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Development and validation of risk prediction model for adverse outcomes in trauma patients.

Qian ZhuangJianchao LiuWei LiuXiaofei YeXuan ChaiSongmei SunCong FengLin Li
Published in: Annals of medicine (2024)
This prognostic study found that three prediction models and nomograms including the patient clinical characteristics, vital signs, diagnoses, and laboratory test values can support clinicians in more accurately identifying patients who are at risk of adverse outcomes in different settings based on data availability.
Keyphrases
  • trauma patients
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • peritoneal dialysis
  • palliative care
  • case report
  • electronic health record
  • machine learning
  • deep learning