Early Hospital Mortality Prediction Using Routine Vital Signs in ICU Patients

In a clinical setting, there are countless scenarios in which a statistical prognosis for patients can be extremely beneficial to medical professionals so that they may better allocate resources to provide the best patient care. The purpose of this paper is to identify when in a patient’s stay a meaningful prediction of hospital mortality can be made to provide that prognosis. In order to accomplish this, eight clinical variables were extracted from the MIMIC-III database for ICU patients and were supplied to a XGBoost model, an advanced Decision Tree Classifier that employs gradient boosting. Because of the imbalanced data, the positive values were weighted more heavily along with other optimized parameter values found from the use of GridSearchCV. A static model demonstrated an average accuracy of 80.50% with an AUC-ROC of 0.800 and an AUC-PR of 0.429. However, a time-series analysis using extracted statistics from twelve-hours of compounded, time-varying data generated a model with an 83.28% accuracy with an AUC-ROC of 0.846 and an AUC-PR of 0.562. Additionally, the model demonstrated the importance of GCS and airway management in the prediction of mortality indicating the need to focus more on these vitals in emergency situations. The time-series model was shown to be most effective in predicting mortality, exemplifying the importance of providing time-series data that can detail the progress/decline of the patient. This implementation especially could be very impactful in clinical settings to provide healthcare professionals with the means to make quick and effective decisions

Developing curriculum on “minority rights in a democratic society”

This study primarily focuses on two broad objectives: first, to develop an understanding on the issues and challenges faced by minority groups in a democratic society and the different approaches to address these; and, second, to develop a curriculum module for middle-school students with the aim of creating sensitivity among students towards the concerns of minority groups. The literature on various democratic theories and minority rights were reviewed for this study. The teaching module comprised concepts such as democracy, minority rights, plural notions of good life, multiculturalism, deliberation, positive discrimination and self-government. A baseline survey and an endline survey were conducted at the beginning and end of this module to check its effectiveness. This was towards analysing any shift in the approach of students’ responses towards the given situations and to see if the module had been able to make them consider the concerns of minority groups. A combination of quantitative and qualitative analysis of their responses suggests that some of the students had a positive change in their approaches and had begun to think from the positions of minority groups

TorchFL: A Performant Library for Bootstrapping Federated Learning Experiments

With the increased legislation around data privacy, federated learning (FL) has emerged as a promising technique that allows the clients (end-user) to collaboratively train deep learning (DL) models without transferring and storing the data in a centralized, third-party server. Despite the theoretical success, FL is yet to be adopted in real-world systems due to the hardware, computing, and various infrastructure constraints presented by the edge and mobile devices of the clients. As a result, simulated datasets, models, and experiments are heavily used by the FL research community to validate their theories and findings. We introduce TorchFL, a performant library for (i) bootstrapping the FL experiments, (ii) executing them using various hardware accelerators, (iii) profiling the performance, and (iv) logging the overall and agent-specific results on the go. Being built on a bottom-up design using PyTorch and Lightning, TorchFL provides ready-to-use abstractions for models, datasets, and FL algorithms, while allowing the developers to customize them as and when required.Comment: 20 pages, 15 figures, 4 table

FedClean: A Defense Mechanism Against Parameter Poisoning Attacks in Federated Learning

Peer reviewe

Frequency and variation of neural tube defects at Liaquat University Hospital Jamshoro, Sindh, Pakistan

Background: Neural tube defects (NTDs) are a group of congenital malformations of the neural tube. The incidence of NTDs in Pakistan is 13.90 per 1000 deliveries. Such type of study in our setup is conducted for the first time which shows that different varieties of (NTDs) are seen commonly in our setup also. Methods: This descriptive study was conducted in department of Neurosurgery of Liaquat University Hospital Jamshoro, Sindh Pakistan with collaboration of department of Anatomy of Liaquat University of Medical and Health Sciences Jamshoro to determine the frequency and variations of neural tube defects seen in this institution. 45 patients with (NTDs) were included in the study. Out of 45 patients 18 were males and 27 were females. All were admitted through the outpatient department. The type of anomaly was recorded with other bio data.Results: In this study Hydrocephalous accounts for 25 cases (55.5%), hydrocephalus with meningocele in 01 case (2.2%) and hydrocephalus with encephalocele in 02 cases (4.4%) in addition is seen. Myelomeningocele seen in 04 cases (8.8%), Meningocele in 06 cases (13.3%), congenital dermal sinus and dandy walker syndrome 01 (2.2%) cases of each, also seen in this study 01 cases of Lipomyelocele with mengiocele and 01 case of Encephalocele with microcephaly which accounts for 2.2% of all neural tube defects.Conclusions: The high occurrence of NTDs observed in this study calls for a special attention. A nationwide surveillance can recognize the disease burden in pre & post-natal period and related risk factors to plan future strategies for prevention, early diagnosis and timely management.

