Key result
The 8-variable SURPAS model accurately predicted postoperative discharge not to home with a C index of 0.914, comparable to the 0.921 C index of the 28-variable full model.
Why the study?
Discharge destination is an important quality metric and planning tool, but whether the parsimonious 8-variable SURPAS tool can accurately predict discharge destination remained unknown.
Does the 8-variable SURPAS model accurately predict postoperative discharge destination compared to a 28-variable full model in surgical patients?
Population
5,303,519 patients from the ACS NSQIP 2012-2017 dataset
Comparison
8-variable SURPAS model vs 28-variable full model
Design
Retrospective database analysis / risk model evaluation
Authors
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May support simplified preoperative risk assessment; leaves open need for prospective validation before routine use.
Cohort (n=5,303,519)
Yes
Does the 8-variable SURPAS model accurately predict postoperative discharge destination compared to a 28-variable full model in surgical patients?
Effect estimate: C index 0.914 vs 0.921
A parsimonious 8-variable preoperative risk assessment tool (SURPAS) predicts discharge destination as accurately as a 28-variable model, facilitating integration into electronic health records for surgical planning.
Singh et al. (2019) conducted a cohort in Surgical patients (n=5,303,519). 8-variable SURPAS model vs. 28-variable ACS NSQIP full model was evaluated on Risk of postoperative discharge not to home (C index 0.914 vs 0.921). The 8-variable SURPAS model accurately predicted postoperative discharge not to home with a C index of 0.914, comparable to the 0.921 C index of the 28-variable full model.
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