bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the quality of care in health systems: towards better strategies
Authors: Dixon Jennifer 
Published: February 2021

AbstractImproving the quality of health care across a nation is complex and hard. Countries often rely on multiple single national level programmes to make progress. But the key is to use a framework to develop a balanced overall strategy, and evaluate the main elements continuously and over time. Achieving that requires having a critical mass of leaders who collectively can see the bigger picture now, envision a roadmap for the future to chart an intelligent course, and course correct regularly. This is a long-term agenda requiring commitment, careful stewardship, different perspectives, trust, and the building of knowledge and experience over time. It is also almost completely at odds with much current policymaking which is short term, reactive and demands hard results. Many countries are making progress. But the rapid introduction of new types of care during the COVID 19 pandemic, such as online and digital, the use of new technologies which could soon revolutionalise the way care is delivered, experienced and evaluated, and the huge pressures on spending on health care in future mean we will have to do better. Achieving system-wide quality of care requires having a critical mass of leaders who collectively can see the bigger picture now, envision a roadmap for the future to chart a balanced intelligent course. For the Israeli health system, the recent IJHPR article by Dreiher et al. will help, but it will be important, in the future, to analyse how Israel measures up on the framework outlined above. This ideally would be supplemented with a survey of key leaders for their assessment, and both would be a regular (say 5 yearly) exercise and would help inform future strategies.
Stable routing and energy-conserved data transmission over wireless sensor networks
Authors: Shukry Suzan 
Published: February 2021

AbstractStable routing and energy conservation over a wireless sensor network (WSN) is a major issue in Internet of Things applications. The network lifetime can be increased when studying this issue with interest. Data transmission is a dominant factor in IoT networks for communication overhead and energy consumption. A proposed efficient node stable routing ($$ENSR$$

ENSR

) protocol is introduced to guarantee the stability of transmission data between the source and destination nodes, in a dynamic WSN conditions. $$ENSR$$

ENSR

minimizes energy consumption and selects more stable nodes for packets forwarding. Stability becomes the most important factor that qualifies the node's centrality. A node’s stability is characterized by residual energy, link quality, and number of hops needed to reach the destination from the node. To calculate node's stability, an enhanced centrality concept, known as stable betweenness centrality ($$SBC$$

SBC

) is introduced. In $$ENSR$$

ENSR

, at first, some nodes will be selected as the stable forwarding nodes, usually with maximum $$SBC$$

SBC

between their neighbors within a limited communication radio range of a particular region. Furthermore, each stable forwarding node then broadcasts its identity, including $$SBC$$

SBC

, to the source node separately. The source node can compute a stable path to forward packets to the corresponding stable forwarding node, based on a proper designed stable path routing metric ($$SPRM$$

SPRM

). Then, the stable forwarding node will behave as a new source node and start another stable path routing process until the packets are forwarded and reached to the destination node. In addition, the change of stable nodes over time balances and conserves node energy consumption, thereby mitigating “hot spots”. The proposed routing protocol is validated through simulation. The numerical results show that the proposed protocol outperforms the existing algorithms, global and local reliability-based routing ($$GLRR$$

GLRR

) and reliable energy-aware routing protocol $$(RER)$$

(
R
E
R
)

, in terms of network efficiency and reliability.
Creation of an algorithm for clinical decision support for treatment of opioid use disorder with buprenorphine in primary care
Authors: dela Cruz Adriane M. , Walker Robrina , Pipes Ronny , Wakhlu Sidarth , Trivedi Madhukar H. 
Published: February 2021

Abstract
Background
The treatment capacity for opioid use disorder (OUD) lags far behind the number of patients in need of treatment. Capacity is limited, in part, by the limited number of physicians who offer office based OUD treatment with buprenorphine. Measurement based care (MBC) has been proposed as a means to support primary care physicians in treating OUD. Here, we propose a set of measures and a clinical decision support algorithm to provide MBC for the treatment of OUD.

Methods
We utilized literature search and expert consensus to identify measures for universal screening and symptom tracking. We used expert consensus to create the clinical decision support algorithm.

