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To determine if the addition of home environmental control strategies (ECSs) to controller medication titration reduces asthma controller medication requirements and in-home allergen concentrations among children with persistent asthma in Baltimore City. 155 children ages 5–17 with allergen-sensitized asthma were enrolled in a 6-month randomized clinical trial of multifaceted, individually-tailored ECS plus asthma controller medication titration compared to controller medication titration alone. Participants had to meet criteria for persistent asthma and have had an exacerbation in the previous 18 months. Allergen sensitization (mouse, cockroach, cat, dog, dust mite) was assessed at baseline and home dust allergen concentrations were measured at baseline, 3 and 6 months. ECS was delivered 3–4 times over the trial. Asthma controller medication was titrated using a guidelines-based algorithm at baseline, 2, 4, and 6 months. The primary outcome was controller medication treatment step at 6 months (0–6, as-needed albuterol to high-dose ICS + LABA). The population was predominately Black (90%), on public insurance (93%), and male (61%). The mean age was 10.1 years (SD 3.3). More than 70% were sensitized to a rodent, >50% to cockroach, and 70% were polysensitized. At 6 months, there were no differences in either treatment step (3.8 [SD 1.4] vs. 3.7 [SD 1.5]) or allergen concentrations between groups. Among this predominantly low-income, Black pediatric asthma population, the addition of ECS to controller medication titration reduced neither indoor allergen concentrations nor controller medication requirements compared to controller medication titration alone.

BACKGROUND Higher-volume centers for pancreatic cancer surgeries have been shown to have improved outcomes such as length of stay. We examined how centralization of pancreatic cancer care within a regional integrated healthcare system improves overall survival. METHODS We conducted a retrospective study of 1621 patients treated for pancreatic cancer from February 2010 to December 2018. Care was consolidated into 4 Centers of Excellence (COE) in surgery, medical oncology, and other specialties. Descriptive statistics, bivariate analysis, Chi-square tests, and Kaplan-Meier analysis were performed. RESULTS Neoadjuvant chemotherapy use rose from 10% to 31% (p

This study aimed to investigate Chinese physicians' perception and attitudes toward menopausal hormone therapy (MHT).This nationwide online survey was conducted in China. Physicians registered in the WeChat groups of the Gynecological Endocrinology Committee of China's Maternal and Child Health Care Association received a message invitation to complete this anonymous online survey from April 2020 to July 2020. Physicians' knowledge of and attitudes toward MHT were surveyed.In total, 4672 questionnaires were submitted; only completed questionnaires could be submitted. The message was sent to 6021 doctors, so the response rate was 77.6%. Overall, 77.9-92.9% of physicians knew the common indications and contraindications to MHT. Additionally, 90.6%, 85.4%, 80.7% and 37.5% of physicians thought that MHT would increase the risk of venous thrombosis, breast cancer, endometrial cancer and weight gain, respectively. In total, 58.1% of the physicians mistakenly believed that a sex hormone test was one of the necessary examinations to reassess MHT prescription during follow-up visits. We found that 68.5% of physicians would consider using MHT themselves or recommend MHT to their partners in the future, and 11.4% were currently using MHT.Most Chinese physicians have basic knowledge of MHT. Their misunderstandings about MHT mainly centered on the risks of endometrial cancer, weight gain and the necessary examinations during follow-up visits. These misunderstandings need to be clarified in future professional training programs.

The field of data science currently enjoys a broad definition that includes a wide array of activities which borrow from many other established fields of study. Having such a vague characterization of a field in the early stages might be natural, but over time maintaining such a broad definition becomes unwieldy and impedes progress. In particular, the teaching of data science is hampered by the seeming need to cover many different points of interest. Data scientists must ultimately identify the core of the field by determining what makes the field unique and what it means to develop new knowledge in data science. In this review we attempt to distill some core ideas from data science by focusing on the iterative process of data analysis and develop some generalizations from past experience. Generalizations of this nature could form the basis of a theory of data science and would serve to unify and scale the teaching of data science to large audiences.

Rationale: Indoor particulate matter is associated with worse COPD outcomes. It remains unknown whether reductions of indoor pollutants improve respiratory morbidity. Methods: Eligible former smoke...

