bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Patient-Centered Care for Veterans With Treatment-Resistant Depression Using Shared Decision-Making Tools
Authors: Allen Cheyenne M. , Bray Carla 
Published: December 2022

INTRODUCTION: Treatment-resistant depression (TRD) exists when patient depression continues without remission or reduction despite treatment. There are no standardized guidelines for identifying TRD, but one failed antidepressant treatment at an adequate dose and duration can constitute TRD, especially in cases of severe depression or suicidality. TRD rates for depressed patients average approximately 50% to 60% of the general population. These numbers are higher in the military population and are often complicated by comorbidities. AIM: Chart audits revealed 68% of psychiatric clinic outpatient veterans met criteria for TRD. Only 25% of patients were being treated adequately for TRD, and 0% were offered other options for treatment. This project aimed to improve patient-centered TRD care at a veteran’s hospital to 80% within 90 days. METHODS: This quality improvement project was implemented using plan-do-study-act (PDSA) cycles. Interventions were tested over four rapid-cycle phases with improvements for screening, handouts, surveys, and team meetings over 8 weeks. Four core interventions were followed throughout the project: screening for TRD, right-care case management tracking, patient engagement with shared decision-making (SDM), and team engagement. RESULTS: Starting from a baseline right-care score of 25%, the project attained an overall mean of 99.6% representing improved patient-centered TRD care and surpassing the 80% goal defined in the aim. CONCLUSION: Overall TRD care was improved using SDM options and inter-clinic teamwork and communication.
A Nomogram for Predicting the Cancer-Specific Survival of Patients with Initially Diagnosed Metastatic Gastric Cancer
Authors: Ren Jun , Dai Yuedi , Chao Fei , Tang Dong , Gu Jiawei , Niu Gengming , Xia Jie , Wang Xin , Song Tao , Hu Zhiqing , Hong Runqi , Ke Chongwei 
Published: December 2022

Background: There are few models to predict the survival of patients of different ethnicities initially diagnosed with metastatic gastric cancer (mGC). Therefore, the aim of this study was to construct a nomogram to predict the cancer-specific survival (CSS) of these patients. Methods: Data for 994 patients initially diagnosed with mGC between 2000 and 2013 were extracted from the Surveillance, Epidemiology, and End Results database. Patients were randomly classified into a training (n = 696) or internal validation (n = 298) cohort, and a cohort of 133 patients from Fudan cohort was used for external validation. A nomogram to predict the CSS of mGC patients was derived and validated using a concordance index (C-index), calibration curves, and decision-curve analysis (DCA). Results: Multivariate Cox regression indicated that five factors were independent predictors of CSS: differentiation grade, T stage, N stage, metastatic site at diagnosis, and with or without chemotherapy. Thus, these factors were integrated into the nomogram model. The C-index value of the nomogram model was 0.63 (95% CI: 0.60–0.65), and those of the internal and external validation cohorts were 0.60 (95%: CI 0.55–0.64) and 0.63 (95%: CI 0.57–0.69), respectively. The calibration curves showed good consistency between the actual and predicted survival rates in both the internal and external validation cohorts. The DCA also showed the clinical utility of the nomogram model. Conclusions: We established a practical nomogram to predict the CSS of patients initially diagnosed with mGC. The nomogram can be used for individualized prediction of survival and to guide clinicians in making treatment decisions.
Understanding language preference: Autism knowledge, experience of stigma and autism identity
Authors: Bury Simon M , Jellett Rachel , Haschek Alex , Wenzel Michael , Hedley Darren , Spoor Jennifer R 
Published: December 2022

Prior research has studied preferences for identity- or person-first language among persons with an autism diagnosis. The current study differs from this previous body of research by specifically examining quantitative predictors of language preferences through a social identity theoretical approach, thereby leading to a better understanding of psychological and social factors that might underlie language use and preference within the autistic community. Australian adults with an autism diagnosis ( N = 198) completed the measures of autism knowledge, internalised stigma, and autism identity to determine whether these factors predict language preference. Results indicated a stronger autism identity was associated with a preference for identity-first terms (autistic/autistic person) and finding these less offensive. Contrastingly, stigma was associated with finding identity-first language less favourable and more offensive. Person-first terms (e.g. person with autism) were not associated with any of the predictors. Together, these findings suggest decision-making around identity-first language is influenced by a strong sense of autistic identity and experiences of stigma. Lay abstract There is ongoing discussion around what language is acceptable when talking about someone with an autism diagnosis, especially regarding person-first (e.g. person with autism) or identity-first (e.g. autistic person) language. We asked 198 Australian adults with an autism diagnosis what terminology they prefer and what they find offensive. We also asked questions to understand their experience of stigma, their autism knowledge and how much they endorse an autism identity, to investigate if these factors were associated with their language preferences. Overall, there was no significant association between these three factors and person-first terminology. For identity-first terms, those who endorse a stronger autism identity tended to find identity-first terms more preferable and less offensive, whereas those who reported greater experiences and internalisation of stigma tended to find identity-first terms less preferable and more offensive. Previous research has tended to ask what language participants prefer. The findings of this work help provide some context as to why people prefer or find offensive specific terms, at least for identity-first language.
Aboutness in a second language text: A large-scale study on topic reactivation by L2 Italian learners
Authors: Rastelli Stefano 
Published: December 2022

