bluuebunny/crossref_metadata_2025 huggingface dataset:
An LRFM Model to Analyze Outpatient Loyalty From a Medical Center in Taiwan
Authors: Chao Shu-Hui , Chen Mu-Kuan , Wu Hsin-Hung
Published: July 2021

This research is intended to study the behaviors of outpatients in a medical center and constructs a set of data exploration procedures such that hospital management can deal with patient relationship management more effectively. This study adopts LRFM (length, recency, frequency, and monetary) model and cluster analysis, including self-organizing maps and K-means method, to categorize 321,908 outpatients of the medical center into 12 groups and then uses the multidimensional customer clustering philosophy to classify the outpatients. Outpatients can be categorized into five different types of groups, namely, core customer groups, potential customer groups, new customer groups, lost customer groups, and resource-consuming customer groups. In addition, seven types of outpatients based on five types of categories are identified. The similarities and differences of each group based on the patients’ characteristics are analyzed to give differentiation strategy advices for hospital management. Hospital management thus can design the optimal service strategies, provide the best care services, enhance hospital’s performance, and reduce the overall cost to establish quality relationships with outpatients.
Biomechanical Comparison of Ulnar Collateral Ligament Reconstruction with and without Internal Bracing
Authors: Youssefzadeh Keon , Nelson Trevor , Metzger Melodie , Limpisvasti Orr , Narvaez Michael
Published: July 2021

Objectives:

A common concern associated with elbow ulnar collateral ligament (UCL) reconstruction surgery is the amount of time required for recovery and rehabilitation. For example, the average time to return to competition is around 15-18 months for major league baseball pitchers. The Internal Brace (Arthrex Inc.) has shown to provide additional soft tissue stability across other joints in the body. By providing an additional checkrein to the UCL reconstruction while the graft is healing, it may be possible to expedite the rehabilitation process in throwing athletes, providing a quicker return to sport.

Purpose:

To compare elbow valgus stability and load to failure between UCL reconstructions with and without suture augmentation.

Methods:

24 fresh-frozen cadaveric elbows were dissected to expose the UCL. Medial elbow stability was tested with the UCL intact, deficient, and reconstructed utilizing the 3-ply docking technique either with or without suture augmentation. A 3 N·m valgus torque was applied to the elbow and valgus rotation of the ulna was recorded via motion tracking cameras as the elbow was cycled through a full range of motion. After kinematic testing, specimens were loaded to failure at 70 degrees of elbow flexion.

Results:

UCL-deficient elbows demonstrated significantly greater valgus rotation compared to intact and internally-braced reconstructed elbows at every angle of flexion tested and at 50-120o flexion when compared to un-braced UCL reconstructed elbows, p<0.05. There were no significant differences at any angle of flexion between intact and UCL reconstructed elbows both with and without an internal brace at any flexion angle tested. Braced reconstructions had consistently greater valgus stability at every angle tested compared to unbraced reconstructions, but this was not significant, Figure 1B. When loaded to failure un-braced reconstructed elbows failed at a significantly lower torque value compared to UCL reconstructions with a brace, p<0.01, Figure 1A.

Conclusions:

UCL reconstruction with internal bracing does not over constrain the elbow throughout all flexion angles when compared to the 3-ply docking technique while providing greater biomechanical stiffness. Internal bracing may provide the additional stability necessary to accelerate rehabilitation following ulnar collateral ligament reconstruction.
Treatment of Partial-Thickness Rotator Cuff Repairs With A Resorbable Bioinductive Bovine Collagen Implant: 1-Year Results From A Prospective Multi-Center Registry
Authors: Bishai Shariff , Krupp Ryan , McMillan Sean , Schofield Brian , Trenhaile Scott , McIntyre Louis , Bushnell Brandon
Published: July 2021

Objectives:

Surgical treatment of partial-thickness rotator cuff tears remains challenging and controversial, with several traditional options including debridement with acromioplasty, transtendon or in-situ repair, and take-down and repair. A bioinductive resorbable bovine collagen implant has shown promise as an alternative treatment option for partial-thickness tears. It was our hypothesis that data from a comprehensive, prospective, multi-center registry will further establish the implant’s efficacy and safety across larger numbers of patients.

Methods:

Nineteen US centers enrolled patients >21 years old with partial-thickness tears of the rotator cuff. Patient-reported outcome (PRO) scores including the American Shoulder and Elbow Surgeons (ASES), single-assessment numeric evaluation (SANE), Veterans RAND 12-Item (VR-12) for both Physical Component Score (PCS) and Mental Component Score (MCS), and Western Ontario Rotator Cuff (WORC) outcome measures were recorded at pre-operative baseline, surgery, and postoperatively at 2 and 6 weeks, 3 and 6 months, and 1 year. Revisions were reported throughout the study.

