Chronic hand eczema (CHE) is persistent inflammatory dermatitis that may significantly affect the quality of life, with psychosocial effects, impact on school, work, and leisure activities, influence on socioeconomic status, and high health care costs. Pediatric-CHE (P-CHE) has a high prevalence yet has not been extensively studied in children and adolescents. There is minimal published data on P-CHE in North America, and no specific management guidelines. Limited prevalence data show broad ranges (0.9%-4.4%) in preschool and school children, with 1 study stating up to 10.0% 1-year prevalence for ages 16 to 19 years. Atopic dermatitis and allergic contact dermatitis appear important in the pathogenesis of this disease process, although there is limited pediatric data assessing disease associations and no standardized methodology for evaluating this disorder. Given the potential life-changing consequences of P-CHE, further research into this disease process is warranted to help generate best therapeutic practices and minimize this disease process' morbidity in adulthood.

Background

Hepatitis C virus (HCV) screening remains suboptimal. We assessed the efficacy of a mobile application and provider alert in enhancing HCV screening among Asian Americans.

Methods

A secondary analysis of a cluster-randomized clinical trial was performed during the birth cohort screening era to assess the efficacy of a Hepatitis App (intervention), a multilingual mobile application delivering interactive video education on viral hepatitis and creating a Provider Alert printout, at primary care clinics within 2 healthcare systems in San Francisco from 2015 to 2017. A comparison group received usual care and a similar intervention on nutrition and physical activity. The outcome was electronic health record (EHR) documentation of HCV screening along with patient-provider communication about testing and test ordering.

Results

Four hundred fifty-two participants (mean age 57 years, 36% male, 80% foreign-born) were randomized by provider clusters to the intervention (n = 270) or comparison groups (n = 182). At 3-month follow up, the intervention group was more likely than the comparison group to be aware of HCV (75% vs 59%, P = .006), to discuss HCV testing with their providers (63% vs 13%, P < .001), to have HCV testing ordered (39% vs 10%, P < .001), and to have EHR-verified HCV testing (30% vs 6%, P < .001). Within the intervention group, being born between 1945 and 1965 (odds ratio, 3.15; 95% confidence interval, 1.35-7.32) was associated with increased HCV testing.

Conclusions

The Hepatitis App delivered in primary care settings was effective in increasing HCV screening in a socioeconomically diverse Asian American cohort. This highlights the importance of mobile technology as a patient-centered strategy to address gaps in HCV care.

Background

Chronic hand eczema (CHE) significantly impacts quality of life. Published literature on pediatric CHE (P-CHE) in North America including knowledge on epidemiology and standard evaluation and management is limited.

Objective

Our objective was to assess diagnostic practices when evaluating patients with P-CHE in the US and Canada, produce data on therapeutic agent prescribing practices for the disorder, and lay the foundation for future studies.

Methods

We surveyed pediatric dermatologists to collect data on clinician and patient population demographics, diagnostic methods, therapeutic agent selection, among other statistics. From June 2021 to January 2022, a survey was distributed to members of the Pediatric Dermatology Research Alliance (PeDRA).

Results

Fifty PeDRA members responded stating that they would be interested in participating, and 21 surveys were completed. For patients with P-CHE, providers most often utilize the diagnoses of irritant contact dermatitis, allergic contact dermatitis, dyshidrotic hand eczema, and atopic dermatitis. Contact allergy patch testing and bacterial hand culture are the most used tests for workup. Nearly all utilize topical corticosteroids as first line therapy. Most responders report that they have treated fewer than six patients with systemic agents and prefer dupilumab as first-line systemic therapy.

Conclusions

This is the first characterization of P-CHE among pediatric dermatologists in the United States and Canada. This assessment may prove useful in designing further investigations including prospective studies of P-CHE epidemiology, morphology, nomenclature, and management.