The control of ambient air quality in the United States has been a major public health success since the passing of the Clean Air Act, with particulate matter (PM) reductions resulting in an estimated 160 000 premature deaths prevented in 2010 alone. Currently, public policy is oriented around lowering the levels of individual pollutants and this focus has driven the nature of much epidemiological research. Recently, attention has been given to viewing air pollution as a complex mixture and to developing a multi-pollutant approach to controlling ambient concentrations. We present a statistical approach for estimating the health impacts of complex environmental mixtures using a mixture-altering contrast, which is any comparison, intervention, policy, or natural experiment that changes a mixture's composition. We combine the notion of mixture-altering contrasts with sliced inverse regression, propensity score matching, and principal stratification to assess the health effects of different air pollution chemical mixtures. We demonstrate the application of this approach in an analysis of the health effects of wildfire PM air pollution in the Western US.

Teaching data analysis by providing students with real-world problems and datasets allows students to integrate a variety of skills in a situation that mirrors how data analysis actually works. However, whole data analyses may obscure the individual skills of data analytic practice that are generalizable across data analyses. One such skill is the ability to diagnose the cause of unexpected results in a data analysis. While experienced analysts can quickly iterate through a series of potential explanations when confronted with unexpected results, novice analysts often struggle to figure out how to move forward. The goal of this article is to describe an approach to teaching students skills in diagnosing data analytic problems. The exercise described here is targeted to allow students to practice this skill and to assess the depth of their knowledge about the statistical tools they have learned. We take a hypothetical case study approach and focus on the students’ reasoning through their diagnoses and suggestions for follow-up action. We found the implementation of this exercise in a small graduate course to provide valuable information about the students’ diagnostic thought processes, but further work is needed regarding structured approaches to implementation and the design of assessments. Supplementary materials for this article are available online.

INTRODUCTION: Adenosquamous carcinoma (ASC) of the pancreas is a rare form of pancreatic cancer with a worse prognosis than pancreatic ductal adenocarcinoma. The authors report on a retrospective study of 13 patients diagnosed with ASC in an integrated health care system. METHODS: A retrospective review was performed of all patients with pancreatic cancer identified between February 2010 and December 2018. Twenty-three patients were diagnosed with pancreatic ASC. Patient demographics, tumor characteristics, treatment modalities, and median survival were evaluated. RESULTS: Median overall survival was 8 months (standard devision [SD] = 18.6). Eight out of 13 patients who received surgery upfront had a positive surgical margin (62%). Eleven patients received adjuvant therapy. Median survival for patients who received multimodal treatment was 57 months (SD = 5.7) compared with 2.5 months for patients who received only surgery. Median survival for patients with negative pathologic margins was 17 months (SD = 23.6). One patient was receiving neoadjuvant chemotherapy (6 months into treatment without any evidence of metastatic disease). DISCUSSION: The high proportion of positive surgical margins and large tumor size upon presentation suggest that primary tumor downstaging should be considered. The positive results from recent prospective trials on neoadjuvant chemoradiation for pancreatic ductal adenocarcinoma could be a promising foundation of information for the treatment of ASC. CONCLUSION: ASC of the pancreas is an extremely aggressive malignancy with poor prognosis. Further work is needed to determine the optimal multimodal treatment regimen.

Indoor air pollution represents a modifiable risk factor for respiratory morbidity in COPD. The effects of indoor air pollution, as well as the impact of interventions to improve indoor air quality, on cardiovascular morbidity in COPD remain unknown.To determine the association between indoor particulate matter(PM) and heart rate variability(HRV), a measure of cardiac autonomic function tied to cardiovascular morbidity and mortality, as well as the impact of household air purifiers on HRV.Former smokers with moderate-severe COPD were recruited from a six-month randomized controlled trial of a portable air cleaner intervention, to undergo paired assessment of both in-home PM and HRV, using 24-hour Holter monitoring, at up to 5 time points. Primary outcomes were HRV measures tied to cardiovascular morbidity (SDNN and RMSSD).85 participants contributed 317 HRV measurements. A two-fold increase in household PM2.5 was associated with decreases in SDNN (ß -2.98% [95% CI, -5.12 to -0.78]) and RMSSD (ß -4.57% [95% CI, -10.1 to -1.60]). The greatest effects were observed with ultrafine particles(100 nm) (RMSSD; ß -16.4% [95% CI, -22.3 to -10.1]) and among obese participants. Participants randomized to the active air cleaner saw improvements in RMSSD (ß 25.2% [95% CI, 2.99 to 52.1]), but not SDNN (ß 2.65% [95% CI, -10.8 to 18.1]), compared to the placebo group.This is the first US study to describe the association between household PM and cardiac autonomic function among individuals with COPD, and the potential cardiovascular health benefits of household air cleaners.

