Mental health priorities and cultural-responsiveness of the Mental Health First Aid (MHFA) training for Asian immigrant populations in Greater Boston, Massachusetts.

BACKGROUND: Asians and Asian Americans have the lowest rate of mental health service utilization (25%) in the US compared to other racial/ethnic groups (39 - 52%), despite high rates of depression, anxiety, and suicidal ideation. The lack of culturally-responsive mental health trainings hinders access to mental health services for these populations. We assessed the mental health priorities of Asian communities in Greater Boston and evaluated cultural responsiveness of the Mental Health First Aid (MHFA), a first-responder training teaching participants skills to recognize signs of mental health and substance use challenges, and how to appropriately respond. METHODS: This is community-based participatory research with the Boston Chinatown Neighborhood Center (BCNC), Asian Women For Health (AWFH), and the Addressing Disparities in Asian Populations through Translational Research (ADAPT) Coalition. We conducted focus groups with community-based organization staff and community members to assess mental health priorities of Asian populations in Boston, MA. We then evaluated the utility and cultural-responsiveness of the English-language MHFA for Asian populations through pre- and post-training questionnaires and focus groups with community participants. Paired t-tests were used to evaluate questionnaire responses. Thematic analysis was used to analyze interviews. RESULTS: In total, ten staff and eight community members participated in focus groups, and 24 community members completed the MHFA and pre- and post-training questionnaires. Common mental health challenges in the Asian communities reported by participants were loneliness, high stigma around mental illnesses, academic pressure, and acculturation stress. Compared to pre-training, MHFA participants demonstrated lower personal mental health stigma (p < 0.001) and higher mental health literacy (p = 0.04) post-training. Participants also noted the lack of data statistics and case studies relevant to Asian populations in the training, and desired the training be offered in languages spoken by Asian ethnic subgroups (e.g., Chinese, Vietnamese). CONCLUSION: Cultural-responsiveness of the MHFA for Asian populations could be improved with the inclusion of data and case studies that capture common mental health challenges in the Asian communities and with translation of the MHFA to non-English languages predominant in Asian communities. Increasing the cultural relevance and language accessibility of the MHFA could facilitate wider adoption of these trainings across communities and help to reduce mental health stigma and gaps in literacy and service utilization.

Delivery of Outpatient Cirrhosis Care Via Tele-visit is Not Associated with Increased Mortality as Compared to Traditional In-Person Visits.

INTRODUCTION: Providers and patients have expressed concern that care provided via telehealth results in poorer outcomes than traditional in-person care. On the contrary, we hypothesized that patients with cirrhosis engaging in video/phone-based outpatient GI/Hepatology tele-visits do not differ in mortality from those receiving in-person outpatient clinic visits. METHODS: Retrospective, case-control study using VHA administrative data of veterans with a cirrhosis diagnosis. Cases were patients who died between 04/2021-07/2022 and had a cirrhosis diagnosis for ≥1 year prior to death. For each case, a control was randomly selected from the pool of patients alive on the date of death of the case (index date) and matched on age, average MELD, and number of GI/Hepatology clinic visits in the prior year. Primary exposure variable was % tele-visits (video/phone) out of total visits in the year prior to the index date, scaled in 10% increments. Conditional logistic regression was used to assess the association between mortality and % tele-visits. A secondary analysis matched on Child Turcotte Pugh (eCTP) score rather than MELD. RESULTS: 2,933 cases were identified and matched with 2,933 controls. After adjusting for covariates, tele-visit-based outpatient care was associated with a small reduction in mortality (ORTH = 0.95, 95% CI = 0.94-0.97). Matching on eCTP score did not change the results. DISCUSSION: Our findings suggest that outpatient cirrhosis care by tele-visit is associated with outcomes no worse than traditional in-person visits. This should reassure providers who hesitate to provide virtual care to patients with cirrhosis due to concerns for poorer outcomes.

Machine learning methods in automated detection of CT enterography findings in Crohn's disease: A feasibility study.

