Risk of obstructive sleep apnea in pregnant females in different trimester

Background: Obstructive Sleep Apnea (OSA) is a common sleep-related breathing disorder, is characterized by recurrent collapse or blockage of the pharynx during sleep that causes intermittent cessation of airflow and a hallmark snoring gasping pattern. When OSA occurs in pregnancy, it is independently associated with increased risk of gestational hypertension, preeclampsia, gestational diabetes and possibly fetal growth restriction and other adverse neonatal outcomes. In particular, OSA affects sleep quality and duration of sleep in pregnant women. The aim was to study the risk of Obstructive Sleep Apnea in pregnant females in different trimester. Methods: The study consists of a non-experimental, quantitative and cross sectional research design. A total of 60 pregnant females were included in the study and conducted at maternity clinic.    Results: By analyzing data we found that females in 3rd trimester shows symptoms of compromised breathing and thus are at high risk of developing OSA followed by 2nd trimester. Conclusions: Our study shows that breathing limitation starts from 2nd trimester onwards, so, we conclude that starting breathing exercises early in antenatal period would be beneficial for the expecting mothers. The study concludes that there is high risk of obstructive sleep apnea in 3rd trimester of the pregnancy

Hemophagocytic syndrome, a rare variant of Still’s disease

Adult onset still’s disease is a rare systemic inflammatory disorder of unknown etiology that is responsible for a significant number of cases of fever of unknown origin (FUO) and musculoskeletal diseases. The diagnosis in adult onset still’s disease is mainly clinical and requires exclusion of other infections. Laboratory tests are nonspecific and treatment mainly comprises of corticosteroids, NSAIDS, immunosuppressive drugs, iv gamma globulin, anti-tumour necrosis factor, anti-interleukin. AOSD (adult onset stills disease) is a diagnostic challenge. Discovery of new serological tests and a specific diagnostic criterion may help the clinician in faster diagnosis and better management of the disease.

Preparation and evaluation of mucoadhasive microspheres of Propranolol HCl for nasal delivery

In the recent decades, the interest in intranasal route for drug delivery is increased as the nasal mucosa offers numerous benefits such as rapid systemic drug absorption and fast onset of action. Additionally, intranasal absorption avoids the hepatic presystemic metabolism and enhances drug bioavailability in comparison to that obtained after oral administration. Also, it offers patient ease being non invasive, offers favourable tolerability profile and it is also pharmaceutically economic as dont require sterilization. Propranolol HCl is the most commonly used ? blocker drug for the prophylaxis of migraine. The problem with the oral route is low bioavailability (26%) due to pre-systemic metabolism. So, the aim of the work is to formulate and evaluate mucoadhesive microsphere of Propranolol HCl to increase its bioavailability and reduce its dose. Mucoadhesive microspheres increase the residence time of the drug by gel formation mechanism and hence improve bioavailability as compared to powder and liquid formulations. The prepared formulation was evaluated for particle size, shape and morphology, mucoadhesive strength, micrometric properties, in vitro drug diffusion study, entrapment efficiency and stability studies

Enhancing Upper Limb Recovery and Reducing Stress and Anxiety Through Non-Immersive Virtual Reality in Subacute and Chronic Stroke Survivors: An Experimental Study

Introduction: Stroke is the third-leading cause of major long-term disability and the second-leading cause of mortality worldwide. Paralysis, paresis (muscle weakness), spasticity, difficulty walking, difficulty controlling motions, and limb discomfort are frequent limb impairments. Nearly 80% of stroke survivors are affected. Stroke survivors suffer with physical disabilities in addition to a reduced quality of life in terms of their health, a higher degree of worry, and a loss of independence. With a prevalence of 55% to 75%, hand motor deficits are the most prevalent post-stroke.1 The most common impairment is motor dysfunction, which affects 90% of stroke survivors with some kind of upper limb motor disability. Motor dysfunction is a strong indicator of poor functional recovery. The most typical post-stroke symptom is hemiparesis.1 Objectives: The study's objective was to use a virtual reality system to enhance upper limb strength and function in hemiparesis. The study's secondary goal was to lessen tension and anxiety in stroke Survivors. Methods: This research was experimental. A patient was chosen from UEM Hospital in Jaipur, Rajasthan, based on inclusion and exclusion criteria. Upper Extremity Functional Index (UEFI) and Depression Anxiety Stress Scale (DASS-21) were employed as outcome measures to evaluate the patients. Result: The outcome of the post-intervention data revealed that the Upper Extremity Functional Index (UEFI) had significant values of P.311. P .002 was used to determine the importance of the Depression Anxiety Stress Scale (DASS-21). That indicates that following the intervention, all outcome indicators showed a considerable improvement. Conclusion: The post-intervention values of the depression anxiety stress scale (DASS 21) and the upper extremity functional index (UEFI) both indicated a substantial improvement. In order to improve strength and upper limb functions following hemiparesis and to lessen tension and anxiety as a result of the handicap, a low-cost VR system might be employed

