Prediction of aspiration in dysphagia using logistic regression: oral intake and self-evaluation

Abstract

Objectives: Oropharyngeal dysphagia (OD) has a major influence on health in general and health-related quality of life (HR-QoL) in particular. The gold standard assessments for OD, especially for aspiration in OD, are fiberoptic endoscopic evaluation of swallowing (FEES) and videofluoroscopy (VFSS), but not all patients have access to such procedures. Therefore, the current study built a prediction model to forecast aspiration in patients with OD on the basis of common self-evaluation questionnaires and oral intake status.

Methods: A consecutive series of 111 patients with confirmed diagnosis of OD was measured according to a standardised protocol using the following tools: the Swallowing Quality of Life Questionnaire (SWAL-QOL), the Dysphagia Handicap Index (DHI), two self-report visual analogue scales which measure the Severity and the Impairment of the swallowing problem on everyday social life as experienced by the patient, the Eating Assessment Tool 10 (EAT-10), the Functional Oral Intake Scale (FOIS) and subsequently FEES (the gold standard). Penalised logistic regression was carried out to predict aspiration. The performance of the resulting models was evaluated by constructing receiver operating characteristics (ROC) curves and computing areas under the curve (AUC).

Results: The final model showed an AUC of 0.92, indicating excellent performance.

Conclusion: This study shows that it may be possible to accurately predict aspiration in oropharyngeal dysphagia by a non-invasive and non-instrumental assessment protocol including oral intake status and self-report questionnaires on functional health status and HR-QoL.

Keywords: Aspiration; Assessment; Deglutition; Logistic regression; Predictive model; Swallowing disorders.

Fig. 1

a ROC Model 1 Variable set (A) included the following variables: SWAL-QOL subscales Burden, Food selection, Eat duration, Eat desire and Symptom scale, DHI subscales (Functional, Physical and Emotional), VAS scales (Severity and Impairment), EAT-10 item 9 (‘I cough when I eat’) and FOIS. AUC 0.862. b ROC Model 1 Variable set (B). Reduced model to SWAL-QOL Food Selection, DHI subscales (Functional, Physical and Emotional), EAT-10 item 9 (‘I cough when I eat’) and FOIS. AUC 0.852. c ROC Model 2 Variable set (A), included the following variables: SWAL-QOL subscales Burden, Food selection, Eat duration, Eat desire, Symptom scale and Symptom scale squared, DHI subscales (Functional, Physical and Emotional), VAS scales (Severity and Impairment), EAT-10 item 9 (‘I cough when I eat’) and FOIS. AUC 0.874. d ROC Model 3 Variable set (A) included the following variables: SWAL-QOL subscales Burden, Food selection, Eat duration, Eat desire, Symptom scale and Symptom scale squared, DHI item 1p (‘I cough when I drink’), DHI Severity Question, VAS scales (Severity and Impairment), EAT-10 item 9 (‘I cough when I eat’) and FOIS. AUC 0.922. e ROC Model 3 Variable set (B) included the following variables: SWAL-QOL subscales Food selection and the Symptom scale squared, DHI subscales (Functional, Physical and Emotional), DHI item 1p (‘I cough when I drink’), DHI Severity question, EAT-10 item 9 (‘I cough when I eat’) and FOIS. AUC 0.915