PURPOSE: Qualitative findings in Crohn's disease (CD) can be challenging to reliably report and quantify. We evaluated machine learning methodologies to both standardize the detection of common qualitative findings of ileal CD and determine finding spatial localization on CT enterography (CTE). MATERIALS AND METHODS: Subjects with ileal CD and a CTE from a single center retrospective study between 2016 and 2021 were included. 165 CTEs were reviewed by two fellowship-trained abdominal radiologists for the presence and spatial distribution of five qualitative CD findings: mural enhancement, mural stratification, stenosis, wall thickening, and mesenteric fat stranding. A Random Forest (RF) ensemble model using automatically extracted specialist-directed bowel features and an unbiased convolutional neural network (CNN) were developed to predict the presence of qualitative findings. Model performance was assessed using area under the curve (AUC), sensitivity, specificity, accuracy, and kappa agreement statistics. RESULTS: In 165 subjects with 29,895 individual qualitative finding assessments, agreement between radiologists for localization was good to very good (κ = 0.66 to 0.73), except for mesenteric fat stranding (κ = 0.47). RF prediction models had excellent performance, with an overall AUC, sensitivity, specificity of 0.91, 0.81 and 0.85, respectively. RF model and radiologist agreement for localization of CD findings approximated agreement between radiologists (κ = 0.67 to 0.76). Unbiased CNN models without benefit of disease knowledge had very similar performance to RF models which used specialist-defined imaging features. CONCLUSION: Machine learning techniques for CTE image analysis can identify the presence, location, and distribution of qualitative CD findings with similar performance to experienced radiologists.

Committed to Success: A Structured Mentoring Program for Clinically Oriented Physicians.

Objective: To examine impacts of a structured mentorship committee program on academic promotion and participant perceptions because impacts of formal mentorship programs for clinical faculty are unknown. Participants and Methods: This prospective cohort study at a Midwestern Veterans Affairs tertiary care system from December 17, 2019 to December 31, 2022 included clinical track faculty in the Medicine Service below the rank of Clinical Associate Professor. Mentoring meetings (mentee, committee chair, and mentors) were generally held twice annually. All participants were surveyed after each meeting (response rate: 100%). Results: All 23 of 23 (100%) eligible faculty were enrolled as mentees, and 49 distinct meetings occurred. Three (13%) mentees were promoted, and the remaining 20 (87%) continued in the program. Mean scores (SD), scaled 1 (strongly disagree) to 5 (strongly agree), for mentors and mentees were 4.71 (0.51) and 4.80 (0.54) for "effective use of my time"; 4.58 (0.64) and 4.37 (0.49) for "appropriate progress since last meeting"; 4.52 (0.66) and 4.31 (0.64) for "program increased my work satisfaction"; and 4.07 (0.96) and 3.75 (0.92) for "program reduced my work burnout," respectively. Conclusion: Clinically oriented physicians viewed the program positively. It appeared to help junior faculty get promoted and led to improved work satisfaction and reduced burnout.

Preformed Vesicle Approach to LNP Manufacturing Enhances Retinal mRNA Delivery.

Complete encapsulation of nucleic acids by lipid-based nanoparticles (LNPs) is often thought to be one of the main prerequisites for successful nucleic acid delivery, as the lipid environment protects mRNA from degradation by external nucleases and assists in initiating delivery processes. However, delivery of mRNA via a preformed vesicle approach (PFV-LNPs) defies this precondition. Unlike traditional LNPs, PFV-LNPs are formed via a solvent-free mixing process, leading to a superficial mRNA localization. While demonstrating low encapsulation efficiency in the RiboGreen assay, PFV-LNPs improved delivery of mRNA to the retina by up to 50% compared to the LNP analogs across several benchmark formulations, suggesting the utility of this approach regardless of the lipid composition. Successful mRNA and gene editors' delivery is observed in the retinal pigment epithelium and photoreceptors and validated in mice, non-human primates, and human retinal organoids. Deploying PFV-LNPs in gene editing experiments result in a similar extent of gene editing compared to analogous LNP (up to 3% on genomic level) in the Ai9 reporter mouse model; but, remarkably, retinal tolerability is significantly improved for PFV-LNP treatment. The study findings indicate that the LNP formulation process can greatly influence mRNA transfection and gene editing outcomes, improving LNP treatment safety without sacrificing efficacy.

Local Assessment and Small Bowel Crohn's Disease Severity Scoring using AI.

