This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative.Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV1, dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years).A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes.
Introduction: Bruxism is a repetitive masticatory muscle activity that may cause substantial morbidity and reduce the quality of life in children with profound intellectual and multiple disabilities. Assessment methods most commonly used were caregiver reporting and dental examination, This systematic review with meta-analysis aims to determine the prevalence of bruxism in children with profound intellectual and multiple disabilities and to describe the currently used assessment methods for bruxism in this population. Methods: We conducted a systematic review and meta-analysis using a multi-component search strategy. We used a random effects model to calculate the prevalence and 95 % confidence intervals for each study, for all studies combined, and specifically for Rett syndrome (RS), cerebral palsy (CP), Down syndrome (DS), and “other disorders (primarily Angelman syndrome and Prader–Willi syndrome).” Results: The prevalence for the entire group based on a random effects model was found to be 49 % (95 %CI 41–57 %) with high heterogeneity (I2 = 93 %, p < 0.01), for RS 74 % (95 %CI 53–88 %, I2 = 84 %, p < 0.01), CP 48 % (95 %CI 38–57 %, I2 = 86 %, p < 0.01), DS 40 % (95 %CI 33–47 %, I2 = 60 %, p < 0.01) and “other disorders” 40 % (95 %CI 18–67 %, I2 = 98 %, p < 0.01). The group prevalences were not equal, indicating a significant difference (P-value = 0.03), with a notably higher likelihood of RS. Conclusion: We observed a five-fold increased likelihood of bruxism in children with profound intellectual and multiple disabilities. The disorder with the highest prevalence was Rett syndrome, with a seven-fold increased likelihood of bruxism. The increased likelihood of bruxism in this vulnerable group of children demands clinicians pay heed to this substantial morbidity.
