bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of myocardial strain imaging in diagnosing inducible myocardial ischemia with treadmill contrast-enhanced stress echocardiography
Authors: Abazid Rami M. , Pati Nilkanth , Elrayes Maged , Chandy Mark , Hassanin Magdi , Mathew Andrew , De Sabe , Bagur Rodrigo , Tzemos Nikolaos 
Published: May 2024

Abstract
Introduction
The aim of this study is to analyze the diagnostic value of global longitudinal strain (GLS) in detecting inducible myocardial ischemia in patients with chest pain undergoing treadmill contrast-enhanced stress echocardiography (SE).

Methods
We retrospectively enrolled all patients who underwent invasive coronary angiography after treadmill contrast-enhanced SE. Rest and peak-stress myocardial GLS, segmental LS, and LS of 4-chamber (CH), 2-CH, and 3-CH views were reported. Luminal stenosis of more than 70% or fractional flow reserve (FFR) of < 0.8 was considered significant.

Results
In total 33 patients were included in the final analysis, among whom sixteen patients (48.4%) had significant coronary artery stenosis. Averaged GLS, 3-CH, and 4-CH LS were significantly lower in patients with critical coronary artery stenosis compared to those without significant stenosis (-17.1 ± 7.1 vs. -24.2 ± 7.2, p = 0.041), (-18.2 ± 8.9 vs. -24.6 ± 8.2, p = 0.045) and (-14.8 ± 6.2 vs. -22.8 ± 7.8, p = 0.009), respectively. Receiver operating characteristic (ROC) analysis of ischemic and non-ischemic segments demonstrated that a cut-off value of -20% of stress LS had 71% sensitivity and 60% specificity for ruling out inducible myocardial ischemia (Area under the curve was AUC = 0.72, P < 0.0001).

Conclusion
Myocardial LS measured with treadmill contrast-enhanced stress echocardiography demonstrates potential value in identifying patients with inducible myocardial ischemia.
Serrated polyposis syndrome: defining the epidemiology and predicting the risk of dysplasia
Authors: Dierick Natalie R. , Nicholson Brian D. , Fanshawe Thomas R. , Sundaralingam Praka , Kostalas Stuart N. 
Published: May 2024

Abstract
Background
Serrated polyposis syndrome is the most common polyposis syndrome that has neoplastic potential. However, the natural history, genetic basis, and risk of dysplasia and neoplasia of serrated polyposis syndrome are incompletely understood. The objective of this study is to define the epidemiology of serrated polyposis syndrome. Using this data, we aim to evaluate candidate variables for predicting the risk of dysplasia and neoplasia in sessile serrated lesions found in serrated polyposis syndrome patients. Finally, we aim to use this data to create and evaluate clinical prediction models for accuracy in predicting dysplastic sessile serrated lesions in serrated polyposis syndrome patients.

Methods
This was a regional Australian single-centre retrospective cohort study. Data was prospectively collected data from the clinical record database of a regional Australian gastroenterology practice. All patients undergoing colonoscopy at Port Macquarie Gastroenterology between January 2015 and September 2021 were screened for this study. Collected data included patient demographic, endoscopic, and histopathological findings. Clinical and endoscopic multivariate logistic regression models were created to predict dysplastic sessile serrated lesions. Model performance was examined using the area under the receiver operating curve.

Results
In total 8401 patients underwent a colonoscopy procedure during the study period. Serrated polyposis syndrome was diagnosed in 247, representing a prevalence of 2.94% (mean age 67.15 years, 62.75% female). Logistic regression identified; older age at serrated polyposis syndrome diagnosis, a personal history of colorectal cancer, size of the largest sessile serrated lesions removed, and total sessile serrated lesions count as predictors of dysplastic sessile serrated lesions. The clinical and endoscopic model had an area under the receiver operating curve of 0.75.

Conclusion
Serrated polyposis syndrome is more common than previously described. The clinical and endoscopic variables identified in logistic regression have acceptable accuracy in predicting the risk of dysplasia, however other populations need to be studied to achieve generalisability and improve model performance.
Exploration of lymph node recurrence patterns and delineation guidelines of radiation field in middle thoracic oesophageal carcinomas after radical surgery: a real-world study
Authors: Du Rongxu , Fan Songqing , Yang Dan , Wang Xiaobin , Hou Xia , Zeng Cheng , Guo Dan , Tian Rongrong , Jiang Leilei , Dong Xin , Yu Rong , Yu Huiming , Zhu Shuchai , Li Jie , Shi Anhui 
Published: May 2024

Abstract
Background
Oesophageal squamous cell carcinoma is one of the most commonly diagnosed carcinomas in China, and postoperative radiotherapy plays an important role in improving the prognosis of patients. Carcinomas in different locations of the oesophagus could have different patterns of lymph node metastasis after surgery.

