bluuebunny/crossref_metadata_2025_split huggingface dataset:
MPFL Length Change Patterns in Asymptomatic Knees of Patients with Contralateral Patellar Instability
Authors: Simeone F Joseph , Berkson Eric , Varadarajan Kartik , Tanaka Miho 
Published: July 2021

Objectives: Recreating the isometry of the medial patellofemoral ligament (MPFL) is critical during patellar stabilization surgery to restore patellar kinematics. The native MPFL is reported to remain constant in length from 0-70°knee flexion in normal knees. However, patients with patellar instability have morphologic abnormalities that may alter the isometric function of the ligament. Length change patterns of the intact MPFL in such patients have not been described. Methods: 3D digital knee models were created from dynamic CT images of 10 patients with unilateral patellar instability who were confirmed to have no symptoms on the contralateral knee. At each flexion angle, MPFL length was calculated based on the distance between its known attachment points. Straight line representation of the MPFL was allowed to wrap around the femoral condyle to ensure accurate length measurement. Morphologic characteristics of each knee were recorded, including sulcus angle and lateral trochlear inclination (LTI) as measurements of trochlear dysplasia, trochlear alpha angle to measure trochlear length, tibial tuberosity to trochlear groove (TTTG) distance to measure malalignment, and Caton Deschamps Index (CDI) to measure patellar height. Changes in MPFL length were assessed relative to knee flexion angle in each patient and correlated with morphologic characteristics. Results: 10 knees were included in this study, with a mean age of 20.4+/-4.7 yrs. Mean sulcus angle was 153.4+/-8.9°, LTI 14.1+/-4.0°, trochlear alpha angle 66.1+/-5.8°, TTTG distance 18.3+/-3.1mm, CDI 1.1+/-0.1. Mean MPFL length varied from 62.5+/-4.9mm at 50° knee flexion to 74.4+/-3.9mm at 0°, with a 20.1+/-8.8% change in length (p<0.001). No significant length changes were noted between 30° and 50° flexion. Moderate correlation was noted between increasing MPFL length change and measurements of trochlear length (R=-0.55, p=0.017). Conclusions: In the asymptomatic knees of patients with contralateral patellar instability, the calculated MPFL length based on known anatomic attachment points varied by 20.1%, or an average of 12.1mm, between 50° flexion and full extension. This suggests that the isometric function of the intact MPFL in these patients may not reflect previously described findings in anatomically normal patients. Further studies are needed to understand the pathoanatomy related to these changes, as well as the implications for graft placement and assessment of isometry in MPFL reconstruction techniques.
Failure of Posterior Capsulolabral Repair is Correlated with Percent of Glenoid Bone Loss
Authors: Provencher Matthew , Ruzbarsky Joseph , Peebles Liam , Midtgaard Kaare , Bradley James , Arner Justin 
Published: July 2021

Objectives: The purpose of this study was to evaluate previously described advanced MRI measures specific to posterior bone loss on both standard and manually reformatted MRIs in patients who underwent posterior shoulder capsulolabral repair. It was hypothesized that those who failed surgical repair would have increased posterior glenoid bone loss and decreased glenoid width. Methods: Athletes greater than 18 years of age with unidirectional posterior instability treated with arthroscopic repair were evaluated at 2 year minimum follow-up. Traditional MRIs measurements from nineteen patients who failed arthroscopic posterior shoulder capsulolabral repair were compared with 56 patients who did not. MRIs were then manually reformatted and these measurements were repeated as well as recently described measures of defect slope, bone loss angle, and defect length. Results: Glenoid width loss and percent glenoid bone loss were significantly greater on both the corrected and non-corrected MRI images (25.5 mm vs 28.8 mm, p<0.001; 6.8% vs 4.6%, p=0.008) in those that failed surgery. There was no difference in glenoid version or other measurements between the failures and non-failures. On non-corrected MRIs, percentage glenoid bone loss was significantly overestimated by 2% when compared to the corrected scans (p<0.0001, 95% CI [-2.7, -1.1]). A critical amount of 11% glenoid bone loss resulted in a 10 times higher surgical failure rate while 15% bone loss resulted in a 25 times higher failure rate. Conclusions: Risk factors for failure of arthroscopic posterior shoulder capsulolabral repair include greater glenoid bone width loss and greater glenoid bone loss percentage. Failure to appropriately align axial MRI rotation affects the characteristics of the sagittal images, leading to overestimation of glenoid bone loss percentage which may have surgical implications. Although 11% glenoid bone loss implicated a 10 times higher surgical failure rate and 15% bone loss has a 25 times higher failure rate, posterior capsulolabral repair is an overall successful intervention.
Effectiveness of a new cardiac risk scoring model reclassified by QRS fragmentation as a predictor of postoperative cardiac event in patients with severe renal dysfunction
Authors: Cho Hyun Jun , Kim Namkyun , Kim Hyeon Jeong , Park Bo Eun , Kim Hong Nyun , Jang Se Yong , Bae Myung Hwan , Lee Jang Hoon , Yang Dong Heon , Park Hun Sik , Cho Yongkeun , Chae Shung Chull 
Published: July 2021