Hepatitis C virus (HCV) prevalence is high among people experiencing homelessness, but barriers to scaling up HCV testing and treatment persist. We aimed to implement onsite HCV testing and education and evaluate the effectiveness of low-barrier linkage to HCV therapy among individuals accessing homeless shelters. HCV rapid testing was performed at four large shelters in San Francisco (SF) and Minneapolis (MN). Sociodemographic status, HCV risk, barriers to testing, and interest in therapy were captured. Participants received information about HCV. Those testing positive underwent formal HCV education and onsite therapy. Multivariable modeling assessed predictors of receipt of HCV therapy and sustained virologic response (SVR). A total of 766 clients were tested. Median age was 53.7 years, 68.2% were male participants, 46.3% were Black, 27.5% were White, 13.2% were Hispanic, and 57.7% had high school education or less; 162 (21.1%) were HCV antibody positive, 107 (66.0%) had detectable HCV RNA (82.1% with active drug use, 53.8% history of psychiatric illness), 66 (61.7%) received HCV therapy, and 81.8% achieved SVR. On multivariate analysis, shelter location (MN vs. SF, odds ratio [OR], 0.3; P = 0.01) and having a health care provider (OR, 4.1; P = 0.02) were associated with receipt of therapy. On intention to treat analysis, the only predictor of SVR when adjusted for age, sex, and race was HCV medication adherence (OR, 14.5; P = 0.01). Conclusion: Leveraging existing homeless shelter infrastructure was successful in enhancing HCV testing and treatment uptake. Despite high rates of active substance use, psychiatric illness, and suboptimal adherence, over 80% achieved HCV cure. This highlights the critical importance of integrated models in HCV elimination efforts in people experiencing homelessness that can be applied to other shelter settings.

Purpose

Older patients undergoing radiation therapy (RT) for pelvic malignancies are at increased risk for pelvic fracture, which is associated with significant morbidity and mortality. RT techniques such as brachytherapy or intensity modulated RT (IMRT) allow for more conformal dose distributions, but it is not known whether the risk for pelvic fracture varies by RT modality.

Methods and materials

This observational cohort study involved 28,354 patients ≥65 years old, treated with RT for pelvic malignancies. We evaluated the relative risk of pelvic fracture by type of RT when accounting for baseline factors. To test for nonspecific effects, we also evaluated risk of nonpelvic fractures in the same population.

Results

The 5-year incidence of pelvic fractures was 12.7% (95% confidence interval [CI], 11.6%-13.8%), 11.8% (10.8%-12.8%), and 3.7% (3.4%-4.0%) for patients with gastrointestinal, gynecologic, and prostate cancer, respectively. On multivariable analysis, being treated with IMRT (hazard ratio, 0.85; 95% CI, 0.73-0.99) or brachytherapy therapy alone (hazard ratio, 0.43; 95% CI, 0.34-0.54) was associated with a reduced hazard for pelvic fractures compared with 3D conformal radiation therapy in female patients. In contrast, there was no association with RT modality and the hazard for nonpelvic fractures among females. There was no significant association between pelvic fractures and IMRT or brachytherapy for male patients. White race, advanced age, and higher comorbidity were associated with an increased hazard for pelvic fracture.

Conclusions

IMRT and brachytherapy were associated with a reduced risk of pelvic fractures in older women undergoing RT for pelvic malignancies. Pelvic insufficiency fracture risk should be considered when treating with pelvic RT.

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and "transduce" signals to adjust internal processes. We hypothesized that an ecosystem's unique stimuli leave a sensor "fingerprint," able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection's nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient's disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model's feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

BACKGROUND/OBJECTIVES: The primary objective was to assess pain catastrophizing and functional disability in pediatric patients with epidermolysis bullosa (EB) and their parents/guardians. Secondary objectives included examining relationships between pain catastrophizing, functional disability, and correlations with other factors (e.g., age, disease severity, and percent of body surface area (BSA) involved). METHODS: Patients with EB ages 8-16 and their parents/guardians who were English or Spanish speaking completed a one-time online survey. Parent measures included: demographics questionnaire, Pain Catastrophizing Scale-Parent (PCS), and Parent Functional Disability Inventory (FDI). Child measures included: PCS child and child FDI. Higher scores on both scales indicate higher levels of catastrophizing and functional disability. RESULTS: Of 31 children, the mean age was 11.47 years and the majority (70.97%) had dystrophic EB. Mean scores were: 35.84 = PCS parent; 34.58 = PCS child; 30.87 = parent FDI; 29.77 = child FDI. Total scores for PCS parent, parent FDI, and child FDI increased significantly with disease severity and percentage of involved BSA (p < .01 for all). Total scores for PCS child increased significantly with percent of EB skin involvement (p = .04) but not disease severity. Older children reported more functional disability than their parents and younger children (p = .02). CONCLUSIONS: Our results demonstrate significant positive correlations between negative thoughts related to pain and the experience of functional difficulties in patients with EB and their caregivers. Psychological, psychiatric, and/or behavioral interventions to help managing chronic pain may be effective for patients with EB.

Purpose

Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues.

Methods

The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging.

Results

A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D_1,3 = 0, D_2,3 = 1.5 × 10^-3 , and D_3,3 = 10.8 × 10^-3 mm² /s. The RSI-derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast-to-noise and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent.

Conclusion

Breast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.