Methods
In this multicentric retrospective study, we enrolled patients with middle thoracic oesophageal squamous cell carcinomas from 3 cancer centres, and none of the patients underwent radiotherapy before or after surgery. We analysed the lymph node recurrence rates in different stations to explore the postoperative lymphatic recurrence pattern.

Results
From January 1st, 2014, to December 31st, 2019, 132 patients met the criteria, and were included in this study. The lymphatic recurrence rate was 62.1%. Pathological stage (P = 0.032) and lymphadenectomy method (P = 0.006) were significant predictive factors of lymph node recurrence. The recurrence rates in the supraclavicular, upper and lower paratracheal stations of lymph nodes were 32.6%, 28.8% and 16.7%, respectively, showing a high incidence. The recurrence rate of the subcarinal node station was 9.8%, while 8.3% (upper, middle and lower) thoracic para-oesophageal nodes had recurrences.

Conclusions
We recommend including the supraclavicular, upper and lower paratracheal stations of lymph nodes in the postoperative radiation field in middle thoracic oesophageal carcinomas. Subcarinal station is also potentially high-risk, while whether to include thoracic para-oesophageal or abdominal nodes needs careful consideration.
Exploring the psychometric properties of the premonitory urge for tics scale (PUTS) and its association with psychiatric symptoms in Chinese children with tic disorders
Authors: Ding Qiang , Woods Douglas W. , Xu Wen , Zhao Ying , Shen Shuqin , Sun Jinhua 
Published: May 2024

Abstract
Background
The Premonitory Urge for Tics Scale (PUTS) is a common self-report measure of premonitory urges for patients with tic disorders. This study aims to evaluate the Chinese version of the PUTS (PUTS-C) and to explore its association with psychiatric symptoms in Chinese children diagnosed with tic disorders.

Methods
The psychometric evaluation involved 204 outpatients with tic disorders, aged 7–16 years, who were divided into two age groups: (7–10 years, n = 103; 11–16 years, n = 95).

Results
The PUTS-C demonstrated good internal consistency (McDonald’sω = 0.84) and two-week test-retest reliability (0.76). We observed a statistically significant correlation between the total PUTS-C score and various Yale Global Tic Severity Scale (YGTSS) subscales and total tic severity scores. The PUTS-C score also showed significant correlations with the Children Yale-Brown Obsessive Compulsive Scale (CY-BOCS), Screening Child Anxiety-Related Emotional Disorders (SCARED), and Children’s Depression Inventory (CDI). Notably, premonitory urges independently predicted tic severity, beyond the influence of comorbid symptoms. A two-factor structure of the PUTS-C was identified in the total sample through factor analysis.

Conclusions
The PUTS-C possesses acceptable validity and good reliability. It appears that premonitory urges in Chinese patients with tic disorders are associated with obsessive-compulsive symptoms, anxiety, and depression, but can independently predict tic severity. Specific PUTS-C factors possibly related to motor and vocal tics. Future research should continue to investigate age-related differences and the association with tics and other sensory symptoms.
A study of the effects of screen exposure on the neuropsychological development in children with autism spectrum disorders based on ScreenQ
Authors: Peng Xinyue , Xue Yang , Dong Hanyu , Ma Chi , Jia Feiyong , Du Lin 
Published: May 2024

Abstract
Purpose
To investigate the relationship between multi-dimensional aspects of screen exposure and autistic symptoms, as well as neuropsychological development in children with ASD.

Methods
We compared the ScreenQ and Griffiths Development Scales-Chinese Language Edition (GDS-C) of 636 ASD children (40.79 ± 11.45 months) and 43 typically developing (TD) children (42.44 ± 9.61 months). Then, we analyzed the correlations between ScreenQ and Childhood Autism Rating Scale (CARS), and GDS-C. We further used linear regression model to analyze the risk factors associated with high CARS total scores and low development quotients (DQs) in children with ASD.

