bluuebunny/crossref_metadata_2025_split huggingface dataset:
Early postoperative serum aspartate aminotransferase for prediction of post-hepatectomy liver failure
Authors: Vassanasiri Watoo , Rungsakulkij Narongsak , Suragul Wikran , Tangtawee Pongsatorn , Muangkaew Paramin , Mingphruedhi Somkit , Aeesoa Suraida 
Published: October 2021

Abstract
Background

Post-hepatectomy liver failure (PHLF) is a serious complication of hepatectomy. The current criteria for PHLF diagnosis (ISGLS consensus) require laboratory data on or after postoperative day (POD) 5, which may delay treatment for patients at risk. The present study aimed to determine the associations between early postoperative (POD1) serum aminotransferase levels and PHLF.
Methods

The medical records of patients who underwent hepatectomy at Ramathibodi Hospital from January 2008 to December 2019 were retrospectively examined. Patients were classified into PHLF and non-PHLF groups. Preoperative characteristics, intraoperative findings, and early postoperative laboratory data (serum AST, ALT, bilirubin, and international normalized ratio (INR) on POD0 to POD5) were analyzed.
Results

A total of 890 patients were included, of whom 31 (3.4%) had PHLF. Cut-off points for AST of 260 U/L and ALT of 270 U/L on POD1 were predictive of PHLF. In multivariate analysis, AST >260 U/L on POD1, ICG-R15, major hepatectomy, blood loss, and INR were independently associated with PHLF.
Conclusions

Early warning from elevated serum AST on POD1, before a definitive diagnosis of PHLF is made on POD5, can help alert physicians that a patient is at risk, meaning that active management and vigilant monitoring can be initiated as soon as possible.
A Partnership Among Local Public Health Agencies, Elementary Schools, and a University to Address Childhood Obesity: A Scalable Model of the Assess, Identify, Make it Happen Process
Authors: Ingman Benjamin C , Loecke Carla J , Belansky Elaine S 
Published: October 2021

Abstract
BACKGROUND: One pathway to addressing childhood obesity is through implementing evidence-based practices (EBPs) shown to promote nutrition and physical activity in K-12 school settings. AIM (Assess, Identify, Make it happen) is a strategic planning process to engage stakeholders in implementing EBPs in their K-12 schools. Local Public Health Agencies (LPHAs) are a potential partner to facilitate this process to a broader audience of rural school communities.METHODS: A process and outcome evaluation design was applied in this study to examine the extent to which LPHAs effectively implemented AIM with rural/frontier schools in comparison to university staff. Data collection included a post-meeting surveys completed by facilitators, a post-intervention interview with facilitators, a survey of school task force members at the end of the AIM process, and systematic documentation of the intervention.RESULTS:Reach. Among the 26 eligible elementary schools, 18 (69.2%) agreed to participate.Effect. In total, schools facilitated by LPHAs fully implemented an average of 4.0 changes per school, while schools facilitated by the university staff fully implemented an average of 3.7 changes.Adoption. Among the five LPHAs in the target region, all five agreed to partner on the initiative, but some agencies were unable to identify sufficient personnel to facilitate all schools in their catchment area.Implementation. · In total, 89 of 94 (94.68%) meetings scheduled by LPHA facilitators occurred. 47 of 48 (97.92%) meetings scheduled by the university staff occurred.· The university staff self-reported 93% of agenda items in the AIM process as “completely” followed while LPHA facilitators reported 41% of agenda items as “completely” followed.· Task force satisfaction with the AIM process and facilitator showed limited variance across LPHAs and university-facilitated schools.Maintenance. Of the 16 school districts that agreed to participate in the school-based version of AIM, 9 (56.25%) also participated in a district-wide version of AIM two years later.CONCLUSION: AIM is an effective process for implementing EBPs in elementary schools when facilitated by LPHAs. Effective partnerships, a nuanced approach to fidelity, scalability considerations, and the role of technical assistance and training all contributed to the successful implementation of this LPHA-Elementary school partnership.
Health Equity Impact Evaluation of New Treatments – Evidence Synthesis Methods to Overcome Data Gaps
Authors: Jansen Jeroen P 
Published: October 2021

