Pressure Ulcer Prevention in the Post- Anesthesia Care Unit

Pressure Ulcer Prevention in the Post- Anesthesia Care Unit Abstract Keywords- PACU, post-anesthesia care unit, pressure ulcers, hospital acquired, skin breakdown Background: Post-operative patients are often in the PACU for longer periods because of short staffing and awaiting room assignments. Due to the patients laying in one position for longer periods of time without ambulating or positioning, this increases their risk for skin breakdown and hospital-acquired pressure ulcers. The purpose of this project is to implement a pressure ulcer care package to reduce the risk of hospital-acquired pressure ulcer development for post-operative patients. This will decrease the patient’s recovery time, reduce hospital length of stay, and decrease the risk of developing more serious patient complications. Brief Literature Review: Risk factors, such as obesity and diabetes increase the risk for a surgical patient to develop a pressure ulcer (Nilsson, 2013). On top of that, patients are often laying in one position for longer periods of time in the PACU. This leads to further health complications and longer recovery times. On the other hand, treating hospital-acquired pressure is costly and ranges from 3.3 to 11 billion annually (Padula & Delarmente, 2019). Also, with the PACU being known as a transient unit, emphasis and education on more thorough skin assessments are not being done. Method: A pressure ulcer care package will be presented to the nurses at the PACU. The pressure ulcer care package will include repositioning protocol every 2 hours, skin assessments with use of Braden Scale every 2 hours, and use of pressure ulcer cushions and dressings at bony prominences. After presenting the package to all the nurses, the package will be applied to all PACU patients. Evaluation: In order to evaluate the effectiveness of the pressure ulcer care package in the PACU, the number of times the nurses implemented and documented the pressure ulcer care package will be assessed. Additionally, early identification of skin breakdown will be assessed pre and post implementation through chart reviews of Epic documentation

Four factors driving the price Bitcoin

In this article, we discuss four key factor driving the price of Bitcoin. These include media hype and uptake by peers, political uncertainty and risk (such as the election of Donald Trump or the vote for Brexit), moves by governments and regulators, and the governance of Bitcoin itself

Forecasting emergency department waiting time using a state space representation

The provision of waiting time information in emergency departments (ED) has become an increasingly popular practice due to its positive impact on patient experience and ED demand management. However, little scientific attention has been given to the quality and quantity of waiting time information presented to patients. To improve both aspects, we propose a set of state space models with flexible error structures to forecast ED waiting time for low acuity patients. Our approach utilizes a Bayesian framework to generate uncertainties associated with the forecasts. We find that the state-space models with flexible error structures significantly improve forecast accuracy of ED waiting time compared to the benchmark, which is the rolling average model. Specifically, incorporating time-varying and correlated error terms reduces the root mean squared errors of the benchmark by 10%. Furthermore, treating zero-recorded waiting times as unobserved values improves forecast performance. Our proposed model has the ability to provide patient-centric waiting time information. By offering more accurate and informative waiting time information, our model can help patients make better informed decisions and ultimately enhance their ED experience

Ensemble Machine Learning Model Trained on a New Synthesized Dataset Generalizes Well for Stress Prediction Using Wearable Devices

Introduction. We investigate the generalization ability of models built on datasets containing a small number of subjects, recorded in single study protocols. Next, we propose and evaluate methods combining these datasets into a single, large dataset. Finally, we propose and evaluate the use of ensemble techniques by combining gradient boosting with an artificial neural network to measure predictive power on new, unseen data. Methods. Sensor biomarker data from six public datasets were utilized in this study. To test model generalization, we developed a gradient boosting model trained on one dataset (SWELL), and tested its predictive power on two datasets previously used in other studies (WESAD, NEURO). Next, we merged four small datasets, i.e. (SWELL, NEURO, WESAD, UBFC-Phys), to provide a combined total of 99 subjects,. In addition, we utilized random sampling combined with another dataset (EXAM) to build a larger training dataset consisting of 200 synthesized subjects,. Finally, we developed an ensemble model that combines our gradient boosting model with an artificial neural network, and tested it on two additional, unseen publicly available stress datasets (WESAD and Toadstool). Results. Our method delivers a robust stress measurement system capable of achieving 85% predictive accuracy on new, unseen validation data, achieving a 25% performance improvement over single models trained on small datasets. Conclusion. Models trained on small, single study protocol datasets do not generalize well for use on new, unseen data and lack statistical power. Ma-chine learning models trained on a dataset containing a larger number of varied study subjects capture physiological variance better, resulting in more robust stress detection.Comment: 37 pages, 11 figure

