bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of health-related quality of life in musculoskeletal disease patients: a longitudinal analysis
Authors: Madrid-García Alfredo , León-Mateos Leticia , Pato Esperanza , Jover Juan A , Fernández-Gutiérrez Benjamín , Abasolo Lydia , Menasalvas Ernestina , Rodríguez-Rodríguez Luis 
Published: July 2021

Introduction: Rheumatic and musculoskeletal diseases (RMDs) have a significant impact on patients’ health-related quality of life (HRQoL) exacerbating disability, reducing independence and work capacity, among others. Predictors’ identification affecting HRQoL could help to place efforts that minimize the deleterious impact of these conditions on patients’ wellbeing. This study evaluates the influence of demographic and clinical predictors on the HRQoL of a cohort of RMD patients, measured using the Rosser classification index (RCI). Methods: We included patients attending the Hospital Clínico San Carlos (HCSC) rheumatology outpatient clinic from 1 April 2007 to 30 November 2017. The primary outcome was the HRQoL assessed in each of the patient’s visits using the RCI. Demographic and clinical variables extracted from a departmental electronic health record (EHR) were used as predictors: RMD diagnoses, treatments, comorbidities, and averaged HRQoL values from previous periods (for this last variable, values were imputed if no information was available). Association between predictors and HRQoL was analyzed using penalized generalized estimating equations (PGEEs). To account for imputation bias, the PGEE model was repeated excluding averaged HRQoL predictors, and common predictors were considered. Discussion: A total of 18,187 outpatients with 95,960 visits were included. From 410 initial predictors, 19 were independently associated with patients’ HRQoL in both PGEE models. Chronic kidney disease (CKD), an episode of prescription of third level analgesics, monoarthritis, and fibromyalgia diagnoses were associated with worse HRQoL. Conversely, the prescription in the previous visit of acid-lowering medication, colchicine, and third level analgesics was associated with better HRQoL. Conclusion: We have identified several diagnoses, treatments, and comorbidities independently associated with HRQoL in a cohort of outpatients attending a rheumatology clinic.
Isolated Penile Calciphylaxis Diagnosed by Ultrasound Imaging in a New Dialysis Patient: A Case Report
Authors: Helmeczi Wryan , Pitre Tyler , Hudson Emma , Mondhe Suhas , Burns Kevin 
Published: July 2021

Rationale: The recognition of calciphylaxis often eludes practitioners because of its multiple ambiguous presentations. It classically targets areas of the body dense with adipose tissue. A heightened suspicion for the disorder is therefore required in the case of penile calciphylaxis, given its unconventional location. The diagnosis of calciphylaxis is also challenging as the gold standard for diagnosis is biopsy which can often yield equivocal results. Unfortunately, in penile calciphylaxis, the utility of biopsies is further debated due to their potential to precipitate new lesions and their decreased sensitivity due to the limited depth of tissue that can be sampled. For these reasons, it is important that practitioners recognize other accessible and accurate investigative tools which can aid in their diagnosis. Presenting concerns of the patient: We present the case of a 49-year-old man who presented to the emergency room with penile pain in the context of known chronic kidney disease secondary to diabetic nephropathy. The pain had been present for about a week, was exquisitely tender, and was initially associated with a faint violaceous lesion. This gentleman had just recently initiated peritoneal dialysis and had no other lesions on his body. Diagnosis: His pain was determined by ultrasound and plain radiograph to be secondary to calciphylaxis after two biopsies were nondiagnostic. Interventions: The patient had already made changes to his diet to reduce phosphate and calcium intake, and had been on phosphate-lowering therapy with both calcium and phosphate being within their respective target range. Following his diagnosis, this patient was promptly converted from peritoneal dialysis to hemodialysis with sodium thiosulphate and initiated hyperbaric oxygen therapy. This patient continues to be followed by nephrology and urology specialists.
A phase 2 study of nilotinib in pediatric patients with CML: long-term update on growth retardation and safety
Authors: Hijiya Nobuko , Maschan Alexey , Rizzari Carmelo , Shimada Hiroyuki , Dufour Carlo , Goto Hiroaki , Kang Hyoung Jin , Guinipero Terri , Karakas Zeynep , Bautista Francisco , Ducassou Stéphane , Yoo Keon Hee , Zwaan Christian Michel , Millot Frédéric , Patterson Briana , Samis Jill , Aimone Paola , Allepuz Alex , Titorenko Ksenia , Sosothikul Darintr 
Published: July 2021