Results
The Tobacco, Alcohol, Prescription medication, and other Substance use (TAPS) tool was selected as the best published measure for universal screening in primary care. No published measure was identified as appropriate for symptom tracking or medication adherence; therefore, we created the OUD Symptom Checklist from the DSM-5 criteria for OUD and the Patient Adherence Questionnaire for Opioid Use Disorder Treatment (PAQ-OUD) to assess medication adherence. We developed and present a clinical decision support algorithm to provide direct guidance regarding treatment interventions during the first 12 weeks of buprenorphine treatment.

Conclusion
Creation of these tools is the necessary first step for implementation of MBC for the treatment of OUD with buprenorphine in primary care. Further work is needed to test the feasibility and acceptability of these tools.
Trial Registration ClinicalTrials.gov; NCT04059016; 16 August 2019; retrospectively registered; https://clinicaltrials.gov/ct2/show/NCT04059016
Vaginal colonization with antimicrobial-resistant bacteria among women in labor in central Uganda: prevalence and associated factors
Authors: Tumuhamye Josephine , Steinsland Hans , Bwanga Freddie , Tumwine James K. , Ndeezi Grace , Mukunya David , Namugga Olive , Kasede Agnes Napyo , Sommerfelt Halvor , Nankabirwa Victoria 
Published: February 2021

AbstractBackgroundAccording to WHO ( CISMAC. Centre for Intervention Science in Maternal and Child health), the antimicrobial resistant bacteria considered to be clinically most important for human health and earmarked for surveillance include extended-spectrum beta-lactamase (ESBL)-producingEnterobacteriaceae,carbapenem-resistant bacteria, methicillin-resistant (MRSA) and, macrolide-lincosamide-streptogramin B -resistant vancomycin-resistant (VRSA)Staphylococcus aureusand vancomycin-resistantEnterococcus(VRE). If these bacteria are carried in the female genital tract, they may be transmitted to the neonate causing local or systemic neonatal infections that can be difficult to treat with conventionally available antimicrobials. In order to develop effective treatment strategies, there is need for updated information about the prevalence of colonization with important antimicrobial-resistant pathogens.ObjectiveWe sought to estimate the prevalence of vaginal colonization with potentially pathogenic and clinically important AMR bacteria among women in labour in Uganda and to identify factors associated with colonization.MethodsWe conducted a cross-sectional study among HIV-1 and HIV-2 negative women in labour at three primary health care facilities in Uganda. Drug susceptibility testing was done using the disk diffusion method on bacterial isolates cultured from vaginal swabs. We calculated the prevalence of colonization with potentially pathogenic and clinically important AMR bacteria, in addition to multidrug-resistant (MDR) bacteria, defined as bacteria resistant to antibiotics from ≥ 3 antibiotic classes.ResultsWe found that 57 of the 1472 enrolled women (3.9% prevalence; 95% Confidence interval [CI] 3.0%, 5.1%) were colonized with ESBL-producingEnterobacteriaceace,27 (1.8%; 95% CI 1.2%, 2.6%) were colonized with carbapenem-resistantEnterobacteriaceae, and 85 (5.8%; 95% CI 4.6%, 7.1%) were colonized with MRSA. The prevalence of colonization with MDR bacteria was high (750/1472; 50.9%; 95% CI 48.4%, 53.5%). Women who were ≥ 30 years of age had higher odds of being colonized with MDR bacteria compared to women aged 20–24 years (OR 1.6; 95% CI 1.1, 2.2).ConclusionMost of the women included in our study were vaginally colonized with potentially pathogenic MDR and other clinically important AMR bacteria. The high prevalence of colonization with these bacteria is likely to further increase the incidence of difficult-to-treat neonatal sepsis.
Visual biofeedback for paradoxical vocal fold motion (PVFM)
Authors: LeBlanc Rachelle Alyce , Aalto Daniel , Jeffery Caroline C. 
Published: February 2021

