Telehealth Utilization and Associations in the United States During the Third Year of the COVID-19 Pandemic: Population-Based Survey Study in 2022.

BACKGROUND: The COVID-19 pandemic rapidly changed the landscape of clinical practice in the United States; telehealth became an essential mode of health care delivery, yet many components of telehealth use remain unknown years after the disease's emergence. OBJECTIVE: We aim to comprehensively assess telehealth use and its associated factors in the United States. METHODS: This cross-sectional study used a nationally representative survey (Health Information National Trends Survey) administered to US adults (≥18 years) from March 2022 through November 2022. To assess telehealth adoption, perceptions of telehealth, satisfaction with telehealth, and the telehealth care purpose, we conducted weighted descriptive analyses. To identify the subpopulations with low adoption of telehealth, we developed a weighted multivariable logistic regression model. RESULTS: Among a total of 6252 survey participants, 39.3% (2517/6252) reported telehealth use in the past 12 months (video: 1110/6252, 17.8%; audio: 876/6252, 11.6%). The most prominent reason for not using telehealth was due to telehealth providers failing to offer this option (2200/3529, 63%). The most common reason for respondents not using offered telehealth services was a preference for in-person care (527/578, 84.4%). Primary motivations to use telehealth were providers' recommendations (1716/2517, 72.7%) and convenience (1516/2517, 65.6%), mainly for acute minor illness (600/2397, 29.7%) and chronic condition management (583/2397, 21.4%), yet care purposes differed by age, race/ethnicity, and income. The satisfaction rate was predominately high, with no technical problems (1829/2517, 80.5%), comparable care quality to that of in-person care (1779/2517, 75%), and no privacy concerns (1958/2517, 83.7%). Younger individuals (odd ratios [ORs] 1.48-2.23; 18-64 years vs ≥75 years), women (OR 1.33, 95% CI 1.09-1.61), Hispanic individuals (OR 1.37, 95% CI 1.05-1.80; vs non-Hispanic White), those with more education (OR 1.72, 95% CI 1.03-2.87; at least a college graduate vs less than high school), unemployed individuals (OR 1.25, 95% CI 1.02-1.54), insured individuals (OR 1.83, 95% CI 1.25-2.69), or those with poor general health status (OR 1.66, 95% CI 1.30-2.13) had higher odds of using telehealth. CONCLUSIONS: To our best knowledge, this is among the first studies to examine patient factors around telehealth use, including motivations to use, perceptions of, satisfaction with, and care purpose of telehealth, as well as sociodemographic factors associated with telehealth adoption using a nationally representative survey. The wide array of descriptive findings and identified associations will help providers and health systems understand the factors that drive patients toward or away from telehealth visits as the technology becomes more routinely available across the United States, providing future directions for telehealth use and telehealth research.

Prevalence and associations of poor mental health in the third year of COVID-19: U.S. population-based analysis from 2020 to 2022.

BACKGROUND: Poorer mental health was found early in the COVID-19 pandemic, yet mental health in the third year of COVID-19 has not been assessed on a general adult population level in the United States. METHODS: We used a nationally representative cross-sectional survey (Health Information National Trends Survey, HINTS 5 2020 n = 3,865 and HINTS 6 2022 n = 6,252). The prevalence of poor mental health was examined using a Patient Health Questionnaire-4 scale in 2020 and 2022. We also investigated the factors associated with poor mental health in 2022 using a weighted multivariable logistic regression adjusting for sociodemographic and health status characteristics to obtain the odds ratio (OR). OUTCOMES: The prevalence of poor mental health in adults increased from 2020 to 2022 (31.5% vs 36.3 %, p = 0.0005). U.S. adults in 2022 were 1.28 times as likely to have poor mental health than early in the pandemic. Moreover, individuals with food insecurity, housing instability, and low income had greater odds of poor mental health (ORs=1.78-2.55). Adults who were females, non-Hispanic Whites, or age 18-64 years were more likely to have poor mental health (ORs=1.46-4.15). INTERPRETATION: Mental health of U.S. adults worsened in the third year of COVID-19 compared to the beginning of the pandemic.

Assessing Biases in Medical Decisions via Clinician and AI Chatbot Responses to Patient Vignettes.

This cross-sectional study compares clinician and artificial intelligence (AI) chatbot responses to patient vignettes used to identify bias in medical decisions.

Incidence Trends of Primary Cutaneous T-Cell Lymphoma in the US From 2000 to 2018: A SEER Population Data Analysis.

Using SEER database data, this cohort study analyzed cutaneous T-cell lymphoma incidence by tumor subtype, sex, age, race and ethnicity, socioeconomic status, and geography.

A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis.

Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability.

