An observational feasibility study of a new anaesthesia drug storage tray

Drug errors in the anaesthetic domain remains a serious cause of iatrogenic harm. To help reduce this issue, we aimed to explore the potential impact of a simple colour-coded tray to drug preparation and storage on safe drug administration during anaesthesia. Over a six-month period, a total of 30 cases were observed. The observations were conducted at three NHS Trusts by three different trained researchers. Ten observations involved the standard drug trays in ‘normal’ practice and 20 observations, before and after, were conducted where the new “Rainbow trays” were used. A total of 20 semi-structured interviews were conducted immediately upon completing the second observation with the involved anaesthetists. All discussions and detailed notes taken were transcribed and qualitatively analysed using line-byline coding. These codes were then synthesized into themes. Current practice using unicompartmental trays is quick, cheap, and portable but linked to potential or actual harmful errors such as syringe swaps. The Rainbow trays, seem to aid drug identification, allow for drug separation and act as a prompt to guard against drug errors. Limitations to the feasibility of use were around design and placement. The Rainbow trays were perceived as likely to reduce drug errors and improve patient safety. Additionally, there was an overall preference for this novel system at all three sites, as they were perceived to be easy to use and effective

Traditions of research into interruptions in healthcare: A conceptual review

Background Researchers from diverse theoretical backgrounds have studied workplace interruptions in healthcare, leading to a complex and conflicting body of literature. Understanding pre-existing viewpoints may advance the field more effectively than attempts to remove bias from investigations. Objective To identify research traditions that have motivated and guided interruptions research, and to note research questions posed, gaps in approach, and possible avenues for future research. Methods A critical review was conducted of research on interruptions in healthcare. Two researchers identified core research communities based on the community’s motivations, philosophical outlook, and methods. Among the characteristics used to categorise papers into research communities were the predominant motivation for studying interruptions, the research questions posed, and key contributions to the body of knowledge on interruptions in healthcare. In cases where a paper approached an equal number of characteristics from two traditions, it was placed in a blended research community. Results A total of 141 papers were identified and categorised; all papers identified were published from 1994 onwards. Four principal research communities emerged: epidemiology, quality improvement, cognitive systems engineering (CSE), and applied cognitive psychology. Blends and areas of mutual influence between the research communities were identified that combine the benefits of individual traditions, but there was a notable lack of blends incorporating quality improvement initiatives. The question most commonly posed by researchers across multiple communities was: what is the impact of interruptions? Impact was measured as a function of task time or risk in the epidemiology tradition, situation awareness in the CSE tradition, or resumption lag (time to resume an interrupted task) in the applied cognitive psychology tradition. No single question about interruptions in healthcare was shared by all four of the core communities. Conclusions Much research on workplace interruptions in healthcare can be described in terms of fundamental values of four distinct research traditions and the communities that bring the values and methods: of those research traditions to their investigations. Blends between communities indicate that mutual influence has occurred as interruptions research has progressed. It is clear from this review that there is no single or privileged perspective to study interruptions. Instead, these findings suggest that researchers investigating interruptions in healthcare would benefit from being more aware of different perspectives from their own, especially when they consider workplace interventions to reduce interruptions

Phoenix: Federated Learning for Generative Diffusion Model

Thesis (Master's)--University of Washington, 2023Generative AI has made impressive strides in enabling users to create diverse and realistic visual content such as images, videos, and audio. However, training generative models on large centralized datasets can pose challenges in terms of data privacy, security, and accessibility. Federated learning is an approach that uses decentralized techniques to collaboratively train a shared deep learning model while retaining the training data on individual edge devices to preserve data privacy. This paper proposes a novel method for training a Denoising Diffusion Probabilistic Model (DDPM) across multiple data sources, using federated learning techniques. Diffusion models, a newly emerging generative model, show promising results in achieving superior quality images than Generative Adversarial Networks (GANs). Our proposed method Phoenix is an unconditional diffusion model that leverages strategies to improve the data diversity of generated samples even when trained on data with statistical heterogeneity (Non-IID data). We demonstrate how our approach outperforms the default diffusion model in a federated learning setting. These results are indicative that high-quality samples can be generated by maintaining data diversity, preserving privacy, and reducing communication between data sources, offering exciting new possibilities in the field of generative AI