Results:

The registry included 272 patients with partial-thickness tears (49 grade 1 tears, 101 grade 2 tears, and 122 grade 3 tears), 241 who underwent isolated bioinductive repair (“IBR”; collagen implant placed over the tear following bursectomy without a traditional rotator cuff repair - FIGURE 1) and 31 tradtitional take-down and repair with supplemental placement of the implant. Patients experienced statistically significant and sustained improvement from baseline for all PRO scores beginning at 3 months (TABLE 1). Among patients with grade ≥2 tears, those with take-down and repair had significantly inferior scores at 2 and 6 weeks for most PRO scores compared with those undergoing IBR, but the difference was no longer significant at 1 year for all but VR-12 PCS. There were 11 revisions, which occurred at a mean of 188.7 days (standard deviation, 88.0) after index surgery.

Conclusions:

Efficacy and safety of the implant are further established across a larger data set. IBR may offer improved early clinical outcomes and equivalent long-term results to supplemented take-down and repair, potentially with lower risk of complications. This implant can improve rotator cuff healing and clinical outcomes with minimal revisions.

[Table: see text]
Platelet Rich Plasma in Arthroscopic Rotator Cuff Repair: Clinical and Radiological Results of A Prospective RCT Study at 10-Year Follow-Up
Authors: Randelli Pietro , Stoppani Carlo Alberto , Nocerino Elisabetta , Menon Alessandra , Compagnoni Riccardo
Published: July 2021

Objectives:

Despite the technical advancement in arthroscopic rotator cuff repair, inadequate healing or retear of the repaired rotator cuff frequently occurs. The use of biological factors in the surgical treatment has been proved to be effective to enhance tendon healing in the post-operative period. The aim of the study is to compare clinical and radiological outcomes of arthroscopic rotator cuff repair with or without the addition of platelet-rich plasma (PRP) at 10-year follow-up.

Methods:

Of 53 patients recruited in the study, and randomly divided into two groups (PRP=26; control=27), 38 were re-evaluated at least 10 years after the index procedure. The clinical evaluation was carried out through: University of California at Los Angeles (UCLA) Shoulder Score, Visual Analogue Scale (VAS), Simple Shoulder Test (SST), Constant-Murley Score (CMS), Single Assessment Numerical Evaluation (SANE), American Shoulder and Elbow Surgeons (ASES) and isometric strength in abduction and external rotation. Musculoskeletal ultrasound had been used to evaluate the integrity of the repaired cuff.

Results:

A number of 38 (71%) patients (PRP=17; control=21) with a median age of 71 [64.75-76.50] years have been evaluated. Satisfaction at follow-up is high (90%), without statistically significant difference between the two groups. We report good and excellent clinical results in both groups (PRP vs control): CMS (81.62 [72.47-85.75] vs 77.97 [69.52-82.55] points), UCLA (34 [29.00-35.00] vs 33 [29.00-35.00] points), VAS (0.34 [0.00-1.85] vs 0.70 [0.00-2.45] cm), ASES (100.00 [94.17-100.00] vs 93.33 [68.33-100.00] points), SANE (100 [80-100] vs 80 [70-90] points), SST (12.00 [11.00-12.00] vs 12.00 [9.00-12.00] points),shoulder abduction strength (3.92 ± 2.30 vs 3.20 [1.72-4.65] kg), shoulder external rotation strength (5.31 ± 2.77 vs 4.36 ± 2.05 kg). It was not possible to find a statistically significant difference for the variables analysed, except for few subjective variables (ASES, SANE). On average, 37% of the operated patients had a re-rupture at the ultrasound examination, with no significant difference between the two groups (p=1.00). Compared with the previous radiological control at the 2-year follow-up, new retears occurred in 6% of the patients that received PRP treatment, whereas in the control group the percentage raises to 14% (p=0.61).

Conclusions:

The clinical and radiological outcomes at the 10-year follow-up show a substantial uniformity of results between the two groups. The clinical differences that had been observed at 2-year follow-up disappeared at long term. A reduction in retear rate is observed at US evaluation in the PRP group at 10 years follow-up and this trend needs to be further analyzed. Patients’ satisfaction is still high 10 years after surgical treatment, in both groups.
Refractory Ameloblastoma in the Maxilla: Clinical, Imaging, Histological, Surgical and Mutational Characterization: A Case Series
Authors: Bernaola-Paredes Wilber E. , Albuja-Rivadeneira Estefani , Novelli Franco , Dalcin José Francisco , Vartanian José Guilherme , Kohler Hugo Fontan , Pellizzon Antonio Cássio Assis
Published: July 2021

Study Design:

Ameloblastoma is a benign odontogenic tumor of epithelial origin, with locally aggressive behavior; and due to its invasiveness has increased recurrence rates. It is more frequent in the mandible than the maxilla. Surgical treatment is performed with approaches ranging from conservative to radical surgery, either followed by microvascular reconstruction, or not. Adjuvant treatment has shown better local control in refractory cases. Multiple relapses are associated with BRAF gene mutation at codon 600.

Objective:

This case series aimed to describe the clinical, imaging, histopathological, therapeutic and mutational characterization of 3 patients with refractory ameloblastoma in the maxilla.

Methods:

Data of 3 patients were collected, and descriptions were provided of procedures such as clinical, imaging, surgical technique, histopathological subtype and molecular analysis for detection of BRAFV600E mutation. Results It was obtained a locoregional control after RT of two cases described. After BRAF mutation molecular analysis, no patient presented it.

