Background

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on COVID-19. Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC codes. COVID-19 TestNorm was developed and evaluated using 568 test names collected from eight healthcare systems. Our results show that it could achieve an accuracy of 97.4% on an independent test set. COVID-19 TestNorm is available as an open-source package for developers and as an online web application for end-users (https://clamp.uth.edu/covid/loinc.php). We believe it will be a useful tool to support secondary use of EHRs for research on COVID-19.

Original Article Cite this article: Harper J, Liu M, Malone SM, McGue M, Iacono WG, Vrieze SI (2021). Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment. Psychological Medicine 1-11. https://doi. Abstract Background. To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/ cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment. Method. A large community-based twin/family sample (N = 4893) was genome-wide geno-typed and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis. Results. Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizo-phrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [β = −0.032, nonparametric bootstrap 95% confidence interval (CI) −0.059 to −0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (β = −0.034, 95% CI −0.063 to −0.006) and regular smoking PGSs (β = −0.032, 95% CI −0.061 to −0.005) and positively associated with educational attainment PGS (β = 0.031, 95% CI 0.003-0.058). Conclusions. Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophre-nia, and educational attainment PGSs and represent promising targets for future research.

We study and establish a foundation for dimension reduction methods that compress the response and predictor vectors in multivariate regression. While all of the methods studied can perform competitively, depending on the characteristics of the regression, using partial least squares to compress the response and predictor vectors was judged to be the best for prediction and parameter estimation.

This study evaluated the success rate of orthodontic treatment of linguoverted mandibular canines in dogs using a directly applied inclined plane device. Medical records were retrospectively evaluated from 11 veterinary dental specialty hospitals from 1999-2021. Malocclusion class included 41.7% class 1, 47.2% class 2, 6.9% class 3, and 4.2% class 4 respectively. Severity of linguoversion was mild in 7.6% of teeth, moderate in 33.9%, and severe in 58.5%. There was complete resolution of linguoversion in 71.2% of teeth, functional resolution in 25.4%, and failure in 3.4%. The median treatment time was 42 (11-174) days. Adjuvant orthodontic treatments were performed at the same time as the inclined plane in 45.7% of teeth, including active force orthodontics, extractions of non-strategic teeth, gingivectomy, and odontoplasty. While the inclined plane was in place, 31.4% of dogs required an anesthetized appliance adjustment, and at the time of appliance removal, complications occurred in 19.4% of dogs. Of the teeth that had initial resolution, 14.4% had rebound movement that required additional treatment. This study supports that acrylic inclined plane is a good treatment option for linguoverted mandibular canines with a 96.6% success rate within a median of 6 weeks. Yet, orthodontic retention may be necessary in these cases to avoid the need for additional therapies.