bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of clinical competence of graduating medical students and associated factors in Ethiopia
Authors: Dejene Daniel , Ayalew Firew , Yigzaw Tegbar , Woretaw Alemseged , Versluis Marco , Stekelenburg Jelle 
Published: January 2024

Abstract
Background
Ethiopia has scaled up medical education to improve access to healthcare which presented challenges to maintaining training quality. We conducted a study to assess the clinical competence of graduating medical students and the associated factors.

Methods and materials
A pretest assessment of a quasi-experimental study was conducted in 10 medical schools with a sample size of 240 students. We randomly selected 24 students per school. Clinical competence was assessed in a 12-station objective structured clinical examination. The clinical learning environment (CLE), simulation training, and practice exposure were self-rated. Mean scores for clinical competence, and satisfaction in the CLE and simulation training were calculated. Proportions of students with practice exposure, and who agreed on CLE and simulation items were done. Independent t-tests were used to look at competence differences among subgroups. Bivariate and multiple linear regression models were fitted for the outcome variable: competence score. A 95% statistical confidence interval and p-value < 0.05 were used for making statistical decisions. A 75% cut-off score was used to compare competence scores.

Results
Graduating medical students had a mean competence score of 72%. Low scores were reported in performing manual vacuum aspiration (62%), lumbar puncture (64%), and managing childbirth (66%). Female students (73%) had a significantly higher competence score than males (70%). Higher cumulative grade point average (CGPA), positive appraisal of the CLE, and conducting more clinical procedures were associated with greater competence scores. Nearly half of the students were not satisfied with the clinical practice particularly due to the large student number and issues affecting the performance assessment. About two-thirds of the students were not satisfied with the sufficiency of models and equipment, and the quality of feedback during simulation training. Nearly one-third of the students never performed lumbar puncture, manual vacuum aspiration, and venipuncture.

Conclusions
Medical students had suboptimal clinical competence. A better clinical learning environment, higher cumulative GPA, and more practice exposure are associated with higher scores. There is a need to improve student clinical practice and simulation training. Strengthening school accreditation and graduates’ licensing examinations is also a way forward.
Development of the EVIBEC Learning Outcomes Framework to support the delivery of evidence-based practice curricula in health care professional programmes: a codesign approach
Authors: Redmond Catherine , Farrell Robin , Cunningham Catriona , Dineen Andrea , Foley Shane , O’Donnell Deirdre , O’Reilly Sharleen , Stokes Diarmuid , O’Neill Emma 
Published: January 2024

Abstract
Background
All healthcare professional education programmes must adopt a systematic approach towards ensuring graduates achieve the competencies required to be an evidence-based practitioner. While a list of competencies for evidence-based practice exist, health care educators continue to struggle with effectively integrating the necessary competencies into existing curricula. The purpose of this project was to develop an open access cross-discipline, learning outcomes framework to support educators in integrating the teaching, learning and assessment required to ensure all graduates of health care professional programmes can achieve the necessary evidence-based practice competencies.

Methods
An interdisciplinary team of health care professional educators and a librarian completed a review of the health professions literature on the teaching and assessment of evidence-based practice. The literature, coupled with the teams’ collective experiences in evidence-based education and research, were used to identify relevant teaching, learning and evidence-based competency frameworks to inform the project design. The guide and toolkit for experience-based co-design developed by the National Health Service Institute for Innovation and Improvement was adopted for this study ( Institute for Innovation and Improvement: Experience Based Design: Guide & Tools In. Leeds: NHS; 2009.). A four-step approach involving three online participatory co-design workshops and a national validation workshop was designed. Students (n = 33), faculty (n = 12), and clinical educators (n = 15) participated in formulating and mapping learning outcomes to evidence-based competencies.

Results
Through a rigorous, systematic co-design process the Evidenced-based Education Collaborative (EVIBEC) Learning Outcomes Framework was developed. This framework consists of a series of student-centred learning outcomes, aligned to evidence-based practice competencies, classified according to the 5 As of EBP and mapped to the cognitive levels of Bloom’s taxonomy. Associated learning activities for each step of EBP are suggested.