Objectives Paradoxical vocal fold motion (PVFM) is a common condition where the vocal folds inappropriately adduct during inspiration. This results in dyspnea and occasionally significant distress. The condition is thought to be primarily functional, with behavioural therapy considered mainstay in the non-acute setting. However, practice variations and limited access to speech language pathology (SLP) services can pose management challenges. We aimed to examine the efficacy of surgeon performed visual biofeedback as first-line treatment for PVFM. Study design Prospective, non-randomized, non-comparative clinical study. Methods Adult patients referred for possible PVFM and congruent laryngoscopy findings over a two-year period were included. Patients were excluded if they presented in acute distress, had alternate diagnosis to explain symptomology and/or coexisting untreated lower respiratory pathology. Patients underwent immediate surgeon-performed visual biofeedback on the same visit day. The primary outcome of interest was change in Dyspnea Index (DI) scores pre- and post-intervention 3 months follow-up. The secondary outcome measured was change in asthma medication use from baseline to follow-up. Results Of 34 patients presenting, 25 met inclusion criteria. Of these, 72% were female with an average age of 36.9 ± 14.1. Approximately 48% of patients had a diagnosis of well-controlled asthma at presentation and co-morbid psychiatric diagnoses were common (52%). Pre- and post-intervention analysis showed significant improvement in DI scores ( p < 0.001) and reduction in bronchodilator use ( p = 0.003). Conclusion This is a prospective study that evaluates the role of visual biofeedback in PVFM patients. Our data suggests that visual biofeedback effectively reduces short-term subjective symptoms and asthma medication use. Level of evidence 3 Graphical abstract
Development and validation of an online model to predict critical COVID-19 with immune-inflammatory parameters
Authors: Gao Yue , Chen Lingxi , Chi Jianhua , Zeng Shaoqing , Feng Xikang , Li Huayi , Liu Dan , Feng Xinxia , Wang Siyuan , Wang Ya , Yu Ruidi , Yuan Yuan , Xu Sen , Li Chunrui , Zhang Wei , Li Shuaicheng , Gao Qinglei 
Published: February 2021

AbstractBackgroundImmune and inflammatory dysfunction was reported to underpin critical COVID-19(coronavirus disease 2019). We aim to develop a machine learning model that enables accurate prediction of critical COVID-19 using immune-inflammatory features at admission.MethodsWe retrospectively collected 2076 consecutive COVID-19 patients with definite outcomes (discharge or death) between January 27, 2020 and March 30, 2020 from two hospitals in China. Critical illness was defined as admission to intensive care unit, receiving invasive ventilation, or death. Least Absolute Shrinkage and Selection Operator (LASSO) was applied for feature selection. Five machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), Gradient Boosted Decision Tree (GBDT), K-Nearest Neighbor (KNN), and Neural Network (NN) were built in a training dataset, and assessed in an internal validation dataset and an external validation dataset.ResultsSix features (procalcitonin, [T + B + NK cell] count, interleukin 6, C reactive protein, interleukin 2 receptor, T-helper lymphocyte/T-suppressor lymphocyte) were finally used for model development. Five models displayed varying but all promising predictive performance. Notably, the ensemble model, SPMCIIP (severity prediction model for COVID-19 by immune-inflammatory parameters), derived from three contributive algorithms (SVM, GBDT, and NN) achieved the best performance with an area under the curve (AUC) of 0.991 (95% confidence interval [CI] 0.979–1.000) in internal validation cohort and 0.999 (95% CI 0.998–1.000) in external validation cohort to identify patients with critical COVID-19. SPMCIIP could accurately and expeditiously predict the occurrence of critical COVID-19 approximately 20 days in advance.ConclusionsThe developed online prediction model SPMCIIP is hopeful to facilitate intensive monitoring and early intervention of high risk of critical illness in COVID-19 patients.Trial registrationThis study was retrospectively registered in the Chinese Clinical Trial Registry (ChiCTR2000032161).Graphical abstracthelper lymphocytvevv
Imaging features of fumarate hydratase-deficient renal cell carcinomas: a retrospective study
Authors: Nikolovski Ines , Carlo Maria I. , Chen Ying-Bei , Vargas Hebert Alberto 
Published: February 2021

Abstract
Backgound
Fumarate hydratase-deficient renal cell carcinoma (FH-RCC) is a subtype of RCC that is increasingly recognized pathologically. The aim of this study was to evaluate the imaging features of FH-RCC on computed tomography (CT), magnetic resonance imaging (MRI), and fluorodeoxyglucose positron emission tomography (FDG PET), and to determine the pre-operative diagnostic potential of imaging.

