Clinical Data-Driven AI Model for Mortality Prediction After Hip Fracture

NCT07495527 | Completed

• 1 other identifier: 2025-12/209
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

Hip fractures are a major cause of morbidity and mortality, particularly in elderly patients. Accurate prediction of postoperative mortality is critical for risk stratification and clinical decision-making. Traditional scoring systems, such as the Nottingham Hip Fracture Score, have limitations in capturing complex, non-linear relationships among clinical variables. This retrospective cohort study aims to develop and validate an artificial intelligence-based model to predict 30-day mortality in patients undergoing hip fracture surgery. Clinical and laboratory data of approximately 1000 patients operated between January 1, 2022 and December 1, 2025 will be extracted from electronic health records. Variables include demographic characteristics, comorbidities, laboratory parameters, perioperative data, and postoperative complications. The performance of the artificial intelligence model will be evaluated and compared with conventional risk scoring systems. The study seeks to determine whether AI-based approaches can provide improved predictive accuracy for postoperative mortality in hip fracture patients.

Conditions

Hip Fracture , Postoperative Mortality

Outcome Measures

Primary Outcomes (1)

• 30-Day Postoperative Mortality

  All-cause mortality occurring within 30 days following hip fracture surgery, determined from hospital records and electronic health data.

  30 days after surgery and 1 year later

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This study population consists of adult patients who underwent surgical treatment for hip fractures at a tertiary care oncology training and research hospital between January 1, 2022 and December 1, 2025. The cohort is derived retrospectively from electronic health records and includes approximately 1000 patients. The population includes individuals with varying demographic characteristics, comorbidities, and perioperative risk profiles. Clinical data encompass demographic information, baseline functional and cognitive status, comorbid conditions, laboratory parameters, intraoperative variables, and postoperative complications. Patients with malignancy and those undergoing revision surgery are excluded. The study population represents a real-world clinical cohort used to develop and validate an artificial intelligence-based model for predicting 30-day postoperative mortality following hip fracture surgery.

You may qualify if:

• Patients who underwent surgical treatment for hip fracture between January 1, 2022 and December 1, 2025 Age ≥18 years Availability of complete demographic, clinical, and laboratory data in the electronic health record system Documented 30-day follow-up or mortality status

You may not qualify if:

• Patients with malignancy Patients undergoing revision hip surgery Patients with missing or incomplete key clinical or laboratory data required for analysis Patients with unavailable or undocumented 30-day mortality status

Sponsors & Collaborators

• Dr Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital: lead

Study Sites (1)

Dr. Abdurrahman Yurtaslan Ankara Oncology Training and Research Hospital

Ankara, 06200, Turkey (Türkiye)

Location

Related Publications (3)

• Ju M, Lee S, Marvich HM, Lin S. Accessing Alkoxy Radicals via Frustrated Radical Pairs: Diverse Oxidative Functionalizations of Tertiary Alcohols. J Am Chem Soc. 2024 Jul 24;146(29):19696-19703. doi: 10.1021/jacs.4c07125. Epub 2024 Jul 16.

  PMID: 39012345 BACKGROUND

• Wanchaijiraboon P, Sainamthip P, Teeyapun N, Luangdilok S, Poovorawan Y, Wanlapakorn N, Tanasanvimon S, Sriuranpong V, Susiriwatananont T, Zungsontiporn N, Pakvisal N. Safety Following COVID-19 Booster Vaccine with BNT162b2 Compared to mRNA-1273 in Solid Cancer Patients Previously Vaccinated with ChAdOx1 or CoronaVac. Vaccines (Basel). 2023 Feb 3;11(2):356. doi: 10.3390/vaccines11020356.

  PMID: 36851234 BACKGROUND

• Gonzalez Martinez J, Chen JJ, Aung T, Constantine T, Gonzalez-Martinez JA. Comparative Feasibility and Complication Analyses of Extraoperative (Bedside) Removal of Stereo-Electroencephalography Electrodes. Stereotact Funct Neurosurg. 2025;103(5):302-311. doi: 10.1159/000545984. Epub 2025 Apr 23.

  PMID: 40267891 BACKGROUND

MeSH Terms

Conditions

Hip Fractures

Condition Hierarchy (Ancestors)

Femoral Fractures; Fractures, Bone; Wounds and Injuries; Hip Injuries; Leg Injuries

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: M.D

Study Record Dates

• First Submitted: March 21, 2026
• First Posted: March 27, 2026
• Study Start: December 1, 2025
• Primary Completion: March 10, 2026
• Study Completion: March 20, 2026
• Last Updated: March 27, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)