Conclusion:

Surgery remains the gold standard for the treatment of ameloblastomas, even in refractory cases; however, an expanded approach to obtain free surgical margins, and reconstruction of the maxilla itself may be challenging. Adjuvant radiotherapy is still a controversial topic, but could favor reduction of the local recurrence rate in cases where the surgical margins are compromised after surgical resection. Further studies will be necessaries for analysis of the BRAFV600E mutation, for therapeutic purposes.
Trauma in the correctional field and the correctional worker habitus
Authors: McKendy Laura , Ricciardelli Rose , Konyk Kate
Published: July 2021

Prisons and other correctional settings are spaces often marked by numerous sources of physical, psychological, and emotional insecurity. Researchers have consistently found correctional work to be associated with outcomes such as burnout, posttraumatic stress disorder, and depression. Drawing on open-ended survey questions with correctional workers (CWs) in the province of Ontario, we first identify salient themes in discussions of work stressors and potentially psychologically traumatic events (PPTEs); these include situations involving harm to prisoners, harm to staff, and harms associated with occupational and organizational culture. Next, employing the concept of “habitus,” we consider the social-subjective effects of exposure to PPTEs as revealed in respondent accounts. Key aspects include a disposition of hypervigilance, desensitization, disillusionment, and distrust. We suggest that the CW habitus may, in some ways, serve to mitigate threats in the work environment, though may have negative effects on job performance and well-being, and come to shape social experiences in everyday life.
The push and pull of radicalization and extremist disengagement: The application of criminological theory to Indonesian and Australian cases of radicalization
Authors: Cherney Adrian , Putra Idhamsyah E , Putera Vici Sofianna , Erikha Fajar , Magrie Muhammad Faisal
Published: July 2021

Research shows there is variability in factors that cause a person to radicalize to violent extremism. The use of the push/pull distinction has been one way in which scholars have aimed to provide clarity to the process of radicalization and extremist disengagement. However, it remains a conceptually underdeveloped distinction. In this paper, we draw on aspects of criminological theory to better understand the push and pull distinction. The paper draws on research comprising interviews with three Indonesians and two Australian individuals who have radicalized to violent extremism that is aligned with jihadist ideologies. Based on this primary data, case descriptions and narratives are provided on each individual examining pathways into and away from violent extremism. We draw on aspects of strain theory, social control, differential association, and desistance theory to understand common patterns across each case and to highlight the relative influence of various push and pull factors. Implications for theory and policy are highlighted. We also acknowledge limitations in our approach.
The secreted tyrosine kinase VLK is essential for normal platelet activation and thrombus formation
Authors: Revollo Leila , Merrill-Skoloff Glenn , De Ceunynck Karen , Dilks James R. , Guo Shihui , Bordoli Mattia R. , Peters Christian G. , Noetzli Leila , Ionescu Andreia , Rosen Vicki , Italiano Joseph E. , Whitman Malcolm , Flaumenhaft Robert
Published: July 2021

Tyrosine phosphorylation of extracellular proteins is observed in cell cultures and in vivo, but little is known about the functional roles of tyrosine phosphorylation of extracellular proteins. Vertebrate lonesome kinase (VLK) is a broadly expressed secretory pathway tyrosine kinase present in platelet α-granules. It is released from platelets upon activation and phosphorylates substrates extracellularly. Its role in platelet function, however, has not been previously studied. In human platelets, we identified phosphorylated tyrosines mapped to luminal or extracellular domains of transmembrane and secreted proteins implicated in the regulation of platelet activation. To determine the role of VLK in extracellular tyrosine phosphorylation and platelet function, we generated mice with a megakaryocyte/platelet-specific deficiency of VLK. Platelets from these mice are normal in abundance and morphology but have significant changes in function both in vitro and in vivo. Resting and thrombin-stimulated VLK-deficient platelets exhibit a significant decrease in several tyrosine phosphobands. Results of functional testing of VLK-deficient platelets show decreased protease-activated receptor 4–mediated and collagen-mediated platelet aggregation but normal responses to adenosine 5′-diphosphate. Dense granule and α-granule release are reduced in these platelets. Furthermore, VLK-deficient platelets exhibit decreased protease-activated receptor 4–mediated Akt (S473) and Erk1/2 (T202/Y204) phosphorylation, indicating altered proximal signaling. In vivo, mice lacking VLK in megakaryocytes/platelets display strongly reduced platelet accumulation and fibrin formation after laser-induced injury of cremaster arterioles compared with control mice but with normal bleeding times. These studies show that the secretory pathway tyrosine kinase VLK is critical for stimulus-dependent platelet activation and thrombus formation, providing the first evidence that a secreted protein kinase is required for normal platelet function.
Structural and Chemical Modifications Towards High-Performance of Triboelectric Nanogenerators
Authors: Nurmakanov Yerzhan , Kalimuldina Gulnur , Nauryzbayev Galymzhan , Adair Desmond , Bakenov Zhumabay
Published: July 2021

