bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isolated diastolic hypertension as defined by the 2017 American College of Cardiology/American Heart Association blood pressure guideline and incident cardiovascular events in Chinese
Authors: Wu Shouling , Ji Chunpeng , Shi Jihong , Chen Shuohua , Huang Zhe , Jonas Jost B. 
Published: October 2020

Objective:
The new arterial hypertension guidelines by the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) changed the definition of isolated diastolic hypertension (IDH). We assessed and compared in a Chinese population the IDH prevalence, newly defined by the 2017 ACC/AHA guidelines versus the former definition by the Joint National Committee 7 (JNC7) criteria, and examined longitudinal associations of IDH with cardiovascular disease (CVD) outcomes.

Methods:
The prospective community-based Kailuan Study included participants aged 18–98 years who underwent a detailed medical examination at baseline in 2006/2007 and who were biennially re-examined till 2017. History of antihypertensive medication at baseline was an exclusion criterion.

Results:
The study population consisted of 87 346 individuals (mean age: 50.9 years; range: 18–98 years). Prevalence of IDH was 7.79% [95% confidence interval (CI): 7.62, 7.97] by JNC7 guidelines and 24.72% (95% CI: 24.43, 25.01) by 2017 ACC/AHA criteria [difference: 19.93% (95% CI: 16.81, 17.04)]. Applying the 2017 ACC/AHA guidelines, the prevalence of IDH-recommended antihypertensive therapy was 7.73% (95% CI: 7.55, 7.90). In multivariable analysis, IDH by JNC7 criteria was significantly associated with incident myocardial infarction [n = 93 events; hazard ratio: 1.30 (95 CI: 1.02, 1.66)], cerebral hemorrhage [n = 73 events; hazard ratio: 1.79 (95% CI: 1.35, 2.38)], and total CVD [n = 373 events; hazard ratio: 1.15 (95% CI: 1.02, 1.30)], when compared with normotension. IDH based on 2017 ACC/AHA guidelines was associated with incident cerebral hemorrhage [n = 129 events; hazard ratio: 1.47 (95% CI: 1.12, 1.94)] and total CVD [n = 828 events; hazard ratio: 1.13 (95% CI: 1.02, 1.26)].

Conclusion:
In this adult Chinese community, 2017 ACC/AHA-defined IDH was associated with the incidence of cerebral hemorrhage and total CVD, and as compared with JNC7-defined IDH, it was more prevalent.
DETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES
Authors: Wu Qiaowei , Zhang Bin , Hu Yijun , Liu Baoyi , Cao Dan , Yang Dawei , Peng Qingsheng , Zhong Pingting , Zeng Xiaomin , Xiao Yu , Li Cong , Fang Ying , Feng Songfu , Huang Manqing , Cai Hongmin , Yang Xiaohong , Yu Honghua 
Published: October 2020

Purpose:
To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images.

Methods:
In the training set, 12,365 OCT images were extracted from a public data set and an ophthalmic center. A total of 656 OCT images were extracted from another ophthalmic center for external validation. The presence or absence of three OCT patterns of DME, including diffused retinal thickening, cystoid macular edema, and serous retinal detachment, was labeled with 1 or 0, respectively. A DL model was trained to detect three OCT patterns of DME. The occlusion test was applied for the visualization of the DL model.

Results:
Applying 5-fold cross-validation method in internal validation, the area under the receiver operating characteristic curve for the detection of three OCT patterns (i.e., diffused retinal thickening, cystoid macular edema, and serous retinal detachment) was 0.971, 0.974, and 0.994, respectively, with an accuracy of 93.0%, 95.1%, and 98.8%, respectively, a sensitivity of 93.5%, 94.5%, and 96.7%, respectively, and a specificity of 92.3%, 95.6%, and 99.3%, respectively. In external validation, the area under the receiver operating characteristic curve was 0.970, 0.997, and 0.997, respectively, with an accuracy of 90.2%, 95.4%, and 95.9%, respectively, a sensitivity of 80.1%, 93.4%, and 94.9%, respectively, and a specificity of 97.6%, 97.2%, and 96.5%, respectively. The occlusion test showed that the DL model could successfully identify the pathologic regions most critical for detection.

