Development and validation of a nomogram for predicting dysphagia in long-term care facility residents

Dysphagia is a common problem that can seriously affect the health of elderly residents in long-term care facilities. Early identification and targeted measures can significantly reduce the incidence of dysphagia.

This study aims to establish a nomogram to evaluate the risk of dysphagia for elderly residents in long-term care facilities.

A total of 409 older adults were included in the development set, and 109 were included in the validation set. Least absolute shrinkage selection operator (LASSO) regression analysis was used to select the predictor variables, and logistic regression was used to establish the prediction model. The nomogram was constructed based on the results of logistic regression. The performance of the nomogram was evaluated by receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA). Internal validation was performed using tenfold cross-validation with 1000 iterations.

The predictive nomogram included the following variables: stroke, sputum suction history (within one year), Barthel Index (BI), nutrition status, and texture-modified food. The area under the curve (AUC) for the model was 0.800; the AUC value for the internal validation set was 0.791, and the AUC value for the external validation set was 0.824. The nomogram showed good calibration in both the development set and validation set. Decision curve analysis (DCA) demonstrated that the nomogram was clinically valuable.

This predictive nomogram provides a practical tool for predicting dysphagia. The variables included in this nomogram were easy to assess.

The nomogram may help long-term care facility staff identify older adults at high risk for dysphagia.