Abstract
Background: Distributional cost-effectiveness analysis (DCEA) has been introduced as an extension of conventional cost-effectiveness analysis to quantify health equity impacts. Although health disparities are recognized as an important concern, the typical analyses conducted to inform health technology assessment of a new intervention do not include a formal health equity impact evaluation or DCEA. One of the reasons is that the clinical trials for new interventions frequently do not have the power or are not designed to estimate the required treatment effects for sub-populations across which you want to analyze equity. The objective of the paper is to discuss how gaps in evidence regarding equity-relevant subgroup effects for new and existing interventions can potentially be overcome with advanced Bayesian evidence synthesis methods to facilitate a credible model-based DCEA. Methods: First, the evidence needs and challenges for a model-based DCEA are outlined. Next, alternative evidence synthesis methods will be summarized, followed by an illustrative example of implementing these methods. The paper will conclude with some practical recommendations. Results: The key evidence challenges for a DCEA relate to estimating relative treatment effects due to lack of inclusion of relevant subgroups in the randomized controlled trials (RCTs), lack of access to individual patient data (IPD) for all trials, small subgroups resulting in uncertain effects, and reporting gaps. Advanced Bayesian evidence synthesis methods can help overcome evidence gaps by considering all relevant direct, indirect, and external evidence simultaneously. Methods discussed include (network) meta-analysis with shrinkage estimation, conventional (network) meta-regression analysis, multi-level (network) meta-regression analysis, and generalized evidence synthesis. For a new intervention for which only RCT evidence is available and no real-world data, estimates can be improved if the assumption of exchangeable subgroup effects or the shared or exchangeable effect-modifier assumption among competing interventions can be defended. Furthermore, formal expert elicitation is worthwhile to improve estimates. Conclusion: This paper provides an overview of advanced evidence synthesis methods that may help overcome typical gaps in the evidence base to perform model-based DCEA along with some practical recommendations. Future simulation studies are needed to assess the pros and cons of different methods for different data gap scenarios.
Willingness to Join Community-Based Health Insurance and Its Associated Factors among Households in West Gojjam Zone, North Mecha Woreda ,Amhara region, Ethiopia
Authors: Demeke Getaneh Bizuayehu 
Published: October 2021

Abstract
Background

Community-based health insurance schemes are becoming increasingly recognized as a potential strategy to achieve universal health coverage in developing countries. Ethiopia is a low income country with more of health spending out of pocket payment by households. Health insurance is also expected to provide financial protection because it reduces the financial risk associated with falling ill. Therefore; financial risk in the absence of health insurance is equal to the out-of-pocket expenditures because of illness.
Method

Cross-sectional community based study design was conducted by using a pretested structured questionnaire. Multi-stage cluster, simple random and systematic sampling techniques was used to select 296 households as study units which were allocated to the kebeles proportionately. The sampled households were selected using simple random sampling technique. Bivariate and multivariate logistic regression was used for analysis of variables and 95% confidence level and P value <0.05 was used to measure strength of association.
Results

A total of 296 sampled study participants, 285 participated in this study with a response rate of 96.3%.From this, (90.9%) were willing to join and (89.8%) of them were willingness to pay CBHI. the benefits of join the scheme were as follows, (86.8%) were reduce OOP expenditure, (8.3%) of them improve health status, (2.3%) were reduce the risk of severity and (2.6%) foster productivity.
Conclusions

