| Literature DB >> 22842793 |
Catriona M Steele1, Ervin Sejdić, Tom Chau.
Abstract
Aspiration (the entry of foreign contents into the upper airway) is a serious concern for individuals with dysphagia and can lead to pneumonia. However, overt signs of aspiration, such as cough, are not always present, making noninstrumental diagnosis challenging. Valid, reliable tools for detecting aspiration during clinical screening and assessment are needed. In this study we investigated the validity of a noninvasive accelerometry signal-processing classifier for detecting aspiration. Dual-axis cervical accelerometry signals were collected from 40 adults on thin-liquid swallowing tasks during videofluoroscopic swallowing examinations. Signal-processing algorithms were used to remove known sources of artifact and a classifier was trained to identify signals associated with penetration-aspiration. Validity was measured in comparison to blinded ratings of penetration-aspiration from the concurrently recorded videofluoroscopies. On a bolus-by-bolus basis, the accelerometry classifier had a 10 % false-negative rate (90 % sensitivity) and a 23 % false-positive rate (77 % specificity) for detecting penetration-aspiration. We conclude that accelerometry can be used to support valid, reliable, and efficient detection of aspiration risk in patients with suspected dysphagia.Entities:
Mesh:
Year: 2012 PMID: 22842793 PMCID: PMC3576558 DOI: 10.1007/s00455-012-9418-9
Source DB: PubMed Journal: Dysphagia ISSN: 0179-051X Impact factor: 3.438
Summary of previously reported sensitivity/specificity statistics for aspiration detection by swallow screening and clinical assessment tools compared to gold-standard instrumental swallowing examinations
| Test and population | Population | Sensitivity (%) | Specificity (%) | False-positive rate (%) | False-negative rate (%) | Blinding? |
|---|---|---|---|---|---|---|
| Daniels swallow screen [ | Acute stroke | 92 | 66 | 33 | 8 | Yes |
| Gugging swallow screen [ | Stroke | 100 | 50 | 50 | 0 | Yes |
| Standardized clinical swallowing assessment [ | Stroke | 47 | 86 | 14 | 53 | Yes |
| Volume-viscosity screening test [ | Heterogeneous | 100 | 29 | 72 | 0 | Yes |
Participant demographics
| Sex | No. of participants | Mean age | SD | Age range |
|---|---|---|---|---|
| Female | 20 | 67 | 14 | 37–90 |
| Male | 20 | 67 | 14 | 40–90 |
Fig. 1Videofluoroscopic image showing the accelerometry sensor in situ on the front of the neck, with the superior-inferior (S–I) axis aligned vertically with the surface of the participant’s neck and the anterior-posterior (A–P) axis derived at 90° to the S–I axis
Fig. 2Flowchart showing the signal-processing steps used to analyze the dual-axis accelerometry signals
Accuracy statistics for the accelerometry signal-processing classifier algorithm for detecting aspiration in comparison to concurrent videofluoroscopy
| Parameter | Statistic | Per bolus | Per participant |
|---|---|---|---|
| Impaired swallowing safety (13/37 patients; 55/154 swallows) | Sensitivity (%) | 90 | 100 |
| Specificity (%) | 77 | 54 | |
| Negative predictive value (%) | 97 | 100 | |
| False-positive rate (%) | 23 | 48 | |
| False-negative rate (%) | 10 | 0 |