bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classification of chest X-ray images by incorporation of medical domain knowledge into operation branch networks
Authors: Tsuji Takumasa , Hirata Yukina , Kusunose Kenya , Sata Masataka , Kumagai Shinobu , Shiraishi Kenshiro , Kotoku Jun’ichi 
Published: May 2023

Abstract
Background
This study was conducted to alleviate a common difficulty in chest X-ray image diagnosis: The attention region in a convolutional neural network (CNN) does not often match the doctor’s point of focus. The method presented herein, which guides the area of attention in CNN to a medically plausible region, can thereby improve diagnostic capabilities.

Methods
The model is based on an attention branch network, which has excellent interpretability of the classification model. This model has an additional new operation branch that guides the attention region to the lung field and heart in chest X-ray images. We also used three chest X-ray image datasets (Teikyo, Tokushima, and ChestX-ray14) to evaluate the CNN attention area of interest in these fields. Additionally, after devising a quantitative method of evaluating improvement of a CNN’s region of interest, we applied it to evaluation of the proposed model.

Results
Operation branch networks maintain or improve the area under the curve to a greater degree than conventional CNNs do. Furthermore, the network better emphasizes reasonable anatomical parts in chest X-ray images.

Conclusions
The proposed network better emphasizes the reasonable anatomical parts in chest X-ray images. This method can enhance capabilities for image interpretation based on judgment.
Validated risk prediction models for outcomes of acute kidney injury: a systematic review
Authors: Haredasht Fateme Nateghi , Vanhoutte Laban , Vens Celine , Pottel Hans , Viaene Liesbeth , De Corte Wouter 
Published: May 2023

AbstractBackgroundAcute Kidney Injury (AKI) is frequently seen in hospitalized and critically ill patients. Studies have shown that AKI is a risk factor for the development of acute kidney disease (AKD), chronic kidney disease (CKD), and mortality.MethodsA systematic review is performed on validated risk prediction models for developing poor renal outcomes after AKI scenarios. Medline, EMBASE, Cochrane, and Web of Science were searched for articles that developed or validated a prediction model. Moreover, studies that report prediction models for recovery after AKI also have been included. This review was registered with PROSPERO (CRD42022303197).ResultWe screened 25,812 potentially relevant abstracts. Among the 149 remaining articles in the first selection, eight met the inclusion criteria. All of the included models developed more than one prediction model with different variables. The models included between 3 and 28 independent variables and c-statistics ranged from 0.55 to 1.ConclusionFew validated risk prediction models targeting the development of renal insufficiency after experiencing AKI have been developed, most of which are based on simple statistical or machine learning models. While some of these models have been externally validated, none of these models are available in a way that can be used or evaluated in a clinical setting.
Deep learning-based multi-model approach on electron microscopy image of renal biopsy classification
Authors: Zhang Jingyuan , Zhang Aihua 
Published: May 2023

Abstract
Background
Electron microscopy is important in the diagnosis of renal disease. For immune-mediated renal disease diagnosis, whether the electron-dense granule is present in the electron microscope image is of vital importance. Deep learning methods perform well at feature extraction and assessment of histologic images. However, few studies on deep learning methods for electron microscopy images of renal biopsy have been published. This study aimed to develop a deep learning-based multi-model to automatically detect whether the electron-dense granule is present in the TEM image of renal biopsy, and then help diagnose immune-mediated renal disease.

Methods
Three deep learning models are trained to classify whether the electron-dense granule is present using 910 electron microscopy images of renal biopsies. We proposed two novel methods to improve the model accuracy. One model uses the pre-trained ResNet convolutional layers for feature extraction with transfer learning which was firstly improved with skip architecture, then uses Support Vector Machine as the classifier. We developed a multi-model to combine the traditional ResNet model with the improved one to further improve the accuracy.

Results
Deep learning-based multi-model has the highest model accuracy, and the average accuracy is about 88%. The improved ReseNet + SVM model performance is much better than the traditional ResNet model. The average accuracy of the improved ResNet + SVM model is 83%, while the traditional ResNet model accuracy is only 58%.