Abstract
The phase 2, open-label study (DIALOG) of nilotinib in pediatric patients with Philadelphia chromosome-positive chronic myelogenous leukemia (CML) met its coprimary end points, showing sustained nilotinib efficacy in patients with newly diagnosed (ND) or imatinib/dasatinib resistant/intolerant (R/I) CML. This update assessed growth and safety profiles in patients who had completed ≥48, 28-day treatment cycles of nilotinib 230 mg/m2 twice daily, or previously discontinued the study. Height was assessed regularly and reported using standard deviation scores (SDSs) based on World Health Organization growth charts. All data were summarized descriptively (cutoff, 6 March 2019). Overall, 33 patients in the R/I cohort and 25 patients in the ND cohort received nilotinib. Each cohort showed a negative slope in height SDS over the course of the study, indicating attenuated growth rates during nilotinib treatment: overall median change from baseline in height SDS after 48 cycles was −0.54 SDS (range, − 1.6 to 0.4) and −0.91 SDS (−1.4 to −0.1) in R/I and ND cohorts, respectively. Patients in the R/I cohort were shorter at baseline than those in the ND cohort, and remained so throughout the study. The most common all-cause adverse events were increased blood bilirubin (53.4%), headache (46.6%), pyrexia (37.9%), and increased alanine transferase (36.2%). Apart from the impact on growth, the safety profile of nilotinib was generally consistent with previous reports. This study was registered on www.clinicaltrials.gov at #NCT01844765.
Associations between elevated kidney and liver biomarker ratios, metabolic syndrome and all-cause and coronary heart disease (CHD) mortality: analysis of the U.S. National Health and Nutrition Examination Survey (NHANES)
Authors: Oye-Somefun Akinkunle , Kuk Jennifer L. , Ardern Chris I. 
Published: July 2021

Abstract
Background
We examined the relationship between ratios of select biomarkers of kidney and liver function on all-cause and coronary heart disease (CHD) mortality, both in isolation, and in combination with metabolic syndrome (MetS), among adults (20 + years, n = 10,604).

Methods
Data was derived from the U.S. National Health and Nutrition Examination Survey (1999–2016) including public-use linked mortality follow-up files through December 31, 2015.

Results
Select biomarker ratios of kidney (UACR or albuminuria and BUN-CR) and liver (AST-ALT and GGT-ALP) function in isolation and in combination with MetS were associated with all-cause and CHD mortality. Compared to individuals with neither elevated biomarker ratios nor MetS (HR = 1.00, referent), increased risk of all-cause mortality was observed in the following groups: MetS with elevated UACR (HR, 95% CI = 2.57, 1.99–3.33), MetS with elevated AST-ALT (HR = 2.22, 1.61–3.07), elevated UACR without MetS (HR = 2.12, 1.65–2.72), and elevated AST-ALT without MetS (HR = 1.71, 1.35–2.18); no other biomarker ratios were associated with all-cause mortality. For cause-specific deaths, elevated risk of CHD mortality was associated with MetS with elevated UACR (HR = 1.67, 1.05–2.67), MetS with elevated AST-ALT (HR = 2.80, 1.62–4.86), and elevated BUN-CR without MetS (HR = 2.12, 1.12–4.04); no other biomarker ratios were associated with CHD mortality.