Abstract
Background
It is difficult to evaluate the risk of patients with severe renal dysfunction before surgery due to various limitations despite high postoperative cardiac events. This study aimed to investigate the value of a newly reclassified Revised Cardiac Risk Index (RCRI) that incorporates QRS fragmentation (fQRS) as a predictor of postoperative cardiac events in patients with severe renal dysfunction.

Methods

Among the patients with severe renal dysfunction, 256 consecutive patients who underwent both a nuclear stress test and noncardiac surgery were evaluated. We reclassified RCRI as fragmented RCRI (FRCRI) by integrating fQRS on electrocardiography. We defined postoperative major adverse cardiac event (MACE) as a composite of cardiac death, nonfatal myocardial infarction, and pulmonary edema.

Results
Twenty-eight patients (10.9%) developed postoperative MACE, and this was significantly frequent in patients with myocardial perfusion defect (41.4% vs. 28.0%, p = 0.031). fQRS was observed 84 (32.8%)
patients, and it was proven to be an independent predictor of postoperative MACE after adjusting for the RCRI (odds ratio 3.279, 95% confidence interval (CI) 1.419–7.580, p = 0.005). Moreover, fQRS had an incremental prognostic value for the RCRI (chi-square = 7.8, p = 0.005), and to the combination of RCRI and age (chi-square = 9.1, p = 0.003). The area under curve for predicting postoperative MACE significantly increased from 0.612 for RCRI to 0.667 for FRCRI (p = 0.027) and 23 patients (32.4%) originally classified as RCRI 2 were reclassified as FRCRI 3.

Conclusions
A newly reclassified FRCRI that incorporates fQRS, is a valuable predictor of postoperative MACE in patients with severe renal dysfunction undergoing noncardiac surgery.
Shared decision making in pregnancy in inflammatory bowel disease: design of a patient orientated decision aid
Authors: Williams Astrid-Jane , Karimi Neda , Chari Radha , Connor Susan , De Vera Mary A. , Dieleman Levinus A. , Hansen Tawnya , Ismond Kathleen , Khurana Rshmi , Kingston Dawn , O’Connor Katie , Sadowski Daniel C. , Fang-Hwa Flora , Wine Eytan , Leung Yvette , Huang Vivian 
Published: July 2021

Abstract
Background
Research has indicated a lack of disease-specific reproductive knowledge among patients with Inflammatory Bowel Disease (IBD) and this has been associated with increased “voluntary childlessness”. Furthermore, a lack of knowledge may contribute to inappropriate medication changes during or after pregnancy. Decision aids have been shown to support decision making in pregnancy as well as in multiple other chronic diseases. A published decision aid for pregnancy in IBD has not been identified, despite the benefit of pre-conception counselling and patient desire for a decision support tool. This study aimed to develop and test the feasibility of a decision aid encompassing reproductive decisions in the setting of IBD.

Methods
The International Patient Decision Aid Standards were implemented in the development of the Pregnancy in IBD Decision Aid (PIDA). A multi-disciplinary steering committee was formed. Patient and clinician focus groups were conducted to explore themes of importance in the reproductive decision-making processes in IBD. A PIDA prototype was designed; patient interviews were conducted to obtain further insight into patient perspectives and to test the prototype for feasibility.

Results
Issues considered of importance to patients and clinicians encountering decisions regarding pregnancy in the setting of IBD included fertility, conception timing, inheritance, medications, infant health, impact of surgery, contraception, nutrition and breastfeeding. Emphasis was placed on the provision of preconception counselling early in the disease course. Decisions relating to conception and medications were chosen as the current focus of PIDA, however content inclusion was broad to support use across preconception, pregnancy and post-partum phases. Favourable and constructive user feedback was received.