Methods
This single-site retrospective study included patients with histologically confirmed FH-RCC or with a renal cancer and known germline FH mutation; imaging of the renal mass before treatment with contrast-enhanced CT, contrast-enhanced MRI, or FDG PET/CT between October 2007 and May 2019. Clinical information, pathological data, and imaging features were analyzed and reported descriptively.

Results
Sixteen patients with sixteen tumors were included (median age 46 years, interquartile range 38–53 years; 31 % female). Almost all tumors were unifocal (15/16, 94 %). Most tumors had infiltrative margins (14/16, 88 %); few were circumscribed (2/16, 12 %). A large cystic tumor component (> 75 % of tumor volume) was seen in 8/16 (50 %) of tumors. Involvement of renal sinus fat was seen in 13/16 (81 %) of tumors, involvement of the hilar collecting system in 8/16 (50 %), and renal vein tumor thrombus in 6/16 (38 %). All 12 tumors (100 %) imaged with MRI had heterogenous tumor enhancement and heterogenous T2 signal. Of those patients that had diffusion-weighted imaging, 11/11 (100 %) of tumors had diffusion restriction in the solid portions of the tumor. Of the patients who had PET, 3/3 (100 %) tumors showed high metabolic activity with mean maximum standardized uptake value (SUVmax) of 16.4 (range 9.6–21.9). Patients presented with retroperitoneal nodal metastases in 69 % of cases and distant metastases in 75 %. Of those four patients without metastatic disease at presentation, three (75 %) developed metastases within 4 years of diagnosis.

Conclusions
In our study, the majority of tumors (≥ 75 %) were unifocal, had an infiltrative margin, invaded the renal sinus fat, and presented with distant metastases. On MRI, most tumors had heterogenous T2 signal and diffusion restriction in their solid components. The small number of cases that had PET imaging showed high metabolic activity.
Using GEDI lidar data and airborne laser scanning to assess height growth dynamics in fast-growing species: a showcase in Spain
Authors: Guerra-Hernández Juan , Pascual Adrián 
Published: February 2021

Abstract
Background
The NASA’s Global Ecosystem Dynamics Investigation (GEDI) satellite mission aims at scanning forest ecosystems on a multi-temporal short-rotation basis. The GEDI data can validate and update statistics from nationwide airborne laser scanning (ALS). We present a case in the Northwest of Spain using GEDI statistics and nationwide ALS surveys to estimate forest dynamics in three fast-growing forest ecosystems comprising 211,346 ha. The objectives were: i) to analyze the potential of GEDI to detect disturbances, ii) to investigate uncertainty source regarding non-positive height increments from the 2015–2017 ALS data to the 2019 GEDI laser shots and iii) to estimate height growth using polygons from the Forest Map of Spain (FMS). A set of 258 National Forest Inventory plots were used to validate the observed height dynamics.

Results
The spatio-temporal assessment from ALS surveying to GEDI scanning allowed the large-scale detection of harvests. The mean annual height growths were 0.79 (SD = 0.63), 0.60 (SD = 0.42) and 0.94 (SD = 0.75) m for Pinus pinaster, Pinus radiata and Eucalyptus spp., respectively. The median annual values from the ALS-GEDI positive increments were close to NFI-based growth values computed for Pinus pinaster and Pinus radiata, respectively. The effect of edge border, spatial co-registration of GEDI shots and the influence of forest cover in the observed dynamics were important factors to considering when processing ALS data and GEDI shots.

Discussion
The use of GEDI laser data provides valuable insights for forest industry operations especially when accounting for fast changes. However, errors derived from positioning, ground finder and canopy structure can introduce uncertainty to understand the detected growth patterns as documented in this study. The analysis of forest growth using ALS and GEDI would benefit from the generalization of common rules and data processing schemes as the GEDI mission is increasingly being utilized in the forest remote sensing community.
Searching in CCTV: effects of organisation in the multiplex
Authors: Tatler Benjamin W. 
Published: February 2021

