Is shortening of displaced mid-shaft clavicle fractures associated with inferior clinical outcomes following non-operative management? A systematic review

Background: Management of displaced mid-shaft clavicle fractures is controversial. Non-operative treatment can lead to shortening, a risk factor for non-union and poor functional outcomes. These inferior results have resulted in authors recommending surgical fixation for fractures with significant shortening. The aim of this systematic review is to analyse the effect of fracture shortening on shoulder function and non-union rate in non-operatively managed displaced mid-shaft clavicle fractures. Methods: A review of the online databases Medline and EMBASE was conducted in accordance with the PRISMA guidelines on the 16th February 2018. The review was registered prospectively on the PROSPERO database. Clinical studies with mid-shaft clavicle fractures treated non-operatively reporting an evaluation of the degree of clavicle shortening, and either shoulder function and/or non-union were included. The studies were appraised using the Methodological index for non-randomised studies tool. Results: The search strategy identified 16 studies eligible for inclusion. Four studies were randomised controlled trials (RCTs) and twelve were non-randomised retrospective comparative studies. Eleven of the twelve case series failed to demonstrate any correlation between shortening and shoulder outcome scores. Of the four RCTs, three reported no significant association between fracture shortening and shoulder outcome scores. The studies also failed to demonstrate a significant association between non union and the presence of clavicle shortening. Conclusion: There is no significant association between fracture shortening and non-union rates or shoulder outcome scores in displaced mid-shaft clavicle fractures managed non-operatively. Level of evidence: II

EFFORT: Energy efficient framework for offload communication in mobile cloud computing

There is an abundant expansion in the race of technology, specifically in the production of data, because of the smart devices, such as mobile phones, smart cards, sensors, and Internet of Things (IoT). Smart phones and devices have undergone an enormous evolution in a way that they can be used. More and more new applications, such as face recognition, augmented reality, online interactive gaming, and natural language processing are emerging and attracting the users. Such applications are generally data intensive or compute intensive, which demands high resource and energy consumption. Mobile devices are known for the resource scarcity, having limited computational power and battery life. The tension between compute/data intensive application and resource constrained mobile devices hinders the successful adaption of emerging paradigms. In the said perspective, the objective of this paper is to study the role of computation offloading in mobile cloud computing to supplement mobile platforms ability in executing complex applications. This paper proposes a systematic approach (EFFORT) for offload communication in the cloud. The proposed approach provides a promising solution to partially solve energy consumption issue for communication-intensive applications in a smartphone. The experimental study shows that our proposed approach outperforms its counterparts in terms of energy consumption and fast processing of smartphone devices. The battery consumption was reduced to 19% and the data usage was reduced to 16%

A Deep Learning-Based Privacy-Preserving Model for Smart Healthcare in Internet of Medical Things Using Fog Computing

With the emergence of COVID-19, smart healthcare, the Internet of Medical Things, and big data-driven medical applications have become even more important. The biomedical data produced is highly confidential and private. Unfortunately, conventional health systems cannot support such a colossal amount of biomedical data. Hence, data is typically stored and shared through the cloud. The shared data is then used for different purposes, such as research and discovery of unprecedented facts. Typically, biomedical data appear in textual form (e.g., test reports, prescriptions, and diagnosis). Unfortunately, such data is prone to several security threats and attacks, for example, privacy and confidentiality breach. Although significant progress has been made on securing biomedical data, most existing approaches yield long delays and cannot accommodate real-time responses. This paper proposes a novel fog-enabled privacy-preserving model called [Formula: see text] sanitizer, which uses deep learning to improve the healthcare system. The proposed model is based on a Convolutional Neural Network with Bidirectional-LSTM and effectively performs Medical Entity Recognition. The experimental results show that [Formula: see text] sanitizer outperforms the state-of-the-art models with 91.14% recall, 92.63% in precision, and 92% F1-score. The sanitization model shows 28.77% improved utility preservation as compared to the state-of-the-art