This study showed that the proportion of willingness to join CBHI was higher than the findings of others study in the country and it is encouraging for planned strategy to expanding the scheme throughout the country. The main challenges utilization of health services in government health institutions were absence of available medicine, poor service delivery, lack of enough laboratory, health professional’s lack of good behavior and shortage of ambulance services. To alleviate such problem the government should be encourage access to health services.
Screening of Potential Biomarkers and Therapeutic Targets for T2DM-related Alzheimer's Disease Based on Bioinformatics Analysis
Authors: He Zhengqiang 
Published: October 2021

Abstract
More and more studies have suggested that type 2 diabetes mellitus (T2DM) was susceptible to trigger Alzheimer’s disease(AD), but the common underlying mechanism were unclear. We want to perform bioinformatic analysis with public databases. The T2DM dataset GSE95849 and AD dataset GSE97760 were selected from Gene Expression Omnibus (GEO) database. Then, we identified differentially expressed genes (DEGs) and the communal DEGs between the two diseases, which perform to the enrichment analysis, protein-protein interaction (PPI) network analysis, correlation analysis.We found 255 communal DEGs between T2DM and AD. They were enriched in negative regulation of actin filament depolymerization and regulation of actin filament depolymerization. Top 5 hub genes which identified from the PPI network were enriched in autophagy. The actin filament and autophagy may be the key association between the two diseases.
Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: A case study on the 2016 Kumamoto Earthquake
Authors: Ozawa Taku , Himematsu Yuji 
Published: October 2021

Abstract
Interferometric Synthetic Aperture Radar (InSAR) is a useful tool for detecting surface deformations at high spatial resolutions. When InSAR is applied to huge surface deformations, clear fringes with complicated phase gaps often appear in the interferograms. Although the surface deformations in such areas are important for understanding their mechanisms and for investigating disasters, it is difficult to convert the data on such fringes to surface deformation information because of difficulties associated with phase unwrapping. To resolve these difficulties, we created multiple SAR pairs with different frequencies using a band-pass filter and derived the difference of interferograms which are generated from these SAR pairs. Generally, its result corresponds to the result of SAR observations made with long-wavelength radar. Therefore, a phase wrap was less likely to occur, and phase unwrapping was easy to accomplish. We applied this method to the PALSAR-2 data pairs for the 2016 Kumamoto Earthquake and succeeded in identifying huge crustal deformations with complicated phase gaps in the vicinity of surface ruptures. Comparing these results with the crustal deformations observed from GNSS measurements, the root-mean-squares of the differences were found to be approximately 4 cm. Although this accuracy was poorer than that of conventional InSAR, it was nearly equivalent to that of the offsettracking method. Furthermore, its spatial resolution was significantly better than that of the offset-tracking method. However, the disadvantage of this method is that its detection accuracy is significantly degraded in zones with low coherence, due to noise amplification. The standard deviation of the noise component was approximately 2 cm for pixels with coherences above 0.7. However, for pixels with a coherence lower than 0.2, the standard deviation was greater than 10 cm, and the noise component occasionally exceeded 1 m. Despite the disadvantages of this method, it is effective for the detection of huge crustal deformations with high spatial resolution in areas where phase unwrapping methods for conventional InSAR are inappropriate.
Predicting the difference in treatment response and survival time of lung adenocarcinoma patients based on a prognostic risk model of glycolysis-related genes
Authors: Zhao Rongchang , Ding Dan , Ding Yan , Han Rongbo , Wang Xiujuan , Zhu Chunrong 
Published: October 2021

Abstract
Background

Multiple factors affect the survival time of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic effect of medicines and the disease recurrence probability differs among patients with the same stage of LUAD. Thus, effective prognostic predictors need to be identified.
Methods

Based on the tumor mutation burden (TMB) data obtained by TCGA, LUAD was divided into high and low groups, and the differentially expressed glycolysis-related genes between the two groups were screened out. Cox regression was used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two datasets (GSE68465 and GSE11969) from Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules and drug susceptibility were assessed for their relationship with the risk score.
Results