Conclusions
A consensus-based, student-centred learning outcomes framework aligned to a contemporary set of EBP core competencies has been developed. The freely accessible EVIBEC framework may support entry level health care professional EBP education, by informing EBP curriculum development and offering the potential for interdisciplinary approaches to and sharing of valuable teaching and learning resources. Co-design proved an effective method in creating and refining this framework.
Quantitative association between lead exposure and amyotrophic lateral sclerosis: a Bayesian network-based predictive study
Authors: Yu Wenxiu , Yu Fangfang , Li Mao , Yang Fei , Wang Hongfen , Song Han , Huang Xusheng 
Published: January 2024

Abstract
Background
Environmental lead (Pb) exposure have been suggested as a causative factor for amyotrophic lateral sclerosis (ALS). However, the role of Pb content of human body in ALS outcomes has not been quantified clearly. The purpose of this study was to apply Bayesian networks to forecast the risk of Pb exposure on the disease occurrence.

Methods
We retrospectively collected medical records of ALS inpatients who underwent blood Pb testing, while matched controlled inpatients on age, gender, hospital ward and admission time according to the radio of 1:9. Tree Augmented Naïve Bayes (TAN), a semi-naïve Bayes classifier, was established to predict probability of ALS or controls with risk factors.

Results
A total of 140 inpatients were included in this study. The whole blood Pb levels of ALS patients (57.00 μg/L) were more than twice as high as the controls (27.71 μg/L). Using the blood Pb concentrations to calculate probability of ALS, TAN produced the total coincidence rate of 90.00%. The specificity, sensitivity of Pb for ALS prediction was 0.79, or 0.74, respectively.

Conclusion
Therefore, these results provided quantitative evidence that Pb exposure may contribute to the development of ALS. Bayesian networks may be used to predict the ALS early onset with blood Pb levels.
Predictors of antipsychotics switching among ambulatory patients with schizophrenia in Ethiopia: a multicenter hospital-based cross-sectional study
Authors: Kiflu Mekdes , Azale Telake , Gubae Kale , Agegnew Wondm Samuel , Mebratu Ephrem , EliasErgena Asrat , Abubeker Ousman , Mekonnen Gizework Alemnew 
Published: January 2024

Abstract
Introduction
A change of therapy from one to another antipsychotic medication is currently the main challenge of therapy. This study aimed to assess the prevalence of antipsychotic medication switches and determinants among patients with schizophrenia in Northwest Ethiopia.

Methods
Multi-center hospital-based cross-sectional study was conducted at five Comprehensive Specialized Hospitals found in Northwest Ethiopia from April 30, 2021, to August 30, 2021. Data were extracted from both patients’ medical charts and interviews. Data were entered into Epi-data software version 3.5.1 and exported to SPSS version 25.0 for analysis. A multivariable logistic regression model was fitted to identify factors associated with medication regimen switch. The level of significance of the study was kept at a p-value of 0.05 with a 95% confidence interval.

Result
A total of 414 patients are involved in the study, and 188 (45.5%) of patients switched antipsychotics within one year. The unavailability of the medication is the commonest reason for switching. Being male [AOR = 2.581, 95% CI (1.463, 4.552)], having relapse [AOR = 2.341,95% CI (1.169,4.687)], history of hospitalization in the past year [AOR = 3.00,95% CI (1.478,5.715)] and taking typical antipsychotics [AOR = 3.340, CI (1.76, 6.00)] had a significant association with antipsychotics switching.

Conclusions and recommendations
There is a high prevalence of antipsychotic switches among schizophrenia patients. Prescribers need to be careful while dosing, selecting, and switching antipsychotics, hence may help reduce discontinuation and unnecessary switch and thus achieve optimal clinical management.
Weight change following diagnosis with psychosis: a retrospective cohort study in Greater Manchester, UK
Authors: Heald Adrian , Daly Chris , Warner-Levy John Julian , Williams Richard , Meehan Cheyenne , Livingston Mark , Pillinger Toby , Hussain Lamiece , Firth Joseph 
Published: January 2024

Abstract
Introduction
Weight gain in the months/years after diagnosis/treatment of severe enduring mental illness (SMI) is a major predictor of future diabetes, dysmetabolic profile and increased risk of cardiometabolic diseases. There is limited data on the longer-term profile of weight change in people with a history of SMI and how this may differ between individuals. We here report a retrospective study on weight change over the 5 years following an SMI diagnosis in Greater Manchester UK, an ethnically and culturally diverse community, with particular focus on comparing non-affective psychosis (NAP) vs affective psychosis (AP) diagnoses.