Summary Background Short-term exposure to fine particulate matter (PM2·5) is associated with increased risk of hospital admissions and mortality, and health risks differ by the chemical composition of PM2·5. Policies to control PM2·5 could change its chemical composition and total mass concentration, leading to change in the subsequent health impact. However, there is little ence on whether associations between PM2·5 and health exhibit temporal variation. We investigated whether risks of hospitalisations from short-term exposure to PM2·5 varied over time in the USA. Methods We did a time-series analysis using a national dataset comprising daily circulatory and respiratory hospitalisation rates of Medicare beneficiaries (age ≥65 years) and PM2·5 in 173 US counties from 1999 to 2016. We fitted modified quasi-Poisson models to estimate temporal trends of associations within a county, and pooled county-level estimates using Bayesian hierarchical modelling to generate an overall estimate. Findings The study included 10 559 654 circulatory and 3 027 281 respiratory hospitalisations. We identified changes in the national average association between previous-day PM2·5 and respiratory hospitalisation over time, with a U-shape that is robust under stratification, linear, and non-linear models. The change in risk of respiratory hospitalisation per 10 μg/m3 increase in previous-day PM2·5 decreased from 0·75% (95% posterior credible interval 0·05 to 1·46) in 1999 to –0·28% (–0·79 to 0·23) in 2008, and then increased to 1·44% (0·00 to 2·91) in 2016. No statistically significant temporal change was observed for associations between same-day PM2·5 and circulatory hospitalisation. Interpretation Hospitalisation risk from PM2·5 changes over time and has increased over the past 7 years in study, especially in northeastern USA. The temporal trend differs by cause of hospitalisation. This study emphasises the necessity of evaluating temporal heterogeneity in health impacts of PM2·5 and suggests caution in applying association estimates to a different time period. Funding US Environmental Protection Agency and Yale Institute for Biospheric Studies.

Rapid advances in computing technology over the past few decades have spurred two extraordinary phenomena in science: large-scale and high-throughput data collection coupled with the creation and implementation of complex statistical algorithms for data analysis. Together, these two phenomena have brought about tremendous advances in scientific discovery but have also raised two serious concerns, one relatively new and one quite familiar. The complexity of modern data analyses raises questions about the reproducibility of the analyses, meaning the ability of independent analysts to re-create the results claimed by the original authors using the original data and analysis techniques. While seemingly a straightforward concept, reproducibility of analyses is typically thwarted by the lack of availability of the data and computer code that were used in the analyses. A much more general concern is the replicability of scientific findings, which concerns the frequency with which scientific claims are confirmed by completely independent investigations. While the concepts of reproduciblity and replicability are related, it is worth noting that they are focused on quite different goals and address different aspects of scientific progress. In this review, we will discuss the origins of reproducible research, characterize the current status of reproduciblity in public health research, and connect reproduciblity to current concerns about replicability of scientific findings. Finally, we describe a path forward for improving both the reproducibility and replicability of public health research in the future.

Clinically relevant postoperative pancreatic fistula (CR-POPF) following pancreaticoduodenectomy (PD) has been associated with soft gland texture and/or small pancreatic duct. We hypothesized that selective use of pancreaticogastrostomy (PG) over pancreaticojejunostomy (PJ) in those scenarios would decrease the rate of CR-POPF.Review of prospective database of all PD's performed at a single institution between 2009 and 2019 was performed. The pancreatic remnant was deemed "high risk" if soft gland and/or small duct were present.PJ was performed in 199 (147 "low-risk" and 52 "high-risk") cases, and 110 patients (all "high-risk") had a PG. Overall CR-POPF rate was 11.9% with no difference between the groups. Risk-stratified analysis within PJ group showed CR-POPF rate of 5.4% versus 36% in "low-risk" versus "high risk" scenarios, respectively; the use of PG significantly decreased CR-POPF rate (9.1%, p 0.0001). Gastrointestinal bleeding was more likely to occur following PG than PJ. Soft gland texture and gastrointestinal bleeding were the strongest predictors of CR-POPF in PJ and PG groups, respectively.Selective use of PG after PD in "high-risk" scenarios mitigates the risk of CR-POPF. Increased rate of gastrointestinal bleeding calls for further refinement of the technique and heightened postoperative vigilance.