Conclusion:
Our DL model demonstrated high accuracy and transparency in the detection of OCT patterns of DME. These results emphasized the potential of artificial intelligence in assisting clinical decision-making processes in patients with DME.
Psychometric Testing of an Indonesian-Version Diabetes Self-Management Instrument
Authors: RAHAYU Henik Tri , CHEN Ching-Min 
Published: October 2020

ABSTRACT

Background
Self-management is one of the vital elements in diabetes management for adults with Type 2 diabetes mellitus (T2DM). Although the number of people with T2DM in Indonesia has risen, clinical understanding of the problems related to practicing diabetes self-management (DSM) is limited because of the lack of a valid measurement instrument. The 35-item Diabetes Self-Management Instrument (DSMI-35) is one instrument widely used in research to assess DSM-related behavior among patients with diabetes.

Purpose
This study was designed to translate the psychometric properties of the Indonesian version of the DSMI-35 and evaluate the efficacy of this instrument in a sample of Indonesian adults with T2DM.

Methods
Forward and backward translation processes were used to translate the DSMI-35 into Indonesian (IDN-DSMI). Then, the translation equivalence, content validity, face validity, construct validity, and internal consistency were assessed using a sample of 222 Indonesian adults with T2DM from eight public health centers. Confirmatory factor analysis was used to test the data.

Results
The confirmatory factor analysis confirmed that the 35 items all had acceptable goodness of fit. Although the analysis supported removing several of the items, removal of these items was not theoretically justified. The average variance extracted was acceptable, and composite reliability was satisfied. The Cronbach's alpha was .96 for the IDN-DSMI and .84–.93 for the subscales. The significant interitem correlations between some items were consistent with the findings of other previous studies.

Conclusions/Implications for Practice
The IDN-DSMI is a valid and reliable instrument that may be used to measure DSM behavior in Indonesian patients with T2DM in primary healthcare settings.
Parkinson Disease and Occupational and Environmental Exposure to Pesticides in a Region of Intense Agribusiness Activity in Brazil
Authors: Silvestre Grasiela Cristina Silva Botelho , Ferreira Marcelo José Monteiro , Figueiredo Sue Ellen Ferreira Modesto Rey de , Silva Cristhiane Almeida Leite da , Siqueira Heloise Helena , Silva Ageo Mário Cândido da 
Published: October 2020

Objective:
To evaluate the relationship between occupational and environmental exposure to pesticides and Parkinson disease in a region of intense agribusiness activity in the state of Mato Grosso/Brazil.

Methods:
Case–control study carried out in a referral hospital for chronic neurodegenerative diseases. Non-conditional logistic regression analyses were performed.

Results:
Having performed direct management of pesticides in the workplace (odds ratio [OR]: 3.43; 95% confidence interval [CI]: 1.55 to 7.28), having a family history of Parkinson (OR: 3.42; 95% CI: 1.61 to 7.28) and being men (OR: 3.01; 95% CI: 1.66 to 5.45) were all factors that contributed to a greater chance for the development of the disease.

Conclusion:
Our study reinforces the associations between occupational and environmental exposure to pesticides and the occurrence of Parkinson disease in regions of intense agribusiness activity in Brazil.
Environmental toxicant exposure and menstrual cycle length
Authors: Hammer Karissa C. , Veiga Alexis , Mahalingaiah Shruthi 
Published: October 2020

Purpose of review
This review seeks to evaluate the impact of environmental exposures on the menstrual cycle length detailing timing of exposure on pathophysiology.

Recent findings
Recent literature has examined the relationship between menstrual cycle length and environmental exposures including air pollutants, parabens, and polybrominated biphenyls.

Summary
Research is limited but suggest importance of further research in evaluating environmental exposures and menstrual cycle length.
Predicting 2-Day Mortality of Thrombocytopenic Patients Based on Clinical Laboratory Data Using Machine Learning
Authors: Lien Frank , Wang Hsin-Yao , Lu Jang-Jih , Wen Ying-Hao , Chiueh Tzong-Shi 
Published: October 2020

Background:
Clinical laboratories have traditionally used a single critical value for thrombocytopenic events. This system, however, could lead to inaccuracies and inefficiencies, causing alarm fatigue and compromised patient safety.

Objectives:
This study shows how machine learning (ML) models can provide auxiliary information for more accurate identification of critical thrombocytopenic patients when compared with the traditional notification system.

Research Design:
A total of 50,505 patients’ platelet count and other 26 additional laboratory datasets of each thrombocytopenic event were used to build prediction models. Conventional logistic regression and ML methods, including random forest (RF), artificial neural network, stochastic gradient descent (SGD), naive Bayes, support vector machine, and decision tree, were applied to build different models and evaluated.