Machine Learning for Stress Monitoring from Wearable Devices: A Systematic Literature Review

Introduction. The stress response has both subjective, psychological and objectively measurable, biological components. Both of them can be expressed differently from person to person, complicating the development of a generic stress measurement model. This is further compounded by the lack of large, labeled datasets that can be utilized to build machine learning models for accurately detecting periods and levels of stress. The aim of this review is to provide an overview of the current state of stress detection and monitoring using wearable devices, and where applicable, machine learning techniques utilized. Methods. This study reviewed published works contributing and/or using datasets designed for detecting stress and their associated machine learning methods, with a systematic review and meta-analysis of those that utilized wearable sensor data as stress biomarkers. The electronic databases of Google Scholar, Crossref, DOAJ and PubMed were searched for relevant articles and a total of 24 articles were identified and included in the final analysis. The reviewed works were synthesized into three categories of publicly available stress datasets, machine learning, and future research directions. Results. A wide variety of study-specific test and measurement protocols were noted in the literature. A number of public datasets were identified that are labeled for stress detection. In addition, we discuss that previous works show shortcomings in areas such as their labeling protocols, lack of statistical power, validity of stress biomarkers, and generalization ability. Conclusion. Generalization of existing machine learning models still require further study, and research in this area will continue to provide improvements as newer and more substantial datasets become available for study.Comment: 50 pages, 8 figure

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Rats and the city: Implications of urbanization on zoonotic disease risk in Southeast Asia

Urbanization is rapidly transforming much of Southeast Asia, altering the structure and function of the landscape, as well as the frequency and intensity of the interactions between people, animals, and the environment. In this study, we explored the impact of urbanization on zoonotic disease risk by simultaneously characterizing changes in the ecology of animal reservoirs (rodents), ectoparasite vectors (ticks), and pathogens across a gradient of urbanization in Kuching, a city in Malaysian Borneo. We sampled 863 rodents across rural, developing, and urban locations and found that rodent species diversity decreased with increasing urbanization—from 10 species in the rural location to 4 in the rural location. Notably, two species appeared to thrive in urban areas, as follows: the invasive urban exploiter Rattus rattus (n = 375) and the native urban adapter Sundamys muelleri (n = 331). R. rattus was strongly associated with built infrastructure across the gradient and carried a high diversity of pathogens, including multihost zoonoses capable of environmental transmission (e.g., Leptospira spp.). In contrast, S. muelleri was restricted to green patches where it was found at high densities and was strongly associated with the presence of ticks, including the medically important genera Amblyomma, Haemaphysalis, and Ixodes. Our analyses reveal that zoonotic disease risk is elevated and heterogeneously distributed in urban environments and highlight the potential for targeted risk reduction through pest management and public health messaging

Delayed blood transfusion is associated with mortality following radical cystectomy

Objectives: To examine the temporal association between blood transfusion and 90-day mortality in patients with bladder cancer treated with radical cystectomy. / Methods: This represents a retrospective cohort study of patients treated with radical cystectomy within the Premier Hospital network between 2003 and 2015. Patients outcomes were stratified those who received early blood transfusion (day of surgery) vs delayed blood transfusion (postoperative day ≥1) during the index admission. Primary end point was 90-day mortality following surgery. / Results: The median age of 12,056 patients identified was 70 years. A total of 7,201 (59.7%) patients received blood transfusion. Within 90 days following surgery, 57 (2.2%), 162 (5.9%) and 123 (6.7%) patients in the early, delayed and both early and delayed transfused patients died respectively. Following multivariate logistic regression to account for patient (age and Charlson Comorbidity Index [CCI]) and hospital (surgeon volume, surgical approach and academic status) factors, delayed blood transfusion was independently associated with 90-day mortality (Odds ratio [OR], 2.64; 95% Confidence Interval [CI], 1.98–3.53; p < 0.001). A sensitivity analysis defining early blood transfusion as <2 days postoperatively, increased 90-day mortality persisted in patients receiving delayed transfusion (OR, 2.20; 95% CI, 1.63-3.00; p < 0.001). Older patients (≥77 years) with the highest CCI (≥2) had a 7% absolute increase in the predicted probability of 90-day mortality if they were transfused late compared to patients transfused early. / Conclusion: Patient undergoing cystectomy may benefit from expedited transfusion to prevent subsequent clinical deterioration which may lead to patient mortality. Future work is needed to elucidate the optimal timing of blood transfusion

