Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

ʔAlsh

An array of Egyptian lifeworlds in 2016.</jats:p

ʔAlsh: An array of Egyptian lifeworlds in 2016

An array of Egyptian lifeworlds in 2016. GOTO ARRAYS: Apartment Wanted | ʿAshwāʾiyyāt | Baby Milk | Celebrities | Clash | Commemoration / Memorial Days | Conversions | Court Trials | Crowdfunding | Dancing | Disappearances | Disasters | Dollar Crisis | Downtown/Centre-ville | Dual Identities / Masking | Éveil d’une nation / Ṣaḥwat umma | Father Figures | Football | Garbage | Gated Communities / Compounds | Hashish | High School Exams | The Honourable Citizen | In Islam, … | Kamīn | Language | LGBT | Manīsh msāmiḥ | Migration | Mobile Phones | The Policeman Criminal | Pop Music | Prison | Psychiatrists | Public Hearings | Red Sea Islands | Self-help | Social Media | Suicide | The Suspect Foreigner | Tourist Resorts | Tricking the System / Tricked by the System | Tuk-tuk | Uber | Valentine’s Day | The Voice from Above | Zaḥma CODES: Affluence vs. Destitution | Beautiful vs. Ugly | Center vs. Periphery | Freedom vs. Constraint | Hope vs. Hell | Inferiority vs. Superiority | Male vs. Female | Normality vs. Heroism | Past vs. Present | Security vs. Fear | “The System” vs. “The People” | True vs. False | Voice vs. Silence | Young vs. Settled CODES COLLAPSED: Hope = Hell (Dystopia) | Inferiority = Superiority (Satire) | Normality = Heroism (Surviving) | Present = Past (Stuck) | Security = Fear (Police State) | True = False (Life in Limbo

How different typologies of platforms are used to foster platform thinking in established linear value chain firms?

LAUREA MAGISTRALELe piattaforme sono diventate una parte essenziale della nostra vita quotidiana, dipendiamo enormemente da diversi tipi di piattaforme per svolgere un determinato compito, assicurarci un alloggio o spostarci da un luogo a un altro. Tuttavia, questo sembra essere più di un semplice comportamento individuale: molte aziende che operano in catene del valore lineari hanno adottato una combinazione di piattaforme per migliorare le proprie strategie, obiettivi e modelli di business. Questa ricerca mira a spiegare come le aziende con catena del valore lineare che operano in vari settori adottano una combinazione di piattaforme con tipologie uguali o diverse per servire i propri piani strategici a lungo termine; Inoltre, spiegare quanto sia impegnativo questo processo e quali sono i fattori chiave di successo nel processo di adozione. Gli obiettivi della ricerca sono stati raggiunti analizzando la letteratura sulle piattaforme e sul pensiero piattaforma, insieme all'analisi di oltre 500 casi raccolti con la collaborazione di altri colleghi che lavorano sullo stesso progetto, tutti i dati sono stati raccolti sotto forma di un set di dati che è possibile accedervi per ulteriori analisi. Da questo studio è stato possibile definire le ragioni e i risultati dell’adozione di un mix di tipologie di piattaforme in termini di efficienza, creazione di valore e miglioramento del modello di business. Infine, un quadro per il processo decisionale sulla combinazione di piattaforme.Platforms have become an essential part of our daily lives, we hugely depend on different types of platforms to perform a certain task, secure an accommodation, or move from one place to another. However, this appears to be more than just an individual behavior, many firms operating in linear value chains adopted a combination of platforms to enhance their strategies, goals, and business models. This research aims to explain how linear value chain firms operating in various industries adopt a combination of platforms either with the same or different typologies to serve its strategic long-term plans; Furthermore, explaining how challenging this process is, and what are the key success factors in the adoption process. The research objectives were accomplished by analyzing the literature on platforms and platform thinking, along with the analysis of over 500 hundred cases that were gathered with the collaboration of other colleagues working on the same project, all data was gathered in the form of a dataset that could be accessed for further analysis. From this study, it was possible to define the reasons and outcome of adopting a mix of platform typologies in terms of efficiency, value creation, and business model enhancement. Finally, a framework for platform combination decision making

The Impact of Anxiety and Depression on Academic Performance: A Cross-Sectional Study among Medical Students in Syria