KEBIJAKAN KEPALA SEKOLAH DALAM PENINGKATAN EFEKTIVITAS PEMBELAJARAN ONLINE PADA MASA COVID-19 DI SMA NEGERI 2 TANJUNG JABUNG TIMUR

Penelitian ini membahas Tentang Kebijakan Kepala sekolahDalam Peningkatan Efektivitas Pembelajaran Online Pada Masa Covid-19 Di SMA Negeri 2 Tanjung Jabung Timur. Selanjutnya dapat dijadikan refrensi dan motivasi terhadap pengembangan literasi terutama dalam peningkatan efektifitas pembelajaran siswa hingga tercapainya tujuan pembelajaran sesuai yang diharapkan. Penelitian ini menggunakan pendekatan kualitatif deskriftif dengan mengunakan metode pengumpulan data observasi, wawancara dan dokumentasi. Tahap teknik analisis data meliputi reduksi data, penyajian data dan verifikasi data, sedangkan pengecekan keterpercayaan data dilakukan dengan perpanjangan keikutsertaan, ketelitian pengamatan, triangulasi dan melakukan konsultasi ke pembimbing. Hasil penelitian menunjukkan bahwa: (1)Kebijakan Kepala Sekolah dalam peningkatan Efektivitas Pembelajaran Online Pada Masa Covid-19 Di Sman 2 Tanjung Jabung Timurdiantaranya sebagai a). daring dan luring, b). Kurikulum. 3) pembelajaran, melalui beberapa tahapan sebagai berikut: 1) Perencanaan, 2) Pengorganisasian, 3) Pengawasan Yang dilakukan langsung oleh kepala sekolah.(2). Faktor Pendorong dan Penghambat Penerapan Kebijakan Kepalah Sekolah Dalam peningkatan Efektivitas Pembelajaran Online Pada Masa Covid�19 di SMAN 2 Tanjung Jabung Timurseperti:a). Tersedianya perangkat handphone bagi siswa dan guru. 2). Adanya groupWhatsap, 3). Guru dapat memahami tingkat kepedulian orang tua terhadap anaknya dalam hal belajar, 4). Kerjasama yang baik antara orang tua engan guru. Adapun faktor penghambat yaitu, terkendala dalam sinyal dan kuota internet. Sinyal yang tidak stabil serta terbatasnya kuota internet membuat guru dan siswa dalam proses pembelajaran daring/luring tersebut tidak berjalan dengan maksimal. Faktor penghambat lainnya dalam mengimplementasikan pembelajaran daring/luring di SMAN 2 Tanjung Jabung Timur, yaitu dari antusias siswa yang kurang, (3) Efektivitas Pembelajaran SMAN 2 Tanjung Jabung Timur. Telah berjlan dengan efektiv namun belum maksimal

Increased risk of noninfluenza respiratory virus infections associated with receipt of inactivated influenza vaccine

We randomized 115 children to trivalent inactivated influenza vaccine (TIV) or placebo. Over the following 9 months, TIV recipients had an increased risk of virologically-confirmed non-influenza infections (relative risk: 4.40; 95 confidence interval: 1.31-14.8). Being protected against influenza, TIV recipients may lack temporary non-specific immunity that protected against other respiratory viruses. © 2012 The Author.postprin

Beverage patterns and trends among school-aged children in the US, 1989-2008

<p>Abstract</p> <p>Background</p> <p>High intake of sugar-sweetened beverages in childhood is linked to increased risk of obesity and type II diabetes later in life. Using three nationally representative surveys of dietary intake, we investigated beverage patterns and trends among US school-aged children from 1989/91 to 2007/08.</p> <p>Methods</p> <p>3, 583 participants ages 6-11 y old were included. We reported per capita trends in beverage consumption, percent consuming, and amount per consumer for the following categories of beverages: sugar-sweetened beverages (SSB), caloric nutritional beverages (CNB) and low calorie beverages (LCB). Statistically significant differences were tested using the Student's t test in Stata 11.</p> <p>Results</p> <p>While per capita kcal contribution from total beverages remained constant over the study period, per capita consumption of SSBs increased and CNBs decreased in similar magnitude. The substantial increase in consumption of certain SSBs, such as fruit drinks and soda, high fat high sugar milk, and sports drinks, coupled with the decrease in consumption of high fat low sugar milk was responsible for this shift. The percent consuming SSBs as well as the amount per consumer increased significantly over time. Per capita intake of total milk declined, but the caloric contribution from high fat high sugar milk increased substantially. Among ethnicities, important differences in consumption trends of certain SSBs and 100% juice indicate the complexity in determining strategies for children's beverage calorie reduction.</p> <p>Conclusions</p> <p>As upward trends of SSB consumption parallel increases in childhood obesity, educational and policy interventions should be considered.</p