Harvesting abundant mechanical energy has been considered one of the promising technologies for developing autonomous self-powered active sensors, power units, and Internet-of-Things devices. Among various energy harvesting technologies, the triboelectric harvesters based on contact electrification have recently attracted much attention because of their advantages such as high performance, light weight, and simple design. Since the first triboelectric energy-harvesting device was reported, the continuous investigations for improving the output power have been carried out. This review article covers various methods proposed for the performance enhancement of triboelectric nanogenerators (TENGs), such as a triboelectric material selection, surface modification through the introduction of micro-/nano-patterns, and surface chemical functionalization, injecting charges, and their trapping. The main purpose of this work is to highlight and summarize recent advancements towards enhancing the TENG technology performance through implementing different approaches along with their potential applications.

Graphic Abstract

This paper presents a comprehensive review of the TENG technology and its factors affecting the output power as material selection, surface physical and chemical modification, charge injection, and trapping techniques.
The rotational atherectomy with a guide extension catheter for calcified and tortuous lesions in left anterior descending artery: a case report
Authors: Kato Taichi , Fujino Masashi , Takagi Kensuke , Noguchi Teruo
Published: July 2021

Background

The interventional treatment of calcified lesions with severe tortuosity in the left anterior descending artery (LAD) was challenging and the report of rotational atherectomy with mother-and-child technique has been scarce.

Case presentation

An 84-year-old woman was hospitalized for non-ST-segment acute coronary syndrome. Coronary angiography revealed a calcified nodule in the LAD. During rotational atherectomy of the calcified and tortuous lesion in the proximal LAD, eccentric cutting due to wire bias nearly caused perforation. The burr seemed to protrude from the contrast media during angiography. Intravascular ultrasound imaging revealed that extremely eccentric ablation almost reached the adventitia. We successfully ablated the distal calcified nodule by preventing proximal overcutting of the tortuous lesion with support from a guide extension catheter, i.e., the mother-and-child technique, followed by the deployment of the drug-eluting stent. The patient was discharged without chest symptoms and no symptom recurred during 12-month follow-up.

Conclusion

This case demonstrated that safe ablation of a calcified nodule located distal to a tortuous and calcified lesion in the proximal LAD with the mother-and-child technique.
Monitoring the efficacy of tumor necrosis factor alpha antagonists in the treatment of Ankylosing spondylarthritis: a pilot study based on MR relaxometry technique
Authors: Lin Mingui , Chen Xianyuan , Yu Shun , Gao Fei , Ma Mingping
Published: July 2021

Background

SpA is a disease that seriously affects the quality of life and working ability of patients. At present, there is a lack of scientific and effective quantitative indicators to evaluate the activity of sacroilitis and the efficacy of tumor necrosis factor-α antagonists in the treatment of active sacroilitis. MRI STIR sequence is the most commonly used method for the diagnosis of sacroiliac joint inflammation, but its response to the disease still lags behind the pathological changes and cannot provide quantitative indicators. This study aimed to evaluate the feasibility of using MRI Relaxometry technique to monitor the efficacy of TNF-α antagonists in the treatment of SpA, so as to provide an effective quantitative index for monitoring the efficacy.

Methods

This is a prospective study, 114 patients with sacroiliac joint were enrolled, including 15 patients as a control group, 99 patients as the case group, and 20 patients in the case group as the treatment group. The differences of T1 mapping, T2 mapping, T2* mapping of subchondral bone marrow of sacroiliac joint were compared among different groups. The diagnostic efficacy was analyzed by ROC, and the best quantitative index of diagnostic efficiency was used to monitor curative effects of different treatment cycles in the treatment group.

Results

1. Compared with the control group, values of three different relaxation times in the subchondral bone marrow region of the sacroiliac joint in the case group increased in varying degrees, and T1 mapping showed the best diagnostic efficacy. 2. The decreasing rate of T1 mapping in different treatment periods benefits the monitoring of curative effects.

Conclusion

This study indicates that T1 mapping technique is preferred in quantitative diagnosis. T1 mapping is superior to T2* mapping and T2 mapping in the diagnosis of subchondral BME of SpA. It can quantitatively monitor edema changes during treatment, benefiting clinical individualized treatment and timely adjustment of the treatment plan.
The impact of COVID-19 quarantine on dietary habits and physical activity in Saudi Arabia: a cross-sectional study
Authors: Bakhsh Manar Abduljalil , Khawandanah Jomana , Naaman Rouba Khalil , Alashmali Shoug
Published: July 2021

Background

The COVID-19 pandemic has forced governments around the world to impose strict hygiene and national lockdown measures, which in turn has changed the dietary and lifestyle habits of the world’s population. Thus, the aim of this study is to evaluate whether dietary and physical activity behaviors of Saudi Arabia’s adult population changed during the COVID-19 quarantine.

Methods

An electronic questionnaire which assessed changes in body weight, dietary habits, and physical activity of Saudi Arabia’s adult population (n = 2255) during the COVID-19 quarantine was distributed on social media between June and July 2020. To test the differences between changes in dietary and physical activity behaviors in relation to changes in body weight a Chi-square test was used.

