Genetic and clinical predictors of rifapentine and isoniazid pharmacokinetics in paediatrics with tuberculosis infection.

OBJECTIVES: Twelve weekly doses of rifapentine and isoniazid (3HP regimen) are recommended for TB preventive therapy in children with TB infection. However, they present with variability in the pharmacokinetic profiles. The current study aimed to develop a pharmacokinetic model of rifapentine and isoniazid in 12 children with TB infection using NONMEM. METHODS: Ninety plasma and 41 urine samples were collected at Week 4 of treatment. Drug concentrations were measured using a validated HPLC-UV method. MassARRAY® SNP genotyping was used to investigate genetic factors, including P-glycoprotein (ABCB1), solute carrier organic anion transporter B1 (SLCO1B1), arylacetamide deacetylase (AADAC) and N-acetyl transferase (NAT2). Clinically relevant covariates were also analysed. RESULTS: A two-compartment model for isoniazid and a one-compartment model for rifapentine with transit compartment absorption and first-order elimination were the best models for describing plasma and urine data. The estimated (relative standard error, RSE) of isoniazid non-renal clearance was 3.52 L·h-1 (23.1%), 2.91 L·h-1 (19.6%), and 2.58 L·h-1 (20.0%) in NAT2 rapid, intermediate and slow acetylators. A significant proportion of the unchanged isoniazid was cleared renally (2.7 L·h-1; 8.0%), while the unchanged rifapentine was cleared primarily through non-renal routes (0.681 L·h-1; 3.6%). Participants with the ABCB1 mutant allele had lower bioavailability of rifapentine, while food prolonged the mean transit time of isoniazid. CONCLUSIONS: ABCB1 mutant allele carriers may require higher rifapentine doses; however, this must be confirmed in larger trials. Food did not affect overall exposure to isoniazid and only delayed absorption time.

Pharmacometric modeling of drug adverse effects: an application of mixture models in schizophrenia spectrum disorder patients treated with clozapine.

Clozapine has superior efficacy to other antipsychotics yet is underutilized due to its adverse effects, such as neutropenia, weight gain, and tachycardia. The current investigation aimed to introduce a pharmacometric approach to simultaneously model drug adverse effects, with examples from schizophrenia spectrum patients receiving clozapine. The adverse drug effects were represented as a function of time by incorporating a mixture model to describe individual susceptibility to the adverse effects. Applications of the proposed method were presented by analyzing retrospective data from patients' medical records in Psychiatric Clinic, Penang General Hospital. Tachycardia, weight gain, and absolute neutrophils count (ANC) decrease were best described by an offset, a piecewise linear, and a transient surge function, respectively. 42.9% of the patients had all the adverse effects, including weight gain (0.01 kg/m2 increase every week over a baseline of 24.7 kg/m2 until stabilizing at 279 weeks), ANC decrease (20% decrease from 4540 cells/µL week 12-20.8), and tachycardia (14% constant increase over a baseline of 87.9 bpm for a clozapine maintenance dose of 450 mg daily). 32.5% of the patients had only tachycardia, while the remaining 24.6% had none of the adverse effects. A new pharmacometric approach was proposed to describe adverse drug effects with examples of clozapine-induced weight gain, ANC drop, and tachycardia. The current approach described the longitudinal time changes of continuous data while assessing patient susceptibility. Furthermore, the model revealed the possible co-existence of ANC drop and weight gain; thus, neutrophil monitoring might predict future changes in body weight.

Patterns of dyslipidemia and its associated factors among prediabetic subjects. A cross-sectional study at a primary care clinic.

Introduction: Diabetes is closely linked to cardiovascular diseases, with diabetic dyslipidaemia serving as an established marker of the acceleration of complications, contributing to an increased cardiovascular risk among patients. Timely detection and early characterization of lipid abnormalities can help clinicians in implementing effective preventive measures. This study aimed to determine the patterns and associated factors of dyslipidaemia among Malaysian subjects with borderline diabetes. Methods: A retrospective study was conducted among subjects with borderline diabetes aged ≥18 years who visited a primary healthcare centre at Universiti Sains Malaysia from January 2017 to December 2018. Sociodemographic, clinical and laboratory data were obtained from electronic medical records. Data were analysed using SPSS version 25. Results: A total of 250 participants with borderline diabetes were included in the analysis. Of them, 93.6% (n=234) had lipid abnormalities. Isolated dyslipidaemia characterised by a high low-density lipoprotein cholesterol (LDL-C) level (38.8%, n=97) was the most common pattern found, followed by combined dyslipidaemia of high LDL-C and triglyceride (TG) levels (22.8%, n=57). The male sex was found to be significantly associated with hypertriglyceridemia (adjusted odds ratio [AOR] = 1.86, 95% confidence interval [CI] =1.09-3.1)(P=0.02). Diastolic blood pressure ≥90mmHg was significantly associated with a low HDL-C level (A0R=2.09, 95% CI=1.0-4.1) (P=0.03). Conclusion: The majority of subjects with borderline diabetes have lipid abnormalities. Specifically, isolated dyslipidaemia characterised by a high LDL-C level is alarmingly prevalent. Further large-scale robust studies are needed to confirm the present findings.