RATIONALE AND OBJECTIVES: We present a machine learning and computer vision approach for a localized, automated, and standardized scoring of Crohn's disease (CD) severity in the small bowel, overcoming the current limitations of manual measurements CT enterography (CTE) imaging and qualitative assessments, while also considering the complex anatomy and distribution of the disease. MATERIALS AND METHODS: Two radiologists introduced a severity score and evaluated disease severity at 7.5 mm intervals along the curved planar reconstruction of the distal and terminal ileum using 236 CTE scans. A hybrid model, combining deep-learning, 3-D CNN, and Random Forest model, was developed to classify disease severity at each mini-segment. Precision, sensitivity, weighted Cohen's score, and accuracy were evaluated on a 20% hold-out test set. RESULTS: The hybrid model achieved precision and sensitivity ranging from 42.4% to 84.1% for various severity categories (normal, mild, moderate, and severe) on the test set. The model's Cohen's score (κ = 0.83) and accuracy (70.7%) were comparable to the inter-observer agreement between experienced radiologists (κ = 0.87, accuracy = 76.3%). The model accurately predicted disease length, correlated with radiologist-reported disease length (r = 0.83), and accurately identified the portion of total ileum containing moderate-to-severe disease with an accuracy of 91.51%. CONCLUSION: The proposed automated hybrid model offers a standardized, reproducible, and quantitative local assessment of small bowel CD severity and demonstrates its value in CD severity assessment.

Independent Associations of Aortic Calcification with Cirrhosis and Liver Related Mortality in Veterans with Chronic Liver Disease.

INTRODUCTION: Abdominal aortic calcifications (AAC) are incidentally found on medical imaging and useful cardiovascular burden approximations. The Morphomic Aortic Calcification Score (MAC) leverages automated deep learning methods to quantify and score AACs. While associations of AAC and non-alcoholic fatty liver disease (NAFLD) have been described, relationships of AAC with other liver diseases and clinical outcome are sparse. This study's purpose was to evaluate AAC and liver-related death in a cohort of Veterans with chronic liver disease (CLD). METHODS: We utilized the VISN 10 CLD cohort, a regional cohort of Veterans with the three forms of CLD: NAFLD, hepatitis C (HCV), alcohol-associated (ETOH), seen between 2008 and 2014, with abdominal CT scans (n = 3604). Associations between MAC and cirrhosis development, liver decompensation, liver-related death, and overall death were evaluated with Cox proportional hazard models. RESULTS: The full cohort demonstrated strong associations of MAC and cirrhosis after adjustment: HR 2.13 (95% CI 1.63, 2.78), decompensation HR 2.19 (95% CI 1.60, 3.02), liver-related death HR 2.13 (95% CI 1.46, 3.11), and overall death HR 1.47 (95% CI 1.27, 1.71). These associations seemed to be driven by the non-NAFLD groups for decompensation and liver-related death [HR 2.80 (95% CI 1.52, 5.17; HR 2.34 (95% CI 1.14, 4.83), respectively]. DISCUSSION: MAC was strongly and independently associated with cirrhosis, liver decompensation, liver-related death, and overall death. Surprisingly, stratification results demonstrated comparable or stronger associations among those with non-NAFLD etiology. These findings suggest abdominal aortic calcification may predict liver disease severity and clinical outcomes in patients with CLD.

Artificial Intelligence for Quantifying Cumulative Small Bowel Disease Severity on CT-Enterography in Crohn's Disease.

INTRODUCTION: Assessing the cumulative degree of bowel injury in ileal Crohn's disease (CD) is difficult. We aimed to develop machine learning (ML) methodologies for automated estimation of cumulative ileal injury on computed tomography-enterography (CTE) to help predict future bowel surgery. METHODS: Adults with ileal CD using biologic therapy at a tertiary care center underwent ML analysis of CTE scans. Two fellowship-trained radiologists graded bowel injury severity at granular spatial increments along the ileum (1 cm), called mini-segments. ML segmentation methods were trained on radiologist grading with predicted severity and then spatially mapped to the ileum. Cumulative injury was calculated as the sum (S-CIDSS) and mean of severity grades along the ileum. Multivariate models of future small bowel resection were compared with cumulative ileum injury metrics and traditional bowel measures, adjusting for laboratory values, medications, and prior surgery at the time of CTE. RESULTS: In 229 CTE scans, 8,424 mini-segments underwent analysis. Agreement between ML and radiologists injury grading was strong (κ = 0.80, 95% confidence interval 0.79-0.81) and similar to inter-radiologist agreement (κ = 0.87, 95% confidence interval 0.85-0.88). S-CIDSS (46.6 vs 30.4, P = 0.0007) and mean cumulative injury grade scores (1.80 vs 1.42, P < 0.0001) were greater in CD biologic users that went to future surgery. Models using cumulative spatial metrics (area under the curve = 0.76) outperformed models using conventional bowel measures, laboratory values, and medical history (area under the curve = 0.62) for predicting future surgery in biologic users. DISCUSSION: Automated cumulative ileal injury scores show promise for improving prediction of outcomes in small bowel CD. Beyond replicating expert judgment, spatial enterography analysis can augment the personalization of bowel assessment in CD.