Solid Dispersions: A tool for improving the Solubility and Dissolution of Metronidazole

Metronidazole is a broad spectrum antibiotic. It is sparingly soluble in water but has oral bioavailability of 93-95%. So solid dispersions (SDs) containing metronidazole was prepared in different ratios (1:1, 1:2 and 1:5) and using different carriers like dextrose, citric acid, polyethylene glycol (PEG-4000) and polyvinylpyrrolidone (PVP). Fusion or melting method was used for SD containing dextrose and citric acid and Solvent evaporation method was used for SD containing PVP and PEG-4000. The solubility studies revealed that solubility of metronidazole was enhanced to manifolds. Best result was exhibited when drug carrier ratio is in the order of 1:5>1:2>1:1. Among the different carriers, the solubility and dissolution was increased to maximum in case of PVP and PEG and almost 100 % drug released within 1 hour. The development of solid dispersions was further confirmed by DSC and XRD

Solid Dispersions: A tool for improving the Solubility and Dissolution of Metronidazole

Metronidazole is a broad spectrum antibiotic. It is sparingly soluble in water but has oral bioavailability of 93-95%. So solid dispersions (SDs) containing metronidazole was prepared in different ratios (1:1, 1:2 and 1:5) and using different carriers like dextrose, citric acid, polyethylene glycol (PEG-4000) and polyvinylpyrrolidone (PVP). Fusion or melting method was used for SD containing dextrose and citric acid and Solvent evaporation method was used for SD containing PVP and PEG-4000. The solubility studies revealed that solubility of metronidazole was enhanced to manifolds. Best result was exhibited when drug carrier ratio is in the order of 1:5>1:2>1:1. Among the different carriers, the solubility and dissolution was increased to maximum in case of PVP and PEG and almost 100 % drug released within 1 hour. The development of solid dispersions was further confirmed by DSC and XRD

Survey and evaluation of hypertension machine learning research

Background: Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision‐making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studies employing ML in hypertension research is growing rapidly. In this study, we aimed to survey hypertension research using ML, evaluate the reporting quality, and identify barriers to ML's potential to transform hypertension care. Methods and Results: The Harmonious Understanding of Machine Learning Analytics Network survey questionnaire was applied to 63 hypertension‐related ML research articles published between January 2019 and September 2021. The most common research topics were blood pressure prediction (38%), hypertension (22%), cardiovascular outcomes (6%), blood pressure variability (5%), treatment response (5%), and real‐time blood pressure estimation (5%). The reporting quality of the articles was variable. Only 46% of articles described the study population or derivation cohort. Most articles (81%) reported at least 1 performance measure, but only 40% presented any measures of calibration. Compliance with ethics, patient privacy, and data security regulations were mentioned in 30 (48%) of the articles. Only 14% used geographically or temporally distinct validation data sets. Algorithmic bias was not addressed in any of the articles, with only 6 of them acknowledging risk of bias. Conclusions: Recent ML research on hypertension is limited to exploratory research and has significant shortcomings in reporting quality, model validation, and algorithmic bias. Our analysis identifies areas for improvement that will help pave the way for the realization of the potential of ML in hypertension and facilitate its adoption

Implementation of a Virtual Interprofessional ICU Learning Collaborative: Successes, Challenges, and Initial Reactions From the Structured Team- Based Optimal Patient-Centered Care for Virus COVID-19 Collaborators