Objectives: The study reports adult L2 Italian learners’ and native speakers’ (NS) choices between null and overt subject pronouns in a written illustrated story. The aim of the study is to ascertain whether learners have different perceptions of the aboutness topic compared with NS. Methodology: A total of 338 adult L2 Italian learners having different L1s filled in the blanks of a written story by choosing between the null pronoun and the third-person pronoun lui “he.” Data and analysis: The outcome variable was learners’ and NS’ choices between null and overt pronominal subject. Independent variables were: “anaphora” (“null” or “pronominal”) and “position” (“intrasentential,” when the antecedent and the gap were in the same sentence, and “intersentential,” when the antecedent and the gap were in two separate sentences). Findings: When the antecedent and the gap occurred in adjacent scenes of the story separated by punctuation, L2 learners—unlike NS—tended to reactivate the overt subject pronoun. Learners’ proficiency, L1, length of instruction, and knowledge of verb morphology significantly modulated the results. Originality: Punctuation in written texts strongly affects the likelihood that L2 learners use anaphoric means to reactivate the topic. L2 learners’ perception of aboutness in discourse is less robust and more affected by topic shifts and interruptions. Implications: Null subjects in texts should be dealt with upfront in second language instruction. Syllabi should deal with the difference between the use of overt and null pronouns in discourse.
Examining Pareto Law across department store shoppers
Authors: Tanusondjaja Arry , Romaniuk Jenni , Nenycz-Thiel Magda , Sakashita Mototaka , Viswanathan Vijay 
Published: December 2022

Department stores invest in loyalty strategies that largely focus on retaining current high value customers in response to increasing competition in retail shopping. In this study, we examine the contribution of the top 20% customers for transaction frequency and value (“heavy buyers”) to the total sales, and the consistency of this contribution across departments within a store. We also investigate the heavy buyer stability over time across 3 years, from over 550 million transactions from a department store chain in East Asia. The results show that the Pareto ratio of the top 20% spenders account for 71% of revenue (and 52% of the total transactions), and the top 20% transactors represent 58% of revenue (and 62% of total transactions), which may signal the role of such heavy buyers to overall stores sales. At each department level, the heavy buyers (by value) contribute from 65% to 86% of the department revenue. Despite this, the stability of the top 20% segment over time varies greatly by department from 11% to 74%. Finally, whether high value customers in one department store also translate across departments, depends mainly on the department size in terms of its shopper penetration. The research furthers our knowledge on Pareto Law, with important implications for customer retention strategies and loyalty programs especially for retailers.
Yoga Therapy in Cancer Care via Telehealth During the COVID-19 Pandemic
Authors: Mallaiah Smitha , Narayanan Santhosshi , Wagner Richard , Cohen Chiara , Christie Aimee J. , Bruera Eduardo , Lopez Gabriel , Cohen Lorenzo 
Published: December 2022

Background: Yoga is an evidence-based mind-body practice known to improve physical and mental health in cancer patients. We report on the processes and patient-reported outcomes of one-on-one yoga therapy (YT) consultations delivered via telehealth. Methods: For patients completing a YT consultation between March 2020 and October 2021, we examined demographics, reasons for referral, and self-reported symptom burden before and after one YT session using the Edmonton Symptom Assessment Scale (ESAS). Changes in ESAS symptom and subscale scores [physical distress (PHS), psychological distress (PSS), and global distress (GDS)] were evaluated by Wilcoxon signed-rank test. Descriptive statistics summarized the data. Results: Ninety-seven initial YT consults were completed, with data evaluated for 95 patient encounters. The majority were women (83.2%) and white (75.8%), The mean age for females was 54.0 and for males was 53.4; the most common diagnosis was breast cancer (48%), 32.6% had metastatic disease, and nearly half (48.4%) were employed full-time. Mental health (43.0%) was the most common reason for referral, followed by fatigue (13.2%) and sleep disturbances (11.7%). The highest symptoms at baseline were sleep disturbance (4.3), followed by anxiety (3.7) and fatigue (3.5). YT lead to clinically and statistically significant reductions in PHS (mean change = −3.1, P < .001) and GDS (mean change = −5.1, P < .001) and significant reductions in PSS (mean change = −1.6, P < .001). Examination of specific symptom scores revealed clinically and statistically significant reductions in anxiety (mean change score −1.34, P < .001) and fatigue (mean change score −1.22, P < .001). Exploratory analyses of patients scoring ≥1 for specific symptoms pre-YT revealed clinically and statistically significant improvements in almost all symptoms and those scoring ≥4 pre-YT. Conclusions: As part of an integrative oncology outpatient consultation service, a single YT intervention delivered via telehealth contributed to a significant improvement in global, physical, and psychosocial distress. Additional research is warranted to explore the long-term sustainability of the improvement in symptoms.
Ultra-Low-Dose Contrast Using Transluminal Renal Angioplasty: The ULTRA Study
Authors: Kawano Megumi , Suzuki Kenji , Fujimura Naoki , Endo Ayaka , Kato Ai , Fujii Kentaro , Komatsu Motoaki , Takahashi Toshiyuki , Ryuzaki Munekazu , Harada Hirohisa 
Published: December 2022

