Treatment outcome of falls injury and its associates in middle-aged and elderly inpatients: medical records-based analysis and prediction model construction

  Objective  To examine treatment outcome of falls injury and its influencing factors in middle-aged and elderly inpatients and to establish a nomogram prediction model of treatment efficacy for providing evidence to effective treatment of falls injury of the inpatients.

  Methods  The medical records of 1 500 patients aged 45 years and above and hospitalized due to falls injury from January 2017 through January 2022 were collected from Fenyang Hospital of Shanxi province. Unconditional multivariate logistic regression model was used to analyze factors affecting treatment efficacy of falls injury of the inpatients. A nomogram model for predicting falls injury treatment efficacy was established with R4.2.0 software; the discrimination of the established model was evaluated with the area under the receiver operating characteristic curve (AUC) and the goodness of fit of the model was assessed with Hosmer-Lemeshow test and calibration curve.

  Results  Of all the inpatients, 1 017 (67.8%) were cured at the discharges. The results of logistic regression analysis showed that the inpatients with following characteristics were more likely to have poor treatment outcome: with emergency admission to hospital, suffering from torso injury, with other unspecified falls injury, and being assessed as having an age-adjusted Charlson comorbidity index (aCCI) of 6 and greater; while, the inpatients with falls-induced upper or lower limb injury and having moderate or severe falls injury were more likely to have a better treatment outcome. A nomogram prediction model involving 5 variables was constructed, with an AUC of 0.732 (95% confidence interval: 0.705, 0.759) and a good goodness-of-fit (χ² = 12.692, P = 0.123).

  Conclusion  Admission mode, body part of falls injury, type of falls injury, severity of falls injury, and aCCI are closely related to treatment outcome of falls injury in middle-aged and elderly inpatients. The established nomogram model covering those variables for predicting treatment outcome of falls injury could be helpful for individualized and targeted treatment of falls injury among middle-aged and elderly inpatients.