bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perception of the operation theater learning environment and related factors among anesthesia students in Ethiopian higher education teaching hospitals: a multicenter cross-sectional study
Authors: Wubshet Habtemariam , Agegnehu Abatneh Feleke , Workie Misganaw Mengie , Addisu Yonas 
Published: March 2024

Abstract
Introduction
Operation theater learning involves three key elements: clinical work, learning, and the environment. There is little evidence regarding the operating theatre learning environment for anesthesia trainees. Identifying the overall perception of the operation theater learning environment helps to establish an efficient operation theater learning environment and produce competent anesthesia professionals.

Objective
The aim of this study was to assess the perceptions of the operating theater learning environment and associated factors among undergraduate anesthesia students in Ethiopian higher education teaching hospitals from April to May 2023.

Methods
A multicenter cross-sectional study was conducted on 313 undergraduate anesthesia students who began operation room clinical practice at 13 higher education teaching hospitals. The data were entered into EpiData version 4.6. A generalized ordered logistic regression model was used to analyze and identify factors associated with the operating theater learning environment using STATA software version MP17.

Results
The findings of this study revealed that 45.05%,26.52%), 23% and 5.43% of the participants reported having desirable, moderately desirable, very desirable and undesirable perceptions of the operating theater learning environment, respectively, from highest to lowest. Preoperative discussion (AOR = 4.98 CI = 1.3–18.8), lack of teaching facilities (AOR = 0.16 CI = 0.03–0.75), noise from played music (AOR = 0.22 CI = 0.07–0.63), absence of tutors (AOR = 0.03 CI = 0.01–0.22), respect for students (AOR = 3.44 CI = 1.6–7.2), roll modeling for students (AOR = 3.23 CI = 1.5–6.8) and strict supervision of students (AOR = 0.24 CI = 0.07–0.88) were significantly associated with perceptions of the operation theater learning environment, with 95% CIs.

Conclusion
No study participant agreed that the operation theater learning environment in operation theatres was very undesirable. A lack of teaching facilities at the OR, a lack of tutors from the OR, noise from played music in the OR, a tutor respecting their student, a tutor role model for their student, a preoperative discussion with a tutor and strict supervision of the student are strongly associated with the operation theatre learning environment.
What are the views of Quebec and Ontario citizens on the tiebreaker criteria for prioritizing access to adult critical care in the extreme context of a COVID-19 pandemic?
Authors: Calderon Ramirez Claudia , Farmer Yanick , Frolic Andrea , Bravo Gina , Gaucher Nathalie Orr , Payot Antoine , Opatrny Lucie , Poirier Diane , Dahine Joseph , L’Espérance Audrey , Downar James , Tanuseputro Peter , Rousseau Louis-Martin , Dumez Vincent , Descôteaux Annie , Dallaire Clara , Laporte Karell , Bouthillier Marie-Eve 
Published: March 2024

Abstract
Background
The prioritization protocols for accessing adult critical care in the extreme pandemic context contain tiebreaker criteria to facilitate decision-making in the allocation of resources between patients with a similar survival prognosis. Besides being controversial, little is known about the public acceptability of these tiebreakers. In order to better understand the public opinion, Quebec and Ontario’s protocols were presented to the public in a democratic deliberation during the summer of 2022.

Objectives
(1) To explore the perspectives of Quebec and Ontario citizens regarding tiebreakers, identifying the most acceptable ones and their underlying values. (2) To analyze these results considering other public consultations held during the pandemic on these criteria.

Methods
This was an exploratory qualitative study. The design involved an online democratic deliberation that took place over two days, simultaneously in Quebec and Ontario. Public participants were selected from a community sample which excluded healthcare workers. Participants were first presented the essential components of prioritization protocols and their related issues (training session day 1). They subsequently deliberated on the acceptability of these criteria (deliberation session day 2). The deliberation was then subject to thematic analysis.

Results
A total of 47 participants from the provinces of Quebec (n = 20) and Ontario (n = 27) took part in the online deliberation. A diverse audience participated excluding members of the healthcare workforce. Four themes were identified: (1) Priority to young patients - the life cycle - a preferred tiebreaker; (2) Randomization - a tiebreaker of last resort; (3) Multiplier effect of most exposed healthcare workers - a median acceptability tiebreaker, and (4) Social value – a less acceptable tiebreaker.