Background Although severe atherosclerotic renal artery stenosis (ARAS) is a predictor of future cardiovascular events, large trials have not shown the benefits of percutaneous transluminal renal angioplasty (PTRA). This study aimed to validate the safety and efficacy of PTRA using low-concentration digital subtraction angiography (LC-DSA) in patients with severe ARAS and advanced chronic kidney disease (CKD). Materials and Methods This prospective study was conducted between August 2018 and October 2021. Eighteen patients with 20 lesions, CKD stage 3b or worse, and significant renal artery stenosis were included and underwent PTRA using ultra-low-dose contrast medium. The primary endpoint was a change in renal function based on serum creatinine (sCr) level. Results The mean sCr level significantly improved from 3.34 ± 1.8 mg/dL pre-PTRA to 2.48 ± 1.19 mg/dL at 1 month post-PTRA ( P = .02). The mean amount of contrast used was 8.3 ± 3.9 mL per vessel. More severe stenosis and rapid deterioration of renal function before treatment were associated with improved kidney function. No cardiovascular or renal complications such as stroke or contrast-induced nephropathy were observed during the 30-day period. Conclusions PTRA using an ultra-low-dose contrast medium is safe and provides acceptable results.
Pregnancy and parental leave policies at Australian and New Zealand medical schools
Authors: McGrath Caroline , Szabo Rebecca A , Bilszta Justin L 
Published: December 2022

Background: Research into how medical schools support students who are pregnant or with current parental responsibilities has been mostly limited to the US context. Objectives: To review pregnancy and parental leave policies for students at Australian/New Zealand medical schools. Design: A cross-sectional survey. Methods: Data were collected between June and September 2021. Websites of Australian/New Zealand medical schools (n = 23) were searched for freely available information on pregnancy and parental leave policies. Each school was contacted to provide supplementary information on the processes to support students who apply for pregnancy and/or parental leave. Outcome harvesting techniques were used to analyse the key attributes and processes used by medical schools. Results: None of the 23 accredited Australian/New Zealand medical schools had specific pregnancy and/or parental leave policies. Fourteen of the 23 Australian/New Zealand medical schools responded to the request for more information. All confirmed, beyond their University’s general student leave policies, they had no additional pregnancy and parental leave policy. Analysis of each school’s processes identified the following themes: lack of school specific pregnancy and/or parental leave policies; lack of public statements of support for medical students who are pregnant and/or with current parental responsibilities; and lack of attention to the specific needs of medical students who are pregnant and/or with current parental responsibilities, including those with pregnant partners or are a birth support person. Conclusion: There was a lack of documentation and formalized processes related to the support of this group of students. By creating easily accessible information on pregnancy and parental leave which is nuanced to the challenges of medical school and clinical placements, medical schools and medical education accreditation bodies in Australia/New Zealand can address the needs of medical students who are pregnant and/or with current parental responsibilities and normalize pregnancy and parental status within entry-to-practice medical courses.
Open vs Closed Management of Condylar Fracture Our Experience of 100 Cases in a Suburban Tertiary Care Hospital
Authors: Kumar Manoj , Ramanujam Sathyanarayanan , Kumaravelu Raghu , Cheeman Raja Sethupathy , Periera Raymond Joseph , Titus Sarah 
Published: December 2022