Conclusion
Future longitudinal studies are necessary to examine the utility of these biomarker ratios in risk stratification for chronic disease management.
Physicians’ decreased tendency to choose palliative care for patients with advanced dementia between 1999 and 2015
Authors: Haapasalmi Saila , Piili Reetta P. , Metsänoja Riina , Kellokumpu-Lehtinen Pirkko-Liisa I. , Lehto Juho T. 
Published: July 2021

AbstractBackgroundPhysicians’ decision-making for seriously ill patients with advanced dementia is of high importance, especially as the prevalence of dementia is rising rapidly, and includes many challenging ethical, medical and juridical aspects. We assessed the change in this decision-making over 16 years (from 1999 to 2015) and several background factors influencing physicians’ decision.MethodsA postal survey including a hypothetical patient-scenario representing a patient with an advanced dementia and a life-threatening gastrointestinal bleeding was sent to 1182 and 1258 Finnish physicians in 1999 and 2015, respectively. The target groups were general practitioners (GPs), surgeons, internists and oncologists. The respondents were asked to choose between several life-prolonging and palliative care approaches. The influence of physicians’ background factors and attitudes on their decision were assessed.ResultsThe response rate was 56%. A palliative care approach was chosen by 57 and 50% of the physicians in 1999 and 2015, respectively (p = 0.01). This change was statistically significant among GPs (50 vs 40%,p = 0.018) and oncologists (77 vs 56%,p = 0.011). GPs chose a palliative care approach less often than other responders in both years (50 vs. 63% in 1999 and 40 vs. 56% in 2015,p < 0.001). In logistic regression analysis, responding in 2015 and being a GP remained explanatory factors for a lower tendency to choose palliative care. The impact of family’s benefit on the decision-making decreased, whereas the influence of the patient’s benefit and ethical values as well as the patient’s or physician’s legal protection increased from 1999 to 2015.ConclusionsPhysicians chose a palliative care approach for a patient with advanced dementia and life-threatening bleeding less often in 2015 than in 1999. Specialty, attitudes and other background factors influenced significantly physician decision-making. Education on the identification and palliative care of the patients with late-stage dementia are needed to make these decisions more consistent.
Distance education perception scale for medical students: a validity and reliability study
Authors: Özkaya Güven , Aydin Mevlüt Okan , Alper Züleyha 
Published: July 2021

AbstractBackgroundThere are major changes in education strategies as higher education institutions urgently need to adopt distance education tools and practices due to the Covid-19 pandemic. Medical education is also trying to get out of this emergency using distance education. In this study, we aimed to develop a reliable and valid scale in order to evaluate the perceptions of medical students towards distance education.MethodsThe students taking part in the study were in the first five academic years of the medical faculty in Bursa in Turkey. At first, 57 items were determined to evaluate students’ perceptions. Content validity was examined according to the assessment of the expert team. Construct validity of these items was examined by exploratory and confirmatory factor analysis. Also, Cronbach’s alpha coefficients were calculated for reliability analysis. The medical students’ responses were scored using a five-point Likert scale.ResultsWhen the content validity was examined, the number of items was determined to be 38 items. Construct validity of these items was examined by exploratory and confirmatory factor analysis. Because of the exploratory factor analysis performed on the responses of 429 medical students, 22 items were included in four factors. This four-factor model was applied to 286 medical students and validated by confirmatory factor analysis. Also, Cronbach’s alpha coefficients were calculated for reliability analysis and values were between 0.713 and 0.930.ConclusionsThis study demonstrated validation and reliability of perceptions of distance education for medical students. We suggest a 22-item model with a four-factorial scale.
Health economic evidence in clinical guidelines in South Africa: a mixed-methods study
Authors: Wilkinson Maryke , Hofman Karen J. , Young Taryn , Schmidt Bey-Marrié , Kredo Tamara 
Published: July 2021

Abstract
Background
Evidence-informed clinical practice guidelines (CPGs) are useful tools to inform transparent healthcare decision-making. Consideration of health economic evidence (HEE) during CPG development in a structured manner remains a challenge globally and locally. This study explored the views, current practice, training needs and challenges faced by CPG developers in the production and use of HEE for CPGs in South Africa.

Methods
This mixed-methods study comprised an online survey and a focus group discussion. The survey was piloted and subsequently sent to CPG role players - evidence reviewers, CPG panellists, academics involved with training in relevant disciplines like health economics and public health, implementers and funders. The focus group participants hold strategic roles in CPG development and health economic activities nationally. The survey evaluated mean values, measures of variability, and percentages for Likert scales, while narrative components were thematically analysed. Focus group data were manually coded, thematically analysed and verified.