Background While injuries experienced during hurricanes and other tropical cyclones have been relatively well- characterized through traditional surveillance, less is known about tropical cyclones' impacts on non-injury morbidity, which can be triggered through pathways that include psychosocial stress or interruption in medical treatment. Methods We investigated daily emergency Medicare hospitalizations (1999-2010) in 180 United States counties, drawing on an existing cohort of high-population counties. We classified counties as exposed to tropical cyclones when storm-associated peak sustained winds were ≥ 21 m/s at the county center; secondary analyses considered other wind thresholds and hazards. We matched storm-exposed days to unexposed days by county and seasonality. We estimated change in tropical cyclone-associated hospitalizations over a storm period from 2 days before to 7 days after the storm's closest approach, compared to unexposed days, using generalized linear mixed-effect models. Results For 1999-2010, 175 study counties had at least one tropical cyclone exposure. Cardiovascular hospitalizations decreased on the storm day, then increased following the storm, while respiratory hospitalizations were elevated throughout the storm period. Over the 10-day storm period, cardiovascular hospitalizations increased 3% (95% confidence interval [CI]: 2%, 5%) and respiratory hospitalizations increased 16% (95% CI: 13%, 20%) compared to matched unexposed periods. Relative risks varied across tropical cyclone exposures, with strongest association for the most restrictive wind-based exposure metric. Conclusions In this study, tropical cyclone exposures were associated with a short-term increase in cardiorespiratory hospitalization risk among the elderly, based on a multi-year/multi-site investigation of US Medicare beneficiaries ≥ 65 years.

Heat exposure of a population is often estimated by applying temperatures from outdoor monitoring stations. However, this can lead to exposure misclassification if residents do not live close to the monitoring station and temperature varies over small spatial scales due to land use/built environment variability, or if residents generally spend more time indoors than outdoors. Here, we compare summertime temperatures measured inside 145 homes in low-income households in Baltimore city with temperatures from the National Weather Service weather station in Baltimore. There is a large variation in indoor temperatures, with daily-mean indoor temperatures varying from 10 °C lower to 10 °C higher than outdoor temperatures. Furthermore, there is only a weak association between the indoor and outdoor temperatures across all houses, indicating that the outdoor temperature is not a good predictor of the indoor temperature for the residences sampled. It is shown that much of the variation is due to differences in the availability of air conditioning (AC). Houses with central AC are generally cooler than outdoors (median difference of − 3.4 °C) while those with no AC are generally warmer (median difference of 1.4 °C). For the collection of houses with central or room AC, there is essentially no relationship between indoor and outdoor temperatures, but for the subset of houses with no AC, there is a weak relationship (correlation coefficient of 0.36). The results presented here suggest future epidemiological studies of indoor exposure to heat would benefit from information on the availability of AC within the population.

Economic growth and convergence issues arise in humanity continually, especially in developing countries. With Rwandan and Peruvian common vital economic variables from 1960 to 2017, we analyze their economic growth, causality, and convergence. The cointegration shows the long-run equilibrium correlation among the explained and explanatory variables, indicating the causality occurrence. The causality direction is defined by the Error Correction Model (ECM) using the Chi-square (χ2) short-run test, long-run T-test, and joint F-test statistics. The estimated values support a generalized Broadwell model equation with linear and quadratic terms. Through ANOVA with the F test, the economic convergence scenario for the two countries is testified. Thus, joint countries' strategies for economic improvement are suggested with the reduction of unnecessary losses.

While associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM2.5 concentrations originally estimated at 1km×1km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10μg/m3 increase in PM2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM2.5-related health burden. This study raises the importance of considering environmental justice issues in PM2.5-related health impacts with respect to how associations may change over time.