Conclusions
This study presents the first models for electron microscopy image classification of Renal Biopsy. Identifying whether the electron-dense granule is present plays an important role in the diagnosis of immune complex nephropathy. This study made it possible for Artificial Intelligence models assist to analyze complex electron microscopy images for disease diagnosis.
Bleeding risk and mortality according to antithrombotic agents’ exposure in cancer-related stroke patients: nationwide population-based cohort study in South Korea
Authors: Choi Bo Kyu , Lee Ji Sung , Kim Hae Reong , Kim Han Sang , Jung Yo Han , Park Yu Rang 
Published: May 2023

AbstractBackgroundIschemic stroke with active cancer is thought to have a unique mechanism compared to conventional stroke etiologies. There is no gold standard guideline for secondary prevention in patients with cancer-related stroke, hence, adequate type of antithrombotic agent for treatment is controversial.MethodsSubjects who were enrolled in National Health Insurance System Customized Research data during the period between 2010 and 2015 were observed until 2019. Subject diagnosed with ischemic stroke within six months before and 12 months after a cancer diagnosis was defined as cancer-related stroke patient. To solve immeasurable time bias, the drug exposure evaluation was divided into daily units, and each person-day was classified as four groups: antiplatelet, anticoagulant, both types, and unexposed to antithrombotic drugs. To investigate bleeding risk and mortality, Cox proportional hazards regression model with time-dependent covariates were used.ResultsTwo thousand two hundred eighty-five subjects with cancer-related stroke were followed and analyzed. A group with anticoagulation showed high estimated hazard ratios (HRs) of all bleeding events compared to a group with antiplatelet (major bleeding HR, 1.35; 95% confidence interval [CI], 1.20–1.52;p < 0.001). And the result was also similar in the combination group (major bleeding HR, 1.54; 95% CI, 1.13–2.09;p = 0.006). The combination group also showed increased mortality HR compared to antiplatelet group (HR, 1.72; 95% CI, 1.47–2.00;p < 0.001).ConclusionsBleeding risk increased in the anticoagulant-exposed group compared to antiplatelet-exposed group in cancer-related stroke patients. Thus, this result should be considered when selecting a secondary prevention drug.
Adverse infant outcomes following low-risk pregnancies in England: a retrospective cohort study
Authors: Riley Megan , Lambrelli Dimitra , Graham Sophie , Henry Ouzama , Sutherland Andrea , Schmidt Alexander , Sawalhi-Leckenby Nicola , Donaldson Robert , Stoszek Sonia K. 
Published: May 2023

Abstract
Background
There are limited data describing adverse infant outcomes in infants born to women with a low risk of complications during pregnancy, such as those who may be enrolled in maternal immunization trials. This retrospective study estimated incidence proportions of infant outcomes in different cohorts of liveborn infants in England between 2005 and 2017.

Methods
The incidence proportions of 10 infant outcomes were calculated for liveborn infants from pregnancies represented in the Clinical Practice Research Datalink (CPRD) Mother-Baby Link (MBL) and linkage to Hospital Episode Statistics (HES). Three infant cohorts were designed: (1) the all pregnancies infants cohort (N = 185,119), (2) the all pregnancies with a gestational age (GA) ≥ 24 weeks infants cohort (N = 183,869), and (3) the low-risk pregnancies infants cohort (LR infants cohort, N = 121,871), which included pregnancies with a GA ≥ 24 weeks and no diagnosis of predefined high-risk medical conditions until 24 weeks GA.

Results
The most common adverse infant outcome in the three infant cohorts was macrosomia (e.g., 1,085.9/10,000 live births in the LR infants cohort), followed by minor congenital anomalies (e.g., 800.6/10,000 in the LR infants cohort), very low/low birth weight (e.g., 400.6/10,000 in the LR infants cohort), and major congenital anomalies (e.g., 270.4/10,000 in the LR infants cohort). The incidence proportions for early-onset sepsis, very low/low birth weight, and minor and major congenital anomalies were lower in the LR infants than in the other cohorts (non-overlapping confidence intervals [CIs]). The incidence proportions of neonatal death, infant death, late-onset sepsis, macrosomia, small for GA, and large for GA were similar between cohorts (overlapping CIs).