Differences in Thickness-Specific Incidence and Factors Associated With Cutaneous Melanoma in the US From 2010 to 2018.

Importance: The recent incidence of cutaneous melanoma of different thicknesses in the US is not well described. Objective: To evaluate recent patterns in the incidence of melanoma by tumor thickness and examine associations of sex, race and ethnicity, and socioeconomic status with melanoma thickness-specific incidence. Design, Setting, and Participants: This population-based cohort study analyzed data for 187 487 patients with a new diagnosis of invasive cutaneous melanoma from the Surveillance, Epidemiology, and End Results Registry from January 1, 2010, to December 31, 2018. The study was conducted from May 27 to December 29, 2021. Data were analyzed from June 21 to October 24, 2021. Main Outcomes and Measures: Age-adjusted incidence rates of melanoma were calculated by tumor thickness (categorized by Breslow thickness) and annual percentage change (APC) in incidence rates. Analyses were stratified by sex and race and ethnicity. The associations with socioeconomic status were evaluated in 134 359 patients diagnosed with melanoma from 2010 to 2016. Results: This study included 187 487 patients with a median (IQR) age of 62 (52-72) years and 58.4% men. Melanoma incidence was higher in men compared with women across all tumor thickness groups. Individuals in lower socioeconomic status quintiles and members of minority groups were more likely to be diagnosed with thicker (T4) tumors (20.7% [169 of 816] among non-Hispanic Black patients, 11.2% [674 of 6042] among Hispanic patients, and 6.3% [10 774 of 170 155] among non-Hispanic White patients). Between 2010 and 2018, there was no significant increase in incidence of cutaneous melanoma across the full population (APC, 0.39%; 95% CI, -0.40% to 1.18%). The incidence of the thickest melanomas (T4, >4.0 mm) increased between 2010 and 2018, with an APC of 3.32% (95% CI, 2.06%-4.60%) overall, 2.50% (95% CI, 1.27%-3.73%) in men, and 4.64% (95% CI, 2.56%-6.75%) in women. Conclusions and Relevance: In this population-based cohort study, the incidence of the thickest cutaneous melanoma tumors increased from 2010 to 2018, in contrast with the incidence patterns for thinner melanomas. The findings suggest potential stabilization of overall melanoma incidence rates in the US after nearly a century of continuous increase in incidence. Patients with low socioeconomic status and Hispanic patients were more likely to be diagnosed with thick melanoma. The continued rise in incidence of thick melanoma is unlikely to be attributable to overdiagnosis given the stability of thin melanoma rates.

Refractive Outcomes for Cataract Surgery With Toric Intraocular Lenses at a Veterans Affairs Medical Center.

Background: Refractive outcomes for cataract surgery with toric intraocular lenses (IOLs) are not well described in a teaching hospital setting. This study investigated the refractive outcomes of cataract surgery with toric IOLs at an academic-affiliated Veterans Affairs Medical Center (VAMC) and compared the accuracy of 2 biometric formulae for toric IOL power calculation. Methods: A retrospective chart review of patients who received cataract surgery with toric IOLs from November 2013 to May 2018 was conducted. The Holladay 2 and Barrett toric IOL formulae were used to predict the postoperative refraction for each cataract surgery. The main outcome measures were best-corrected visual acuity (BCVA) and the difference in cylinder between the preoperative and postoperative manifest refractions. The accuracy of each biometric formula was also assessed using 2-tailed t tests of the mean absolute error, and subgroup analyses were conducted for short, medium, and long eyes. Results: Of 325 charts reviewed, 283 patients met the inclusion criteria; 87% (248/283) of these surgeries were performed by resident surgeons. The median postoperative BCVA was 20/20, and 92% of patients had a postoperative BCVA of 20/25 or better. There was no statistically significant difference in mean absolute error between the 2 formulae for the entire axial length range (P = .21), as well as the short (P = .94), medium (P = .49), and long axial length (P = .08) groups. Conclusions: To our knowledge, this is the largest study that compared the performance of the Barrett toric and Holladay 2 formulae and the first that made the comparison in a teaching hospital setting. This study suggests that the 2 formulae have similar refractive outcomes across all axial lengths.

Hiding in Plain Sight: The Globally Distributed Bacterial Candidate Phylum PAUC34f.

Bacterial candidate phylum PAUC34f was originally discovered in marine sponges and is widely considered to be composed of sponge symbionts. Here, we report 21 single amplified genomes (SAGs) of PAUC34f from a variety of environments, including the dark ocean, lake sediments, and a terrestrial aquifer. The diverse origins of the SAGs and the results of metagenome fragment recruitment suggest that some PAUC34f lineages represent relatively abundant, free-living cells in environments other than sponge microbiomes, including the deep ocean. Both phylogenetic and biogeographic patterns, as well as genome content analyses suggest that PAUC34f associations with hosts evolved independently multiple times, while free-living lineages of PAUC34f are distinct and relatively abundant in a wide range of environments.

Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.

BACKGROUND: The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited scope of conventional phenotypic antimicrobial susceptibility, but gaps remain for predicting phenotype accurately from genotypic data especially for certain drugs. Our primary aim was to perform an exploration of statistical learning algorithms and genetic predictor sets using a rich dataset to build a high performing and fast predicting model to detect anti-tuberculosis drug resistance. METHODS: We collected targeted or whole genome sequencing and conventional drug resistance phenotyping data from 3601 Mycobacterium tuberculosis strains enriched for resistance to first- and second-line drugs, with 1228 multidrug resistant strains. We investigated the utility of (1) rare variants and variants known to be determinants of resistance for at least one drug and (2) machine and statistical learning architectures in predicting phenotypic drug resistance to 10 anti-tuberculosis drugs. Specifically, we investigated multitask and single task wide and deep neural networks, a multilayer perceptron, regularized logistic regression, and random forest classifiers. FINDINGS: The highest performing machine and statistical learning methods included both rare variants and those known to be causal of resistance for at least one drug. Both simpler L2 penalized regression and complex machine learning models had high predictive performance. The average AUCs for our highest performing model was 0.979 for first-line drugs and 0.936 for second-line drugs during repeated cross-validation. On an independent validation set, the highest performing model showed average AUCs, sensitivities, and specificities, respectively, of 0.937, 87.9%, and 92.7% for first-line drugs and 0.891, 82.0% and 90.1% for second-line drugs. Our method outperforms existing approaches based on direct association, with increased sum of sensitivity and specificity of 11.7% on first line drugs and 3.2% on second line drugs. Our method has higher predictive performance compared to previously reported machine learning models during cross-validation, with higher AUCs for 8 of 10 drugs. INTERPRETATION: Statistical models, especially those that are trained using both frequent and less frequent variants, significantly improve the accuracy of resistance prediction and hold promise in bringing sequencing technologies closer to the bedside.

Association of Caffeine Intake and Caffeinated Coffee Consumption With Risk of Incident Rosacea in Women.

Importance: Caffeine is known to decrease vasodilation and have immunosuppressant effects, which may potentially decrease the risk of rosacea. However, the heat from coffee may be a trigger for rosacea flares. The relationship between the risk of rosacea and caffeine intake, including coffee consumption, is poorly understood. Objective: To determine the association between the risk of incident rosacea and caffeine intake, including coffee consumption. Design, Setting, and Participants: This cohort study included 82 737 women in the Nurses' Health Study II (NHS II), a prospective cohort established in 1989, with follow-up conducted biennially between 1991 and 2005. All analysis took place between June 2017 and June 2018. Exposures: Data on coffee, tea, soda, and chocolate consumption were collected every 4 years during follow-up. Main Outcomes and Measures: Information on history of clinician-diagnosed rosacea and year of diagnosis was collected in 2005. Results: A total of 82 737 women responded to the question regarding a diagnosis of rosacea in 2005 in NHS II and were included in the final analysis (mean [SD] age at study entry, 50.5 [4.6] years). During 1 120 051 person-years of follow-up, we identified 4945 incident cases of rosacea. After adjustment for other risk factors, we found an inverse association between increased caffeine intake and risk of rosacea (hazard ratio for the highest quintile of caffeine intake vs the lowest, 0.76; 95% CI, 0.69-0.84; P < .001 for trend). A significant inverse association with risk of rosacea was also observed for caffeinated coffee consumption (HR, 0.77 for those who consumed ≥4 servings/d vs those who consumed <1/mo; 95% CI, 0.69-0.87; P < .001 for trend), but not for decaffeinated coffee (HR, 0.80; 95% CI, 0.56-1.14; P = .39 for trend). Further analyses found that increased caffeine intake from foods other than coffee (tea, soda, and chocolate) was not significantly associated with decreased risk of rosacea. Conclusions and Relevance: Increased caffeine intake from coffee was inversely associated with the risk of incident rosacea. Our findings do not support limiting caffeine intake as a means to prevent rosacea. Further studies are required to explain the mechanisms of action of these associations, to replicate our findings in other populations, and to explore the relationship of caffeine with different rosacea subtypes.

Complete resolution of erythema elevatum diutinum using oral sulfasalazine.