Conclusion
Life cycle was the preferred tiebreaker as this criterion respects intergenerational equity, which was considered relevant when allocating scarce resources to adult patients in a context of extreme pandemic. Priority to young patients is in line with other consultations conducted around the world. Additional studies are needed to further investigate the public acceptability of tiebreaker criteria.
Enhancing automated lower limb rehabilitation exercise task recognition through multi-sensor data fusion in tele-rehabilitation
Authors: Ettefagh Alireza , Roshan Fekr Atena 
Published: March 2024

AbstractBackgroundTele-rehabilitation is the provision of physiotherapy services to individuals in their own homes. Activity recognition plays a crucial role in the realm of automatic tele-rehabilitation. By assessing patient movements, identifying exercises, and providing feedback, these platforms can offer insightful information to clinicians, thereby facilitating an improved plan of care. This study introduces a novel deep learning approach aimed at identifying lower limb rehabilitation exercises. This is achieved through the integration of depth data and pressure heatmaps. We hypothesized that combining pressure heatmaps and depth data could improve the model’s overall performance.MethodsIn this study, depth videos and body pressure data from an accessible online dataset were used. This dataset comprises data from 30 healthy individuals performing 7 lower limb rehabilitation exercises. To accomplish the classification task, three deep learning models were developed, all based on an established 3D-CNN architecture. The models were designed to classify the depth videos, sequences of pressure data frames, and combination of depth videos and pressure frames. The models’ performance was assessed through leave-one-subject-out and leave-multiple-subjects-out cross-validation methods. Performance metrics, including accuracy, precision, recall, and F1 score, were reported for each model.ResultsOur findings indicated that the model trained on the fusion of depth and pressure data showed the highest and most stable performance when compared with models using individual modality inputs. This model could effectively identify the exercises with an accuracy of 95.71%, precision of 95.83%, recall of 95.71%, and an F1 score of 95.74%.ConclusionOur results highlight the impact of data fusion for accurately classifying lower limb rehabilitation exercises. We showed that our model could capture different aspects of exercise movements using the visual and weight distribution data from the depth camera and pressure mat, respectively. This integration of data provides a better representation of exercise patterns, leading to higher classification performance. Notably, our results indicate the potential application of this model in automatic tele-rehabilitation platforms.
Impact of an oral care subsidization reform on intersectional inequities in self-rated oral health in Sweden
Authors: Anticona Cynthia , Suominen Anna Liisa , Holgerson Pernilla Lif , Gustafsson Per E 
Published: March 2024

Abstract
Background
Oral health in Sweden is good at the population level, but seemingly with persisting or increasing inequities over the last decades. In 2008, a major Swedish reform introduced universal partial subsidies to promote preventive care and reduce the treatment cost for patients with extensive care needs. This study aimed to apply an intersectional approach to assess the impact of the 2008 subsidization reform on inequities in self-rated oral health among adults in Sweden over the period 2004–2018.

Methods
Data from 14 national surveys conducted over 2004–2018 were divided into three study periods: pre-reform (2004–2007), early post-reform (2008–2012) and late post-reform (2013–2018). The final study population was 118,650 individuals aged 24–84 years. Inequities in self-rated oral health were examined by intersectional analysis of individual heterogeneity and discriminatory accuracy across 48 intersectional strata defined by gender, age, educational level, income, and immigrant status.

Results
Overall, the prevalence of poor self-rated oral health decreased gradually after the reform. Gender-, education- and income-related inequities increased after the reform, but no discernible change was seen for age- or immigration-related inequities. The majority of intersectional strata experienced patterns of persistently or delayed increased inequities following the reform.