Effect of monoalgal diet on the growth, survival and egg production in Nannocalanus minor (Copepoda: Calanoida)

1579-1584The effect of monoalgal diet on the growth, survival, egg production and egg hatching succession in calanoid copepod Nannocalanus minor was studied under laboratory condition. There are seven different microalgae such as Chlorella marina, Dunaliella salina, Isochrysis galbana, Nannochloropsis sp., Coscinodiscus centralis, Chaetoceros affinis and Skeletonema costatum were tested for their efficacy on survival of N. minor at two different algal cell concentrations viz. 10,000 and 20,000 cells/ml. Among the six diets tested, Chlorella marina shows the extensive survival in both lowest and highest algal concentrations where the 100% survival extends for 7th and 9th days of experiment while the least survival was obtained in diatom Skeletonema costatum. Likewise, copepod N. minor grew faster at C. marina than other algal feed tested presently. The egg production (32±1.52 eggs/female/day) and hatching succession (93.75%) both are proportionally increased with increasing algal concentration (20,000 cells/ml) while at low algal concentration (1000 cells/ml) it was recorded as 3±1 eggs/female/day and 44.33% respectively. The study provides a realistic basis for formulating suitable algal food and algal concentration required for copepod N. minor to achieve utmost growth, survival and fecundity in captive condition. This information can help in developing the culture technology on copepod Nannocalanus minor for it use in larval fish culture

Renal sympathetic denervation using an externally irrigated radiofrequency ablation catheter for treatment of resistant hypertension – Acute safety and short term efficacy

Objectives: This study was conducted to assess the acute safety and short term efficacy of renal sympathetic denervation (RSDN) using solid tip radiofrequency ablation (RFA) catheter and saline irrigation through the renal guiding catheter to achieve effective denervation. Background: RSDN using a specialized solid-tip RFA catheter has recently been demonstrated to safely reduce systemic blood pressure in patients with refractory hypertension, the limitation being inadequate power delivery in renal arteries. So, we used solid-tip RFA catheter along with saline irrigation for RSDN. Methods: Nine patients with resistant hypertension underwent CT and conventional renal angiography, followed by bilateral or unilateral RSDN using 5F RFA catheter with saline irrigation through renal guiding catheter. Repeat renal angiography was performed at the end of the procedure. In all patients, pre- and post-procedure serum creatinine was measured. Results: Over 1-month period: 1) the systolic/diastolic blood pressure decreased by −57 ± 20/−25 ± 7.5 mm Hg; 2) all patients experienced a decrease in systolic blood pressure of at least −36 mm Hg (range 36–98 mm Hg); 3) there was no evidence of renal artery injury immediate post-procedure. There was no significant change in serum creatinine level. Conclusions: This data shows the acute procedural safety and short term efficacy of RSDN using modified externally irrigated solid tip RFA catheter

Automated Epileptic Seizure Detection in Pediatric Subjects of CHB-MIT EEG Database—A Survey

Epilepsy is a neurological disorder of the brain that causes frequent occurrence of seizures. Electroencephalography (EEG) is a tool that assists neurologists in detecting epileptic seizures caused by an unexpected flow of electrical activities in the brain. Automated detection of an epileptic seizure is a crucial task in diagnosing epilepsy which overcomes the drawback of a visual diagnosis. The dataset analyzed in this article, collected from Children’s Hospital Boston (CHB) and the Massachusetts Institute of Technology (MIT), contains long-term EEG records from 24 pediatric patients. This review paper focuses on various patient-dependent and patient-independent personalized medicine approaches involved in the computer-aided diagnosis of epileptic seizures in pediatric subjects by analyzing EEG signals, thus summarizing the existing body of knowledge and opening up an enormous research area for biomedical engineers. This review paper focuses on the features of four domains, such as time, frequency, time-frequency, and nonlinear features, extracted from the EEG records, which were fed into several classifiers to classify between seizure and non-seizure EEG signals. Performance metrics such as classification accuracy, sensitivity, and specificity were examined, and challenges in automatic seizure detection using the CHB-MIT database were addressed