Methods
We undertook an anonymised search in the Greater Manchester Care Record (GMCR). We reviewed the health records of anyone who had been diagnosed for the first time with first episode psychosis, schizophrenia, schizoaffective disorder, delusional disorder (non-affective psychosis = NAP) or affective psychosis (AP). We analysed body mass index (BMI) change in the 5-year period following the first prescription of antipsychotic medication. All individuals had taken an antipsychotic agent for at least 3 months. The 5-year follow-up point was anywhere between 2003 and 2023.

Results
We identified 9125 people with the diagnoses above. NAP (n = 5618; 37.3% female) mean age 49.9 years; AP (n = 4131; 60.5% female) mean age 48.7 years. 27.0% of NAP were of non-White ethnicity vs 17.8% of AP individuals. A higher proportion of people diagnosed with NAP were in the highest quintile of social disadvantage 52.4% vs 39.5% for AP. There were no significant differences in baseline BMI profile. In a subsample with HbA1c data (n = 2103), mean HbA1c was higher in NAP at baseline (40.4 mmol/mol in NAP vs 36.7 mmol/mol for AP). At 5-year follow-up, there was similarity in both the overall % of individuals in the obese ≥ 30 kg/m2 category (39.8% NAP vs 39.7% AP), and % progressing from a normal healthy BMI transitioned to obese/overweight BMI (53.6% of NAP vs 55.6% with AP). 43.7% of those NAP with normal BMI remained at a healthy BMI vs 42.7% with AP. At 5-year follow-up for NAP, 83.1% of those with BMI ≥ 30 kg/m2 stayed in this category vs 81.5% of AP.

Conclusion
The results of this real-world longitudinal cohort study suggest that the changes in BMI with treatment of non-affective psychosis vs bipolar disorder are not significantly different, while 43% maintain a healthy weight in the first 5 years following antipsychotic prescription.
Proximal junctional kyphosis in Lenke 5C adolescent idiopathic scoliosis after selective posterior thoracolumbar/lumbar fusion: risk factors and predictive index
Authors: Bai Jinyi , Liu Shu , Liu Chen , Zhao Yingchuan , Li Ming 
Published: January 2024

Abstract
Background
Although several studies have reported that selective posterior thoracolumbar/lumbar (TL/L) fusion can yield satisfactory results in Lenke 5C adolescent idiopathic scoliosis (AIS), the proximal junctional kyphosis (PJK) is still a common complication that occurs after surgery. The purpose of this study is to analyse the risk factors for postoperative proximal junctional kyphosis in Lenke 5C patients who underwent selective posterior TL/L fusion and explore whether PJK can be predicted.

Methods
A total of 83 AIS patients with Lenke 5C curves who met the inclusion criteria were analysed. All patients were divided into two groups based on the occurrence of postoperative PJK. Univariate and multivariate analyses were used to identify independent factors significantly associated with PJK, and an PJK index was proposed and verified.

Results
PJK was observed in 27 of 83 (32.5%) patients in the study. Preoperative thoracic kyphosis (TK) and the immediate postoperative proximal junctional angle (PJA) were the primary factors identified by the binary logistic regression analysis. The PJK index was defined as 1.1× preoperative TK + 2.3× immediate postoperative PJA. The receiver operating characteristics curve indicated that the occurrence rate of PJK was 85% and non-occurrence rate was 82% when the PJK index was greater than 42.