Results
The CARS of children with ASD was positively correlated with the ScreenQ total scores and “access, frequency, co-viewing” items of ScreenQ. The personal social skills DQ was negatively correlated with the “access, frequency, content, co-viewing and total scores” of ScreenQ. The hearing-speech DQ was negatively correlated with the “frequency, content, co-viewing and total scores” of ScreenQ. The eye-hand coordination DQ was negatively correlated with the “frequency and total scores” of ScreenQ. The performance DQ was negatively correlated with the “frequency” item of ScreenQ.

Conclusion
ScreenQ can be used in the study of screen exposure in children with ASD. The higher the ScreenQ scores, the more severe the autistic symptoms tend to be, and the more delayed the development of children with ASD in the domains of personal-social, hearing-speech and eye-hand coordination. In addition, “frequency” has the greatest impact on the domains of personal social skills, hearing-speech, eye-hand coordination and performance of children with ASD.
Exacerbation of central serous chorioretinopathy during trauma-confronting psychotherapy– a case report
Authors: Schäflein Eva , Mardin Christian , Morawa Eva , Rudolf Sophia , Erim Yesim , Rhein Cosima 
Published: May 2024

Abstract
Background
Psychotherapy for post-traumatic stress disorder, in particular trauma-confronting psychotherapy, can be associated with increased stress. However, research on the somatic impact and psychosomatic interactions of these psychological stress reactions is lacking. We report on a 43-year old man whose central serous chorioretinopathy exacerbated upon trauma-confronting psychotherapy.

Case presentation
We report on a man with pre-diagnosed, asymptomatic central serous chorioretinopathy who underwent inpatient psychosomatic therapy. He disclosed a history of sexual abuse by a family member and consequently showed intrusions, flashbacks, nightmares, avoidance behavior, and hyperarousal. Thus, we diagnosed post-traumatic stress disorder. After a stabilization phase, he underwent trauma-focused psychotherapy including trauma confrontation. In the course of this treatment, acute vision loss with blurred vision and image distortion of his right eye occurred. An ophthalmologic visit confirmed a relapse of a pre-diagnosed central serous chorioretinopathy. The analysis of stress biomarkers showed a decrease in testosterone levels and a noon peak in diurnal cortisol secretion, which is indicative of a stress reaction.

Conclusion
Central serous chorioretinopathy may exacerbate upon psychotherapeutic treatment. In this case, an exacerbation of chorioretinopathy was observed in direct relation to the therapeutic intervention. Psychotherapists and ophthalmologists should collaborate in the psychotherapeutic treatment of patients with chorioretinopathy. Our case demonstrates the need to consider the possible increased stress levels during psychotherapy and resulting physical side effects, such as exacerbation of an existing condition. It is advisable to adjust the level of generated stress particularly well in the presence of stress-inducible physical diseases. Our case is a good example of the interplay between psychological and physical stress.
Characteristics of children readmitted with severe pneumonia in Kenyan hospitals
Authors: Marangu-Boore Diana , Mwaniki Paul , Isaaka Lynda , Njoroge Teresiah , Mumelo Livingstone , Kimego Dennis , Adem Achieng , Jowi Elizabeth , Ithondeka Angeline , Wanyama Conrad , Agweyu Ambrose 
Published: May 2024

Abstract
Background
Pneumonia is a leading cause of childhood morbidity and mortality. Hospital re-admission may signify missed opportunities for care or undiagnosed comorbidities.

Methods
We conducted a retrospective cohort study including children aged $$\ge$$
≥
2 months-14 years hospitalised with severe pneumonia between 2013 and 2021 in a network of 20 primary referral hospitals in Kenya. Severe pneumonia was defined using the 2013 World Health Organization criteria, and re-admission was based on clinical documentation from individual patient case notes. We estimated the prevalence of re-admission, described clinical management practices, and modelled risk factors for re-admission and inpatient mortality.