Results
The survey (n = 55 respondents to 245 surveys distributed) and one focus group (n = 5 participants from 10 people invited) occurred between October 2018 and February 2019. We found the most consistent reason why HEE should inform CPG decisions was ‘making more efficient use of limited financial resources’. This was explained by numerous context and methodological barriers. Focus groups participants noted that consideration of complex HEE are not achievable without bolstering skills in applying evidence-based medicine principles. Further concerns include lack of clarity of standard methods; inequitable and opaque topic selection across private and public sectors; inadequate skills of CPG panel members to use HEE; and the ability of health economists to communicate results in accessible ways. Overall, in the absence of clarity about process and methods, politics and interests may drive CPG decisions about which interventions to implement.

Conclusions
HEE should ideally be considered in CPG decisions in South Africa. However, this will remain hampered until the CPG community agree on methods and processes for using HEE in CPGs. Focused investment by national government to address the challenges identified by the study is imperative for a better return on investment as National Health Insurance moves forward.
Self-supervised deep learning model for COVID-19 lung CT image segmentation highlighting putative causal relationship among age, underlying disease and COVID-19
Authors: Fung Daryl L. X. , Liu Qian , Zammit Judah , Leung Carson Kai-Sang , Hu Pingzhao 
Published: July 2021

Abstract
Background
Coronavirus disease 2019 (COVID-19) is very contagious. Cases appear faster than the available Polymerase Chain Reaction test kits in many countries. Recently, lung computerized tomography (CT) has been used as an auxiliary COVID-19 testing approach. Automatic analysis of the lung CT images is needed to increase the diagnostic efficiency and release the human participant. Deep learning is successful in automatically solving computer vision problems. Thus, it can be introduced to the automatic and rapid COVID-19 CT diagnosis. Many advanced deep learning-based computer vison techniques were developed to increase the model performance but have not been introduced to medical image analysis.

Methods
In this study, we propose a self-supervised two-stage deep learning model to segment COVID-19 lesions (ground-glass opacity and consolidation) from chest CT images to support rapid COVID-19 diagnosis. The proposed deep learning model integrates several advanced computer vision techniques such as generative adversarial image inpainting, focal loss, and lookahead optimizer. Two real-life datasets were used to evaluate the model’s performance compared to the previous related works. To explore the clinical and biological mechanism of the predicted lesion segments, we extract some engineered features from the predicted lung lesions. We evaluate their mediation effects on the relationship of age with COVID-19 severity, as well as the relationship of underlying diseases with COVID-19 severity using statistic mediation analysis.

Results
The best overall F1 score is observed in the proposed self-supervised two-stage segmentation model (0.63) compared to the two related baseline models (0.55, 0.49). We also identified several CT image phenotypes that mediate the potential causal relationship between underlying diseases with COVID-19 severity as well as the potential causal relationship between age with COVID-19 severity.

Conclusions
This work contributes a promising COVID-19 lung CT image segmentation model and provides predicted lesion segments with potential clinical interpretability. The model could automatically segment the COVID-19 lesions from the raw CT images with higher accuracy than related works. The features of these lesions are associated with COVID-19 severity through mediating the known causal of the COVID-19 severity (age and underlying diseases).
VMP1, a novel prognostic biomarker, contributes to glioma development by regulating autophagy
Authors: Lin Wanzun , Sun Yun , Qiu Xianxin , Huang Qingting , Kong Lin , Lu Jiade J. 
Published: July 2021

Abstract
Background
Malignant glioma, especially glioblastoma, is a highly aggressive disease with a dismal prognosis. Vacuole membrane protein 1 (VMP1) is a critical autophagy-associated protein with roles in oncogenesis and tumor progression. However, the contribution of VMP1 to glioma development as well as its prognostic value has not been established.