Conclusion
Large preoperative TK and a large immediate postoperative PJA play important roles in the development of PJK in Lenke 5C patients treated with selective posterior thoracolumbar/lumbar fusion. The PJK index can be used to predict the occurrence of PJK with high accuracy. To prevent the occurrence of PJK, we should pay attention to the TLK, and preserving more posterior proximal intervertebral elements at the upper instrumented vertebral level would be an important part of corrective surgery; however, moderate correction of the lumbar curve is recommended.
Development and external validation of a nomogram for predicting postoperative adverse events in elderly patients undergoing lumbar fusion surgery: comparison of three predictive models
Authors: Wang Shuai-Kang , Wang Peng , Li Zhong-En , Li Xiang-Yu , Kong Chao , Lu Shi-Bao 
Published: January 2024

Abstract
Background
The burden of lumbar degenerative diseases (LDD) has increased substantially with the unprecedented aging population. Identifying elderly patients with high risk of postoperative adverse events (AEs) and establishing individualized perioperative management is critical to mitigate added costs and optimize cost-effectiveness to the healthcare system. We aimed to develop a predictive tool for AEs in elderly patients with transforaminal lumbar interbody fusion (TLIF), utilizing multivariate logistic regression, single classification and regression tree (hereafter, “classification tree”), and random forest machine learning algorithms.

Methods
This study was a retrospective review of a prospective Geriatric Lumbar Disease Database (age ≥ 65). Our outcome measure was postoperative AEs, including prolonged hospital stays, postoperative complications, readmission, and reoperation within 90 days. Patients were grouped as either having at least one adverse event (AEs group) or not (No-AEs group). Three models for predicting postoperative AEs were developed using training dataset and internal validation using testing dataset. Finally, online tool was developed to assess its validity in the clinical setting (external validation).

Results
The development set included 1025 patients (mean [SD] age, 72.8 [5.6] years; 632 [61.7%] female), and the external validation set included 175 patients (73.2 [5.9] years; 97 [55.4%] female). The predictive ability of our three models was comparable, with no significant differences in AUC (0.73 vs. 0.72 vs. 0.70, respectively). The logistic regression model had a higher net benefit for clinical intervention than the other models. A nomogram based on logistic regression was developed, and the C-index of external validation for AEs was 0.69 (95% CI 0.65–0.76).

Conclusion
The predictive ability of our three models was comparable. Logistic regression model had a higher net benefit for clinical intervention than the other models. Our nomogram and online tool (https://xuanwumodel.shinyapps.io/Model_for_AEs/) could inform physicians about elderly patients with a high risk of AEs within the 90 days after TLIF surgery.
Dimension independent data sets approximation and applications to classification
Authors: Guidotti Patrick 
Published: January 2024

AbstractWe revisit the classical kernel method of approximation/interpolation theory in a very specific context from the particular point of view of partial differential equations. The goal is to highlight the role of regularization by casting it in terms of actual smoothness of the interpolant obtained by the procedure. The latter will be merely continuous on the data set but smooth otherwise. While the method obtained fits into the category of RKHS methods and hence shares their main features, it explicitly uses smoothness, via a dimension dependent (pseudo-)differential operator, to obtain a flexible and robust interpolant, which can adapt to the shape of the data while quickly transitioning away from it and maintaining continuous dependence on them. The latter means that a perturbation or pollution of the data set, small in size, leads to comparable results in classification applications. The method is applied to both low dimensional examples and a standard high dimensioal benchmark problem (MNIST digit classification).
The influence of childhood trauma and chronotype on suicide attempts in Chinese emerging adults with severe depressive symptoms
Authors: Yu Yi , Feng Yi , Xu Shicun , Wilson Amanda , Chen Chang , Ling Xi , Chen Runsen , Wang Yuanyuan 
Published: January 2024

Abstract
Background
Studies have investigated how adults with severe depressive symptoms are more likely to attempt suicide, and these adults often have traumatic experiences and chaotic sleep/wake rhythms. Thus, this study using Latent class analysis aimed to investigate the relationship between childhood trauma class, chronotype, and suicide attempts among emerging adults with severe depressive symptoms.

Methods
This study was conducted among emerging adults with severe depressive symptoms covering 63 Universities in Jilin Province, China. A total of 1,225 emerging adults (mean age = 19.6 ± 1.78) constructed the final sample. In addition to measuring socio-demographic characteristics, the Childhood Trauma Questionnaire-Short Form, the Single-Item Chronotyping, and a single item for suicide attempts were used to evaluate childhood trauma, chronotype, and suicide attempts, respectively. Latent class analysis was applied to identify the classes of childhood trauma within emerging adults who had severe depressive symptoms. Hierarchical logistic regression models were run to investigate the effects of socio-demographic characteristics, chronotype, and childhood trauma class on suicide attempts.