Study Design Retrospective Observational Study. Objective Mandibular condyle fractures are distinctive among maxillofacial injuries in which they disrupt mandibular function in a way that other traumatic injuries do not. Condylar fractures can be treated using either the conservative (closed reduction and immobilisation) or surgical (open reduction and internal fixation) approaches. Both of these modalities of treatment have advantages and disadvantages, as well as indications and contraindications. The purpose of this study is to compile and compare our experience in the management of condylar fractures through open and closed reduction. Methods The present retrospective analysis included a total 100 patients of condylar fractures in patients > 18 years of age who were randomly divided into nonsurgical and surgical group based on Edward Ellies criteria. In the present study, the outcomes of conservative vs surgical management of condylar fractures were discussed in terms of seven parameters, including the maximal inter-incisal mouth opening, protrusive and lateral excursive movements of the mandible, status of occlusion, deviation of mandible during mouth opening, temporo-mandibular disorders and facial nerve paralysis which were measured and evaluated pre- and post-operatively at different intervals of time. Follow-up period was for 6 months. Results It was noted that the main cause of condylar fracture was trauma with a male predilection with an average age of 32.6 ± 1.2 years. Subcondylar fracture was the commonest type of condylar fracture that we encountered. 33.3% of the patients had restricted mouth opening and 57% of the patients had deranged occlusion. 37% of the patients were treated surgically and 48.6% of these fractures were approached using peri-angular approach. More patients had an increased mouth opening and a stable occlusion at the 6 months follow-up when compared to that of the 2 month follow up. Conclusions From the above study we can conclude that the treatment plan should be patient specific and follow the algorithm for a particular type of fracture. We endorse the same based on our experience in treating condylar fractures over the last 5 years. The art of decision making solely depends on the surgeon’s expertise in managing condylar fractures.
If not now, when? Climate disaster and the Green vote following the 2021 Germany floods
Authors: Garside Susanna , Zhai Haoyu 
Published: December 2022

Can first-hand experience of a climate-related natural disaster make citizens more likely to vote in favour of progressive climate politics? Leveraging the rare occurrence of a large-scale disaster just two months before a federal election, we use a difference-in-differences design to study the short-term electoral effects of the devastating 2021 Germany floods on voter support for Germany’s major environmentalist party, the Green Party. Compared to other German voters, those living in areas affected by the floods were marginally (0.4–1.6 percentage points) more likely to vote for the Greens. The largest increases in Green vote share are observed in municipalities which were directly exposed to flooding. Contrary to expectation, we tend to find larger increases in Green Party support in the less severely affected areas. Despite substantial increases in turnout in affected areas, we find that the observed increase in vote share for the Greens was rather driven by a persuasion effect on voters who previously supported other parties. In the absence of evidence that the floods led to an increase in voters’ issue prioritisation of climate change, our results highlight the limited possibility for major natural disasters to induce increased localised support for Green parties.
Artificial intelligence-enabled electrocardiogram screens low left ventricular ejection fraction with a degree of confidence
Authors: Lee Chun-Ho , Liu Wei-Ting , Lou Yu-Sheng , Lin Chin-Sheng , Fang Wen-Hui , Lee Chia-Cheng , Ho Ching-Liang , Wang Chih-Hung , Lin Chin 
Published: December 2022

Background Artificial intelligence-enabled electrocardiogram has become a substitute tool for echocardiography in left ventricular ejection fraction estimation. However, the direct use of artificial intelligence-enabled electrocardiogram may be not trustable due to the uncertainty of the prediction. Objective The study aimed to establish an artificial intelligence-enabled electrocardiogram with a degree of confidence to identify left ventricular dysfunction. Methods The study collected 76,081 and 11,771 electrocardiograms from an academic medical center and a community hospital to establish and validate the deep learning model, respectively. The proposed deep learning model provided the point estimation of the actual ejection fraction and its standard deviation derived from the maximum probability density function of a normal distribution. The primary analysis focused on the accuracy of identifying patients with left ventricular dysfunction (ejection fraction ≤ 40%). Since the standard deviation was an uncertainty indicator in a normal distribution, we used it as a degree of confidence in the artificial intelligence-enabled electrocardiogram. We further explored the clinical application of estimated standard deviation and followed up on the new-onset left ventricular dysfunction in patients with initially normal ejection fraction. Results The area under receiver operating characteristic curves (AUC) of detecting left ventricular dysfunction were 0.9549 and 0.9365 in internal and external validation sets. After excluding the cases with a lower degree of confidence, the artificial intelligence-enabled electrocardiogram performed better in the remaining cases in internal (AUC = 0.9759) and external (AUC = 0.9653) validation sets. For the application of future left ventricular dysfunction risk stratification in patients with initially normal ejection fraction, a 4.57-fold risk of future left ventricular dysfunction when the artificial intelligence-enabled electrocardiogram is positive in the internal validation set. The hazard ratio was increased to 8.67 after excluding the cases with a lower degree of confidence. This trend was also validated in the external validation set. Conclusion The deep learning model with a degree of confidence can provide advanced improvements in identifying left ventricular dysfunction and serve as a decision support and management-guided screening tool for prognosis.