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Predicting Elective Surgical Patient Outcome Destination Based on the Preoperative Modified Frailty Index and

Steven Walczak1, Vic Velanovich2

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The modified frailty index (mFI) with laboratory values accurately predicts postoperative discharge destinations. Combining clinical and lab data improves prediction accuracy for better patient care planning.

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FrailtyLaboratory valuesPostoperative discharge destination

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Area of Science:

  • Surgical outcomes research
  • Health services research
  • Predictive analytics in healthcare

Background:

  • Accurate prediction of postoperative discharge destination is crucial for patient care and resource management.
  • The modified frailty index (mFI) is a tool used to assess patient frailty.
  • Integrating laboratory values into frailty assessment may enhance predictive capabilities.

Purpose of the Study:

  • To evaluate the accuracy of the preoperative modified frailty index (mFI), with and without laboratory values (mFI-labs), in predicting postoperative discharge destination.
  • To compare the predictive performance of mFI-clinical versus mFI-labs for discharge destination.
  • To assess the utility of artificial neural networks in predicting discharge destination.

Main Methods:

  • Cohort analysis of the 2018 American College of Surgeon National Surgical Quality Improvement Project (ACS-NSQIP) database.
  • Inclusion of patients with complete data for age, sex, operation work relative-value units, mFI-clinical (12 findings), and mFI-labs (7 values).
  • Analysis using univariate analysis, multiple logistic regression, and supervised learning artificial neural networks.

Main Results:

  • Higher mFI-clinical and mFI-lab scores, older age, and more complex operations correlated with non-home discharge destinations.
  • Traditional statistical methods showed limitations in predicting exact discharge destinations.
  • Artificial neural network analysis achieved perfect prediction in 64.9% of cases and within one level in 87.4%.

Conclusions:

  • Combining mFI-clinical with laboratory values significantly enhances the prediction of postoperative discharge destination compared to using either alone.
  • Preoperative prediction of discharge destination using mFI and lab values can optimize postoperative care planning and delivery.
  • This approach aids in setting realistic expectations for patients and families regarding their recovery environment.