Conclusions
This study generated background rates of adverse infant outcomes from liveborn infants of all and low-risk pregnancies represented in the CPRD Pregnancy Register MBL and linkage to HES. The results indicate lower incidence proportions of several adverse infant outcomes in infants from low-risk pregnancies compared to all pregnancies, illustrating the importance of considering maternal risk factors. These background rates may facilitate the interpretation of safety data from maternal immunization trials and of pharmacovigilance data from maternal vaccines. They may also be of interest for other interventions studied in pregnant women.
The optimal time of starting adjuvant chemotherapy after curative surgery in patients with colorectal cancer
Authors: Yang Yuchong , Lu Yao , Tan Hui , Bai Ming , Wang Xia , Ge Shaohua , Ning Tao , Zhang Le , Duan Jingjing , Sun Yansha , Liu Rui , Li Hongli , Ba Yi , Deng Ting 
Published: May 2023

Abstract
Background
Postoperative adjuvant chemotherapy (AC) is now well-accepted as standard for high-risk stage II and stage III colorectal cancer (CRC) patients, however the optimal time to initiate AC remains elusive.

Methods
A comprehensive literature search was performed using the PubMed and Embase databases. The Hazard ratio (HR) with the corresponding 95% confidence interval (CI) was used as an effect measure to evaluate primary endpoints. All analyses were conducted using Stata software version 12.0 with the Random-effects model.

Results
A total of 30 studies were included in our study. Upon comparison on overall survival (OS), we identified that delaying the initiation of AC for > 8 weeks after operation was significantly associated with poor OS (HR: 1.37; 95% CI: 1.27—1.48; P < 0.01). The poor prognostic value of AC delay for > 8 weeks was not undermined by subgroup analysis based on region, tumor site, sample size and study quality. No obvious differences were observed in survival between AC within 5–8 weeks and ≤ 4 weeks (HR: 1.03; 95% CI: 0.96 -1.10; P = 0.46). Moreover, two studies both highlighted that the survival benefit of AC was still statistically significant when AC was applied 5–6 months after surgery compared with the non-chemotherapy group.

Conclusions
Delaying the initiation of AC for > 8 weeks after surgery was significantly associated with poor OS. AC started within 8 weeks after surgery brought more benefits to CRC patients. There were no obvious differences in survival benefits between AC within 5–8 weeks and ≤ 4 weeks. Compared to patients not receiving AC after surgery, a delay of approximately 5–6 months was still useful to improve prognosis.
ZDHHC15 promotes glioma malignancy and acts as a novel prognostic biomarker for patients with glioma
Authors: Liu Zhen-Yuan , Lan Tian , Tang Feng , He Yong-Ze , Liu Jin-Sheng , Yang Jin-Zhou , Chen Xi , Wang Ze-Fen , Li Zhi-Qiang 
Published: May 2023

Abstract
Background
Glioma is the most common and aggressive tumor in the adult brain. Recent studies have indicated that Zinc finger DHHC-type palmitoyltransferases (ZDHHCs) play vital roles in regulating the progression of glioma. ZDHHC15, a member of the ZDHHCs family, participates in various physiological activities in the brain. However, the biological functions and related mechanisms of ZDHHC15 in glioma remain poorly understood.

Methods
Data from multiple glioma-associated datasets were used to investigate the expression profiles and potential biological functions of ZDHHC15 in glioma. Expression of ZDHHC15 and its association with clinicopathological characteristics in glioma were validated by quantitative reverse transcription PCR (RT-qPCR) and immunohistochemical experiments. GO enrichment analysis, KEGG analysis, GSEA analysis, CCK-8, EdU, transwell, and western blotting assays were performed to confirm the functions and mechanism of ZDHHC15 in glioma. Moreover, we performed Kaplan-Meier analysis and Cox progression analysis to explore the prognostic significance of ZDHHC15 in glioma patients.

Results
ZDHHC15 expression was significantly up-regulated in glioma and positively associated with malignant phenotypes. Results from the GO and KEGG enrichment analysis revealed that ZDHHC15 was involved in regulating cell cycle and migration. Knockdown of ZDHHC15 inhibited glioma cell proliferation and migration, while overexpression of ZDHHC15 presented opposite effects on glioma cells. Besides, results from GSEA analysis suggested that ZDHHC15 was enriched in STAT3 signaling pathway. Knockdown or overexpression of ZDHHC15 indeed affected the activation of STAT3 signaling pathway. Additionally, we identified ZDHHC15 as an independent prognostic biomarker in glioma, and higher expression of ZDHHC15 predicted a poorer prognosis in glioma patients.