Results

Over 40 and 45% of participants reported eating and snacking more, respectively, which led to weight gain in around 28%. Most participants reported that they consumed home-cooked (73%) and healthy meals (47%), while only 7% reported that they consumed foods from restaurants. Feelings of boredom and emptiness (44%) and the availability of time for preparing meals (40%) were the main reasons for changing dietary habits. Honey (43%) and vitamin C (50%) were the most consumed immune-boosting food and dietary supplement, respectively. COVID-19 also had a negative impact on physical activity, lowering the practice in 52% subjects, which was associated with significant weight gain (p < 0.001).

Conclusion

Assessing the changes to the population’s dietary habits and physical activity during the lockdown will help predict the outcome of the population’s future health and wellbeing after the pandemic.
The association between manual handling operations and pain in the hands and arms in the context of the 2018 BIBB/BAuA Employment Survey
Authors: Mueller Charlotte , Sauter Martha , Barthelme Julia , Liebers Falk
Published: July 2021

Background

Manual handling operations (MHO) are tasks performed by hand that require repetitive and forceful hand and arm movements. MHO are currently performed in many workplaces in skilled and unskilled jobs in the production and service sectors. MHO are considered as work-related health risk factors. The relationship between MHO and the occurrence of disorders of the upper extremities has been established. MHO can cause diseases such as tenosynovitis or carpal tunnel syndrome. This study aims to assess the current prevalence of MHO in the German workforce and to evaluate the relationship between MHO and the occurrence of hand and arm complaints.

Methods

The analysis was based on the German 2018 BIBB/BAuA Employment Survey. For this analysis we included subjects aged between 16 and 66 who work at least 35 h per week. The self-reported frequency of MHO (never; rarely; sometimes; often) was considered as the exposure of interest and was stratified by gender and occupation. Prevalence ratios (PR) were used to report the relationship between MHO and self-reported pain in the hands and arms (robust log-linear Poisson regression). Adjustments were made for age, gender, actual weekly working hours, psychosocial workload, and other physical workloads. The regression analyses considered complete cases.

Results

The analyses included 14,299 employees. Frequent MHO were reported by 32.6% of men and 31.1% of women. These workloads were often reported by respondents who work in the agricultural sector (men: 70.1%; women: 79.0%), in unskilled (men: 59.4%; women: 66.9%), and skilled manual occupations (men: 72.7%; women: 66.7%).

A higher frequency of self-reported MHO was associated with a higher prevalence of hand complaints (PR 2.26 CI 2.00–2.55 “often” vs. “never” = ref.) as well as arm pain (PR 1.73 CI 1.55–1.92 for “often” vs. “never” = ref.).

Conclusion

MHO are still frequent in many occupations. The shown association between MHO and pain in the hands and arms demonstrates the importance of MHO in the current German workforce and the necessity to further develop prevention strategies.
The use of Web-based interactive technology to promote HPV vaccine uptake among young females: a randomized controlled trial
Authors: Wang Qi , Zhang Wen
Published: July 2021

Background

Currently no study has investigated whether Web-based interactive technology can influence females to adopt healthy behaviors. We investigated how and under what conditions do Web-based interactivity influence vaccination intentions among young females.

Methods

In this randomized controlled trail, we conduct a 2 (mode of information presentation: narrative vs. data visualization) × 2 (interactivity: interactive information vs. noninteractive information) between-groups design. A total of 180 Chinese female undergraduate students who had never received HPV vaccination were randomly allocated to 4 experimental groups. Each participant was assessed for their information avoidance behavior and vaccination intention. The hypotheses were tested using a moderated mediation model. All analyses were performed using SPSS version 22.0 with probability set at 0.05 alpha level.

Results

The indirect relationship between interactivity and behavioral intention though information avoidance was moderated by the mode of presentation. Under the narrative condition, interactivity (vs. non-interactivity) decreased information avoidance and increased the intention to receive HPV vaccination (B = -.23, SE = 0.10, P < 0.05). However, under data visualization condition, no significant difference was observed between the effects of interactivity and non-interactivity on intention.

Conclusion

The findings suggest that when young females experience difficulties in manipulating or understanding HPV-related information, their information-avoidance behavior is likely to increase. Rather than use interactive statistical or graphical information, young females are more likely to be persuaded by interactive narratives.
Medical code prediction via capsule networks and ICD knowledge
Authors: Bao Weidong , Lin Hongfei , Zhang Yijia , Wang Jian , Zhang Shaowu
Published: July 2021

Background

Clinical notes record the health status, clinical manifestations and other detailed information of each patient. The International Classification of Diseases (ICD) codes are important labels for electronic health records. Automatic medical codes assignment to clinical notes through the deep learning model can not only improve work efficiency and accelerate the development of medical informatization but also facilitate the resolution of many issues related to medical insurance. Recently, neural network-based methods have been proposed for the automatic medical code assignment. However, in the medical field, clinical notes are usually long documents and contain many complex sentences, most of the current methods cannot effective in learning the representation of potential features from document text.