Results
Among 20,603 children diagnosed with severe pneumonia, 2,274 (11.0%, 95% CI 10.6–11.5) were readmitted. Re-admission was independently associated with age (12–59 months vs. 2–11 months: adjusted odds ratio (aOR) 1.70, 1.54–1.87; >5 years vs. 2–11 months: aOR 1.85, 1.55–2.22), malnutrition (weight-for-age-z-score (WAZ) <-3SD vs. WAZ> -2SD: aOR 2.05, 1.84–2.29); WAZ − 2 to -3 SD vs. WAZ> -2SD: aOR 1.37, 1.20–1.57), wheeze (aOR 1.17, 1.03–1.33) and presence of a concurrent neurological disorder (aOR 4.42, 1.70-11.48). Chest radiography was ordered more frequently among those readmitted (540/2,274 [23.7%] vs. 3,102/18,329 [16.9%], p < 0.001). Readmitted patients more frequently received second-line antibiotics (808/2,256 [35.8%] vs. 5,538/18,173 [30.5%], p < 0.001), TB medication (69/2,256 [3.1%] vs. 298/18,173 [1.6%], p < 0.001), salbutamol (530/2,256 [23.5%] vs. 3,707/18,173 [20.4%], p = 0.003), and prednisolone (157/2,256 [7.0%] vs. 764/18,173 [4.2%], p < 0.001). Inpatient mortality was 2,354/18,329 (12.8%) among children admitted with a first episode of severe pneumonia and 269/2,274 (11.8%) among those who were readmitted (adjusted hazard ratio (aHR) 0.93, 95% CI 0.82–1.07). Age (12–59 months vs. 2–11 months: aHR 0.62, 0.57–0.67), male sex (aHR 0.81, 0.75–0.88), malnutrition (WAZ <-3SD vs. WAZ >-2SD: aHR 1.87, 1.71–2.05); WAZ − 2 to -3 SD vs. WAZ >-2SD: aHR 1.46, 1.31–1.63), complete vaccination (aHR 0.74, 0.60–0.91), wheeze (aHR 0.87, 0.78–0.98) and anaemia (aHR 2.14, 1.89–2.43) were independently associated with mortality.

Conclusions
Children readmitted with severe pneumonia account for a substantial proportion of pneumonia hospitalisations and deaths. Further research is required to develop evidence-based approaches to screening, case management, and follow-up of children with severe pneumonia, prioritising those with underlying risk factors for readmission and mortality.
Association between sleep patterns and galectin-3 in a Chinese community population
Authors: Liu Lin , Zhen Juanying , Liu Shuyun , Ren Lijie , Zhao Guoru , Liang Jianguo , Xu Aimin , Li Chao , Wu Jun , Cheung Bernard Man Yung 
Published: May 2024

Abstract
Background
Irregular sleep patterns have been associated with inflammation. Galectin-3, a novel biomarker, plays an important role in inflammation. We investigated the relationship between sleep patterns and galectin-3 in a Chinese population.

Methods
A total of 1,058 participants from the Shenzhen-Hong Kong United Network on Cardiovascular Disease study were included in the analysis. Age and sex-adjusted linear regression models were employed to investigate the relationship between galectin-3 level and traditional metabolic biomarkers. Logistic regression models were used to estimate the association among sleep disturbance, nighttime sleep duration, and daytime napping duration and elevated galectin-3, with elevated galectin-3 defined as galectin-3 level > 65.1 ng/ml.

Results
Of study participants, the mean age was 45.3 years and 54.3% were women. Waist circumference, natural logarithm (ln)-transformed triglyceride, and ln-transformed high sensitivity C-reactive protein were positively associated with galectin-3 level (age and sex-adjusted standardized β [95% confidence interval (CI)], 0.12 [0.04, 0.21], 0.11 [0.05, 0.17], and 0.08 [0.02, 0.14], respectively). Sleep disturbance was associated with elevated galectin-3 (odds ratio [95% CI], 1.68 [1.05, 2.68], compared to those without sleep disturbance) after adjusting for traditional metabolic biomarkers. No interaction was observed between galectin-3 and age, sex, obesity, hypertension, and diabetes on sleep disturbance. No association was found between nighttime sleep duration or daytime napping duration and elevated galectin-3.