We confirmed a 5-gene signature (FKBP4, HMMR, B4GALT1, ERO1L, ENO1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (P = 1.085e-4), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 1.289, 95% CI = 1.202-1.383, P < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Additionally, there were significant differences in cisplatin, paclitaxel, gemcitabine, docetaxel, gefitiniband erlotinib sensitivity between the low-risk and high-risk groups.
Conclusions

Our results reveal that glycolysis-related gene are feasible predictors of LUAD patient survival and response to therapeutics.
Neural Architecture Search For Skin Cancer Detection
Authors: Kandukuri Nikhil , Sakhtivel Sangeetha , Xie Pengtao 
Published: October 2021

Abstract
Neural Architectural Search (NAS) is a novel method capable of achieving state-of-the-art performance with limited computational resources and time. These coupled factors have resulted in its increasing popularity in many domains. NAS helps to discover an effective architecture for a given task. In parallel, learning through tests, a technique used in human learning aims at improving learning results: a chain of new assessments are conducted with increasing difficulty; the learner uses them to discover susceptible points, and those susceptible points are further addressed to pass the evaluation effectively. When applied in the case of learning in machines, this technique enhances their learning ability and is called Learning by passing tests(LPT). We propose to use the LPT technique in combination with NAS, particularly for Differentiable Architecture Search(DARTS), Progressive Differentiable Architecture Search(PDARTS) and, Partially Connected Differentiable Architecture Search(PCDARTS) to solve the medical challenge of Skin Cancer Classification. A bilevel optimization algorithm is formulated using LPT and is applied on the HAM10000 dataset and the Kaggle Skin Cancer: Malignant Vs. Benign dataset. Our LPT algorithm coupled with NAS can attain better performance than the traditional NAS methods and different state-of-the-art models for the given classification task.
Assessing the Psychometric Properties of the Chinese Return-to-Work Self-Efficacy Questionnaire Using Rasch Model Analysis
Authors: Liu Feng , Zhang Zhen-xiang , Lin Bei-lei , Ping Zhi-guang , Mei Yong-xia 
Published: October 2021

Abstract
Background Self-efficacy is a significant predictor of return to work and affects the confidence of survivors to return to work after illness. The Return-to-work self-efficacy (RTW-SE) questionnaire is a self-report questionnaire to assess confidence in returning to work with good reliability and validity. The aim of this study was to translate and cross-culturally adapt the RTW-SE questionnaire into Chinese and examine the psychometric properties among young and middle-aged stroke survivors using rasch model analysis.Methods The cross-cultural adaptation and translation procedures followed a dual-translation approach. The psychometric properties of the RTW-SE questionnaire were examined using Rasch model analysis by Winsteps software. The unidimensionality and local independence were analyzed by principal component analysis and standardized residual correlations. Category diagnostics were performed for scale function, and the item fit, reliability, and separation were also validated. Item-person maps were used to examine the distribution and matching of item’s difficulty and person ability. Finally, the differential item functioning (DIF) was used to measure gender-related group equivalence.Results A total of 366 participants aged 23–59 years were recruited from three communities in Zhengzhou. The RTW-SE questionnaire demonstrated unidimensionality and a 5-point Likert rating scale was more appropriate to investigate young and middle-aged stroke survivors’self-efficacy. There was a good fit for the items with both person and item reliabilities greater than 0.8 and separation indices of 3.75 and 3.94, respectively. The item difficulty was identified from the item-person map as not covering person ability, but the scale did not have an age-related DIF.Conclusions The results confirm evidence of appropriate psychometric properties of the RTW-SE questionnaire and can be used as a reliable and validated instrument for measuring self-efficacy to return to work in young and middle-aged Chinese patients with stroke.
Incidence, Mortality, Survival, and Prognostic Analysis of Epithelial Ovarian Cancer Patients in Brunei Darussalam: A Population-Based Study
Authors: Leong Elvynna , Ong Sok King , Jali Fadzilah , Naing Lin 
Published: October 2021