Conclusions
Increased inequities in self-rated oral health were found in most intersectional strata following the reform, despite the seemingly positive oral health trends at the population level. Applying an intersectional approach might be particularly relevant for welfare states with overall good oral health outcomes but unsuccessful efforts to reduce inequities.
Clinical effectiveness of a multitarget urine DNA test for urothelial carcinoma detection: a double-blinded, multicenter, prospective trial
Authors: Wu Junlong , Lin Yuda , Yang Kaiwei , Liu Xiao , Wang Huina , Yu Tingting , Tao Ran , Guo Jing , Chen Libin , Cheng Huanqing , Lou Feng , Cao Shanbo , Yu Wei , Hu Hailong , Ye Dingwei 
Published: March 2024

AbstractUrine-based testing is promising for noninvasive diagnosis of urothelial carcinoma (UC) but has suboptimal sensitivity for early-stage tumors. Herein, we developed a multitarget urine tumor DNA test, UI-Seek, for UC detection and evaluated its clinical feasibility. The prediction model was developed in a retrospective cohort (n = 382), integrating assays for FGFR3 and TERT mutations and aberrant ONECUT2 and VIM methylation to generate a UC-score. The test performance was validated in a double-blinded, multicenter, prospective trial (n = 947; ChiCTR2300076543) and demonstrated a sensitivity of 91.37% and a specificity of 95.09%. The sensitivity reached 75.81% for low-grade Ta tumors and exceeded 93% in high-grade Ta and higher stages (T1 to T4). Simultaneous identification of both bladder and upper urinary tract tumors was enabled with sensitivities exceeding 90%. No significant confounding effects were observed regarding benign urological diseases or non-UC malignancies. The test showed improved sensitivities over urine cytology, the NMP22 test, and UroVysion FISH alongside comparable specificities. The single-target accuracy was greater than 98% as confirmed by Sanger sequencing. Post-surgery UC-score decreased in 97.7% of subjects. Overall, UI-Seek demonstrated robust performance and considerable potential for the early detection of UC.
Two cases of venous thromboembolism in siblings after splenectomy due to a novel PROC gene mutation
Authors: Zhang Yunfang , Wang Bo , Bai Yuxin , Wang Anxin 
Published: March 2024

Abstract
Background
Venous thromboembolism(VTE)is a common multifactorial disease. Anticoagulant protein deficiency is the most usual hereditary thrombophilia in the Chinese people, which includes protein C(PC), protein S and antithrombin deficiencies.

Case presentation
A retrospective analysis was conducted on clinical manifestations, laboratory tests, genetic information, and other relevant data of siblings diagnosed with VTE in 2020 at the Department of Pediatrics of Shenzhen Second People’s Hospital. The proband, a 12-year-old female, was admitted to the hospital in December 2020 with a complaint of pain in the left lower limb for four days. The examination found that the PC activity was 53%, and B-ultrasound showed bilateral thrombosis of the great saphenous vein in the thigh segment. The proband’s younger brother, a 10-year-old male, was admitted to the hospital in January 2021 due to right lower limb pain for two weeks. PC activity is 40%. B-ultrasound showed superficial venous thrombosis in the left lower limb and upper limb. Both siblings suffered from thalassemia and underwent splenectomy before recurrent thrombosis occurred. The proband’s mother was asymptomatic, and her PC activity was 45%. Both cases were treated with warfarin anticoagulation, and their symptoms improved. The proband’s mother was found to have a heterozygous mutation at this locus through Sanger sequencing.

Conclusion
Protein C deficiency should be considered for venous thromboembolism in childhood. The heterozygous mutation 1204 A > G in PROC exon 9 in this family is reported for the first time.
A meta-analysis and trial sequential analysis of randomised controlled trials comparing nonoperative and operative management of chest trauma with multiple rib fractures
Authors: Hisamune Ryo , Kobayashi Mako , Nakasato Karin , Yamazaki Taiga , Ushio Noritaka , Mochizuki Katsunori , Takasu Akira , Yamakawa Kazuma 
Published: March 2024

Abstract
Background
Operative treatment of traumatic rib fractures for better outcomes remains under debate. Surgical stabilization of rib fractures has dramatically increased in the last decade. This study aimed to perform a systematic review and meta-analysis of randomised controlled trials (RCTs) to assess the effectiveness and safety of operative treatment compared to conservative treatment in adult patients with traumatic multiple rib fractures.