Results:
Models using logistic regression [area under the curve (AUC)=0.842], RF (AUC=0.859), artificial neural network (AUC=0.867), or SGD (AUC=0.826) achieved the desired average AUC>0.80. The highest positive predictive value was obtained by the SGD model in the testing data (72.2%), whereas overall, the RF model showed higher sensitivity and total positive predictions in both the training and testing data and outperformed other models. The positive 2-day mortality predictive rate of RF methods is as high as 46.1%—significantly higher than using the traditional notification system at only 14.8% [χ2
(1)=81.66, P<0.001].

Conclusions:
This study demonstrates a data-driven ML approach showing a significantly more accurate 2-day mortality prediction after a critical thrombocytopenic event, which can reinforce the accuracy of the traditional notification system.
Novel approaches to management of hyperkalaemia in kidney transplantation
Authors: Rizk John , Quan David , Gabardi Steven , Rizk Youssef , Kalantar-Zadeh Kamyar 
Published: October 2020

Purpose of review
Medications used frequently after kidney transplantation, including calcineurin inhibitors, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta blockers and antimicrobials, are considered the leading culprit for posttransplant hyperkalaemia in recipients with a well functioning allograft. Other risk factors include comorbidities such as diabetes, hypertension and heart failure; and consumption of a potassium-enriched diet. We review the mechanisms for hyperkalaemia following kidney transplantation that are addressed using nonpharmacological and pharmacological interventions. We also discuss emerging therapeutic approaches for the management of recurrent hyperkalaemia in solid organ transplantation, including newer potassium binding therapies.

Recent findings
Patiromer and sodium zirconium cyclosilicate are emerging potassium binders approved for the treatment of hyperkalaemia. Patiromer is a polymer that exchanges potassium for calcium ions. In contrast, sodium zirconium cyclosilicate is a nonpolymer compound that exchanges potassium for sodium and hydrogen ions. Both agents are efficacious in the treatment of chronic or recurrent hyperkalaemia and may result in fewer gastrointestinal side effects than older potassium binders such as sodium polystyrene sulfonate and calcium polystyrene sulfonate. Large-scale clinical studies have not been performed in kidney transplant patients. Patiromer may increase serum concentrations of tacrolimus, but not cyclosporine. Sodium zirconium cyclosilicate does not appear to compromise tacrolimus pharmacokinetics, although it may have a higher sodium burden.

Summary
Patiromer and sodium zirconium cyclosilicate may be well tolerated options to treat asymptomatic hyperkalaemia and have the potential to ease potassium dietary restrictions in kidney transplant patients by maintaining a plant-dominant, heart-healthy diet. Their efficacy, better tolerability and comparable cost with respect to previously available potassium binders make them an attractive therapeutic option in chronic hyperkalaemia following kidney transplantation.
Feasibility of Family-Assisted Severity of Illness Monitoring for Hospitalized Children in Low-Income Settings
Authors: von Saint Andre-von Arnim Amelie O. , Kumar Rashmi K. , Oron Assaf P. , Nguyen Quynh-Uyen P. , Mutonga Daniel M. , Zimmerman Jerry , Walson Judd L. 
Published: October 2020

Objectives:
To determine the feasibility of having caregivers assist in recognition of clinical deterioration in children hospitalized with febrile illness in a resource-limited setting.

Design:
Single-center, prospective, interventional pilot study.

Setting:
General pediatric wards at Kenyatta National Hospital, Nairobi, Kenya’s largest public tertiary-care hospital.

Patients:
Children hospitalized with acute febrile illness, accompanied by caregivers available at the bedside for 24 hours soon after hospital admission.

Interventions:
Caregivers were trained to recognize signs of critical illness using the Family-Assisted Severe Febrile Illness Therapy tool, which quantifies patients’ work of breathing, mental status, and perfusion, producing color-coded flags to signal illness severity. Caregivers’ Family-Assisted Severe Febrile Illness Therapy assessments were compared with healthcare professional assessments and to established Pediatric Early Warning Scores (PEWS). An initial study stage was followed by refinement of training and a larger second stage with intervention/control arms.

Measurements and Main Results:
A total of 107 patient/caregiver pairs were enrolled in the interventional arm; 106 caregivers underwent Family-Assisted Severe Febrile Illness Therapy training and were included in the analysis. Patient characteristics included median age 1.1 years (0.2–10 yr), 55 (52%) female, and diagnoses: pneumonia (64 [60%]), meningitis (38 [36%]), gastroenteritis (24 [23%]), and malaria (21 [20%]). Most caregivers had primary (34 [32%]) or secondary (53 [50%]) school education. Fourteen of 106 patients (13%) died during their stay, six within 2 days. Across all severity levels, caregiver Family-Assisted Severe Febrile Illness Therapy assessments matched professionals in 87% and 94% for stages 1 and 2, respectively. Caregiver Family-Assisted Severe Febrile Illness Therapy assessments had a moderate to strong correlation with coinciding Pediatric Early Warning Scores and were sensitive to life-threatening deterioration: for all six patients who died within 2 days of admission, caregiver assessment reached the highest alert level.