Morphomics-informed population pharmacokinetic and physiologically-based pharmacokinetic modeling to optimize cefazolin surgical prophylaxis.

INTRODUCTION: Cefazolin is the leading antibiotic used to prevent surgical site infections worldwide. Consensus guidelines recommend adjustment of the cefazolin dose above and below 120 kg without regard to body composition. Algorithms exist to repurpose radiologic data into body composition (morphomics) and inform dosing decisions in obesity. OBJECTIVES: To compare the current standard of body weight to morphomic measurements as covariates of cefazolin pharmacokinetics and aid dose stratification of cefazolin in patients with obesity undergoing colorectal surgery. METHODS: This prospective study measured cefazolin plasma, fat, and colon tissue concentrations in colorectal surgery patients in order to develop a morphomics-informed population pharmacokinetic (PopPK) model to guide dose adjustments. A physiologically-based pharmacokinetic (PBPK) model was also constructed to inform tissue partitioning in morbidly obese patients (n = 21, body mass index ≥35 kg/m2 with one or more co-morbid conditions). RESULTS: Morphomics and pharmacokinetic data were available in 58 patients with a median [min, max] weight and age of 95.9 [68.5, 148.8] kg and 55 [25, 79] years, respectively. The plasma-to-subcutaneous fat partition coefficient was predicted to be 0.072 and 0.060 by the PopPK and PBPK models, respectively. The estimated creatinine clearance (eCLcr ) and body depth at the third lumbar vertebra (body depth_L3) were identified as covariates of cefazolin exposure. The probability of maintaining subcutaneous fat concentrations above 2 µg/mL for 100% of a 4-h surgical period was below 90% when eCLcr ≥105 mL/min and body depth_L3 ≥ 300 mm and less sensitive to the rate of infusion between 5 and 60 min. CONCLUSIONS: Kidney function and morphomics were more informative than body weight as covariates of cefazolin target site exposure. Data from more diverse populations, consensus on target cefazolin exposure, and comparative studies are needed before a change in practice can be implemented.

Cultural-Responsiveness of the Mental Health First Aid Training for Asian Immigrant Populations in Greater Boston, Massachusetts.

Background: The COVID-19 pandemic and rise in anti-Asian racism have had adverse mental health impacts in Asian communities. The lack of culturally-responsive and linguistically-accessible mental health trainings hinders access to mental health services for Asian populations. In this study, we assessed the mental health needs of Asian communities in Greater Boston and evaluated cultural responsiveness of the Mental Health First Aid (MHFA), a first-responder training teaching participants skills to recognize signs of mental health and substance use challenges, and how to appropriately respond. Methods: This community-based participatory research with the Boston Chinatown Neighborhood Center (BCNC), Asian Women For Health (AWFH), and the Addressing Disparities in Asian Populations through Translational Research (ADAPT) Coalition employed two phases. In phase 1, we conducted focus groups with BCNC and AWFH staff and peer educators to assess mental health priorities of Asian populations in Boston. Findings informed phase 2, which evaluated cultural responsiveness of the MHFA through pre- and post-training questionnaires and focus groups with community participants. The pre-training questionnaire asked about mental health needs and barriers, help-seeking behaviors, and literacy; and personal and Asian community stigma. The post-training questionnaire and focus group with community participants asked about cultural competence of MHFA training for Asian populations. Paired t-tests were used to evaluate questionnaire responses. Thematic analysis was used to analyze interviews. Results: In total, 10 staff/educators and 8 community members participated in focus groups. They identified common mental health needs and workforce and culturally-responsive community strategies to support persons with mental health issues. Twenty-four community participants completed pre- and post-training questionnaires. They reported the MHFA training reduced mental health care stigma and increased mental health literacy. Recommendations to increase cultural-responsiveness of the MHFA were to include mental health case studies common in Asian populations and provide the training in other languages (e.g., Chinese, Vietnamese). Conclusion: Cultural responsiveness of the MHFA for Asian populations could be improved with the inclusion of case studies specific to the Asian communities and accessibility of the training in other languages. Increasing the cultural relevance and language accessibility of these trainings could help reduce mental health stigma and gaps in mental health awareness and service utilization among Asian populations.

