COVID-19 is a current global pandemic. However, comprehensive global data analyses for its mortality risk factors are lacking. The current investigation aimed to assess the predictors of death among COVID-19 patients from worldwide open access data. Methods: A total of 828 confirmed cases of COVID-19 with definite outcomes were retrospectively identified from open access individual-level worldwide data. Univariate followed by multivariable regression analysis were used to evaluate the association between potential risk factors and mortality. Results: Majority of the patients were males 59.1% located in Asia 69.3%. Based on the data, older age (adjusted odds ratio (aOR), 1.079; 95% confidence intervals (95% CI), 1.064-1.095 per year increase), males (aOR, 1.607; 95% CI, 1.002-2.576), patients with hypertension (aOR, 3.576; 95% CI, 1.694-7.548), diabetes mellitus (aOR, 12.234; 95% CI,), and patients located in America (aOR, 7.441; 95% CI, 3.546-15.617) were identified as the risk factors of mortality among COVID-19 patients. Conclusions: Males, advanced age, hypertension patients, diabetes mellitus patients, and patients located in America were the independent risk factors of death among COVID-19 patients. Extra attention is required to be given to these factors and additional studies on the underlying mechanisms of these effects.

Background and Objective. Clozapine is a second-generation antipsychotic drug that is considered the most effective treatment for refractory schizophrenia. Several clozapine population pharmacokinetic models have been introduced in the last decades. Thus, a systematic review was performed (i) to compare published pharmacokinetics models and (ii) to summarize and explore identified covariates influencing the clozapine pharmacokinetics models. Methods. A search of publications for population pharmacokinetic analyses of clozapine either in healthy volunteers or patients from inception to April 2019 was conducted in PubMed and SCOPUS databases. Reviews, methodology articles, in vitro and animal studies, and noncompartmental analysis were excluded. Results. Twelve studies were included in this review. Clozapine pharmacokinetics was described as one-compartment with first-order absorption and elimination in most of the studies. Significant interindividual variations of clozapine pharmacokinetic parameters were found in most of the included studies. Age, sex, smoking status, and cytochrome P450 1A2 were found to be the most common identified covariates affecting these parameters. External validation was only performed in one study to determine the predictive performance of the models. Conclusions. Large pharmacokinetic variability remains despite the inclusion of several covariates. This can be improved by including other potential factors such as genetic polymorphisms, metabolic factors, and significant drug-drug interactions in a well-designed population pharmacokinetic model in the future, taking into account the incorporation of larger sample size and more stringent sampling strategy. External validation should also be performed to the previously published models to compare their predictive performances.

Background The coronavirus disease of 2019 (COVID-19) represents a difficult challenge and could have devastating consequences for the healthcare system and healthcare workers in war-torn countries with poor healthcare facilities such as Yemen. Our study aimed to evaluate the knowledge, preparedness, counselling practices of healthcare workers regarding COVID-19, and the perceived barriers to adequately prevent and control COVID-19 in Yemen. Methods Healthcare workers (HCWs) from major healthcare facilities participated in this cross-sectional study. A self-administered questionnaire comprising of five main domains (demographics, knowledge, self-preparedness, counselling practice, perceived barriers) was distributed among HCWs after obtaining informed consent. A convenient sampling technique was used. Descriptive and inferential analyses were applied using SPSS software. Results A total of 1000 participants were initially targeted to participate in the study with 514 (51.4%) responding, of which 55.3% were female. Physicians and nurses constituted the largest proportion of participants, with 39.5% and 33.3%, respectively. The median scores for knowledge, self-preparedness, and counselling practice were 8 (out of 9), 9 (out of 15), and 25 (out of 30), respectively. The physician group showed a statistically significant association with better knowledge compared to the nurse group only, P<0.001. Males had higher preparedness scores than females, p<0.001. Also, the intensive care unit (ICU) and emergency departments presented a statistically significant difference by which the participants from these departments were more prepared compared to the others (e.g. outpatients, paediatrics and surgery) with P < 0.0001. The lack of awareness among the general population about COVID-19 preventive measures was perceived as the most common barrier for the adequate prevention and control of COVID-19 in Yemen (89.1%). Conclusion The major highlight of this study is that HCWs have, overall, good knowledge, suboptimal preparedness, and adequate counselling practices prior to the outbreak of COVID-19 in Yemen, despite the high number of perceived barriers. However, urgent action and interventions are needed to improve the preparedness of HCWs to manage COVID-19. The perceived barriers also need to be fully addressed by the local healthcare authorities and international organisations working in Yemen for adequate prevention and control measures to be in place in managing COVID-19.