Methods

In this paper, we propose a hybrid capsule network model. Specifically, we use bi-directional LSTM (Bi-LSTM) with forwarding and backward directions to merge the information from both sides of the sequence. The label embedding framework embeds the text and labels together to leverage the label information. We then use a dynamic routing algorithm in the capsule network to extract valuable features for medical code prediction task.

Results

We applied our model to the task of automatic medical codes assignment to clinical notes and conducted a series of experiments based on MIMIC-III data. The experimental results show that our method achieves a micro F1-score of 67.5% on MIMIC-III dataset, which outperforms the other state-of-the-art methods.

Conclusions

The proposed model employed the dynamic routing algorithm and label embedding framework can effectively capture the important features across sentences. Both Capsule networks and domain knowledge are helpful for medical code prediction task.
The trend of direct medical costs and associated factors in patients with chronic hepatitis B in Guangzhou, China: an eight-year retrospective cohort study
Authors: Yang Shuo , Chen Ge , Li Yueping , Li Guanhai , Liang Yingfang , Zhou Feng , Zhou Shudong , Yang Yi , Jia Weidong , Gao Yanhui , Chen Yue
Published: July 2021

Background

Although the expenses of liver cirrhosis are covered by a critical illness fund under the current health insurance program in China, the medical costs associated with hepatitis B virus (HBV) related diseases is not well addressed. In order to provide evidence to address the problem, we investigated the trend of direct medical costs and associated factors in patients with chronic HBV infection.

Methods

A retrospective cohort study of 65,175 outpatients and 12,649 inpatients was conducted using a hospital information system database for the period from 2008 to 2015. Generalized estimating equations (GEE) were applied to explore associations between annual direct medical costs and corresponding factors, meanwhile quantile regression models were used to evaluate the effect of treatment modes on different quantiles of annual direct medical costs stratified by medical insurances.

Results

The direct medical costs increased with time, but the proportion of antiviral costs decreased with CHB progression. Antiviral costs accounted 54.61% of total direct medical costs for outpatients, but only 6.17% for inpatients. Non-antiviral medicine costs (46.06%) and lab tests costs (23.63%) accounted for the majority of the cost for inpatients. The direct medical costs were positively associated with CHB progression and hospitalization days in inpatients. The direct medical costs were the highest in outpatients with medical insurance and in inpatients with free medical service, and treatment modes had different effects on the direct medical costs in patients with and without medical insurance.

Conclusions

CHB patients had a heavy economic burden in Guangzhou, China, which increased over time, which were influenced by payment mode and treatment mode.
A particle swarm optimization improved BP neural network intelligent model for electrocardiogram classification
Authors: Li Guixiang , Tan Zhongwei , Xu Weikang , Xu Fei , Wang Lei , Chen Jun , Wu Kai
Published: July 2021

Background

As proven to reflect the work state of heart and physiological situation objectively, electrocardiogram (ECG) is widely used in the assessment of human health, especially the diagnosis of heart disease. The accuracy and reliability of abnormal ECG (AECG) decision depend to a large extent on the feature extraction. However, it is often uneasy or even impossible to obtain accurate features, as the detection process of ECG is easily disturbed by the external environment. And AECG got many species and great variation. What’s more, the ECG result obtained after a long time past, which can not reach the purpose of early warning or real-time disease diagnosis. Therefore, developing an intelligent classification model with an accurate feature extraction method to identify AECG is of quite significance. This study aimed to explore an accurate feature extraction method of ECG and establish a suitable model for identifying AECG and the diagnosis of heart disease.

Methods

In this research, the wavelet combined with four operations and adaptive threshold methods were applied to filter the ECG and extract its feature waves first. Then, a BP neural network (BPNN) intelligent model and a particle swarm optimization (PSO) improved BPNN (PSO-BPNN) intelligent model based on MIT-BIH open database was established to identify ECG. To reduce the complexity of the model, the principal component analysis (PCA) was used to minimize the feature dimension.

Results

Wavelet transforms combined four operations and adaptive threshold methods were capable of ECG filtering and feature extraction. PCA can significantly deduce the modeling feature dimension to minimize the complexity and save classification time. The PSO-BPNN intelligent model was suitable for identifying five types of ECG and showed better effects while comparing it with the BPNN model.

Conclusion

In summary, it was further concluded that the PSO-BPNN intelligent model would be a suitable way to identify AECG and provide a tool for the diagnosis of heart disease.
Transformers-sklearn: a toolkit for medical language understanding with transformer-based models
Authors: Yang Feihong , Wang Xuwen , Ma Hetong , Li Jiao
Published: July 2021

Background

Transformer is an attention-based architecture proven the state-of-the-art model in natural language processing (NLP). To reduce the difficulty of beginning to use transformer-based models in medical language understanding and expand the capability of the scikit-learn toolkit in deep learning, we proposed an easy to learn Python toolkit named transformers-sklearn. By wrapping the interfaces of transformers in only three functions (i.e., fit, score, and predict), transformers-sklearn combines the advantages of the transformers and scikit-learn toolkits.

