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Pilot Project for a Web-Based Dynamic Nomogram to Predict Survival 1 Year After Hip Fracture Surgery: Retrospective

Graeme McLeod1,2, Iain Kennedy1, Eilidh Simpson3

  • 1Department of Anaesthesia, Ninewells Hospital, National Health Service Tayside, Dundee, United Kingdom.

Interactive Journal of Medical Research
|March 3, 2022
PubMed
Summary

A new web-based nomogram simplifies hip fracture survival prediction. This tool helps clinicians and patients understand mortality risk factors like age, BMI, creatinine, and lactate levels.

Keywords:
fracturehiphip fracturemachine learningmodelmortalitynomogrampostoperativepredictionsurgerysurvivalweb

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Area of Science:

  • Geriatric Medicine
  • Surgical Oncology
  • Data Science in Healthcare

Background:

  • Hip fracture is a critical condition with significant mortality rates.
  • Accurate risk assessment is vital for anesthetic and surgical planning.
  • Existing risk models are often complex and difficult for clinical use.

Purpose of the Study:

  • To develop a user-friendly, web-based nomogram for predicting survival up to 365 days post-hip fracture surgery.
  • To simplify complex mathematical models for both clinicians and patients.
  • To improve decision-making and potentially reduce mortality risk.

Main Methods:

  • Data from 329 hip fracture patients were analyzed, including demographics, lab values (lactate, creatinine, BMI), and surgical details.
  • Cox proportional hazards and logistic regression models were developed and validated for survival prediction.
  • A web application was built using Shiny (RStudio) for accessible nomogram visualization on various devices.

Main Results:

  • Mortality rates were 7.3% (30 days), 19.8% (120 days), and 28.6% (365 days).
  • Key predictors of mortality included age, BMI, creatinine, and lactate levels.
  • The Cox model showed significant hazard ratios for age, lactate, and creatinine levels.

Conclusions:

  • A readily accessible web-based nomogram for hip fracture survival prediction has been developed.
  • The nomogram models demonstrated strong predictive accuracy, with concordance indices of 0.732 (Cox) and 0.781 (logistic).
  • This tool offers a simplified approach to understanding and managing post-hip fracture survival risks.