Communications medicine最新文献

Background: The COVID-19 pandemic induced an increase in telemedicine use in the American health care system. We assess disparities in telemedicine usage, the diseases and conditions it is used for, and the association of payment parity policies with telemedicine use for January 2019-March 2023.

Methods: We include health systems which reported electronic health record data to the Healthjump database. The outcomes of interest are the percentage of outpatient consultations conducted via telemedicine in each health system and the distribution of outpatient and telemedicine consultations across 31 diseases and conditions. We use a difference-in-difference observational design to assess the association of state level payment parity mandates with telemedicine use.

Results: We show telemedicine use grew from less than 0.05% of outpatient consultations in 2019 to 25% in April 2020 and 4% in March 2023. Health systems in urban areas used telemedicine 2.4 times more than health systems in rural areas since April 2020 at the median. In March 2023, 29% of all mental health care visits and 21% of substance use disorder care were provided via telemedicine. Payment parity mandates are associated with a 2.5 percentage point increase in telemedicine use in the first quarter of 2023 compared to states without mandates.

Conclusions: The pandemic resulted in a sustained change in the use of telemedicine. The predominance of mental health care in telemedicine suggests that this mode of service delivery could be instrumental to increasing access to mental health services in the United States.

Background: WNT signaling plays a key role in postnatal bone formation. Individuals with gain-of-function mutations in the WNT co-receptor LRP5 exhibit increased lower-body fat mass and potentially enhanced glucose metabolism, alongside high bone mass. However, the mechanisms by which LRP5 regulates fat distribution and its effects on systemic metabolism remain unclear. This study aims to explore the role of LRP5 in adipose tissue biology and its impact on metabolism.

Methods: Metabolic assessments and imaging were conducted on individuals with gain- and loss-of-function LRP5 mutations, along with age- and BMI-matched controls. Mendelian randomization analyses were used to investigate the relationship between bone, fat distribution, and systemic metabolism. Functional studies and RNA sequencing were performed on abdominal and gluteal adipose cells with LRP5 knockdown.

Results: Here we show that LRP5 promotes lower-body fat distribution and enhances systemic and adipocyte insulin sensitivity through cell-autonomous mechanisms, independent of its bone-related functions. LRP5 supports adipose progenitor cell function by activating WNT/β-catenin signaling and preserving valosin-containing protein (VCP)-mediated proteostasis. LRP5 expression in adipose progenitors declines with age, but gain-of-function LRP5 variants protect against age-related fat loss in the lower body.

Conclusions: Our findings underscore the critical role of LRP5 in regulating lower-body fat distribution and insulin sensitivity, independent of its effects on bone. Pharmacological activation of LRP5 in adipose tissue may offer a promising strategy to prevent age-related fat redistribution and metabolic disorders.

Background: Huntington's disease, a neurodegenerative disorder, impairs both upper and lower limb function, typically assessed in clinical settings. However, wearable sensors offer the opportunity to monitor real-world data that complements clinical assessments, providing a more comprehensive understanding of disease symptoms.

Methods: In this study, we monitor upper limb function in individuals with Huntington's disease (HD, n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor over a 7-day period. Goal-directed hand movements are detected through a deep learning model, and kinematic features of each movement are analyzed. The collected data is used to predict disease groups and clinical scores using statistical and machine learning models.

Results: Here we show that significant differences in goal-directed movement features exist between the groups. Additionally, several of these features strongly correlate with clinical scores. Classification models accurately distinguish between HD, pHD, and CTR individuals, achieving a balanced accuracy of 67% and a recall of 0.72 for the HD group. Regression models effectively predict clinical scores.

Conclusions: This study demonstrates the potential of wearable sensors and machine learning to monitor upper limb function in Huntington's disease, offering a tool for early detection, remote monitoring, and assessing treatment efficacy in clinical trials.

Background: The rapid spread of covid-19 overwhelmed healthcare systems. This study aimed to investigate the impact of the covid-19 pandemic on hospitalizations and hospital deaths due to cerebrovascular diseases (CVD) in São Paulo state, Brazil.

Methods: This ecologic study evaluated the CVD hospitalizations and hospital deaths (2017-2021) by demographic features and CVD type. During the pandemic (2020-2021), segmented regression models were used to detect changes in CVD trends. We also evaluated the detrended cross-correlation between CVD deaths and hospitalization with the SARS-Cov-2 infection series.

