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Discrimination can contribute to adverse mental health outcomes among individuals in romantic partnerships. However, research has yet to examine how differences in partner race/ethnicity can shape the link between gendered racial microaggressions, an intersectional form of discrimination, and depressive symptoms among Asian American women. Accordingly, we assessed the link between gendered racial microaggressions and depressive symptoms, and whether partner race/ethnicity (White vs. Asian) moderated the link. Using a sample of 156 Asian American women (Mage= 26.5, SD= 5.33), we conducted multiple regressions to assess the main effects between four gendered racial microaggression stress subscale factors and depressive symptoms. We then examined partner race/ethnicity as a moderator in these associations. All four gendered racial microaggression stress subscale factors of ascribed submissiveness, assumptions of universal appearance, Asian fetishism, and media invalidation significantly predicted greater depressive symptoms. However, only Asian fetishism experiences maintained a significant and positive association with depressive symptoms for Asian American women with White male partners. The association between Asian fetishism and depressive symptoms was no longer significant for Asian American women with Asian male partners. Results indicate that Asian fetishization may be a uniquely oppressive experience for Asian American women with White partners that can contribute to greater depressive symptoms. These findings demonstrate an increased need for the development of critical consciousness in individual and couples counseling sessions to help Asian American women and their romantic partners identify and mitigate the negative effects of gendered racial microaggressions.

Study Design Multicenter cohort.Objectives A report from the International Spine Study Group (ISSG) noted that surgeons failed to achieve alignment goals in nearly two-thirds of 266 complex adult deformity surgery (CADS) cases. We assess whether personalized interbody spacers are associated with improved rates of achieving goal alignment following adult spinal deformity (ASD) surgery.Methods ASD patients were included if their surgery utilized 3D-printed personalized interbody spacer(s) and they met ISSG CADS inclusion criteria. Planned alignment was personalized by the surgeon during interbody planning. Planned vs achieved alignment was assessed and compared with the ISSG CADS series that used stock interbodies.Results For 65 patients with personalized interbodies, 62% were women, mean age was 70.3 years (SD = 8.3), mean instrumented levels was 9.9 (SD = 4.1), and the mean number of personalized interbodies per patient was 2.2 (SD = .8). Segmental alignment was achieved close to plan for levels with personalized interbodies, with mean difference between goal and achieved as follows: intervertebral lordosis = .9° (SD = 5.2°), intervertebral coronal angle = .1° (SD = 4.7°), and posterior disc height = −0.1 mm (SD = 2.3 mm). Achieved pelvic incidence-to-lumbar lordosis mismatch (PI-LL) correlated significantly with goal PI-LL (r = .668, P< .001). Compared with the ISSG CADS cohort, utilization of personalized interbodies resulted in significant improvement in achieving PI-LL <5° of plan (P= .046) and showed a significant reduction in cases with PI-LL >15° of plan (P= .012).Conclusions This study supports use of personalized interbodies as a means of better achieving goal segmental sagittal and coronal alignment and significantly improving achievement of goal PI-LL compared with stock devices.

Early childhood caries (ECC) is the most common chronic disease affecting young children in Canada. ECC may lead to pain and infection, compromised general health, decreased quality of life and increased risk for dental caries in primary and permanent teeth. A multidisciplinary approach to prevent and identify dental disease is recommended by dental and medical national organizations. Young children visit primary care providers at regular intervals from an early age. These encounters provide an ideal opportunity for primary care providers to educate clients about their children's oral health and its importance for general health. We designed an office-based oral health screening guide to help primary care providers identify ECC, a dental referral form to facilitate dental care access and an oral health education resource to raise parental awareness. These resources were reviewed and trialled with a small number of primary care providers.

Acute otitis externa, cellulitus of the external auditory canal, is most frequently due to bacteria. Patients may present with otalgia, aural fullness, hearing loss and otorrhea. Its diagnosis is a clinical one. Treatment is focused on analgesia, treating the underlying infection, and preventing recurrence.

One potential mechanism for early superficial cartilage wear in normal joints is alteration of the lubricant content and quality of synovial fluid. The purpose of this study was to determine if the concentration and quality of the lubricant, hyaluronan, in synovial fluid: (1) was similar in left and right knees; (2) exhibited similar age-associated trends, whether collected postmortem or antemortem; and (3) varied with age and grade of joint degeneration. Human synovial fluid of donors (23–91 years) without osteoarthritis was analyzed for the concentrations of protein, hyaluronan, and hyaluronan in the molecular weight ranges of 2.5–7 MDa, 1–2.5 MDa, 0.5–1 MDa, and 0.03–0.5 MDa. Similarity of data between left and right knees was assessed by reduced major axis regression, paired t-test, and Bland-Altman analysis. The effect of antemortem versus postmortem collection on biochemical properties was assessed for age-matched samples by unpaired t-test. The relationships between age, joint grade, and each biochemical component were assessed by regression analysis. Joint grade and the concentrations of protein, hyaluronan, and hyaluronan in the molecular weight ranges of 2.5–7 MDa, 1–2.5 MDa, and 0.5–1 MDa in human synovial fluid showed good agreement between left and right knees and were similar between age-matched patient and cadaver knee joints. There was an age-associated decrease in overall joint grade (–15 %/decade) and concentrations of hyaluronan (–10.5 %/decade), and hyaluronan in the molecular weight ranges of 2.5–7 MDa (–9.4 %/decade), 1–2.5 MDa (–11.3 %/decade), 0.5–1 MDa (–12.5 %/decade), and 0.03–0.5 MDa (–13.0 %/decade). Hyaluronan concentration and quality was more strongly associated with age than with joint grade. The age-related increase in cartilage wear in non-osteoarthritic joints may be related to the altered hyaluronan content and quality of synovial fluid.

Introduction:Aortic stenosis (AS) is common, with >= moderate severity ~10% above age 75. Despite new therapies, many with AS go undiagnosed due to lack of echo availability and untreated due to improper interpretation. To expand AS diagnosis, we developed an artificial intelligence (AI) algorithm to characterize AS from routine B-mode echo exams without Doppler (AutoAS).Methods:80,000 de-identified clinical echoes were assembled spanning none, mild, moderate, and severe AS. About 30,000 of these were used to train a convolutional neural network (CNN) using labels derived from a cluster analysis of maximal jet velocity, mean AS gradient, and aortic valve area (AVA). Once labeled, we extracted all available B-mode clips from parasternal long-axis, short axis at aortic level, and apical 5-chamber views, irrespective of image quality. A spatiotemporal CNN was trained to return a probability distribution for none/mild/moderate/severe AS. To assess performance of the model, a hold-out test set of echoes uniformly distributed over patient sex and AS severity was used. Three Level 3 echo trained cardiologists blindly read the complete Doppler echoes and agreed to call AS severity by AVA (< 1 cm2, severe; 1.0-1.5 cm2, moderate; > 1.5 cm2 but restricted, mild; no restriction, none). Results were also dichotomized into none/mild and moderate/severe AS.Results:40 cases comprised this initial test set. Consistency among the readers was outstanding, with κ = 0.95. The table shows the confusion matrix between AutoAS and panel reads, with excellent accuracy (κ = 0.90). Dichotomous results were also outstanding with sensitivity to detect moderate/severe AS of 91% and specificity of 94%.Conclusions:AI can identify AS from 3 B-mode views and characterize AS severity with accuracy highly congruent to an expert panel using full Doppler data. This may allow AS to be detected in low-resource and screening settings. Further assessment with a larger hold-out test set is planned.