-Background/Aim: This investigation assessed the effects of dental trauma on the perception of pain and quality of life (QoL) of patient-parent pairs for a year following severe injuries. Sample: A visual analogue scale (VAS) was used to assess the pain of injury and treatment for 27 individuals 8-20 years and their parents. The Child Oral Health Quality of Life (COHQoL) survey was used to assess the effects of dental injuries on the QoL of 23 children aged 8-14 and their parents. Results: Mean VAS scores revealed that all patients and parents perceived the pain of initial injury to be significantly greater than pain of splint removal (P £ 0.05) and that pain decreased in a stepwise manner from injury through emergency treatment to splint removal. The COHQoL questionnaire demonstrated a profound and continuing effect on children and their parent's QoL following severe dental injury. The initial parental COHQoL score was significantly greater than the 12-month score (P £ 0.05) in both 8-10 and 11-14-year-olds. The COHQoL results indicated a measurable reduction in the QoL of patients and parents was still present 12-months after the injuries. At the end of one-year children were still affected by the social and well-being aspects of the injury yet parents exclusively reported that one-year effects were limited to their children's oral symptoms and functional limitations. Conclusions: Severe dental injuries produce initial and ongoing pain. Detrimental effects on the QoL of both children and parents are still present at one-year and these long-term effects are different for children and parents.

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Abstract-An aspiration signal is the time-varying anterior-posterior acceleration measured infero-anterior to the thyroid notch when foreign material enters the airway during inspiration.

BackgroundSilent aspiration or the inhalation of foodstuffs without overt physiological signs presents a serious health issue for children with dysphagia. To date, there are no reliable means of detecting aspiration in the home or community. An assistive technology that performs in these environments could inform caregivers of adverse events and potentially reduce the morbidity and anxiety of the feeding experience for the child and caregiver, respectively. This paper proposes a classifier for automatic classification of aspiration and swallow vibration signals non-invasively recorded on the neck of children with dysphagia.MethodsVibration signals associated with safe swallows and aspirations, both identified via videofluoroscopy, were collected from over 100 children with neurologically-based dysphagia using a single-axis accelerometer. Five potentially discriminatory mathematical features were extracted from the accelerometry signals. All possible combinations of the five features were investigated in the design of radial basis function classifiers. Performance of different classifiers was compared and the best feature sets were identified.ResultsOptimal feature combinations for two, three and four features resulted in statistically comparable adjusted accuracies with a radial basis classifier. In particular, the feature pairing of dispersion ratio and normality achieved an adjusted accuracy of 79.8 ± 7.3%, a sensitivity of 79.4 ± 11.7% and specificity of 80.3 ± 12.8% for aspiration detection. Addition of a third feature, namely energy, increased adjusted accuracy to 81.3 ± 8.5% but the change was not statistically significant. A closer look at normality and dispersion ratio features suggest leptokurticity and the frequency and magnitude of atypical values as distinguishing characteristics between swallows and aspirations. The achieved accuracies are 30% higher than those reported for bedside cervical auscultation.ConclusionThe proposed aspiration classification algorithm provides promising accuracy for aspiration detection in children. The classifier is conducive to hardware implementation as a non-invasive, portable "aspirometer". Future research should focus on further enhancement of accuracy rates by considering other signal features, classifier methods, or an augmented variety of training samples. The present study is an important first step towards the eventual development of wearable intelligent intervention systems for the diagnosis and management of aspiration.