Conclusion
Our findings suggest that ZDHHC15 promotes glioma malignancy and can serve as a novel prognostic biomarker for glioma patients. Targeting ZDHHC15 may be a promising therapeutic strategy for glioma.
Morphology and microcirculation changes of the optic nerve head between simple high myopia and pathologic myopia
Authors: Tang Wenquan , He Bin , Luo YuLin , Duan Xuanchu 
Published: May 2023

Abstract
Purpose
To investigate morphological and microcirculation changes of optic nerve head (ONH) in simple high myopia (SHM) and pathologic myopia(PM) to evaluate and identify ONH changes in the development of PM.

Methods
A cross-sectional clinical study was used. Medical records from 193 right eyes of 193 patients with high myopia (HM) were included. Using the Topocon swept source optical coherence tomograph (SS-OCT) and fundus camera to detect the parameters, we have assessed the relative position and size of ONH, tilt and rotation of ONH, angle α (Defined as between retinal temporal arterial vascular arcades was measured from the centre of ONH with 250 pixels’ radius), size and type of peripapillary atrophy (PPA), the thickness of peripapillary retinal nerve fiber layer (PRNFL), peripapillary choriodal thickness (PCT) and peripapillary scleral thickness (PST), and peripapillary vessel density (PVD). In addition, subjects were grouped as SHM and PM according to retinopathy, and the above parameters were compared between the two groups.

Results
Patients were divided into the SHM group (138 eyes) and the PM group (55 eyes). Paramters like older age, higher diopter and longer axial length (AL) of the PM were compared to SHM (t=-3.585, -8.808, -11.409, all P<0.05). There were no differences in the smallest diameter and area of ONH, rotation angle and ratio, or PST (all P>0.05). The angle α in PM was smaller than that in SHM (t = 2.728, P<0.01). The disc-fovea distance (DFD), the largest diameter, tilt index and ratio, PPA area and radian in PM were larger than in SHM (t=-3.962, Z=-2.525, t=-2.229, Z=-4.303, Z=-2.834, all P<0.05). The superior and inferior PRNFLs in PM were smaller than in SHM (t = 4.172, 4.263, all P<0.01). The temporoinferior PRNFL was the opposite (t=-2.421, P<0.01). The average PCT in PM (93.82 ± 29.96 μm) was smaller than in SHM (108.75 ± 30.70 μm) (P<0.05). The PVD in each direction of PM was smaller than that in SHM (t = 6.398, 4.196, 4.971, 3.267, 5.029, 5.653, 4.202, 5.146, 2.090, all P<0.05).

Conclusion
Compared with SHM, the PM patients were older, with higher diopter. Their AL and DFD were longer, the angle α was smaller, the tilt index was more extensive, the PPA area and radian were larger, PCT was generally thinner, and PVD was lower. When the PPA area was bigger than the ONH area, this already indicated the presence of PM. Based on these results, we suggest ophthalmologists and myopia patients pay more attention to ONH’s morphology and microcirculation changes as there is a possibility that microcirculatory changes precede morphologic changes.
Development and validation of a new multivariable prediction model to estimate risk of abnormal vault
Authors: Yang Jing , Zou Zongyin , Wu Minhui , He Runzhang , Nong Yating , Li Hui , Zhou Sheng 
Published: May 2023

Abstract
Purpose
To develop and validate a new multivariable prediction model to estimate risk of abnormal vault after EVO Implantable Collamer Lens (EVO-ICL) implantation using the preoperative parameters.

Methods
This retrospective study comprised 282 eyes of 143patients who underwent EVO-ICL surgery between May 2021 and April 2022. We measured preoperative parameters before surgery and vaults in 1 week after the operation using swept-source optical coherence tomography (SS-OCT). Risk factors for abnormal vault were determined by univariate and multivariate logistic regression analyses, and a nomogram was developed to forecast the risk of abnormal vault after EVO-ICL implantation. We assessed the performance of nomogram in terms of discrimination and calibration, including concordance index (C-index), receiver operating characteristic curve (ROC), area under the ROC curve (AUC), and decision curve analysis (DCA). Bootstrap resampling was used as an internal verification method.