Conclusions:
Caregiver involvement in recognition of critical illness in hospitalized children in low-resource settings may be feasible. This may facilitate earlier detection of clinical deterioration where staffing is severely limited by constrained resources. Further validation of the Family-Assisted Severe Febrile Illness Therapy tool is warranted, followed by its application in a larger multisite patient population to assess provider response and associated clinical outcomes.
Connectivity analysis of single cell RNA-sequencing derived transcriptional signature of lymphangioleiomyomatosis
Authors: Al Mahi Naim , Zhang Erik Y. , Sherman Susan , Yu Jane J. , Medvedovic Mario 
Published: October 2020

ABSTRACTLymphangioleiomyomatosis (LAM) is a rare pulmonary disease affecting women of childbearing age that is characterized by the aberrant proliferation of smooth-muscle (SM)-like cells and emphysema-like lung remodeling. In LAM, mutations in TSC1 or TSC2 genes results in the activation of the mechanistic target of rapamycin complex 1 (mTORC1) and thus sirolimus, an mTORC1 inhibitor, has been approved by FDA to treat LAM patients. Sirolimus stabilizes lung function and improves symptoms. However, the disease recurs with discontinuation of the drug, potentially because of the sirolimus-induced refractoriness of the LAM cells. Therefore, there is a critical need to identify remission inducing cytocidal treatments for LAM. Recently released Library of Integrated Network-based Cellular Signatures (LINCS) L1000 transcriptional signatures of chemical perturbations has opened new avenues to study cellular responses to existing drugs and new bioactive compounds. Connecting transcriptional signature of a disease to these chemical perturbation signatures to identify bioactive chemicals that can “revert” the disease signatures can lead to novel drug discovery. We developed methods for constructing disease transcriptional signatures and performing connectivity analysis using single cell RNA-seq data. The methods were applied in the analysis of scRNA-seq data of naïve and sirolimus-treated LAM cells. The single cell connectivity analyses implicated mTORC1 inhibitors as capable of reverting the LAM transcriptional signatures while the corresponding standard bulk analysis did not. This indicates the importance of using single cell analysis in constructing disease signatures. The analysis also implicated other classes of drugs, CDK, MEK/MAPK and EGFR/JAK inhibitors, as potential therapeutic agents for LAM.
Economic precarity, social isolation, and suicidal ideation during the COVID-19 pandemic
Authors: Raifman Julia , Ettman Catherine K. , Dean Lorraine , Barry Colleen , Galea Sandro 
Published: October 2020

AbstractImportanceThe US population faces stressors associated with suicide brought on by the COVID-19 pandemic. Understanding the relationship between stressors and suicidal ideation may inform policies and programs to prevent suicide.ObjectiveTo evaluate the relationship between stressors and suicidal ideation during the COVID-19 pandemic.DesignWe compared suicidal ideation in 2017-2018 to suicidal ideation in 2020. We estimated the association between stressors and suicidal ideation in bivariable and multivariable Poisson regression models with robust variance.SettingUnited StatesParticipantsParticipants were from two, nationally representative surveys of US adults: The 2017-2017 National Health and Nutrition Examination Survey and the 2020 COVID-19 and Life Stressors Impact on Mental Health and Well-being study (conducted March 31 to April 13), analyzed April 28 to September 30, 2020.ExposuresEconomic precarity as measured through job loss or difficulty paying rent and social isolation based on reporting “feeling alone.”Main outcome measureSuicidal ideation based on reporting “Thoughts that you would be better off dead or of hurting yourself in some way” over the past two weeks.ResultsSuicidal ideation increased more than fourfold, from 3.4% in the 2017-2018 NHANES to 16.3% in the 2020 CLIMB survey, and from 5.8% to 26.4% among participants in low-income households. Suicidal ideation was more prevalent among people facing difficulty paying rent (31.5%), job loss (24.1%), and loneliness (25.1%), with each stressor associated with suicidal ideation in bivariable models. In the multivariable model, difficulty paying rent was associated with suicidal ideation (aPR: 1.5, 95% CI: 1.2 to 2.1), while losing a job was not (aPR: 0.9, 95% CI: 0.6 to 1.2). Feeling alone was associated with suicidal ideation (aPR: 1.9, 95% CI: 1.5 to 2.4).Conclusions and relevanceSuicidal ideation increased more than fourfold during the COVID-19 pandemic. Difficulty paying rent and loneliness were most associated with suicidal ideation. Policies and programs to support people experiencing economic precarity and loneliness may contribute to suicide prevention.
Developing a Discrete Choice Experiment to Understand Patient Preferences in Resource-Limited Settings: a Six-Step Guide
Authors: Moor Sarah , Tusubira Andrew K. , Akiteng Ann R , Hsieh Evelyn , Ngaruiya Christine , Rabin Tracy L. , Hawley Nicola L. , Armstrong-Hough Mari , Nugent Rachel , Kalyesubula Robert , Nalwadda Christine , Ssinabulya Isaac , Schwartz Jeremy I. 
Published: October 2020