IMPORTANCE: Initial Society of Critical Care Medicine Discovery Viral Infection and Respiratory illness Universal Study (VIRUS) Registry analysis suggested that improvements in critical care processes offered the greatest modifiable opportunity to improve critically ill COVID-19 patient outcomes. OBJECTIVES: The Structured Team-based Optimal Patient-Centered Care for Virus COVID-19 ICU Collaborative was created to identify and speed implementation of best evidence based COVID-19 practices. DESIGN, SETTING, AND PARTICIPANTS: This 6-month project included volunteer interprofessional teams from VIRUS Registry sites, who received online training on the Checklist for Early Recognition and Treatment of Acute Illness and iNjury approach, a structured and systematic method for delivering evidence based critical care. Collaborators participated in weekly 1-hour videoconference sessions on high impact topics, monthly quality improvement (QI) coaching sessions, and received extensive additional resources for asynchronous learning. MAIN OUTCOMES AND MEASURES: Outcomes included learner engagement, satisfaction, and number of QI projects initiated by participating teams. RESULTS: Eleven of 13 initial sites participated in the Collaborative from March 2, 2021, to September 29, 2021. A total of 67 learners participated in the Collaborative, including 23 nurses, 22 physicians, 10 pharmacists, nine respiratory therapists, and three nonclinicians. Site attendance among the 11 sites in the 25 videoconference sessions ranged between 82% and 100%, with three sites providing at least one team member for 100% of sessions. The majority reported that topics matched their scope of practice (69%) and would highly recommend the program to colleagues (77%). A total of nine QI projects were initiated across three clinical domains and focused on improving adherence to established critical care practice bundles, reducing nosocomial complications, and strengthening patient- and family-centered care in the ICU. Major factors impacting successful Collaborative engagement included an engaged interprofessional team; an established culture of engagement; opportunities to benchmark performance and accelerate institutional innovation, networking, and acclaim; and ready access to data that could be leveraged for QI purposes. CONCLUSIONS AND RELEVANCE: Use of a virtual platform to establish a learning collaborative to accelerate the identification, dissemination, and implementation of critical care best practices for COVID-19 is feasible. Our experience offers important lessons for future collaborative efforts focused on improving ICU processes of care

Metabolic Syndrome and Acute Respiratory Distress Syndrome in Hospitalized Patients With COVID-19

Importance: Obesity, diabetes, and hypertension are common comorbidities in patients with severe COVID-19, yet little is known about the risk of acute respiratory distress syndrome (ARDS) or death in patients with COVID-19 and metabolic syndrome. Objective: To determine whether metabolic syndrome is associated with an increased risk of ARDS and death from COVID-19. Design, setting, and participants: This multicenter cohort study used data from the Society of Critical Care Medicine Discovery Viral Respiratory Illness Universal Study collected from 181 hospitals across 26 countries from February 15, 2020, to February 18, 2021. Outcomes were compared between patients with metabolic syndrome (defined as ≥3 of the following criteria: obesity, prediabetes or diabetes, hypertension, and dyslipidemia) and a control population without metabolic syndrome. Participants included adult patients hospitalized for COVID-19 during the study period who had a completed discharge status. Data were analyzed from February 22 to October 5, 2021. Exposures: Exposures were SARS-CoV-2 infection, metabolic syndrome, obesity, prediabetes or diabetes, hypertension, and/or dyslipidemia. Main outcomes and measures: The primary outcome was in-hospital mortality. Secondary outcomes included ARDS, intensive care unit (ICU) admission, need for invasive mechanical ventilation, and length of stay (LOS). Results: Among 46 441 patients hospitalized with COVID-19, 29 040 patients (mean [SD] age, 61.2 [17.8] years; 13 059 [45.0%] women and 15713 [54.1%] men; 6797 Black patients [23.4%], 5325 Hispanic patients [18.3%], and 16 507 White patients [57.8%]) met inclusion criteria. A total of 5069 patients (17.5%) with metabolic syndrome were compared with 23 971 control patients (82.5%) without metabolic syndrome. In adjusted analyses, metabolic syndrome was associated with increased risk of ICU admission (adjusted odds ratio [aOR], 1.32 [95% CI, 1.14-1.53]), invasive mechanical ventilation (aOR, 1.45 [95% CI, 1.28-1.65]), ARDS (aOR, 1.36 [95% CI, 1.12-1.66]), and mortality (aOR, 1.19 [95% CI, 1.08-1.31]) and prolonged hospital LOS (median [IQR], 8.0 [4.2-15.8] days vs 6.8 [3.4-13.0] days; P \u3c .001) and ICU LOS (median [IQR], 7.0 [2.8-15.0] days vs 6.4 [2.7-13.0] days; P \u3c .001). Each additional metabolic syndrome criterion was associated with increased risk of ARDS in an additive fashion (1 criterion: 1147 patients with ARDS [10.4%]; P = .83; 2 criteria: 1191 patients with ARDS [15.3%]; P \u3c .001; 3 criteria: 817 patients with ARDS [19.3%]; P \u3c .001; 4 criteria: 203 patients with ARDS [24.3%]; P \u3c .001). Conclusions and relevance: These findings suggest that metabolic syndrome was associated with increased risks of ARDS and death in patients hospitalized with COVID-19. The association with ARDS was cumulative for each metabolic syndrome criteria present