Results: During the pandemic, there is a 35% reduction in CVD hospitalizations, mainly in elective admissions and ischemic stroke, but a 6.5% increase in deaths, especially in Black and Brown individuals, and those aged 20-29 years. From 2020 to 2021, Black and Brown individuals experience an earlier and more prolonged increase in hospital deaths. Ischemic CVD hospitalizations decrease in the first quarter of 2020. Older people exhibit a monthly increase of 2.9% in hospitalizations and 5.3% in deaths in the 2nd and 3rd quarters of 2021. SARS-Cov-2 infections are inversely correlated to CVD hospitalizations and directly correlated to CVD hospital deaths.

Conclusions: Covid-19 pandemic negatively affects CVD hospitalizations and deaths, particularly in Black and Brown individuals. The decrease in hospitalizations and increase in hospital deaths of ischemic CVD highlights vulnerability in accessing healthcare resources during the pandemic.

Background: Type 2 diabetes (T2D) etiology is highly complex due to its multiple roots of origin. Polygenic risk scores (PRS) based on genome-wide association studies (GWAS) can partially explain T2D risk. Asian Indian people have up to six times higher risk of developing T2D than European people, and underlying causes of this disparity are unknown.

Methods: We have performed targeted sequencing of ten T2D GWAS/candidate regions using endogamous Punjabi Sikh families and replication studies using unrelated Sikh people and families from three other Indian endogamous ethnic groups (EEGs).

Results: We detect rare and ultra-rare variants (RVs) in KCNJ11-ABCC8 and HNF4A (MODY genes) cosegregated with late-onset T2D. We also identify RV enrichment in two new genes, SLC38A11 and ANPEP, associated with T2D. Gene-burden analysis reveals the highest RV burden contributed by HNF4A (p = 0.0003), followed by KCNJ11/ABCC8 (p = 0.0061) and SLC38A11 (p = 0.03). Some RVs detected in Sikh people are also found in Agarwals from Jaipur, both from Northern India, but were monomorphic in other two EEGs from South Indian people. Despite carrying a high burden of T2D and RVs, most families have a significantly lower burden of PRS. Functional studies show that an intronic regulatory variant (RV) in ABCC8 affects the binding of Pax4 and NF-kB transcription factors, influencing downstream gene regulation.

Conclusions: The high burden of T2D in these families may stem from the enrichment of noncoding RVs in a small number of major known genes (including MODY genes) with oligogenic inheritance alongside RVs from genes associated with polygenic susceptibility. These findings highlight the need to conduct deeper evaluations of families from non-European ancestries to identify potential novel therapeutics and implement preventative strategies.

Background: This systematic review sought to examine the application of decision analytic models (DAMs) to evaluate cardiovascular disease (CVD) prevention interventions in sub-Saharan Africa (SSA), a region that has experienced an increasing CVD burden in the last two decades.

Methods: We searched seven databases and identified model-based economic evaluations of interventions targeting CVD prevention among adult populations in SSA. All articles were screened by two reviewers, data was extracted, and narrative synthesis was performed. Quality assessment was performed using the Philips checklist.

Results: The review included 27 articles from eight SSA countries. The majority of the studies evaluated interventions for primary CVD prevention, with primordial prevention interventions being the least evaluated. Markov models were the most commonly used modelling method. Seven studies incorporated equity dimensions in the modelling, which were assessed mainly through subgroup analysis. The mean quality score of the papers was 68.9% and most studies reported data challenges while only three studies conducted model validation.

Conclusions: The review finds few studies modelling the impact of interventions targeting primordial prevention and those evaluating equitable strategies for improving access to CVD prevention. There is a need for increased transparency in model building, validation and documentation.

Background: Tumor dormancy is a substantial clinical obstacle in treatment of estrogen receptor positive mammary carcinoma (ER+MC), contributing to drug resistance, metastatic outgrowth, relapse, and consequent mortality.

Methods: Preclinical models mimicking clinical anti-estrogen-induced ER+MC dormancy were generated in vivo. Function and a mechanism-based combination treatment were determined in the generated dormancy-like models in vitro, ex vivo, and in vivo.