Prior Coronary Artery Bypass Graft Surgery and Outcome After Percutaneous Coronary Intervention: An Observational Study From the Pan-London Percutaneous Coronary Intervention Registry.

Background Limited information exists regarding procedural success and clinical outcomes in patients with previous coronary artery bypass grafting (CABG) undergoing percutaneous coronary intervention (PCI). We sought to compare outcomes in patients undergoing PCI with or without CABG. Methods and Results This was an observational cohort study of 123 780 consecutive PCI procedures from the Pan-London (UK) PCI registry from 2005 to 2015. The primary end point was all-cause mortality at a median follow-up of 3.0 years (interquartile range, 1.2-4.6 years). A total of 12 641(10.2%) patients had a history of previous CABG, of whom 29.3% (n=3703) underwent PCI to native vessels and 70.7% (n=8938) to bypass grafts. There were significant differences in the demographic, clinical, and procedural characteristics of these groups. The risk of mortality during follow-up was significantly higher in patients with prior CABG (23.2%; P=0.0005) compared with patients with no prior CABG (12.1%) and was seen for patients who underwent either native vessel (20.1%) or bypass graft PCI (24.2%; P<0.0001). However, after adjustment for baseline characteristics, there was no significant difference in outcomes seen between the groups when PCI was performed in native vessels in patients with previous CABG (hazard ratio [HR],1.02; 95%CI, 0.77-1.34; P=0.89), but a significantly higher mortality was seen among patients with PCI to bypass grafts (HR,1.33; 95% CI, 1.03-1.71; P=0.026). This was seen after multivariate adjustment and propensity matching. Conclusions Patients with prior CABG were older with greater comorbidities and more complex procedural characteristics, but after adjustment for these differences, the clinical outcomes were similar to the patients undergoing PCI without prior CABG. In these patients, native-vessel PCI was associated with better outcomes compared with the treatment of vein grafts

Validation of Statistical Models for Estimating Hospitalization Associated with Influenza and Other Respiratory Viruses

BACKGROUND: Reliable estimates of disease burden associated with respiratory viruses are keys to deployment of preventive strategies such as vaccination and resource allocation. Such estimates are particularly needed in tropical and subtropical regions where some methods commonly used in temperate regions are not applicable. While a number of alternative approaches to assess the influenza associated disease burden have been recently reported, none of these models have been validated with virologically confirmed data. Even fewer methods have been developed for other common respiratory viruses such as respiratory syncytial virus (RSV), parainfluenza and adenovirus. METHODS AND FINDINGS: We had recently conducted a prospective population-based study of virologically confirmed hospitalization for acute respiratory illnesses in persons <18 years residing in Hong Kong Island. Here we used this dataset to validate two commonly used models for estimation of influenza disease burden, namely the rate difference model and Poisson regression model, and also explored the applicability of these models to estimate the disease burden of other respiratory viruses. The Poisson regression models with different link functions all yielded estimates well correlated with the virologically confirmed influenza associated hospitalization, especially in children older than two years. The disease burden estimates for RSV, parainfluenza and adenovirus were less reliable with wide confidence intervals. The rate difference model was not applicable to RSV, parainfluenza and adenovirus and grossly underestimated the true burden of influenza associated hospitalization. CONCLUSION: The Poisson regression model generally produced satisfactory estimates in calculating the disease burden of respiratory viruses in a subtropical region such as Hong Kong