Methods
A systematic literature review was performed according to the preferred reporting items for systematic reviews and meta-analyses guidelines. We searched MEDLINE, Scopus, and Cochrane Central Register of Controlled Trials and used the Cochrane Risk-of-Bias 2 tool to evaluate methodological quality. Relative risks with 95% confidence interval (CI) were calculated for outcomes: all-cause mortality, pneumonia incidence, and number of mechanical ventilation days. Overall certainty of evidence was evaluated with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, with trial sequential analysis performed to establish implications for further research.

Results
From 719 records, we included nine RCTs, which recruited 862 patients. Patients were assigned to the operative group (received surgical stabilization of chest wall injury, n = 423) or control group (n = 439). All-cause mortality was not significantly different (RR = 0.53; 95% CI 0.21 to 1.38, P = 0.35, I2 = 11%) between the two groups. However, in the operative group, duration of mechanical ventilation (mean difference -4.62; 95% CI -7.64 to -1.60, P < 0.00001, I2 = 94%) and length of intensive care unit stay (mean difference -3.05; 95% CI -5.87 to -0.22; P < 0.00001, I2 = 96%) were significantly shorter, and pneumonia incidence (RR = 0.57; 95% CI 0.35 to 0.92; P = 0.02, I2 = 57%) was significantly lower. Trial sequential analysis for mortality indicated insufficient sample size for a definitive judgment. GRADE showed this meta-analysis to have very low to low confidence.

Conclusion
Meta-analysis of large-scale trials showed that surgical stabilization of multiple rib fractures shortened the duration of mechanical ventilation and reduced the incidence of pneumonia but lacked clear evidence for improvement of mortality compared to conservative treatment. Trial sequential analysis suggested the need for more cases, and GRADE highlighted low certainty, emphasizing the necessity for further targeted RCTs, especially in mechanically ventilated patients.
Systematic review registration: UMIN Clinical Trials Registry UMIN000049365.
Postoperative hyper-inflammation as a predictor of poor outcomes in patients with acute type A aortic dissection (ATAAD) undergoing surgical repair
Authors: Luo Yuan-Xi , Matniyaz Yusanjan , Tang Yu-Xian , Xue Yun-Xing , Jiang Yi , Pan Ke , Lv Zhi-Kang , Fan Zhi-Wei , Wang Kuo , Zhang Hai-Tao , Zhang He , Wang Wen-Zhe , Pan Tuo , Wang Dong-Jin , Fan Fu-Dong 
Published: March 2024

Abstract
Background
Postoperative hyper-inflammation is a frequent event in patients with acute Stanford type A aortic dissection (ATAAD) after surgical repair. This study's objective was to determine which inflammatory biomarkers could be used to make a better formula for identifying postoperative hyper-inflammation, and which risk factors were associated with hyper-inflammation.

Methods
A total of 405 patients were enrolled in this study from October 1, 2020 to April 1, 2023. Of these patients, 124 exhibited poor outcomes. In order to investigate the optimal cut-off values for poor outcomes, logistic and receiver operating characteristic analyses were performed on the following parameters on the first postoperative day: procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), and systemic immune-inflammation index (SII). These cut-off points were used to separate the patients into hyper-inflammatory (n = 52) and control (n = 353) groups. Finally, the logistic were used to find the risk factors of hyper-inflammatory.

Results
PCT, CRP, IL-6, and SII were independent risk factors of poor outcomes in the multivariate logistic model. Cut-off points of these biomarkers were 2.18 ng/ml, 49.76 mg/L, 301.88 pg/ml, 2509.96 × 109/L respectively. These points were used to define postoperative hyper-inflammation (OR 2.97, 95% CI 1.35–6.53, P < 0.01). Cardiopulmonary bypass (CPB) > 180 min, and deep hypothermia circulatory arrest (DHCA) > 40 min were the independent risk factors for hyper-inflammation.

