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Second Affiliated Hospital of Soochow University901 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

901

Conditions

Delirium

Eligibility

Sex: ALLMin age: 60 YearsHealthy volunteers:

Medical Language ↔ Plain English

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.

Locations (1)

SecondSoochowU

Suzhou, Jiangsu, China

Outcomes

Primary Outcomes

Postoperative delirium

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

Time frame: The day after the operation