Conclusions
The novel development of a decision aid for use in pregnancy and IBD was supported by initial user testing.
Efficacy of osimertinib for preventing leptomeningeal metastasis derived from advanced EGFR-mutated non-small cell lung cancer: a propensity-matched retrospective study
Authors: Wang Xia , Cai Jing , Zeng Zhimin , Liu Anwen 
Published: July 2021

Abstract
Background
Leptomeningeal metastasis (LM) is a severe complication of advanced non-small cell lung cancer (NSCLC). This retrospective study aimed to investigate the potential use of osimertinib for preventing LM in patients with advanced epidermal growth factor receptor (EGFR)-mutated NSCLC.

Methods
Patients with advanced NSCLC harboring EGFR mutations who underwent tyrosine kinase inhibitors (TKIs) therapy for at least 8 weeks between September 2016 and September 2019 were eligible for this study. All included patients were divided into two groups based on whether they received osimertinib, the osimertinib group (patients treated with osimertinib) and the control group (patients not treated with osimertinib). Propensity score matching (PSM, ratio of 1:1) was used to account for differences in baseline characteristics. The cumulative incidence of LM and the overall survival (OS) were evaluated.

Results
A total of 304 patients were included in the study population. Among them, 116 patients received osimertinib, and 188 did not. A total of 112 patients remained in each group after PSM, and the baseline characteristics were not significantly different between the two cohorts. LM developed in 11 patients (9.82%) in the osimertinib group and 24 patients (21.42%) in the control group (hazard ratio [HR] 0.38, 95% confidence interval [CI] 0.19–0.79, p = 0.009). Multivariate analysis indicated that osimertinib was an independent, statistically significant predictor for determining the risk for LM, with an HR of 0.33 (p = 0.042). At present, the OS rate data are too immature for statistical analysis.

Conclusion
Real-world data demonstrate that osimertinib can significantly reduce the incidence of LM in patients with advanced NSCLC harboring common EGFR mutations. Given this result, osimertinib should be encouraged in clinical practice for specific patient populations.
Effect of spectral CT on tumor microvascular angiogenesis in renal cell carcinoma
Authors: Zhang Bei , Wu Qiong , Qiu Xiang , Ding Xiaobo , Wang Jin , Li Jing , Sun Pengfei , Hu Xiaohan 
Published: July 2021

Abstract
Background
To examine the value of energetic-spectrum computed tomography (spectral CT) quantitative parameters in renal cell carcinoma (RCC) microvascular angiogenesis.

Methods
The authors evaluated 32 patients with pathologically confirmed RCC who underwent triple-phase contrast-enhanced CT with spectral CT imaging mode from January 2017 to December 2019. Quantitative parameters include parameters derived from iodine concentration (IC) and water concentration (WC) of 120 keV monochromatic images. All specimens were evaluated including the microvascular density (MVD), microvascular area (MVA) and so on. The correlation between IC and WC (including average values and random values) with microvascular parameters were analyzed with Pearson or Spearman rank correlation coefficients.

Results
The MVD of all tumors was 26.00 (15.00–43.75) vessels per field at × 400 magnification. The MVD of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical phase, WCD1, WCD2, NWCD2 and ICD1 (Spearman rank correlation coefficients, r range, 0.362–0.533; all p < 0.05). The MVA of all tumors was (16.16 ± 8.98) % per field at × 400 magnification. The MVA of RCC correlated positively with the mean IC, mean WC, mean NWC, mean NIC, random IC, random NIC in renal cortical, mean WC and mean NWC in renal parenchymal phase, WCD1, WCD2, WCD3, NWCD2, and NWCD3 (Pearson or Spearman rank correlation coefficients, r range, 0.357–0.576; all p < 0.05). Microvascular grading correlated positively with the mean NWC, mean NIC and random NIC in renal cortical phase, mean NWC in renal parenchymal phase, NWCD2, WCD3, NWCD3, NICD2 and NICD3 (Spearman rank correlation coefficients, r range, 0.367–0.520; all p < 0.05). As for tumor diameter (55.19 ± 19.15), μm, only NWCD3 was associated with it (Spearman rank correlation coefficients, r = 0.388; p < 0.05).