Differentiating Sleep Problems Most Related to Depression and Anxiety in College Students

Sleep problems, anxiety and depression are common amongst college students. Researchers examined the specific sleep problems correlated with anxiety and depression. These sleep problems included sleep duration, sleep disturbances, sleep latency, daytime dysfunction, habitual sleep efficiency, overall sleep quality, and use of sleep medication. Researchers predicted that daytime dysfunction was the most important sleep problem related to greater anxiety symptoms, followed by overall quality of sleep, and sleep duration. Meanwhile, it was also predicted that daytime dysfunction would be the most important sleep problem and sleep latency the second most important sleep problem related to greater depressive symptoms. The study consisted of 561 undergraduate students (55% White, 69.9% female). Two multiple regression analyses were conducted. The first examined the most pertinent sleep problems related to greater anxiety symptoms in college students. The seven sleep problems described above were simultaneously entered into the model. The overall model showed significantly greater anxiety symptoms, F(7, 513) = 19.19, p \u3c .05. Together, these sleep problems accounted for 20.7% of the variance in greater anxiety symptoms. Daytime dysfunction due to sleepiness was the most strongly related to greater anxiety symptoms t(513) = 6.25, p \u3c .05, followed by overall sleep quality, t(513) = 2.27, p \u3c .05, followed by habitual sleep efficiency, t(513) = 2.26, p \u3c .05. The second multiple regression analysis was conducted to examine the relationship between sleep problems and depression symptoms. The same sleep problems were simultaneously entered into the model. The overall model showed the sleep problems significantly predicted depressive symptoms, F(7, 512) = 34.89, p \u3c .001. Together, these sleep problems accounted for 32.3% of the variance in depression symptoms. In order of importance, sleep duration, t(512) = 2.84, p \u3c .05, sleep disturbances, t(512) = 3.82, p \u3c .001, daytime dysfunction due to sleepiness, t(512) = 8.90, p \u3c .001, and overall sleep quality, t(512) = 2.14, p \u3c .05, were all significantly related to depression symptoms. These findings suggest that for individuals with anxiety or depressive symptoms targeting treatments that focus on daytime dysfunction and overall sleep quality may lead to a reduction in these symptoms. Additionally, specific to anxiety, we should focus on ameliorating habitual sleep efficiency by improving the amount of sleep individuals consistently receive. Conversely, in relation to depressive symptoms, future work should focus on increasing the amount of time people sleep and decreasing how much people awake while they are sleeping.https://scholarscompass.vcu.edu/uresposters/1183/thumbnail.jp

Health care professionals’ compliance to tracheal suctioning policy at a tertiary care hospital

Objective: To assess the compliance of tracheal suctioning practices against the standard guidelines of a tertiary care hospital, with regard to the participants’ professional characteristics.Methods: Using cross sectional study design, forty health care professionals (HCPs) were assessed twice, using a quantitative structured observational design, for tracheal suctioning practices, in one of the surgical care units of the tertiary care hospital. Tracheal suctioning policy which was used as a tool, its inter-rater reliability was tested and each step showed the Kappa value of 0.65 to 1.000. Data was analyzed using epidata info version 3.5.1 and SPSS version 19.Results: From a total of 80 observations, 30% showed compliance, 50% partial compliance whereas, 20% indicated non-compliance.Conclusion: The study results highlight the need for improving the overall compliance with the tracheal suctioning guidelines of evidence based practices to minimize the adverse effects and enhance patient safety related to tracheal suctioning practices. The current study also provides an opportunity to motivate the HCPs compliant in the practices of tracheal suctioning by appreciate their competence

FedClean: A Defense Mechanism Against Parameter Poisoning Attacks in Federated Learning

Peer reviewe

Practices of tracheal suctioning technique among health care professionals: Literature review

The current study aims to assess tracheal suctioning practices among health care practitioners; nurses, critical care technicians and physiotherapist. Employing literature review as the methodology, multiple databases were searched focusing on three phases of tracheal suctioning (a) the pre suctioning phase, (b) the suctioning phase, (c) the post suctioning phase and complications related to tracheal suctioning. It was concluded that to provide quality care it is important that the evidence based practice guidelines should be followed