No abstract

Unilateral vocal cord paralysis (UVCP) is relatively common, and previously, thyroidectomy used to be the leading cause. We retrospectively reviewed 98 cases of UVCP. The left vocal cord was involved in 70% of the cases and the right vocal cord in 30%. The cause was neoplastic in 32%, surgical in 30%, idiopathic in 16%, traumatic in 11%, central in 8%, and infectious in 3% of the cases. Only 4 cases were the result of thyroid surgery. Evaluation consisted of a review of the history, a physical examination, and computerized scanning or magnetic resonance imaging, as needed. The functional recovery rate as related to the cause was as follows: surgery 31%, idiopathic 19%, traumatic 18%, and neoplastic 0%. Thirty-five percent of patients required medialization laryngoplasty or Teflon injection. Lung and skull base tumors and their surgical treatment are the most common causes of UVCP.

The ability to accurately predict response and then rigorously optimize a therapeutic regimen on a patient-specific basis, would transform oncology. Toward this end, we have developed an experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into a biophysical model to predict patient-specific treatment response of locally advanced breast cancer to neoadjuvant therapy. Diffusion-weighted and dynamic contrast-enhanced MRI data is collected prior to therapy, after 1 cycle of therapy, and at the completion of the first therapeutic regimen. The model is initialized and calibrated with the first 2 patient-specific MRI data sets to predict response at the third, which is then compared to patient outcomes (N = 18). The model's predictions for total cellularity, total volume, and the longest axis at the completion of the regimen are significant within expected measurement precision ( P < 0.05) and strongly correlated with measured response ( P < 0.01). Further, we use the model to investigate, in silico , a range of (practical) alternative treatment plans to achieve the greatest possible tumor control for each individual in a subgroup of patients (N = 13). The model identifies alternative dosing strategies predicted to achieve greater tumor control compared to the standard of care for 12 of 13 patients ( P < 0.01). In summary, a predictive, mechanism-based mathematical model has demonstrated the ability to identify alternative treatment regimens that are forecasted to outperform the therapeutic regimens the patients clinically. This has important implications for clinical trial design with the opportunity to alter oncology care in the future.

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Two main themes were identified including the legitimacy of seeking help and continuities of care. Most participants were reluctant to seek help, finding it difficult to decide whether their needs were sufficient to contact services. The degree to which services legitimised participants' requests mediated their experiences. Distress arose when services were dismissive of their needs, whereas respondents were appreciative of clinicians who provided them with reassurance. Participants reported a lack of relational and informational continuity of care. Consulting with an unfamiliar clinician out-of-hours raised doubts in some participants' minds about the quality of care. Some participants recounted episodes in which there were problems with pain management. While the themes suggest that the delivery of out-of-hours care as a whole was not always perfect, around-the-clock access to professional sources of support and reassurance was highly valued. However, the transfer of information to out-of-hours providers remains a key challenge; participants did not understand why out-of-hours providers could not access more information on their medical histories given the level of computerisation within the National Health Service. The findings highlight the need to improve continuity between in-hours and out-of-hours services for patients with complex needs.