Catalytic reduction of dinitrogen to silylamines by earth-abundant lanthanide and group 4 complexes

Dinitrogen is a challenging molecule to reduce to useful products under ambient conditions. The range of d-block metal complexes that can catalyze dinitrogen reduction to ammonia or tris(silyl)amines under ambient conditions has increased recently but lacks electropositive metal complexes, such as those of the f-block which lack filled d-orbitals that would support classical binding modes of N2. Here, metallacyclic phenolate structures with lanthanide or group 4 cations can bind dinitrogen and catalyze its conversion to bis(silyl)amines under ambient conditions. The formation of this unusual product is controlled by metallacycle sterics. The group 4 complexes featuring small cavities are most selective for bis(silyl)amine, while the lanthanide complexes and the solvated uranium(IV) congener, with larger cavities, can also make the conventional tris(silyl)amine product. These results offer new catalytic applications for plentiful titanium and the more earth-abundant members of the lanthanides that are also less toxic than many base metals used in catalysis

Defining factors associated with high-quality surgery following radical cystectomy : analysis of the British Association of Urological Surgeons cystectomy audit

Background Radical cystectomy (RC) is associated with high morbidity. Objective To evaluate healthcare and surgical factors associated with high-quality RC surgery. Design, setting, and participants Patients within the prospective British Association of Urological Surgeons (BAUS) registry between 2014 and 2017 were included in this study. Outcome measurements and statistical analysis High-quality surgery was defined using pathological (absence of positive surgical margins and a minimum of a level I lymph node dissection template with a minimum yield of ten or more lymph nodes), recovery (length of stay ≤10 d), and technical (intraoperative blood loss <500 ml for open and <300 ml for minimally invasive RC) variables. A multilevel hierarchical mixed-effect logistic regression model was utilised to determine the factors associated with the receipt of high-quality surgery and index admission mortality. Results and limitations A total of 4654 patients with a median age of 70.0 yr underwent RC by 152 surgeons at 78 UK hospitals. The median surgeon and hospital operating volumes were 23.0 and 47.0 cases, respectively. A total of 914 patients (19.6%) received high-quality surgery. The minimum annual surgeon volume and hospital volume of ≥20 RCs/surgeon/yr and ≥68 RCs/hospital/yr, respectively, were the thresholds determined to achieve better rates of high-quality RC. The mixed-effect logistic regression model found that recent surgery (odds ratio [OR]: 1.22, 95% confidence interval [CI]: 1.11–1.34, p < 0.001), laparoscopic/robotic RC (OR: 1.85, 95% CI: 1.45–2.37, p < 0.001), and higher annual surgeon operating volume (23.1–33.0 cases [OR: 1.54, 95% CI: 1.16–2.05, p = 0.003]; ≥33.1 cases [OR: 1.64, 95% CI: 1.18–2.29, p = 0.003]) were independently associated with high-quality surgery. High-quality surgery was an independent predictor of lower index admission mortality (OR: 0.38, 95% CI: 0.16–0.87, p = 0.021). Conclusions We report that annual surgeon operating volume and use of minimally invasive RC were predictors of high-quality surgery. Patients receiving high-quality surgery were independently associated with lower index admission mortality. Our results support the role of centralisation of complex oncology and implementation of a quality assurance programme to improve the delivery of care. Patient summary In this registry study of patients treated with surgical excision of the urinary bladder for bladder cancer, we report that patients treated by a surgeon with a higher annual operative volume and a minimally invasive approach were associated with the receipt of high-quality surgery. Patients treated with high-quality surgery were more likely to be discharged alive following surgery