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Introduction: The Centre de Médecine de Plongée du Québec (CMPQ) established a bilingual 24-hour dive emergency call line and diving medicine information service in 2004. The toll-free number (888-835-7121) works throughout Canada. Calls and emails (cmpq.cisssca@ssss.gouv.qc.ca) are answered by a CMPQ coordinator or on-call hyperbaric physicians and other consultants as needed. We reviewed 15 years of activity., Methods: Details of phone calls and email enquiries to the centre were reviewed individually and compiled into a database. Data were analysed to characterise contact volume and issues addressed. Contacts were categorised into five groups: information only (INF); medical opinion required (MOP); medical issue after the critical period of urgency had passed (PUR); current urgent but not immediate life-threatening issue (NLT); and immediate life- or health-threatening issue (ILT). Data presented as mean (standard deviation) or percentage., Results: A total of 3,232 contacts were made from May 2004 through December 2018: 19 (SD 8) per month [215 (70) per year]. Primary issues of concern were: emergency planning (20%); technical (not medical/physiology) questions (16%); otorhinolaryngological (12%); and decompression sickness-related (7%). Categorisation was 52% INF, 28% MOP, 13% PUR, 7% NLT, and 0.1% ILT, with 0.2% lacking sufficient detail to categorise. The nature of the diving activity of interest was determined in 67% of cases: 48% (n = 1,039) professional; 46% (n = 1,008) recreational; and 1% (n = 11) breath-hold., Conclusions: The call centre serves as a resource to the community, providing information on health and safety for diving in addition to being available to assist with emergent needs., (Copyright: This article is the copyright of the authors who grant Diving and Hyperbaric Medicine a non-exclusive licence to publish the article in electronic and other forms.)

Three-dimensional classification of scoliosis is important. However, analyzing large databases of 3D spine models is a difficult and time consuming task. To facilitate this task a method that automatically extracts the most important deformation modes from a set of 3D spine models is proposed. The 3D spine models are first converted into vertebrae relative positions and orientations. Then, a variability model composed of the Fréchet mean and of a generalized covariance is computed. A principal component analysis is applied to that variability model and the extracted components are converted into deformation modes. Those modes are visualized by animating a 3D spine model where the deformation strength varies (for a given mode). The proposed method was applied to a group of 307 scoliotic patients and meaningful deformation modes were successfully extracted. For example, patients' growth, double curves, simple thoracic curves and lumbar lordosis were extracted in the first four deformation modes. Moreover, the obtained deformation modes are not disconnected from conventional surgical classifications since a logistic regression confirmed that there is a statistically significant relation between King's classification and the first four principal deformation modes. The proposed method successfully extracted important deformation modes from a set of 3D spine models and can be used to refine arbitrary classes (King's or Lenke's classes, for instance), thus helping the design of new clinically relevant 3D classifications.