Conclusions
ICD and WCD of spectral CT have a potential for evaluating RCC microvascular angiogenesis. MVD, MVA and microvascular grade showed moderate positive correlation with ICD and WCD. ICD displayed more relevant than that of WCD. The parameters of renal cortical phase were the best in three phases. NICD and NWCD manifested stronger correlation with microvascular parameters than that of ICD and WCD.
Measuring hygiene competence: the picture-based situational judgement test HygiKo
Authors: Heininger Susanne Katharina , Baumgartner Maria , Zehner Fabian , Burgkart Rainer , Söllner Nina , Berberat Pascal O. , Gartmeier Martin 
Published: July 2021

Abstract
Background
With the onset of the COVID-19 pandemic at the beginning of 2020, the crucial role of hygiene in healthcare settings has once again become very clear. For diagnostic and for didactic purposes, standardized and reliable tests suitable to assess the competencies involved in “working hygienically” are required. However, existing tests usually use self-report questionnaires, which are suboptimal for this purpose. In the present study, we introduce the newly developed, competence-oriented HygiKo test instrument focusing health-care professionals’ hygiene competence and report empirical evidence regarding its psychometric properties.

Methods
HygiKo is a Situational Judgement Test (SJT) to assess hygiene competence. The HygiKo-test consists of twenty pictures (items), each item presents only one unambiguous hygiene lapse. For each item, test respondents are asked (1) whether they recognize a problem in the picture with respect to hygiene guidelines and, (2) if yes, to describe the problem in a short verbal response. Our sample comprised n = 149 health care professionals (79.1 % female; age: M = 26.7 years, SD = 7.3 years) working as clinicians or nurses. The written responses were rated by two independent raters with high agreement (α > 0.80), indicating high reliability of the measurement. We used Item Response Theory (IRT) for further data analysis.

Results
We report IRT analyses that show that the HygiKo-test is suitable to assess hygiene competence and that it allows to distinguish between persons demonstrating different levels of ability for seventeen of the twenty items), especially for the range of low to medium person abilities. Hence, the HygiKo-SJT is suitable to get a reliable and competence-oriented measure for hygiene-competence.

Conclusions
In its present form, the HygiKo-test can be used to assess the hygiene competence of medical students, medical doctors, nurses and trainee nurses in cross-sectional measurements. In order to broaden the difficulty spectrum of the current test, additional test items with higher difficulty should be developed. The Situational Judgement Test designed to assess hygiene competence can be helpful in testing and teaching the ability of working hygienically. Further research for validity is needed.
AMFormulaS: an intelligent retrieval system for traditional Chinese medicine formulas
Authors: Cui Yidi , Gao Bo , Liu Lihong , Liu Jing , Zhu Yan 
Published: July 2021

Abstract
Background
Formula is an important means of traditional Chinese medicine (TCM) to treat diseases and has great research significance. There are many formula databases, but accessing rich information efficiently is difficult due to the small-scale data and lack of intelligent search engine.

Methods
We selected 38,000 formulas from a semi-structured database, and then segmented text, extracted information, and standardized terms. After that, we constructed a structured formula database based on ontology and an intelligent retrieval engine by calculating the weight of decoction pieces of formulas.

Results
The intelligent retrieval system named AMFormulaS (means Ancient and Modern Formula system) was constructed based on the structured database, ontology, and intelligent retrieval engine, so the retrieval and statistical analysis of formulas and decoction pieces were realized.

Conclusions
AMFormulaS is a large-scale intelligent retrieval system which includes a mass of formula data, efficient information extraction system and search engine. AMFormulaS could provide users with efficient retrieval and comprehensive data support. At the same time, the statistical analysis of the system can enlighten scientific research ideas and support patent review as well as new drug research and development.
Multi-label classification of fundus images based on graph convolutional network
Authors: Cheng Yinlin , Ma Mengnan , Li Xingyu , Zhou Yi 
Published: July 2021