Abstract Background The National Medical Unified Examination (NMUE) is a milestone in the life of medical students in Syria. The selection for residency programs depends mainly on the NMUE score, where competitive specialties require higher scores. Therefore, preparation for the NMUE might be a source of anxiety and depression. This study aims at evaluating the impact of anxiety and depression on the NMUE score. A secondary objective is to determine the effect of some factors (i.e., exercise, having breakfast, adequate sleep, and social media) on anxiety and depression. Methods A cross-sectional study was conducted using an online questionnaire and included medical students who were preparing for the October 2019 NMUE exam. The Generalized Anxiety Disorder scale (GAD-7) and the Patient Health Questionnaire (PHQ-9) were used to screen for anxiety and depression, respectively. NMUE scores were obtained from the official score report. Demographics and other potential confounding factors, such as Cumulative Grade Point Average, were obtained through the questionnaire. Results One hundred and thirty (n = 130) students participated in the study, 83 of them were women (63.8%). The prevalence of anxiety and depression were 59.2 and 58%, respectively, with no difference between men and women. Both anxiety and depression were negatively correlated with the NMUE score. However, this relationship did not persist after controlling for other important predictors through multiple regression. Only exercising was statically significant in reducing PHQ-9 scores. None of the studied factors were significant in reducing GAD-7 scores. Conclusion Although participants with higher anxiety/depression had lower NMUE scores, this association does not imply causation. The high prevalence of anxiety and depression (approximately two-thirds of the participants) is concerning and may pose a great threat to students' well-being and adversely affect the quality of care provided by them as future health care professionals.</jats:p

Enhanced fusidic acid transdermal delivery achieved by newly isolated and optimized Bacillus cereus Keratinase

The expanding interest in bioremediation of poorly degradable wastes has led to the discovery of many microbial enzymes capable of degrading recalcitrant substances such as keratinaceous wastes that are produced in vast quantities on daily basis. Such enzymes don’t only work as a bioremediation tool but also have multiple beneficial applications. Hence, environmental samples were collected from sewage water, soils, animal bodies and feces in order to isolate keratinase producing organisms. Keratinolytic isolates were isolated from sewage water; soils; animal bodies; animal feces, and identified both traditionally and molecularly through 16S-rRNA sequencing to be Bacillus cereus strain. Produced keratinase was purified by centrifugation, ammonium sulfate precipitation, and HPLC, then assayed using Azokeratine based analysis. keratinase quantification yielded a 420 ± 1.63 U/mL. Optimum production was obtained at 40 °C, pH 7, 3 days incubation, 0.5 % substrate, 0.4 g/l magnesium ion, 2% v/v inoculum, 0.5 g/l NaCl, 0.4 g/l K2HPO4, and 0.3 g/l KH2PO4. Production was increased by 1.9 fold after acclimatization to reach 809 ± 2.49 U/mL in only 2 days. Thermal and pH stability testing revealed the effectiveness of the isolated keratinase over a wide range of temperatures at neutral pH. Finally, isolated keratinase enhanced fusidic acid topical penetration to treat induced deep skin bacterial infection in mice. A 1.4 fold decrease in treatment period and a 2 log cycle reduction in the viable count of Staphylococcus aureus were noticed in keratinase/fusidic acid treated mice compared to mice treated with fusidic acid alone. This study shed some light on a simple keratinase production optimization technique and suggested a promising medical application of this enzyme as a drug delivery agent

A Generic AI-Based Technique for Assessing Student Performance in Conducting Online Virtual and Remote Controlled Laboratories

Due to the COVID-19 pandemic and the development of educational technology, e-learning has become essential in the educational process. However, the adoption of e-learning in sectors such as engineering, science, and technology faces a particular challenge as it needs a special Laboratory Learning Management System (LLMS) capable of supporting online lab activities through virtual and controlled remote labs. One of the most challenging tasks in designing such LLMS is how to assess a student&#x2019;s performance while an experiment is being conducted and how stuttering students can be automatically detected while experimenting and providing the appropriate assistance. For this, a generic technique based on Artificial Intelligence (AI) is proposed in this paper for assessing student performance while conducting online labs and implemented as a performance evaluation module in the LLMS. The performance evaluation module is designed to automatically detect the student performance during the experiment run time and triggers the LLMS virtual assistant service to provide struggling students with the appropriate help when they need it. Also, the proposed performance assessment technique is used during the lab exam sessions to support the automatic grading process conducted by the LLMS Auto-Grading Module. The proposed performance evaluation technique has been developed based on analyzing the student&#x2019;s mouse dynamics to work generally with any type of simulation or control software used by virtual or remote controlled laboratories; without the need for special interfacing. The study has been applied to a novel dataset built by the course instructors and students simulating a circuit on TinkerCad. Using mouse dynamics fetching, the system extracts features and evaluates them to determine if the student has built the experiment steps in the right way or not. A comparison study has been developed between different Machine Learning (ML) models and a number of performance metrics are calculated. The study confirmed that Artificial Neural Network (ANN) and Support Vector Machine (SVM) are the best models to be used for automatically evaluating student performance while conducting the online labs with a precision reaching up to 91&#x0025;