The Pediatric Asthma Risk Score: A New Gold Standard for Asthma Prediction

Rationale: Early prediction of asthma is critical to identify potential primary prevention strategies. The Pediatric Asthma Risk Score (PARS) is a continuous score to predict early-life asthma but was developed and validated in relatively homogenous populations. We compared PARS directly to the Asthma Predictive Index (API) and validated in 10 cohorts with varying race, ethnicity, sex, cohort type, missing data and birth decades, and perform a meta-analysis across all 10 cohorts. Methods: We utilized data from 5674 children participating in the Children’s Respiratory and Environmental Workgroup. We applied both PARS and the API in each cohort, as well as harmonized across all cohorts, and directly compared the ability of each tool to predict asthma development at ages 5-10. Results: The PARS area under the curve (AUC) was significantly higher than the AUC of the API in 9 cohorts (p-value range 0.01 - \u3c0.001). The PARS AUC did not differ by cohort type (high risk or general population), decade of enrollment, race, sex, ethnicity, missing PARS factors or polysensitization definition (skin prick test vs. specific IgE). The weights of the 6 PARS factors in the meta-analysis were very similar to the original weights, validating the original PARS scoring. Conclusions: This multi-cohort study makes the PARS the most validated model of asthma prediction in children to date, not only with respect to the number of cohorts used but also with regards to capturing the diversity of asthma in the United States. Future studies may consider PARS the new gold standard in pediatric asthma risk prediction

Prevalence of Disorders Recorded in Dogs Attending Primary-Care Veterinary Practices in England

Purebred dog health is thought to be compromised by an increasing occurence of inherited diseases but inadequate prevalence data on common disorders have hampered efforts to prioritise health reforms. Analysis of primary veterinary practice clinical data has been proposed for reliable estimation of disorder prevalence in dogs. Electronic patient record (EPR) data were collected on 148,741 dogs attending 93 clinics across central and south-eastern England. Analysis in detail of a random sample of EPRs relating to 3,884 dogs from 89 clinics identified the most frequently recorded disorders as otitis externa (prevalence 10.2%, 95% CI: 9.1-11.3), periodontal disease (9.3%, 95% CI: 8.3-10.3) and anal sac impaction (7.1%, 95% CI: 6.1-8.1). Using syndromic classification, the most prevalent body location affected was the head-and-neck (32.8%, 95% CI: 30.7-34.9), the most prevalent organ system affected was the integument (36.3%, 95% CI: 33.9-38.6) and the most prevalent pathophysiologic process diagnosed was inflammation (32.1%, 95% CI: 29.8-34.3). Among the twenty most-frequently recorded disorders, purebred dogs had a significantly higher prevalence compared with crossbreds for three: otitis externa (P = 0.001), obesity (P = 0.006) and skin mass lesion (P = 0.033), and popular breeds differed significantly from each other in their prevalence for five: periodontal disease (P = 0.002), overgrown nails (P = 0.004), degenerative joint disease (P = 0.005), obesity (P = 0.001) and lipoma (P = 0.003). These results fill a crucial data gap in disorder prevalence information and assist with disorder prioritisation. The results suggest that, for maximal impact, breeding reforms should target commonly-diagnosed complex disorders that are amenable to genetic improvement and should place special focus on at-risk breeds. Future studies evaluating disorder severity and duration will augment the usefulness of the disorder prevalence information reported herein