Incorporation of quantitative imaging data using artificial intelligence improves risk prediction in veterans with liver disease.

BACKGROUND AND AIMS: Utilization of electronic health records data to derive predictive indexes such as the electronic Child-Turcotte-Pugh (eCTP) Score can have significant utility in health care delivery. Within the records, CT scans contain phenotypic data which have significant prognostic value. However, data extractions have not traditionally been applied to imaging data. In this study, we used artificial intelligence to automate biomarker extraction from CT scans and examined the value of these features in improving risk prediction in patients with liver disease. APPROACH AND RESULTS: Using a regional liver disease cohort from the Veterans Health System, we retrieved administrative, laboratory, and clinical data for Veterans who had CT scans performed for any clinical indication between 2008 and 2014. Imaging biomarkers were automatically derived using the analytic morphomics platform. In all, 4614 patients were included. We found that the eCTP Score had a Concordance index of 0.64 for the prediction of overall mortality while the imaging-based model alone or with eCTP Score performed significantly better [Concordance index of 0.72 and 0.73 ( p <0.001)]. For the subset of patients without hepatic decompensation at baseline (n=4452), the Concordance index for predicting future decompensation was 0.67, 0.79, and 0.80 for eCTP Score, imaging alone, or combined, respectively. CONCLUSIONS: This proof of concept demonstrates that the potential of utilizing automated extraction of imaging features within CT scans either alone or in conjunction with classic health data can improve risk prediction in patients with chronic liver disease.

Lipid nanoparticles with PEG-variant surface modifications mediate genome editing in the mouse retina.

Ocular delivery of lipid nanoparticle (LNPs) packaged mRNA can enable efficient gene delivery and editing. We generated LNP variants through the inclusion of positively charged-amine-modified polyethylene glycol (PEG)-lipids (LNPa), negatively charged-carboxyl-(LNPz) and carboxy-ester (LNPx) modified PEG-lipids, and neutral unmodified PEG-lipids (LNP). Subretinal injections of LNPa containing Cre mRNA in the mouse show tdTomato signal in the retinal pigmented epithelium (RPE) like conventional LNPs. Unexpectedly, LNPx and LNPz show 27% and 16% photoreceptor transfection, respectively, with striking localization extending from the photoreceptor synaptic pedicle to the outer segments, displaying pan-retinal distribution in the photoreceptors and RPE. LNPx containing Cas9 mRNA and sgAi9 leads to the formation of an oval elongated structure with a neutral charge resulting in 16.4% editing restricted to RPE. Surface modifications of LNPs with PEG variants can alter cellular tropism of mRNA. LNPs enable genome editing in the retina and in the future can be used to correct genetic mutations that lead to blindness.

Using Artificial Intelligence to Predict Cirrhosis From Computed Tomography Scans.

INTRODUCTION: Undiagnosed cirrhosis remains a significant problem. In this study, we developed and tested an automated liver segmentation tool to predict the presence of cirrhosis in a population of patients with paired liver biopsy and computed tomography (CT) scans. METHODS: We used a cohort of 1,590 CT scans within the Morphomics database to train an automated liver segmentation model using 3D-U-Net and Google's DeeplLabv3+. Imaging features were then automatically calculated from an external test cohort of patients with chronic liver disease who had a paired liver biopsy and CT within 6 months of each other in January 2004-2012. Using gradient boosting decision trees, we developed multivariate models to predict the presence of histologic cirrhosis and evaluated with 5-fold cross-validated c-statistic. RESULTS: Our cohort had 351 patients; 96 patients had cirrhosis. Of the total cohort, 72 were postliver transplant. Both fibrosis (FIB)-4 and liver morphomics alone performed equally well with area under the receiving operating characteristics of 0.76 (95% confidence interval 0.70-0.81) and 0.71 (95% confidence interval 0.65-0.76), respectively ( P = 0.2). However, the combination of liver morphomics with laboratory values or liver morphomics with laboratory and demographic data resulted in significant improved performance with area under the receiving operating characteristics of 0.84 (0.80-0.89) and 0.85 (0.81-0.90), respectively, compared with FIB-4 alone ( P < 0.001). In a subgroup analysis, we also examined performance in patients without liver transplantation and saw similar augmentation of FIB-4. DISCUSSION: This proof-of-principle study demonstrates that automatically extracted features within CT scans can be combined with classic electronic medical record data to improve the prediction of cirrhosis in patients with liver disease. This tool may be used in both pretransplant and posttransplant patients and has the potential to improve our ability to detect undiagnosed cirrhosis.