Conclusions
PCT > 2.18, CRP > 49.76, IL-6 > 301.88, and SII < 2509.96 could be used to define postoperative hyper-inflammation which increased mortality and morbidity in patients after ATAAD surgery. Based on these findings, we found that CPB > 180 min and DHCA > 40 min were separate risk factors for postoperative hyper-inflammation.
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer’s disease in patients with mild cognitive symptoms
Authors: Arvidsson Ida , Strandberg Olof , Palmqvist Sebastian , Stomrud Erik , Cullen Nicholas , Janelidze Shorena , Tideman Pontus , Heyden Anders , Åström Karl , Hansson Oskar , Mattsson-Carlgren Niklas 
Published: March 2024

Abstract
Background
Predicting future Alzheimer’s disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be improved using entire brain images in deep learning (DL) models compared to using pre-defined brain regions.

Methods
A cohort of 332 individuals with SCD/MCI were included from the Swedish BioFINDER-1 study. The goal was to predict longitudinal SCD/MCI-to-AD dementia progression and change in Mini-Mental State Examination (MMSE) over four years. Four models were evaluated using different predictors: (1) clinical data only, including demographics, cognitive tests and APOE ε4 status, (2) clinical data plus hippocampal volume, (3) clinical data plus all regional MRI gray matter volumes (N = 68) extracted using FreeSurfer software, (4) a DL model trained using multi-task learning with MRI images, Jacobian determinant images and baseline cognition as input. A double cross-validation scheme, with five test folds and for each of those ten validation folds, was used. External evaluation was performed on part of the ADNI dataset, including 108 patients. Mann-Whitney U-test was used to determine statistically significant differences in performance, with p-values less than 0.05 considered significant.

Results
In the BioFINDER cohort, 109 patients (33%) progressed to AD dementia. The performance of the clinical data model for prediction of progression to AD dementia was area under the curve (AUC) = 0.85 and four-year cognitive decline was R2 = 0.14. The performance was improved for both outcomes when adding hippocampal volume (AUC = 0.86, R2 = 0.16). Adding FreeSurfer brain regions improved prediction of four-year cognitive decline but not progression to AD (AUC = 0.83, R2 = 0.17), while the DL model worsened the performance for both outcomes (AUC = 0.84, R2 = 0.08). A sensitivity analysis showed that the Jacobian determinant image was more informative than the MRI image, but that performance was maximized when both were included. In the external evaluation cohort from ADNI, 23 patients (21%) progressed to AD dementia. The results for predicted progression to AD dementia were similar to the results for the BioFINDER test data, while the performance for the cognitive decline was deteriorated.

Conclusions
The DL model did not significantly improve the prediction of clinical disease progression in AD, compared to regression models with a single pre-defined brain region.
Hybrid modeling design patterns
Authors: Rudolph Maja , Kurz Stefan , Rakitsch Barbara 
Published: March 2024

AbstractDesign patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling techniques. While both approaches have complementary advantages there are often multiple ways to combine them into a hybrid model, and the appropriate solution will depend on the problem at hand. In this paper, we provide four base patterns that can serve as blueprints for combining data-driven components with domain knowledge into a hybrid approach. In addition, we also present two composition patterns that govern the combination of the base patterns into more complex hybrid models. Each design pattern is illustrated by typical use cases from application areas such as climate modeling, engineering, and physics.
AGV monocular vision localization algorithm based on Gaussian saliency heuristic
Authors: Fu Heng , Hu Yakai , Zhao Shuhua , Zhu Jianxin , Liu Benxue , Yang Zhen 
Published: March 2024

AbstractTo address the issues of poor detection accuracy and the large number of target detection model parameters in existing AGV monocular vision location detection algorithms, this paper presents an AGV vision location method based on Gaussian saliency heuristic. The proposed method introduces a fast and accurate AGV visual detection network called GAGV-net. In the GAGV-net network, a Gaussian saliency feature extraction module is designed to enhance the network’s feature extraction capability, thereby reducing the required output for model fitting. To improve the accuracy of target detection, a joint multi-scale classification and detection task header are designed at the stage of target frame regression to classification. This header utilizes target features of different scales, thereby enhancing the accuracy of target detection. Experimental results demonstrate a 12% improvement in detection accuracy and a 27.38 FPS increase in detection speed compared to existing detection methods. Moreover, the proposed detection network significantly reduces the model’s size, enhances the network model’s deployability on AGVs, and greatly improves detection accuracy.