Results
The logistic regression analysis revealed the independent risk factors for abnormal vault were white-to-white(WTW), anterior chamber angle(ACA), pupil size, and ICL-size, all of them were used to establish a nomogram based on multivariate logistic regression to predict the risk of abnormal vault. The C-indexes and AUC were 0.669 (95%CI, 0.605, 0.733). The calibration curves of the nomogram showed relatively small bias from the reference line, implicating an acceptable degree of confidence. The DCA indicates the potential clinical significance of the nomogram.

Conclusions
We developed a new multivariable prediction model to estimate risk of abnormal vault. The model shows good prediction effect and can provide assistance for clinical decision of ICL size.
Using health administrative data to model associations and predict hospital admissions and length of stay for people with eating disorders
Authors: Kim Marcellinus , Holton Matthew , Sweeting Arianne , Koreshe Eyza , McGeechan Kevin , Miskovic-Wheatley Jane 
Published: May 2023

Abstract
Background
Eating disorders are serious mental illnesses requiring a whole of health approach. Routinely collected health administrative data has clinical utility in describing associations and predicting health outcome measures. This study aims to develop models to assess the clinical utility of health administrative data in adult eating disorder emergency presentations and length of stay.

Methods
Retrospective cohort study on health administrative data in adults with eating disorders from 2014 to 2020 in Sydney Local Health District. Emergency and admitted patient data were collected with all clinically important variables available. Multivariable regression models were analysed to explore associations and to predict admissions and length of stay.

Results
Emergency department modelling describes some clinically important associations such as decreased odds of admission for patients with Bulimia Nervosa compared to Anorexia Nervosa (Odds Ratio [OR] 0.31, 95% Confidence Interval [95%CI] 0.10 to 0.95; p = 0.04). Admitted data included more predictors and therefore further significant associations including an average of 0.96 days increase in length of stay for each additional count of diagnosis/comorbidities (95% Confidence Interval [95% CI] 0.37 to 1.55; p = 0.001) with a valid prediction model (R2 = 0.56).

Conclusions
Health administrative data has clinical utility in adult eating disorders with valid exploratory and predictive models describing associations and predicting admissions and length of stay. Utilising health administrative data this way is an efficient process for assessing impacts of multiple factors on patient care and predicting health care outcomes.
Understanding experiences of mental health help-seeking in Arab populations around the world: a systematic review and narrative synthesis
Authors: Khatib Hania El , Alyafei Aisha , Shaikh Madiha 
Published: May 2023

Abstract
Background
Racial and ethnic disparities in mental health service utilisation and access is well established. Mental illness is common among Arab populations globally, but most individuals display negative attitudes towards mental health and do not seek professional help. The aim of this systematic review was to determine 1) help-seeking behaviours 2) help-seeking attitudes and 3) help-seeking barriers and facilitators, related to mental health services among Arab adults.

Method
A pre-defined search strategy and eligibility criteria allowed for database searching using terms related to: mental health, Arabs, help-seeking, as well as experiences and behaviours. Seventy-four articles were included and analysed through narrative synthesis. Results were reported using the PRISMA guidelines. The review protocol was registered prospectively on PROSPERO (CRD42022319889).

Results
Arabs across the world have negative attitudes towards formal help-seeking and are reluctant to seek help, despite the presence of psychological distress. There is little information on factors that influence help-seeking behaviours and rates of service use. Preference for informal help sources such as family and friends were expressed and considered more acceptable. Low mental health literacy, stigma, gender, age, education, religion, acculturation, and immigrant status were the most common factors influencing help-seeking attitudes. Barriers to help-seeking included stigma, privacy and confidentiality, trust, mental health literacy, language, logistics, and culture related barriers. Increasing societal and family awareness, external support and encouragement, shared culture between the client and therapist, quality of doctor patient relationship, and feelings of connectedness with the host country among refugees were mentioned facilitators. Mixed findings for the role of religion, and family and community, in relation to facilitating or hindering help-seeking were reported.

Conclusions
There is an increased likelihood and preference to seek informal sources of psychological support among Arabs. Contextual and cultural factors impeding help-seeking for Arabs are common across the world. Future research should address actual utilisation rates of services to better understand factors that influence help-seeking behaviours and facilitators to help-seeking. Increasing mental health literacy and developing anti stigma campaigns is necessary. Developing culturally informed interventions should inform future efforts to promote help-seeking among this population.