Predicting Delayed In-Hospital Recovery of Physical Function After Total Knee Arthroplasty.

OBJECTIVE: To identify patients at high risk of delayed in-hospital functional recovery after knee replacement surgery by developing and validating a prediction model, including a combination of preoperative physical fitness parameters and patient characteristics.

DESIGN: Retrospective cohort study using binary logistic regression.

SETTING: University hospital, orthopedic department.

PARTICIPANTS: 260 adults (N=260) (≥18y) with knee osteoarthritis awaiting primary unilateral total knee arthroplasty and assessed during usual care between 2016 and 2020.

INTERVENTION: Not applicable.

MAIN OUTCOME MEASURES: Time to reach in-hospital functional independence (in days), measured by the modified Iowa Level of Assistance Scale. A score of 0 means completely independent. Potential predictor variables are a combination of preoperative physical fitness parameters and patient characteristics.

RESULTS: Binary logistic regression modeling was applied to develop the initial model. A low de Morton Mobility Index (DEMMI), walking aid use indoors, and a low handgrip strength (HGS) were the most important predictors of delayed in-hospital recovery. This model was internally validated and had an optimism-corrected R 2 of 0.07 and an area under curve of 61.2%. The probability of a high risk of delayed in-hospital recovery is expressed by the following equation:Phighrisk=(1/(1+e(-(2.638-0.193×DEMMI+0.879×indoorwalkingaid-0.007×HGS))))×100%.

CONCLUSIONS: The model has a low predictive value and a poor discriminative ability. However, there is a positive association between preoperative physical fitness and postoperative recovery of physical function. The validity of our model to distinguish between high and low risk, based on preoperative fitness values and patient characteristics, is limited.