Abstract
Background

Ovarian cancer is the fifth most common cancer among females in Brunei Darussalam in 2017. This study aims to provide nationwide cancer statistics including cancer incidence, mortality, survival rates for women diagnosed with epithelial ovarian cancer, and evaluate the prognostic factors of epithelial ovarian cancer patients survival in Brunei Darussalam.
Methods

This is a retrospective population-based study of patients diagnosed with epithelial ovarian cancer between 1st January 2007 and 31st December 2017 in Brunei Darussalam. Crude, age-specific, age-standardized incidence and mortality rates per 100,000 women were calculated. Kaplan-Meier survival analysis method was used to determine the overall 5-years survival rate of epithelial ovarian cancer patients. Log-rank test was used to examine the differences in survival between groups. The Multivariable Cox Proportional Hazard (PH) regression models were used to estimate the hazard ratio (HRs) for overall survival and to identify the prognostic factor of epithelial ovarian cancer patients. PH assumption over time for these models were evaluated.
Results

A total of 207 patients were included in the study. The crude incidence and mortality rates were 9.7 and 3.6 per 100,000 respectively while the age-standardized incidence and mortality rates were 11.3 (95% CI: 9.7, 12.9) and 4.5 (95% CI: 3.4, 5.6) per 100,000 respectively in the period 2007-2017. The overall mean age at diagnosis was 48.4 (standard deviation=15.3) years. The overall survival rates at 1, 3, and 5 years for epithelial ovarian cancer patients were 79.7%, 69.7%, and 61.4% respectively. Age at diagnosis, district, cancer stage, and histology were the significant prognostic factors for epithelial ovarian cancer patients’ survival. Older age at diagnosis (\(\ge\)70 years vs <40 years), regional or advanced stage (vs localized stage) and having undifferentiated or other epithelial ovarian (vs serous carcinoma) were associated with having higher hazard of death while patients residing in Belait district (vs Brunei Muara) was associated with having lower hazard.
Conclusion

More efforts and research should be made to detect the disease at early stage through education and public awareness to ensure the availability of high-quality care for all women with ovarian cancer and to improve the survival rates of patients with ovarian cancer.
A Retrospective Analysis of the Correlation between Trichomonas Vaginalis Infection and Infertility
Authors: Zhang Zhenchao , Li Yuhua , Lu Haoran , Li Dongxian , Zhang Rui , Xie Xianghuan , Guo Lihua , Hao Lixia , Tian Xiaowei , Yang Zhenke , Wang Shuai , Mei Xuefang 
Published: October 2021

Abstract
Background: Trichomonas vaginalis (T. vaginalis) is an extracellular flagellated protozoan parasitizing the human genital and urinary tracts. T. vaginalis infection impacts human reproductive function, but whether it causes infertility is still a matter of debate.Methods: In this work, we consulted 237 relevant articles, which were classified into three categories: epidemiological investigations (104), review articles (40), and research articles (62). RevMan 5.4 was used to conduct a meta-analysis of the articles reporting epidemiological investigations comparing the incidence of T. vaginalis infection between infertile and fertile groups.Results: The results indicated that rate of T. vaginalis infection in the infertile group was lower than that in the fertile group. However, an epidemiological survey showed that the infertility rate of population infected with T. vaginalis was significantly higher than that of population without T. vaginalis infection. Most review articles stated that T. vaginalis infection causes infertility, while a small fraction of these articles were inconclusive. The conclusion that T. vaginalis infection can lead to infertility is supported by the research articles, which indicated the main pathogenic mechanisms are as follows: T. vaginalis impairs sperm quality, resulting in infertility; the immune response triggered by T. vaginalis infection impacts human reproductive function; and T. vaginalis impairs ovum quality, resulting in infertility.Conclusion: Our study confirmed that T. vaginalis infection can lead to infertility and provides a foundation for further investigations into its pathogenesis.