AbstractCCTV plays a prominent role in public security, health and safety. Monitoring large arrays of CCTV camera feeds is a visually and cognitively demanding task. Arranging the scenes by geographical proximity in the surveilled environment has been recommended to reduce this demand, but empirical tests of this method have failed to find any benefit. The present study tests an alternative method for arranging scenes, based on psychological principles from literature on visual search and scene perception: grouping scenes by semantic similarity. Searching for a particular scene in the array—a common task in reactive and proactive surveillance—was faster when scenes were arranged by semantic category. This effect was found only when scenes were separated by gaps for participants who were not made aware that scenes in the multiplex were grouped by semantics (Experiment 1), but irrespective of whether scenes were separated by gaps or not for participants who were made aware of this grouping (Experiment 2). When target frequency varied between scene categories—mirroring unequal distributions of crime over space—the benefit of organising scenes by semantic category was enhanced for scenes in the most frequently searched-for category, without any statistical evidence for a cost when searching for rarely searched-for categories (Experiment 3). The findings extend current understanding of the role of within-scene semantics in visual search, to encompass between-scene semantic relationships. Furthermore, the findings suggest that arranging scenes in the CCTV control room by semantic category is likely to assist operators in finding specific scenes during surveillance.
Lecanicillium lecanii (Zimmermann) Zare & Gams, as an efficient biocontrol agent of tea thrips, Scirtothrips bispinosus Bagnall (Thysanoptera: Thripidae)
Authors: Subramaniam Mariappan Sankara Rama , Babu Azariah , Deka Bhabesh 
Published: February 2021

Abstract
Background
Continuous and non-judicial application of synthetic insecticides to control the tea thrips, Scirtothrips bispinosus (Bagnall), one of the major tea pests in South India has led to certain undesirable issues in the ecosystem besides the presence of the pesticide residues in manufactured tea. Biological control agents are of immense importance in tea cultivation. The present study was designed to isolate Lecanicillium lecanii (Zimmermann) Zare & Gama from the field-collected cadavers of the insects/mites infected by fungi of tea growing areas of Anamallais (Tamil Nadu, South India), and to evaluate their field bio-efficacy against the tea thrips.

Results
Lecanicillium lecanii isolated from the tea ecosystem had been formulated into a wettable powder (WP) formulation and evaluated against tea thrips under both laboratory and field conditions. Among the several media evaluated, the PDAY (Potato Dextrose Agar + 1% Yeast powder) was found to be the best suitable medium for the growth and germination of spores. Optimum conditions for the growth of L. lecanii were found in PDAY medium at the pH 6-7, temperature 25-30°C and 90-95% RH. Exposure to UV light for more than 30 min significantly inhibited the growth of the fungus. Lecanicillium lecanii at (1 × 107 spore/ha) was found significantly effective against thrips. Fungal development index (FDI) of L. lecanii + jaggery significantly differed than other treatments. Lecanicillium lecanii at 1500g (1×107 conidia/ml) mixed in 400 l of water was effective against the tea thrips. Addition of equal amount of jaggery with L. lecanii wettable powder in the tank mixture could increase the efficacy of the mycopesticide against tea thrips.

Conclusion
The powder formulation of L. lecanii was found safer to natural enemies present in the tea ecosystem. After fulfilling the requirements for its registration and label claim on tea, this strain of L. lecanii could be commercialized for the benefit of the tea industry for the management of tea thrips in an eco-friendly manner.
Successfully managed bilateral pneumothorax and subcutaneous emphysema after emergency open surgical tracheotomy
Authors: Yilmaz Fulya 
Published: February 2021

Abstract
Background
The most common complications we encountered in tracheotomies are hemorrhage, pneumothorax, and tube displacement. In this case report, we describe bilateral pneumothorax following an emergency tracheotomy.

Case presentation
A 57-year-old woman, who was diagnosed with laryngeal carcinoma, was developed sudden respiratory distress in the ear nose throat (ENT) ward before surgery. The patient was taken to the operating room for emergency tracheotomy. After surgery, at the 5th minute of the mechanical ventilator follow-up in ICU, she developed subcutaneous emphysema on her eyes, face, neck, and chest. She was taken to re-operation. On the postoperative follow-up, bilateral pneumothorax was detected on chest X-ray and bilateral thorax tube was applied by thoracic surgeon. She was externed to ENT ward on the 3rd postoperative day. The left thorax tube was removed on the 2nd and right thorax tube was removed on the 6th postoperative day.

Conclusion
Here, we presented a successfully managed bilateral pneumothorax and subcutaneous emphysema after emergency open surgical tracheotomy. If persistence reduction of SPO2 levels after tracheotomy, pneumothorax should be kept in the mind.