Methods

In transformers-sklearn, three Python classes were implemented, namely, BERTologyClassifier for the classification task, BERTologyNERClassifier for the named entity recognition (NER) task, and BERTologyRegressor for the regression task. Each class contains three methods, i.e., fit for fine-tuning transformer-based models with the training dataset, score for evaluating the performance of the fine-tuned model, and predict for predicting the labels of the test dataset. transformers-sklearn is a user-friendly toolkit that (1) Is customizable via a few parameters (e.g., model_name_or_path and model_type), (2) Supports multilingual NLP tasks, and (3) Requires less coding. The input data format is automatically generated by transformers-sklearn with the annotated corpus. Newcomers only need to prepare the dataset. The model framework and training methods are predefined in transformers-sklearn.

Results

We collected four open-source medical language datasets, including TrialClassification for Chinese medical trial text multi label classification, BC5CDR for English biomedical text name entity recognition, DiabetesNER for Chinese diabetes entity recognition and BIOSSES for English biomedical sentence similarity estimation.

In the four medical NLP tasks, the average code size of our script is 45 lines/task, which is one-sixth the size of transformers’ script. The experimental results show that transformers-sklearn based on pretrained BERT models achieved macro F1 scores of 0.8225, 0.8703 and 0.6908, respectively, on the TrialClassification, BC5CDR and DiabetesNER tasks and a Pearson correlation of 0.8260 on the BIOSSES task, which is consistent with the results of transformers.

Conclusions

The proposed toolkit could help newcomers address medical language understanding tasks using the scikit-learn coding style easily. The code and tutorials of transformers-sklearn are available at https://doi.org/10.5281/zenodo.4453803. In future, more medical language understanding tasks will be supported to improve the applications of transformers_sklearn.
Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning
Authors: Zeng Kun , Xu Yibin , Lin Ge , Liang Likeng , Hao Tianyong
Published: July 2021

Background

Eligibility criteria are the primary strategy for screening the target participants of a clinical trial. Automated classification of clinical trial eligibility criteria text by using machine learning methods improves recruitment efficiency to reduce the cost of clinical research. However, existing methods suffer from poor classification performance due to the complexity and imbalance of eligibility criteria text data.

Methods

An ensemble learning-based model with metric learning is proposed for eligibility criteria classification. The model integrates a set of pre-trained models including Bidirectional Encoder Representations from Transformers (BERT), A Robustly Optimized BERT Pretraining Approach (RoBERTa), XLNet, Pre-training Text Encoders as Discriminators Rather Than Generators (ELECTRA), and Enhanced Representation through Knowledge Integration (ERNIE). Focal Loss is used as a loss function to address the data imbalance problem. Metric learning is employed to train the embedding of each base model for feature distinguish. Soft Voting is applied to achieve final classification of the ensemble model. The dataset is from the standard evaluation task 3 of 5th China Health Information Processing Conference containing 38,341 eligibility criteria text in 44 categories.

Results

Our ensemble method had an accuracy of 0.8497, a precision of 0.8229, and a recall of 0.8216 on the dataset. The macro F1-score was 0.8169, outperforming state-of-the-art baseline methods by 0.84% improvement on average. In addition, the performance improvement had a p-value of 2.152e-07 with a standard t-test, indicating that our model achieved a significant improvement.

Conclusions

A model for classifying eligibility criteria text of clinical trials based on multi-model ensemble learning and metric learning was proposed. The experiments demonstrated that the classification performance was improved by our ensemble model significantly. In addition, metric learning was able to improve word embedding representation and the focal loss reduced the impact of data imbalance to model performance.
Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients
Authors: Sengupta Kinshuk , Srivastava Praveen Ranjan
Published: July 2021

Background

In medical diagnosis and clinical practice, diagnosing a disease early is crucial for accurate treatment, lessening the stress on the healthcare system. In medical imaging research, image processing techniques tend to be vital in analyzing and resolving diseases with a high degree of accuracy. This paper establishes a new image classification and segmentation method through simulation techniques, conducted over images of COVID-19 patients in India, introducing the use of Quantum Machine Learning (QML) in medical practice.

Methods

This study establishes a prototype model for classifying COVID-19, comparing it with non-COVID pneumonia signals in Computed tomography (CT) images. The simulation work evaluates the usage of quantum machine learning algorithms, while assessing the efficacy for deep learning models for image classification problems, and thereby establishes performance quality that is required for improved prediction rate when dealing with complex clinical image data exhibiting high biases.

Results

The study considers a novel algorithmic implementation leveraging quantum neural network (QNN). The proposed model outperformed the conventional deep learning models for specific classification task. The performance was evident because of the efficiency of quantum simulation and faster convergence property solving for an optimization problem for network training particularly for large-scale biased image classification task. The model run-time observed on quantum optimized hardware was 52 min, while on K80 GPU hardware it was 1 h 30 min for similar sample size. The simulation shows that QNN outperforms DNN, CNN, 2D CNN by more than 2.92% in gain in accuracy measure with an average recall of around 97.7%.