Results: The dormancy models display molecular features of dormancy and tumor mass and cellular dormancy with associated clinical dormancy behavior. Both serum and cancer tissue expression of Trefoil factor 3 (TFF3) are identified as prognostic indicators of dormant ER+MC with TFF3 functioning as an epigenetically regulated driver of dormancy-associated behaviors. BCL2-dependent pro-survival functions of TFF3 coupled with enhanced attributes of stemness designates TFF3 as an actionable target. Moreover, combination screening of a TFF3 small-molecule-inhibitor (AMPC) with compounds used clinically to treat anti-estrogen-resistant ER+MC identifies strong synergism between AMPC and CDK4/6 inhibitors in the dormancy-like models. The combination results in concomitant suppression of CCND1 expression and CDK4/6 kinase activity to decrease RB phosphorylation, with reduced BCL2 expression, leading to both ER + MC cell cycle arrest and apoptosis. The combined TFF3-CDK4/6 inhibition impedes metastatic outgrowth and ameliorates host animal survival in the dormancy-like models, producing a complete response in a percentage of animals.

Conclusions: Hence, in vivo models of anti-estrogen induced dormancy of ER+MC generated herein, identify TFF3 as a driver of this process. The combined inhibition of TFF3 and CDK4/6 may potentially alleviate the clinical challenges posed by anti-estrogen-induced dormancy in ER+MC.

Background: While there is increasing recognition of the morbidity of cardiovascular disease in cancer survivors, including accelerated atherosclerosis following thoracic radiotherapy, patients are frequently under-optimized for cardiovascular risk.

Methods: In this prospective single-arm cohort pilot study, patients were treated with high-dose thoracic radiotherapy and had early consultation with cardio-oncology. Twenty patients were enrolled. The primary endpoint was adherence to cardio-oncology consultation. Secondary endpoints were cardiovascular medication intervention rate and patient-reported intervention perspectives. Clonal hematopoiesis of indeterminate potential, a major cardiovascular risk marker enriched in patients with cancer and induced by radiation exposure, was measured as an exploratory endpoint.

Results: The cohort median age is 71 years. Most patients are female (13/20), have primary lung or esophageal carcinoma (16/20), and 7/20 have pre-existing cardiovascular disease. We show that cardio-oncology consultation adherence is high (19/20) and results in cardiovascular medication optimization changes in most patients (12/19), most commonly to initiate or intensify statin therapy (8/12). 8/12 patients with a primary cardiologist prior to enrollment have medication changes recommended. Most (12/17) participants are glad to learn about their heart health during cancer treatment. Clonal hematopoiesis is detectable prior to treatment in 8/20 patients and three develop new variants after treatment (1/3 de novo).

Conclusions: We observe that early cardio-oncology consultation is feasible, leads to cardiovascular medication optimization in the majority (>60%) of participants, most commonly to initiate or intensify statin therapy. New clonal hematopoiesis variants are detectable early after radiotherapy and the impact on post-treatment cardiovascular risk is worthy of further study.

Background: Spatial accessibility to healthcare is a critical factor in ensuring equitable health outcomes. While studies on a global, continental, and national level exist, our understanding of intra-urban differences, particularly between formal and informal areas within cities in sub-Saharan Africa, remains limited.

Methods: This study integrates openly available datasets on land use in 19 sub-Saharan cities, healthcare facilities in the region, and street networks from OpenStreetMap. Using these datasets, we calculate service areas around hospitals, considering travel times ranging from 1 to 120 minutes with walking as the mode of travel. The resulting service areas are then merged with population data from WorldPop, allowing us to assess the proportion of the population with specific travel times to healthcare facilities from informal and formal residential areas.

Results: Our analysis reveals that 33% of the urban population can reach hospitals within 15 minutes, 58% within 30 minutes, and 78% within 60 minutes. Importantly, for some cities, we observe significant differences between formal and informal areas, with informal areas experiencing a disadvantage in terms of spatial accessibility to healthcare facilities. The population in informal areas is particularly disadvantaged in medium-sized cities.

Conclusions: This study sheds light on the spatial accessibility of healthcare facilities in sub-Saharan African cities, emphasizing the need to consider intra-urban disparities, particularly in informal areas. The findings underscore the importance of targeted interventions and urban planning strategies to address these disparities and ensure that healthcare services are accessible to all segments of the urban population.

Several transitions, or new patterns and dynamics in the contributors and health outcomes, have altered the character and burden of the multi-decade, worldwide growth in prevalence of type 2 diabetes (T2DM). These changes have led to different needs for prevention and care. These dynamics have been driven by diverse demographic, socio-economic, behavioural, and health system response factors. In this Perspective, we describe these transitions and how their attributes have set the stage for multimorbidity, or multiple long-term conditions (MLTCs), to be the next major challenge in the diabetes epidemic. We also describe how the timing and character of these stages differ in high-, middle-, and low-income countries. These challenges call for innovation and a stronger focus on MLTCs across the spectrum of cause, effectiveness, and implementation studies to guide prevention and treatment priorities.