Reference distributions of aortic calcification and association with Framingham risk score.

Evidence supporting aortic calcification as a leverageable cardiovascular risk factor is rapidly growing. Given aortic calcification's potential as a clinical correlate, we assessed granular vertebral-indexed calcification measurements of the abdominal aorta in a well curated reference population. We evaluated the relationship of aortic calcification measurements with Framingham risk scores. After exclusion, 4073 participants from the Reference Analytic Morphomic Population with varying vertebral levels were included. The percent of the aortic wall calcified was used to assess calcification burden at the L1-L4 levels. Descriptive statistics of participants, sex-specific vertebral indexed calcification measurements, relational plots, and relevant associations are reported. Mean aortic attenuation was higher in female than male participants. Overall, mean aortic calcium was higher with reference to inferior abdominal aortic measurements and demonstrated significant differences across all abdominal levels [L3 Area (mm[Formula: see text]): Females 6.34 (sd 16.60), Males 6.23 (sd 17.21); L3 Volume (mm[Formula: see text]): Females 178.90 (sd 474.19), Males 195.80 (sd 547.36); Wall Calcification (%): Females (L4) 6.97 (sd 16.03), Males (L3) 5.46 (13.80)]. Participants with elevated calcification had significantly higher Framingham risk scores compared to participants with normal calcification scores. Opportunistically measuring aortic calcification may inform further cardiovascular risk assessment and enhance cardiovascular event surveillance efforts.

Validity of Administrative Claims and Electronic Health Registry Data From a Single Practice for Eye Health Surveillance.

Importance: Diagnostic information from administrative claims and electronic health record (EHR) data may serve as an important resource for surveillance of vision and eye health, but the accuracy and validity of these sources are unknown. Objective: To estimate the accuracy of diagnosis codes in administrative claims and EHRs compared to retrospective medical record review. Design, Setting, and Participants: This cross-sectional study compared the presence and prevalence of eye disorders based on diagnostic codes in EHR and claims records vs clinical medical record review at University of Washington-affiliated ophthalmology or optometry clinics from May 2018 to April 2020. Patients 16 years and older with an eye examination in the previous 2 years were included, oversampled for diagnosed major eye diseases and visual acuity loss. Exposures: Patients were assigned to vision and eye health condition categories based on diagnosis codes present in their billing claims history and EHR using the diagnostic case definitions of the US Centers for Disease Control and Prevention Vision and Eye Health Surveillance System (VEHSS) as well as clinical assessment based on retrospective medical record review. Main Outcome and Measures: Accuracy was measured as area under the receiver operating characteristic curve (AUC) of claims and EHR-based diagnostic coding vs retrospective review of clinical assessments and treatment plans. Results: Among 669 participants (mean [range] age, 66.1 [16-99] years; 357 [53.4%] female), identification of diseases in billing claims and EHR data using VEHSS case definitions was accurate for diabetic retinopathy (claims AUC, 0.94; 95% CI, 0.91-0.98; EHR AUC, 0.97; 95% CI, 0.95-0.99), glaucoma (claims AUC, 0.90; 95% CI, 0.88-0.93; EHR AUC, 0.93; 95% CI, 0.90-0.95), age-related macular degeneration (claims AUC, 0.87; 95% CI, 0.83-0.92; EHR AUC, 0.96; 95% CI, 0.94-0.98), and cataracts (claims AUC, 0.82; 95% CI, 0.79-0.86; EHR AUC, 0.91; 95% CI, 0.89-0.93). However, several condition categories showed low validity with AUCs below 0.7, including diagnosed disorders of refraction and accommodation (claims AUC, 0.54; 95% CI, 0.49-0.60; EHR AUC, 0.61; 95% CI, 0.56-0.67), diagnosed blindness and low vision (claims AUC, 0.56; 95% CI, 0.53-0.58; EHR AUC, 0.57; 95% CI, 0.54-0.59), and orbital and external diseases (claims AUC, 0.63; 95% CI, 0.57-0.69; EHR AUC, 0.65; 95% CI, 0.59-0.70). Conclusion and Relevance: In this cross-sectional study of current and recent ophthalmology patients with high rates of eye disorders and vision loss, identification of major vision-threatening eye disorders based on diagnosis codes in claims and EHR records was accurate. However, vision loss, refractive error, and other broadly defined or lower-risk disorder categories were less accurately identified by diagnosis codes in claims and EHR data.