AbstractBackgroundDiabetic Retinopathy (DR) is the most common and serious microvascular complication in the diabetic population. Using computer-aided diagnosis from the fundus images has become a method of detecting retinal diseases, but the detection of multiple lesions is still a difficult point in current research.MethodsThis study proposed a multi-label classification method based on the graph convolutional network (GCN), so as to detect 8 types of fundus lesions in color fundus images. We collected 7459 fundus images (1887 left eyes, 1966 right eyes) from 2282 patients (1283 women, 999 men), and labeled 8 types of lesions, laser scars, drusen, cup disc ratio ($$C/D>0.6$$C/D>0.6), hemorrhages, retinal arteriosclerosis, microaneurysms, hard exudates and soft exudates. We constructed a specialized corpus of the related fundus lesions. A multi-label classification algorithm for fundus images was proposed based on the corpus, and the collected data were trained.ResultsThe average overall F1 Score (OF1) and the average per-class F1 Score (CF1) of the model were 0.808 and 0.792 respectively. The area under the ROC curve (AUC) of our proposed model reached 0.986, 0.954, 0.946, 0.957, 0.952, 0.889, 0.937 and 0.926 for detecting laser scars, drusen, cup disc ratio, hemorrhages, retinal arteriosclerosis, microaneurysms, hard exudates and soft exudates, respectively.ConclusionsOur results demonstrated that our proposed model can detect a variety of lesions in the color images of the fundus, which lays a foundation for assisting doctors in diagnosis and makes it possible to carry out rapid and efficient large-scale screening of fundus lesions.
Learning rich features with hybrid loss for brain tumor segmentation
Authors: Huang Daobin , Wang Minghui , Zhang Ling , Li Haichun , Ye Minquan , Li Ao 
Published: July 2021

Abstract
Background
Accurately segment the tumor region of MRI images is important for brain tumor diagnosis and radiotherapy planning. At present, manual segmentation is wildly adopted in clinical and there is a strong need for an automatic and objective system to alleviate the workload of radiologists.

Methods
We propose a parallel multi-scale feature fusing architecture to generate rich feature representation for accurate brain tumor segmentation. It comprises two parts: (1) Feature Extraction Network (FEN) for brain tumor feature extraction at different levels and (2) Multi-scale Feature Fusing Network (MSFFN) for merge all different scale features in a parallel manner. In addition, we use two hybrid loss functions to optimize the proposed network for the class imbalance issue.

Results
We validate our method on BRATS 2015, with 0.86, 0.73 and 0.61 in Dice for the three tumor regions (complete, core and enhancing), and the model parameter size is only 6.3 MB. Without any post-processing operations, our method still outperforms published state-of-the-arts methods on the segmentation results of complete tumor regions and obtains competitive performance in another two regions.

Conclusions
The proposed parallel structure can effectively fuse multi-level features to generate rich feature representation for high-resolution results. Moreover, the hybrid loss functions can alleviate the class imbalance issue and guide the training process. The proposed method can be used in other medical segmentation tasks.
CapsTM: capsule network for Chinese medical text matching
Authors: Yu Xiaoming , Shen Yedan , Ni Yuan , Huang Xiaowei , Wang Xiaolong , Chen Qingcai , Tang Buzhou 
Published: July 2021

AbstractBackgroundText Matching (TM) is a fundamental task of natural language processing widely used in many application systems such as information retrieval, automatic question answering, machine translation, dialogue system, reading comprehension, etc. In recent years, a large number of deep learning neural networks have been applied to TM, and have refreshed benchmarks of TM repeatedly. Among the deep learning neural networks, convolutional neural network (CNN) is one of the most popular networks, which suffers from difficulties in dealing with small samples and keeping relative structures of features. In this paper, we propose a novel deep learning architecture based on capsule network for TM, called CapsTM, where capsule network is a new type of neural network architecture proposed to address some of the short comings of CNN and shows great potential in many tasks.MethodsCapsTM is a five-layer neural network, including an input layer, a representation layer, an aggregation layer, a capsule layer and a prediction layer. In CapsTM, two pieces of text are first individually converted into sequences of embeddings and are further transformed by a highway network in the input layer. Then, Bidirectional Long Short-Term Memory (BiLSTM) is used to represent each piece of text and attention-based interaction matrix is used to represent interactive information of the two pieces of text in the representation layer. Subsequently, the two kinds of representations are fused together by BiLSTM in the aggregation layer, and are further represented with capsules (vectors) in the capsule layer. Finally, the prediction layer is a connected network used for classification. CapsTM is an extension of ESIM by adding a capsule layer before the prediction layer.ResultsWe construct a corpus of Chinese medical question matching, which contains 36,360 question pairs. This corpus is randomly split into three parts: a training set of 32,360 question pairs, a development set of 2000 question pairs and a test set of 2000 question pairs. On this corpus, we conduct a series of experiments to evaluate the proposed CapsTM and compare it with other state-of-the-art methods. CapsTM achieves the highest F-score of 0.8666.ConclusionThe experimental results demonstrate that CapsTM is effective for Chinese medical question matching and outperforms other state-of-the-art methods for comparison.