Erythema elevatum diutinum (EED) is a rare, chronic small-vessel vasculitis that presents as firm, red, violaceous, or brown papules and nodules on the extensor surfaces of the limbs. Oral dapsone is considered first-line therapy for EED; in the current case report, a patient presenting with EED began dapsone treatment and symptoms subsided within two weeks. Seven months later, the patient became pregnant and stopped dapsone owing to her concerns with dapsone use during pregnancy, resulting in recurrence of EED symptoms. We present a novel treatment approach with oral sulfasalazine, which was given to the patient in lieu of dapsone and resulted in complete resolution of EED symptoms.

Erythroid dysplasia, megaloblastic anemia, and impaired lymphopoiesis arising from mitochondrial dysfunction.

Recent reports describe hematopoietic abnormalities in mice with targeted instability of the mitochondrial genome. However, these abnormalities have not been fully described. We demonstrate that mutant animals develop an age-dependent, macrocytic anemia with abnormal erythroid maturation and megaloblastic changes, as well as profound defects in lymphopoiesis. Mice die of severe fatal anemia at 15 months of age. Bone-marrow transplantation studies demonstrate that these abnormalities are intrinsic to the hematopoietic compartment and dependent upon the age of donor hematopoietic stem cells. These abnormalities are phenotypically similar to those found in patients with refractory anemia, suggesting that, in some cases, the myelodysplastic syndromes are caused by abnormalities of mitochondrial function.

Atypical teratoid/rhabdoid tumors of the central nervous system: management and outcomes.

OBJECT: Atypical teratoid/rhabdoid tumors (ATRTs) represent a relatively newly categorized neoplastic entity. They commonly present in childhood, and have a rapidly progressive clinical course with a survival time of less than 1 year. Treatment regimens have been nonuniform. In this retrospective review of patients with ATRTs who were treated at the authors' institution according to a uniform protocol, the goal was to assess the efficacy of the treatment and its outcome. METHODS: Over a 7-year period, ATRT was diagnosed in 11 patients (six boys and five girls). The median age of the patients was 61 months, and their ages ranged from 3 months to 17 years. Signs and symptoms began, on average, a little more than 1 month before diagnosis and included the following: headache (36%), nausea and vomiting (46%), lethargy (18%), seizures (27%), cranial nerve findings (46%), ataxia (18%), long tract findings (18%), and hydrocephalus (46%). Tumor location was cortical in four patients, in the pineal region in four, in the posterior fossa in two, and spinal in one. In one patient disseminated disease was revealed on the initial imaging study; seven patients had disseminated tumor subsequently. Treatment consisted of chemotherapy in 11 patients, chemotherapy and local radiation in five, and chemotherapy and craniospinal radiation in three. Six patients are alive, three have died, and two were lost to follow-up review. The mean time to death was 24 months, and ranged from 2 to 67 months. Among the surviving patients the mean duration of follow up is 18.5 months and ranges from 2 to 37 months. The median time to progression was 3.5 months. CONCLUSIONS: Atypical teratoid/rhabdoid tumors are malignant lesions with rapid progression. Further study is necessary to determine the efficacy of therapy.

Bone mineral density and fractures in Turner syndrome.

PURPOSE: To determine whether women with Turner syndrome who were treated with estrogen were more likely to have osteoporosis and fractures. METHODS: Areal bone density at the lumbar spine and femoral neck was measured in 40 adult women with Turner syndrome and 43 age-matched healthy women using dual-energy X-ray absorptiometry. Histories of estrogen treatment and fractures were obtained by structured personal interviews. RESULTS: Mean (+/- SD) areal bone density was significantly lower at the lumbar spine (0.87 +/- 0.11 g/cm(2) vs. 0.98 +/- 0.10 g/cm(2), P <0.001) and femoral neck (0.68 +/- 0.07 g/ cm(2) vs. 0.83 +/- 0.08 g/cm(2), P <0.001) in women with Turner syndrome than in controls. The diagnostic criterion for osteoporosis (T-score <-2.5) was met by 8 women with Turner syndrome (20%) with scores at the lumbar spine and by 3 (8%) with scores at the femoral neck. All women diagnosed with osteoporosis were less than 150 cm in height. Areal bone density correlated significantly with height (lumbar spine: R(2) = 0.3, P <0.001; femoral neck: R(2) = 0.4, P <0.001). Adjustments for skeletal size reduced the differences between the groups as well as the number of women diagnosed with osteoporosis (e.g., from 8 to 2 women based on lumbar spine scores). The prevalence and type of fractures were similar in the two groups. CONCLUSIONS: The prevalence of osteoporosis and bone fractures is not increased significantly in women with Turner syndrome who are treated with standard estrogen therapy. Women less than 150 cm in height are likely to be misdiagnosed with osteoporosis when areal bone density is measured, unless adjustments for body size are made.