One of the largest spontaneous adverse events reporting databases in the world is the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Unfortunately, researchers face many obstacles in analyzing data from the FAERS database. One of the major obstacles is the unstructured entry of drug names into the FAERS, as reporters might use generic names or trade names with different naming structures from all over the world and, in some cases, with typographical errors. Moreover, report duplication is a known problem in spontaneous adverse event-reporting systems, including the FAERS database. Hence, thorough text processing for database entries, especially drug name entries, coupled with a practical case-deduplication logic, is a prerequisite to analyze the database, which is a time- and resource-consuming procedure. In this study, we provide a clean, deduplicated, and ready-to-import dataset into any relational database management software of the FAERS database up to September 2021. Drug names are standardized to the RxNorm vocabulary and normalized to the single active ingredient level. Moreover, a pre-calculated disproportionate analysis is provided, which includes the reporting odds ratio (ROR), proportional reporting ratio (PRR), Chi-squared analysis with Yates correction (x2), and information component (IC) for each drug-adverse event pair in the database.

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Background and Purpose Diabetes mellitus has been reported as a strong independent risk factor for stroke recurrence. Data on the modifiable factors contributing to the recurrence of stroke in type 2 diabetic Malaysian population with a history of stroke stratified by genders are lacking, and this supports the importance of this study. Method The data of 4622 patients with T2DM who had a history of stroke was obtained from the Malaysian National Stroke Registry. Univariate analysis was performed to differentiate between genders with and without stroke recurrence in terms of demographics, first stroke attack presentations, and other clinical characteristics. The significant factors determined from the univariate analysis were further investigated using logistic regression. Results Ischemic heart diseases were found significantly associated with the stroke recurrence in males (OR = 1.738; 95% CI: 1.071-2.818) as well as female (OR = 5.859; 95% CI: 2.469-13.752) diabetic patients. The duration of hypertension, as well as the duration of diabetes, has been associated with the recurrence in both male and female subjects (p value < 0.05). Smoking status has an impact on the stroke recurrence in male subjects, while no significant association was observed among their peers. Conclusions Most of the predictive factors contributing to the recurrence of stroke in type 2 diabetic Malaysian population with a history of stroke are modifiable, in which IHD was the most prominent risk factor in both genders. The impact of optimizing the management of IHD as well as blood glucose control on stroke recurrence may need to be elucidated. No major differences in recurrent stroke predictors were seen between genders among the Malaysian population with type 2 diabetes mellitus who had a previous history of stroke.

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Cyclosporine is a primary drug in transplant immunosuppression regimens. It has a narrow therapeutic index and variable pharmacokinetic behavior. This study aimed to develop a population pharmacokinetic model of cyclosporine in Malaysian renal transplant recipients as well as to evaluate the performances of different methodsfor handling missing doses. A total of 2804 concentrationts predose and 2 hours after doses were collected retrospectively from 113 renal transplant patients on cyclosporine in Penang General Hospital. Model structure and pharmacokinetic parameters were estimated using nonlinear mixed-effects modeling software. Missing doses were handled using different methods to evaluate their performance. Covariate analysis was performed using stepwise forward addition (P < .05) followed by backward elimination (P < .001). Prediction-corrected visual predictive check and sampling-importance resampling methods were used to validate the final model. A 1-compartment model with first-order absorption and elimination best fitted the data. All methods to handle missing doses performed well with the missing dose method being superior to other methods and thus was applied in the final model. Cyclosporine clearance (CL/F) was estimated as 15.1 L/h, and volume of distribution (V/F) was 108 L. Postoperative time, sex, and calcium channel blockers were identified as significant covariates on CL/F, whereas sex and cholesterol level were identified as significant covariates on V/F. This is the first population pharmacokinetic model developed in Malaysian renal transplant patients using a large sample with an evaluation of different methods to handle missing doses in less informative conventional therapeutic drug-monitoring data.