Methods
The expression of VMP1 and clinicopathologic data for 1996 glioma samples were collected from authoritative public databases to explore its prognostic value. Lentiviral CRISPR-Cas9 gene editing system was performed to deplete VMP1 expression. Apoptosis assays, cell cycle assays, colony formation assays, and EdU incorporation analysis were conducted to validate the biological function of VMP1. Transmission electron microscopy was used to determine the role of VMP1 in regulating autophagy.

Results
VMP1 overexpression was associated with advanced disease and had a poor prognosis in patients with glioma. The depletion of VMP1 by CRISPR-Cas9 gene editing significantly inhibited cell proliferation, increased cell death, and induced cell cycle arrest. Mechanistically, VMP1 knockout blocked autophagic flux and thus sensitized glioma cells to radiotherapy and chemotherapy. Moreover, a nomogram model showed that VMP1 expression has high prognostic value for determining survival in glioma.

Conclusions
Our results provide insights into the pathological and biological functions of VMP1, including its roles in promoting tumor growth and progression, and support its value as a new diagnostic and prognostic biomarker for glioma.
The COVID-19 pandemic: doom to international medical electives? Results from two German elective databases
Authors: Egiz Abdullah , Storz Maximilian Andreas 
Published: July 2021

Abstract
Objective
International medical electives are an essential part of medical education and popular among medical students. During the COVID-19 pandemic, however, many students had assistantship placements postponed and electives cancelled. Educational institutions switched face-to-face campus-based teaching to virtual platforms. Although it is conceivable that international medical electives were particularly affected by this development, numerical data on this phenomenon is yet scarce. To investigate how the COVID-19 pandemic influenced the clinical elective behavior of German-speaking medical students, we systematically analyzed two large German online databases (Famulatur-Ranking and PJ-Ranking) cataloging medical elective experience testimonies.

Results
The COVID-19 pandemic substantially reduced the number of German medical students undertaking abroad medical electives. Between 2018 and 2020, a total of 10,976 reports were uploaded to both databases. We observed a notable decline in abroad elective reports in 2020. Prior to the COVID-19 pandemic, almost 5% of reports uploaded to “PJ-ranking” covered an international medical elective. This number dropped to 1.68% in 2020. Analyzing “Famulaturranking”, we observed a comparable phenomenon. While 4.74% of reports in 2019 covered an international elective, the number dropped to 2.02% in 2020. The long-term consequences of this phenomenon will be subject to future research.
Attention based multi-component spatiotemporal cross-domain neural network model for wireless cellular network traffic prediction
Authors: Zeng Qingtian , Sun Qiang , Chen Geng , Duan Hua 
Published: July 2021

AbstractWireless cellular traffic prediction is a critical issue for researchers and practitioners in the 5G/B5G field. However, it is very challenging since the wireless cellular traffic usually shows high nonlinearities and complex patterns. Most existing wireless cellular traffic prediction methods lack the abilities of modeling the dynamic spatial–temporal correlations of wireless cellular traffic data, thus cannot yield satisfactory prediction results. In order to improve the accuracy of 5G/B5G cellular network traffic prediction, an attention-based multi-component spatiotemporal cross-domain neural network model (att-MCSTCNet) is proposed, which uses Conv-LSTM or Conv-GRU for neighbor data, daily cycle data, and weekly cycle data modeling, and then assigns different weights to the three kinds of feature data through the attention layer, improves their feature extraction ability, and suppresses the feature information that interferes with the prediction time. Finally, the model is combined with timestamp feature embedding, multiple cross-domain data fusion, and jointly with other models to assist the model in traffic prediction. Experimental results show that compared with the existing models, the prediction performance of the proposed model is better. Among them, the RMSE performance of the att-MCSTCNet (Conv-LSTM) model on Sms, Call, and Internet datasets is improved by 13.70 ~ 54.96%, 10.50 ~ 28.15%, and 35.85 ~ 100.23%, respectively, compared with other existing models. The RMSE performance of the att-MCSTCNet (Conv-GRU) model on Sms, Call, and Internet datasets is about 14.56 ~ 55.82%, 12.24 ~ 29.89%, and 38.79 ~ 103.17% higher than other existing models, respectively.