AbstractA discrete choice experiment (DCE) is a method to quantify preferences for goods and services in a population. Participants are asked to choose between sets of 2 hypothetical scenarios that differ in terms of particular characteristics. Their selections reveal the relative importance of each “attribute”, or characteristic, and the extent to which people consider trade-offs between characteristics. DCEs are increasingly used in healthcare and public health settings as they can inform the design of health-related interventions to achieve maximum impact. Specific efforts must be made in the development process to ensure relevance of DCEs to the communities in which they are administered. Herein, we build upon gaps in the prior literature by offering researchers a step-by-step process to guide DCE development for resource-limited settings, including detailed methodological considerations for each step and a specific actionable approach that we hope will simplify the process for other researchers. We present the 6 steps we followed to develop a DCE to evaluate patient preferences for management of hypertension and diabetes in rural Uganda. These steps are: 1) formative work; 2) attribute selection; 3) attribute level selection; 4) DCE design selection; 5) determination of attribute level combinations; and 6) assessment and enhancement of tool comprehensibility. We describe each of these steps in detail to ease the development process for researchers looking to develop locally contextualized, end-user-centric health interventions.
Antibody reactivity against SARS-CoV-2 in adults from the Vancouver metropolitan area, Canada
Authors: Majdoubi Abdelilah , O’Connell Sarah E. , Michalski Christina , Dada Sarah , Narpala Sandeep , Gelinas Jean , Mehta Disha , Cheung Claire , Basappa Manjula , Görges Matthias , Barakauskas Vilte E , Goldfarb David M. , Douek Daniel C. , McDermott Adrian B. , Lavoie Pascal M. 
Published: October 2020

AbstractBackgroundQuantifying antibody reactivity against multiple SARS-CoV-2 antigens at the population level may help understand individual differences in COVID-19 severity. Pre-existing low antibody cross-reactivity may be particularly prevalent among childcare providers, including pediatric health care workers (HCW) who may be more exposed to circulating coronaviruses.MethodsCross-sectional study that included adults in the Vancouver area in British Columbia (BC), Canada, between May 17 and June 19, 2020. SARS-CoV-2 seroprevalence was ascertained by measuring total SARS-CoV-2 IgG/M/A antibodies against a recombinant spike (S1) protein and adjusted for bias due to false-positive and false-negative test results. A novel, high sensitivity multiplex assay was also used to profile IgG against four SARS-CoV-2 antigens, SARS-CoV and four circulating coronaviruses.FindingsAmong 276 participants (71% HCW), three showed evidence of direct viral exposure, yielding an adjusted seroprevalence of 0.60% [95%CI 0% – 2.71%], with no difference between HCW and non-HCW, or between paediatric and adult HCW. Among the 273 unexposed individuals, 7.3% [95%CI 4.5% – 11.1%], 48.7 [95%CI 42.7% – 54.8%] and 82.4% [95%CI 77.4% – 86.7%] showed antibody reactivity against SARS-CoV-2 RBD, N or Spike proteins, respectively. SARS-CoV-2 reactivity did not significantly correlate with age, sex, did not significantly differ between HCW and non-HCW (prevalence 1.0% vs 1.0%; P=1.00) and between pediatric and adult HCW (0.7% vs 1.6%; P=0.54), and modestly correlated with reactivity to circulating coronaviruses (Spearman rho range: 0.130 to 0.224 for 7 significant (FDR 5%), out of 16 correlations, from 36 correlations tested).InterpretationA substantial proportion of individuals showed low, but detectable antibody reactivity against SARS-CoV-2 antigens in this population despite low evidence of direct SARS-CoV-2 exposure.FundingNIAID/NIH