Comparing Telephone Survey Responses to Best-Corrected Visual Acuity to Estimate the Accuracy of Identifying Vision Loss: Validation Study.

BACKGROUND: Self-reported questions on blindness and vision problems are collected in many national surveys. Recently released surveillance estimates on the prevalence of vision loss used self-reported data to predict variation in the prevalence of objectively measured acuity loss among population groups for whom examination data are not available. However, the validity of self-reported measures to predict prevalence and disparities in visual acuity has not been established. OBJECTIVE: This study aimed to estimate the diagnostic accuracy of self-reported vision loss measures compared to best-corrected visual acuity (BCVA), inform the design and selection of questions for future data collection, and identify the concordance between self-reported vision and measured acuity at the population level to support ongoing surveillance efforts. METHODS: We calculated accuracy and correlation between self-reported visual function versus BCVA at the individual and population level among patients from the University of Washington ophthalmology or optometry clinics with a prior eye examination, randomly oversampled for visual acuity loss or diagnosed eye diseases. Self-reported visual function was collected via telephone survey. BCVA was determined based on retrospective chart review. Diagnostic accuracy of questions at the person level was measured based on the area under the receiver operator curve (AUC), whereas population-level accuracy was determined based on correlation. RESULTS: The survey question, "Are you blind or do you have serious difficulty seeing, even when wearing glasses?" had the highest accuracy for identifying patients with blindness (BCVA ≤20/200; AUC=0.797). The highest accuracy for detecting any vision loss (BCVA <20/40) was achieved by responses of "fair," "poor," or "very poor" to the question, "At the present time, would you say your eyesight, with glasses or contact lenses if you wear them, is excellent, good, fair, poor, or very poor" (AUC=0.716). At the population level, the relative relationship between prevalence based on survey questions and BCVA remained stable for most demographic groups, with the only exceptions being groups with small sample sizes, and these differences were generally not significant. CONCLUSIONS: Although survey questions are not considered to be sufficiently accurate to be used as a diagnostic test at the individual level, we did find relatively high levels of accuracy for some questions. At the population level, we found that the relative prevalence of the 2 most accurate survey questions were highly correlated with the prevalence of measured visual acuity loss among nearly all demographic groups. The results of this study suggest that self-reported vision questions fielded in national surveys are likely to yield an accurate and stable signal of vision loss across different population groups, although the actual measure of prevalence from these questions is not directly analogous to that of BCVA.

Metabolic abnormalities, liver and body fat in American versus Chinese patients with non-alcoholic fatty liver disease.

Background and Aim: Non-alcoholic fatty liver disease (NAFLD) is common in the United States and China. We compared prevalence of metabolic syndrome (MS), hepatic steatosis and fibrosis, and quantity and quality of body fat between American versus Chinese patients with NAFLD. Methods: NAFLD patients were prospectively recruited from the University of Michigan Health System (UMHS) in the United States and Peking University Health Sciences Center (PUHSC) in China. All patients had baseline computed tomography (CT), laboratory tests and Fibroscan® controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Comparisons were made for overall cohorts and matched cohorts (matched for sex, age, and body mass index [BMI] category). Logistic regression was performed to identify independent predictors of moderate and severe steatosis and lack of advanced fibrosis. Results: One-hundred and one American and One-hundred and sixty Chinese patients were included. UMHS patients were older, with higher prevalence of MS, had higher LSM and CAP scores, and more fat in liver, visceral, subcutaneous, and muscle compartments than PUHSC patients. Differences in LSM, visceral fat Hounsfield unit, and subcutaneous fat area (SFA) persisted in the matched cohort. NAFLD patients with MS had significantly higher LSM, and more fat in liver, visceral, subcutaneous and muscle compartments than those without. Moderate or severe steatosis was independently associated with MS, visceral fat quality, and SFA, while the absence of advanced fibrosis was associated with Asian race and not having MS. Conclusion: American patients with NAFLD had more liver fibrosis than Chinese patients despite having better quality visceral fat and after matching for age, sex, and BMI category.

