Chitosan-Coated Azithromycin/Ciprofloxacin-Loaded Polycaprolactone Nanoparticles: A Characterization and Potency Study.

Purpose: Antimicrobial resistance is a major health hazard worldwide. Combining azithromycin (AZ) and ciprofloxacin (CIP) in one drug delivery system was proposed to boost their antibacterial activity and overcome resistance. This study aims to improve azithromycin and ciprofloxacin activity by co-encapsulating them inside chitosan-coated polymeric nanoparticles and evaluating their antibacterial activity. Methods: The double emulsion method was employed to co-encapsulate AZ/CIP inside chitosan-coated polymeric nanoparticles. The formulations were evaluated for their nanoparticle size, size distribution, and zeta potential. Differential scanning calorimetry (DSC) analysis characterized the formula's thermal sustainability. Encapsulation efficiency was measured by HPLC and spectrophotometric analysis. Morphological studies used the Transmission Electron Microscopy (TEM). The in vitro release profiles of both AZ and CIP were monitored utilizing the dialysis membrane bag method. The micro-dilution assay assessed the antimicrobial activity against a clinical isolate of Klebsiella pneumoniae. Results: The prepared AZ/CIP-poly-caprolactone nanoparticles were spherical; their size range was 184.0 ± 3.3-190.4 ± 5.6 nm and had high size uniformity (poly-dispersity index below 0.2). The zeta potential ranged from -21.2 ± 2.4 to -27.0 ± 2.5 mV, while chitosan-coated nanoparticles showed a positive zeta potential value ranging from 8 to 11 mV. The thermal study confirmed the amorphous state of both antibiotics inside the nanoparticles. The results of the in vitro release study indicated a slow and uniform rate of release for both drugs extended over 4-days, with a faster rate in the case of AZ. The MIC values reported for both chitosan-coated NP have been tremendously reduced by at least 15 folds of pure CIP and more than 60 folds of pure AZ. Conclusion: The co-encapsulation of AZ/CIP into chitosan-coated polymeric nanoparticles has been successfully achieved. The produced particles showed many beneficial attributes of uniform particle sizes below 200 nm and high zeta potential values. Chitosan-coated polymeric nanoparticles extensively enhanced the antibacterial activity of both AZ/CIP against bacteria.

Early Prediction of COVID-19 Ventilation Requirement and Mortality from Routinely Collected Baseline Chest Radiographs, Laboratory, and Clinical Data with Machine Learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China, in late 2019 and created a global pandemic that overwhelmed healthcare systems. COVID-19, as of July 3, 2021, yielded 182 million confirmed cases and 3.9 million deaths globally according to the World Health Organization. Several patients who were initially diagnosed with mild or moderate COVID-19 later deteriorated and were reclassified to severe disease type. OBJECTIVE: The aim is to create a predictive model for COVID-19 ventilatory support and mortality early on from baseline (at the time of diagnosis) and routinely collected data of each patient (CXR, CBC, demographics, and patient history). METHODS: Four common machine learning algorithms, three data balancing techniques, and feature selection are used to build and validate predictive models for COVID-19 mechanical requirement and mortality. Baseline CXR, CBC, demographic, and clinical data were retrospectively collected from April 2, 2020, till June 18, 2020, for 5739 patients with confirmed PCR COVID-19 at King Abdulaziz Medical City in Riyadh. However, of those patients, only 1508 and 1513 have met the inclusion criteria for ventilatory support and mortalilty endpoints, respectively. RESULTS: In an independent test set, ventilation requirement predictive model with top 20 features selected with reliefF algorithm from baseline radiological, laboratory, and clinical data using support vector machines and random undersampling technique attained an AUC of 0.87 and a balanced accuracy of 0.81. For mortality endpoint, the top model yielded an AUC of 0.83 and a balanced accuracy of 0.80 using all features with balanced random forest. This indicates that with only routinely collected data our models can predict the outcome with good performance. The predictive ability of combined data consistently outperformed each data set individually for intubation and mortality. For the ventilator support, chest X-ray severity annotations alone performed better than comorbidity, complete blood count, age, or gender with an AUC of 0.85 and balanced accuracy of 0.79. For mortality, comorbidity alone achieved an AUC of 0.80 and a balanced accuracy of 0.72, which is higher than models that use either chest radiograph, laboratory, or demographic features only. CONCLUSION: The experimental results demonstrate the practicality of the proposed COVID-19 predictive tool for hospital resource planning and patients' prioritization in the current COVID-19 pandemic crisis.

Patients' knowledge about epilepsy in a tertiary medical center: A cross-sectional study from Riyadh, Saudi Arabia.

OBJECTIVE: Epilepsy is a noncommunicable disease that affects approximately 65 million people worldwide. Its management depends greatly on the self-management capacity of the individual. Patients with epilepsy (PWE) who have a good level of knowledge about their disease tend to have better coping mechanisms, as well as better compliance in taking their antiepileptic drugs (AEDs), which improves overall control of symptoms. This study aimed to evaluate the current patients' knowledge about epilepsy and identify factors associated with knowledge of different aspects of epilepsy and its management in a tertiary medical center in Riyadh, Saudi Arabia. METHODS: A cross-sectional study was carried out at a tertiary medical center in Riyadh, Saudi Arabia. Participants were included if they had a documented diagnosis of epilepsy and excluded if they were non-Saudi or had nonepileptic seizures. The Arabic version of the Epilepsy Patient Knowledge Questionnaire (EPKQ) was used to assess patient's knowledge of epilepsy definition and etiology, safety concerns, medication compliance, social activities, and legal issues of employment and driving. Fisher's exact and Chi-Square tests were used to investigate differences in knowledge of epilepsy among different segments of participants. Data management and statistical analyses were carried on using the IBM SPSS Statistics for Windows, version 25. RESULTS: A total of 126 PWE were enrolled in the study. About two-thirds of them were females, and about 68% of them were at least high-school graduates. About one-half of PWE had good knowledge of their condition (>75%), and females had better knowledge than males (p = 0.004). The majority (75.4%) of PWE were knowledgeable about the etiology of epilepsy, about 70% knew that putting a foreign object in a seizing patients' mouth was inappropriate, and only 38% of them did not have adequate knowledge of situations that increase the risk of seizure. About 40% of PWE thought pregnant women should discontinue their AEDs, 53.2% of participants knew what to do when they experience side effects from AEDs, but most of them recognized that they should not automatically stop taking their medications when they stop having seizures. Patients older than 50 years or younger than 21 years of age were less likely to recognize that it was safe for PWE to engage in different social activities (p = 0.042). About 30% of respondents believed that PWE cannot engage in most types of jobs, and more than 50% of participants did not know under which situation PWE can drive. CONCLUSION: This study revealed that about half of PWE had inadequate knowledge about their disorder. Patients with epilepsy had better knowledge about the causes of their condition compared with safety concerns and the treatment of epilepsy, whereas the majority of participants knew the types of jobs and activities that they could engage in. Hence, educational interventions are needed to promote patients' knowledge, especially in terms of safety and the legalities of employment and driving.