Results
Three latent classes were identified: the Low-risk for childhood trauma class, the Neglect class, and the High-risk for childhood abuse class. Those who suffered sexual, emotional, and physical abuse at the same time were divided into the High-risk for childhood abuse class, and were significantly more likely to experience suicide attempts than those in the Neglect class (OR = 1.97, 95%CI = 1.34–2.89, p < 0.001) and the Low-risk for childhood trauma class (OR = 2.28, 95% CI = 1.50-3.46, p < 0.001). In terms of chronotype, the results showed that the chaotic type was a risk factor for suicide attempts when compared with the evening type (OR = 0.46, 95%CI = 0.27–0.78, p < 0.01), the moderately active type (OR = 0.53, 95%CI = 0.31–0.89, p < 0.05), and the daytime type (OR = 0.42, 95%CI = 0.21–0.86, p < 0.05). Overall, the significant risk factors for suicide attempts included being female, living in an urban area, having experienced sexual, emotional, and physical abuse simultaneously, and having a chaotic chronotype.

Conclusion
Emerging adults suffering sexual, emotional, and physical abuse at the same time and identifying with chaotic chronotype showed a higher risk of attempting suicide. The findings provided a clinical reference to quickly identify those at high risk of suicide attempts among emerging adults with severe depressive symptoms.
Bi-directional regulation of AIMP2 and its splice variant on PARP-1-dependent neuronal cell death; Therapeutic implication for Parkinson's disease
Authors: Lee Min Hak , Um Ki-Hwan , Lee Seok Won , Sun Ye Ji , Gu Da-Hye , Jo Young Ok , Kim Sung Hyun , Seol Wongi , Hwang Hyorin , Baek Kyunghwa , Choi Jin Woo 
Published: January 2024

Abstract
Background
Parthanatos represents a critical molecular aspect of Parkinson's disease, wherein AIMP2 aberrantly activates PARP-1 through direct physical interaction. Although AIMP2 ought to be a therapeutic target for the disease, regrettably, it is deemed undruggable due to its non-enzymatic nature and predominant localization within the tRNA synthetase multi-complex. Instead, AIMP2 possesses an antagonistic splice variant, designated DX2, which counteracts AIMP2-induced apoptosis in the p53 or inflammatory pathway. Consequently, we examined whether DX2 competes with AIMP2 for PARP-1 activation and is therapeutically effective in Parkinson’s disease.

Methods
The binding affinity of AIMP2 and DX2 to PARP-1 was contrasted through immunoprecipitation. The efficacy of DX2 in neuronal cell death was assessed under 6-OHDA and H2O2 in vitro conditions. Additionally, endosomal and exosomal activity of synaptic vesicles was gauged in AIMP2 or DX2 overexpressed hippocampal primary neurons utilizing optical live imaging with VAMP-vGlut1 probes. To ascertain the role of DX2 in vivo, rotenone-induced behavioral alterations were compared between wild-type and DX2 transgenic animals. A DX2-encoding self-complementary adeno-associated virus (scAAV) was intracranially injected into 6-OHDA induced in vivo animal models, and their mobility was examined. Subsequently, the isolated brain tissues were analyzed.

Results
DX2 translocates into the nucleus upon ROS stress more rapidly than AIMP2. The binding affinity of DX2 to PARP-1 appeared to be more robust compared to that of AIMP2, resulting in the inhibition of PARP-1 induced neuronal cell death. DX2 transgenic animals exhibited neuroprotective behavior in rotenone-induced neuronal damage conditions. Following a single intracranial injection of AAV-DX2, both behavior and mobility were consistently ameliorated in neurodegenerative animal models induced by 6-OHDA.

Conclusion
AIMP2 and DX2 are proposed to engage in bidirectional regulation of parthanatos. They physically interact with PARP-1. Notably, DX2's cell survival properties manifest exclusively in the context of abnormal AIMP2 accumulation, devoid of any tumorigenic effects. This suggests that DX2 could represent a distinctive therapeutic target for addressing Parkinson's disease in patients.