Acknowledging Anti-Blackness, Overlooking Anti-Asian Racism: Missed Developmental Opportunities for Chinese American Youth.

This paper explores the pathways and barriers to critical consciousness development for Chinese American youth. Thirty-five interviews conducted in 2020 with high-school-aged students in Chicago were analyzed to better understand young people's experiences developing an understanding of anti-Asian racism and anti-Blackness. Results indicated that participants overwhelmingly engaged in sustained conversations about Black Lives Matter and/or made efforts to address anti-Blackness within their families, but engaged in limited conversations about anti-Asian racism. Furthermore, conversations at home and school often failed to contextualize anti-Asian racism, specifically in relation to the experiences of other oppressed groups. Findings highlight a need for research on and practice with Chinese American adolescents to recognize the unique racial positioning of Asian Americans under White supremacy.

AGA Clinical Practice Guideline on Systemic Therapy for Hepatocellular Carcinoma.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC), the most common primary liver cancer, remains a deadly cancer, with an incidence that has tripled in the United States since 1980. In recent years, new systemic therapies for HCC have been approved and a critical assessment of the existing data is necessary to balance benefits and harms and inform the development of evidence-based guidelines. METHODS: The American Gastroenterological Association formed a multidisciplinary group consisting of a Technical Review Panel and a Guideline Panel. The Technical Review Panel prioritized clinical questions and outcomes according to their importance for clinicians and patients and conducted an evidence review of systemic therapies in patients with advanced-stage HCC. The Grading of Recommendations Assessment, Development and Evaluation framework was used to assess evidence. The Guideline Panel reviewed the evidence and used the Evidence-to-Decision Framework to develop recommendations. RESULTS: The Panel reviewed the evidence, summarized in the Technical Review, for the following medications approved by the US Food and Drug Administration for HCC: first-line therapies: bevacizumab+atezolizumab, sorafenib, and lenvatinib; second-line therapies: cabozantinib, pembrolizumab, ramucirumab, and regorafenib; and other agents: bevacizumab, nivolumab, and nivolumab+ipilimumab. CONCLUSIONS: The Panel agreed on 11 recommendations focused on systemic therapy for HCC in patients who are not eligible for locoregional therapy or resection, those with metastatic disease and preserved liver function, those with poor liver function, and those on systemic therapy as adjuvant therapy.

Systematic review: development of a consensus code set to identify cirrhosis in electronic health records.

BACKGROUND: Electronic health records (EHRs) collate longitudinal data that can be used to facilitate large-scale research in patients with cirrhosis. However, there is no consensus code set to define the presence of cirrhosis in EHR. This systematic review aims to evaluate the validity of diagnostic coding in cirrhosis and to synthesise a comprehensive set of ICD-10 codes for future EHR research. METHOD: MEDLINE and EMBASE databases were searched for studies that used EHR to identify cirrhosis and cirrhosis-related complications. Validated code sets were summarised, and the performance characteristics were extracted. Citation analysis was done to inform development of a consensus code set. This was then validated in a cohort of patients. RESULTS: One thousand six hundred twenty-six records were screened, and 18 studies were identified. The positive predictive value (PPV) was the most frequently reported statistical estimate and was ≥80% in 17/18 studies. Citation analyses showed continued variation in those used in contemporary research practice. Nine codes were identified as those most frequently used in the literature and these formed the consensus code set. This was validated in diverse patient populations from Europe and North America and showed high PPV (83%-89%) and greater sensitivity for the identification of cirrhosis than the most often used code set in the recent literature. CONCLUSION: There is variation in code sets used to identify cirrhosis in contemporary research practice. A consensus set has been developed and validated, showing improved performance, and is proposed to align EHR study designs in cirrhosis to facilitate international collaboration and comparisons.