Conclusion

The results suggest that quantum neural networks outperform in COVID-19 traits’ classification task, comparing to deep learning w.r.t model efficacy and training time. However, a further study needs to be conducted to evaluate implementation scenarios by integrating the model within medical devices.
A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography
Authors: Gabarre Sergio , Vernaillen Frank , Baatsen Pieter , Vints Katlijn , Cawthorne Christopher , Boeynaems Steven , Michiels Emiel , Vandael Dorien , Gounko Natalia V. , Munck Sebastian
Published: July 2021

Background

Array tomography (AT) is a high-resolution imaging method to resolve fine details at the organelle level and has the advantage that it can provide 3D volumes to show the tissue context. AT can be carried out in a correlative way, combing light and electron microscopy (LM, EM) techniques. However, the correlation between modalities can be a challenge and delineating specific regions of interest in consecutive sections can be time-consuming. Integrated light and electron microscopes (iLEMs) offer the possibility to provide well-correlated images and may pose an ideal solution for correlative AT. Here, we report a workflow to automate navigation between regions of interest.

Results

We use a targeted approach that allows imaging specific tissue features, like organelles, cell processes, and nuclei at different scales to enable fast, directly correlated in situ AT using an integrated light and electron microscope (iLEM-AT). Our workflow is based on the detection of section boundaries on an initial transmitted light acquisition that serves as a reference space to compensate for changes in shape between sections, and we apply a stepwise refinement of localizations as the magnification increases from LM to EM. With minimal user interaction, this enables autonomous and speedy acquisition of regions containing cells and cellular organelles of interest correlated across different magnifications for LM and EM modalities, providing a more efficient way to obtain 3D images. We provide a proof of concept of our approach and the developed software tools using both Golgi neuronal impregnation staining and fluorescently labeled protein condensates in cells.

Conclusions

Our method facilitates tracing and reconstructing cellular structures over multiple sections, is targeted at high resolution ILEMs, and can be integrated into existing devices, both commercial and custom-built systems.
Exosome-derived noncoding RNAs in gastric cancer: functions and clinical applications
Authors: Tang Xiao-Huan , Guo Ting , Gao Xiang-Yu , Wu Xiao-Long , Xing Xiao-Fang , Ji Jia-Fu , Li Zi-Yu
Published: July 2021

Exosomes are a subpopulation of the tumour microenvironment (TME) that transmit various biological molecules to promote intercellular communication. Exosomes are derived from nearly all types of cells and exist in all body fluids. Noncoding RNAs (ncRNAs) are among the most abundant contents in exosomes, and some ncRNAs with biological functions are specifically packaged into exosomes. Recent studies have revealed that exosome-derived ncRNAs play crucial roles in the tumorigenesis, progression and drug resistance of gastric cancer (GC). In addition, regulating the expression levels of exosomal ncRNAs can promote or suppress GC progression. Moreover, the membrane structures of exosomes protect ncRNAs from degradation by enzymes and other chemical substances, significantly increasing the stability of exosomal ncRNAs. Specific hallmarks within exosomes that can be used for exosome identification, and specific contents can be used to determine their origin. Therefore, exosomal ncRNAs are suitable for use as diagnostic and prognostic biomarkers or therapeutic targets. Regulating the biogenesis of exosomes and the expression levels of exosomal ncRNAs may represent a new way to block or eradicate GC. In this review, we summarized the origins and characteristics of exosomes and analysed the association between exosomal ncRNAs and GC development.
Examination of the psychometric properties of the persian version of the COVID-19-impact on Quality of Life Scale
Authors: Dehkordi Ali Hasanpour , Aslani Marzieh , Ebadi Abbas , Repišti Selman , Moradveisi Borhan , Gheshlagh Reza Ghanei
Published: July 2021

Introduction

As a result of high transmission and mortality rates, the Covid-19 pandemic has led to a worldwide health crisis, isolation, and widespread fear, therefore negatively influencing people’s quality of life (QOL). The goal of the present study was to examine the psychometric properties (validity and reliability) of the Persian version of the COVID-19-Impact on Quality of Life (COV19-QoL) scale.

Methods

After translating the scale using the forward–backward method, face and content validly was qualitatively assessed. Then the scale was distributed to 488 individuals from the general population via online platforms. Construct validity was assessed using exploratory (EFA) and confirmatory (CFA) factor analysis. In addition, internal consistency was examined using Cronbach’s alpha coefficient and McDonald’s omega, relative stability was assessed using interclass correlation coefficient (ICC), and absolute stability was calculated through examination of standard error of measurement.

Results

The EFA revealed one factor that explained 55.96% of the total variance of the scale. Internal consistencies of 0.823 and 0.882 were found using Cronbach’s alpha coefficient and McDonald’s omega, respectively. In addition, an ICC of 0.837 (with a two-week interval) was found. Covid-19 had a greater impact on the QOL of healthy participants than that of those with underling conditions (p = 0.004), and also on the QOL of single participants than that of married ones (p = 0.032).

Conclusion

The Persian version of the COV19-QoL is a valid and reliable instrument that can be used to examine the impact of Covid-19 on QOL.