Thyroid cancer is one of the malignancy cancers. CircRNA, a non-coding RNA, plays an important role in the development of cancer. The relationship and roles of circ_0124055, miR-486-3p and MTA1 in thyroid cancer have not been reported.Real-time quantitative polymerase chain reaction (RT-qPCR) was performed to analyze the RNA levels of circ_0124055, miR-486-3p and MTA1. Western blot was conducted to analyze the protein levels of MTA1, Epithelial cadherin (E-cadherin) and Neuro cadherin (N-cadherin). Subcellular localization assay was used to analyze circ_0124055 location in thyroid cancer cells. Colony formation assay and 5-Ethynyl-2'-deoxyuridine (EdU) assay were carried out to analyze cell proliferation. Cell migration and invasion were analyzed by wound-healing assay and transwell assay. Flow cytometry assay was performed to investigate cell apoptosis. Dual-luciferase reporter assay and RIP assay were employed to analyze the interactions among circ_0124055, miR-486-3p and MTA1. Immunohistochemical (IHC) assay was performed to assess the expression of Ki67, MTA1 and E-cadherin in tumor tissues. Thyroid cancer tumor growth in vivo was evaluated by tumor xenograft mouse model assay.The expression of circ_0124055 was up-regulated in tumor tissues and cells. Knockdown of circ_0124055 could inhibit thyroid cancer cell proliferation, migration and invasion and promote cell apoptosis, accompanied by the dysregulation of E-cadherin and N-cadherin expression. Circ_0124055 could target miR-486-3p, and miR-486-3p could target MTA1. MiR-486-3p inhibitor could restore the effect of circ_0124055 knockdown in the progression of thyroid cancer. Moreover, MTA1 overexpression weakened the inhibitory effects of miR-486-3p mimics on the progression of thyroid cancer. Further, circ_0124055 could influence tumor growth in vivo.Circ_0124055 promoted the progression of thyroid cancer cells through the miR-486-3p /MTA1 axis.

ImportanceStructural racism has been implicated in the disproportionally high asthma morbidity experienced by children living in disadvantaged, urban neighborhoods. Current approaches designed to reduce asthma triggers have modest impact.ObjectiveTo examine whether participation in a housing mobility program that provided housing vouchers and assistance moving to low-poverty neighborhoods was associated with reduced asthma morbidity among children and to explore potential mediating factors.Design, Setting, and ParticipantsCohort study of 123 children aged 5 to 17 years with persistent asthma whose families participated in the Baltimore Regional Housing Partnership housing mobility program from 2016 to 2020. Children were matched to 115 children enrolled in the Urban Environment and Childhood Asthma (URECA) birth cohort using propensity scores.ExposureMoving to a low-poverty neighborhood.Main OutcomesCaregiver-reported asthma exacerbations and symptoms.ResultsAmong 123 children enrolled in the program, median age was 8.4 years, 58 (47.2%) were female, and 120 (97.6%) were Black. Prior to moving, 89 of 110 children (81%) lived in a high-poverty census tract (>20% of families below the poverty line); after moving, only 1 of 106 children with after-move data (0.9%) lived in a high-poverty tract. Among this cohort, 15.1% (SD, 35.8) had at least 1 exacerbation per 3-month period prior to moving vs 8.5% (SD, 28.0) after moving, an adjusted difference of −6.8 percentage points (95% CI, −11.9% to −1.7%; P = .009). Maximum symptom days in the past 2 weeks were 5.1 (SD, 5.0) before moving and 2.7 (SD, 3.8) after moving, an adjusted difference of −2.37 days (95% CI, −3.14 to −1.59; P Conclusions and RelevanceChildren with asthma whose families participated in a program that helped them move into low-poverty neighborhoods experienced significant improvements in asthma symptom days and exacerbations. This study adds to the limited evidence suggesting that programs to counter housing discrimination can reduce childhood asthma morbidity.

Although tunable Fabry-Perot (F-P) filters are widely acknowledged as fiber Bragg grating (FBG) demodulators, F-P filters exhibit drift error when subjected to ambient temperature and piezo-electrical transducer (PZT) hysteresis. To address the drift issue, the majority of the existing literature makes use of additional devices like the F-P etalon and gas chamber. In this study, a novel drift calibration method based on two-stage decomposition and hybrid modeling is proposed. The initial drift error sequences are broken down into three frequency components using the variational mode decomposition (VMD), and the medium-frequency components are further broken down using the secondary VMD. The initial drift error sequences are significantly simplified by the two-stage VMD. On this foundation, the long short-term memory (LSTM) network and polynomial fitting (PF) are used to forecast the low-frequency and high-frequency drift errors, respectively. The LSTM enables the prediction of intricate nonlinear local behaviors, while the PF method predicts the overall trend. The benefits of LSTM and PF can be effectively utilized in this manner. Compared to the single-stage decomposition, two-stage decomposition achieves superior results. The suggested method is an affordable and effective alternative to the current drift calibration techniques.