injuries

Age range

60 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

SecondSoochowU

Suzhou, Jiangsu, 215004, China

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age ≥ 60 years; diagnosed with hip fracture by X-ray; patients who underwent surgical treatment.

Exclusion criteria

  • Patients with other severe diseases (Patients who reach grade IV or higher according to the American Society of Anesthesiologists (ASA) health status classification;Suffer from end-stage diseases;there is multiple organ dysfunction syndrome (MODS) or single organ failure); patients with mental disorders; patients participating in other studies.

Treatment and study plan

Primary outcomes

  1. Postoperative delirium

    Time frame: The day after the operation

    The Memory and Delirium Assessment Scale (MDAS) was used for delirium risk screening and assessment, including consciousness, attention, speech, behavior, and sleep aspects.

Sponsors and collaborators

Lead sponsor

Second Affiliated Hospital of Soochow University

Other

Registry information

Official study title

Establishment of a Postoperative Delirium Risk Prediction Model for Elderly Hip Fracture Patients Based on Machine Learning Algorithms

Acronym: POD

Important dates

Study start
2024
Primary completion
2025
Study completion
2025
First posted
Aug 13, 2025
Registry last updated
Aug 13, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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