Conclusions
Our study provides evidence of a significant association between sleep disturbance and elevated galectin-3 level, independent of traditional metabolic biomarkers. Screening and interventions on galectin-3 could assist in preventing sleep disturbance-induced inflammatory disease.
al-BERT: a semi-supervised denoising technique for disease prediction
Authors: Tseng Yun-Chien , Kuo Chuan-Wei , Peng Wen-Chih , Hung Chih-Chieh 
Published: May 2024

Abstract
Background
Medical records are a valuable source for understanding patient health conditions. Doctors often use these records to assess health without solely depending on time-consuming and complex examinations. However, these records may not always be directly relevant to a patient’s current health issue. For instance, information about common colds may not be relevant to a more specific health condition. While experienced doctors can effectively navigate through unnecessary details in medical records, this excess information presents a challenge for machine learning models in predicting diseases electronically. To address this, we have developed ‘al-BERT’, a new disease prediction model that leverages the BERT framework. This model is designed to identify crucial information from medical records and use it to predict diseases. ‘al-BERT’ operates on the principle that the structure of sentences in diagnostic records is similar to regular linguistic patterns. However, just as stuttering in speech can introduce ‘noise’ or irrelevant information, similar issues can arise in written records, complicating model training. To overcome this, ‘al-BERT’ incorporates a semi-supervised layer that filters out irrelevant data from patient visitation records. This process aims to refine the data, resulting in more reliable indicators for disease correlations and enhancing the model’s predictive accuracy and utility in medical diagnostics.

Method
To discern noise diseases within patient records, especially those resembling influenza-like illnesses, our approach employs a customized semi-supervised learning algorithm equipped with a focused attention mechanism. This mechanism is specifically calibrated to enhance the model’s sensitivity to chronic conditions while concurrently distilling salient features from patient records, thereby augmenting the predictive accuracy and utility of the model in clinical settings. We evaluate the performance of al-BERT using real-world health insurance data provided by Taiwan’s National Health Insurance.

Result
In our study, we evaluated our model against two others: one based on BERT that uses complete disease records, and another variant that includes extra filtering techniques. Our findings show that models incorporating filtering mechanisms typically perform better than those using the entire, unfiltered dataset. Our approach resulted in improved outcomes across several key measures: AUC-ROC (an indicator of a model’s ability to distinguish between classes), precision (the accuracy of positive predictions), recall (the model’s ability to find all relevant cases), and overall accuracy. Most notably, our model showed a 15% improvement in recall compared to the current best-performing method in the field of disease prediction.

Conclusion
The conducted ablation study affirms the advantages of our attention mechanism and underscores the crucial role of the selection module within al-BERT.
BarlowTwins-CXR: enhancing chest X-ray abnormality localization in heterogeneous data with cross-domain self-supervised learning
Authors: Sheng Haoyue , Ma Linrui , Samson Jean-François , Liu Dianbo 
Published: May 2024

Abstract
Background
Chest X-ray imaging based abnormality localization, essential in diagnosing various diseases, faces significant clinical challenges due to complex interpretations and the growing workload of radiologists. While recent advances in deep learning offer promising solutions, there is still a critical issue of domain inconsistency in cross-domain transfer learning, which hampers the efficiency and accuracy of diagnostic processes.
This study aims to address the domain inconsistency problem and improve autonomic abnormality localization performance of heterogeneous chest X-ray image analysis, particularly in detecting abnormalities, by developing a self-supervised learning strategy called “BarlwoTwins-CXR”.

Methods
We utilized two publicly available datasets: the NIH Chest X-ray Dataset and the VinDr-CXR. The BarlowTwins-CXR approach was conducted in a two-stage training process. Initially, self-supervised pre-training was performed using an adjusted Barlow Twins algorithm on the NIH dataset with a Resnet50 backbone pre-trained on ImageNet. This was followed by supervised fine-tuning on the VinDr-CXR dataset using Faster R-CNN with Feature Pyramid Network (FPN). The study employed mean Average Precision (mAP) at an Intersection over Union (IoU) of 50% and Area Under the Curve (AUC) for performance evaluation.

Results
Our experiments showed a significant improvement in model performance with BarlowTwins-CXR. The approach achieved a 3% increase in mAP50 accuracy compared to traditional ImageNet pre-trained models. In addition, the Ablation CAM method revealed enhanced precision in localizing chest abnormalities. The study involved 112,120 images from the NIH dataset and 18,000 images from the VinDr-CXR dataset, indicating robust training and testing samples.

Conclusion
BarlowTwins-CXR significantly enhances the efficiency and accuracy of chest X-ray image-based abnormality localization, outperforming traditional transfer learning methods and effectively overcoming domain inconsistency in cross-domain scenarios. Our experiment results demonstrate the potential of using self-supervised learning to improve the generalizability of models in medical settings with limited amounts of heterogeneous data. This approach can be instrumental in aiding radiologists, particularly in high-workload environments, offering a promising direction for future AI-driven healthcare solutions.