A Standardized Dataset of a Spontaneous Adverse Event Reporting System.

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.

Can Newer Anti-Diabetic Therapies Delay the Development of Diabetic Nephropathy?

Type 2 diabetes mellitus (T2DM) is progressive in nature and leads to hyperglycemia-associated microvascular and macrovascular complications. Diabetic nephropathy (DN) is one of the most prominent microvascular complication induced by T2DM and is characterized by albuminuria and progressive loss of kidney function. Aggressive management of hyperglycemia and hypertension has been found effective in delaying the development and progression of DN. Although the conventional antidiabetic treatment is effective in the earlier management of hyperglycemia, the progressive loss of beta cells ultimately needs the addition of insulin to the therapy. The emergence of newer antidiabetic agents may address the limitations associated with conventional antidiabetic therapies, which not only improve the glycemic status but also effective in improving cardio-renal outcomes. Nevertheless, the exact role of these agents and their role in minimizing diabetes progression to DN still needs elaboration. The present review aimed to highlights the impact of these newer antidiabetic agents in the management of hyperglycemia and their role in delaying the progression of diabetes to DN/management of DN in patients with T2DM.

Pharmacometrics Approaches and its Applications in Diabetes: An Overview.

Type 2 diabetes mellitus is the most prevalent and progressive in nature. As the time progress, the multifaceted complications and comorbidities associated to diabetes worsen in the form of macrovascular or microvascular or both. Pharmacometrics modeling is a step forward in minimizing the risk or at least understanding the factors associated to its progression with the passage of time. These models investigate diabetes treatments effects and the progression factors with different viewpoints incorporating insulin-glucose dynamics, dose-response and pharmacokinetics, and pharmacodynamics relationships. Pharmacometrics modeling is an innovative approach in a sense that it is taking us away from the conventional analysis by providing all the opportunities in improving the decision-making in health sector. It has been suggested that we can achieve greater statistical power for determining drug effects through model-based evaluation than through traditional evaluations. The main aim of this review was to evaluate pharmacometrics approaches used in modeling diabetes progression through time and also the integrated models describing glucose-insulin dynamics.

Healthcare workers' knowledge, preparedness, counselling practices, and perceived barriers to confront COVID-19: A cross-sectional study from a war-torn country, Yemen.

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.

Predictors of Recurrent Ischemic Stroke in Obese Patients With Type 2 Diabetes Mellitus: A Population-based Study.

BACKGROUND: Diabetes and obesity are established risk factors for stroke. The current study aimed to assess risk factors of ischemic stroke recurrence in diabetic patients based on their body mass index (BMI). METHODS: A total of 4005 diabetic patients who had a history of ischemic stroke were identified in a retrospective cross-sectional dataset from the Malaysian National Neurology Registry. Patients were classified based on BMI, and multivariable regression analysis was used to evaluate the association between risk factors and recurrent ischemic stroke. RESULTS: Among obese patients, those with ischemic heart disease (aOR, 1.873; 95% CI, 1.131-3.103), received formal education (aOR, 2.236; 95% CI, 1.306-3.830), and received anti-diabetic medication (aOR, 1.788; 95% CI, 1.180-2.708) had a higher stroke recurrence risk, while receiving angiotensin receptors blockers (aOR, 0.261; 95% CI, 0.126-0.543) lowered the odds of recurrence. Overweight patients with hypertension (aOR, 1.011; 95% CI, 1.002-1.019) for over 10 years (aOR, 3.385; 95% CI, 1.088-10.532) and diabetes prior to the first stroke (aOR, 1.823; 95% CI, 1.020-3.259) as well as those received formal education (aOR, 2.403; 95% CI, 1.126-5.129) had higher odds of stroke recurrence, while receiving angiotensin-converting enzyme inhibitors (aOR, 0.244; 95% CI, 0.111-0.538) lowered the recurrence risk. Normal weight East Malaysians (aOR, 0.351; 95% CI, 0.164-0.750) receiving beta-blockers (aOR, 0.410; 95% CI, 0.174-0.966) had lower odds of stroke recurrence. CONCLUSIONS: Ischemic heart disease, hypertension, receiving anti-hypertensive agents, and educational level were independent predictors of recurrent stroke in obese patients. Managing the modifiable risk factors can decrease the odds of stroke recurrence.

Diet quality and its association with glycemic parameters in different diabetes progression stages. A cross-sectional questionnaire study at a primary care clinic.

BACKGROUND: Diabetes mellitus is a leading cause of preventable deaths and becomes a major public health concern in Malaysia. Multiple studies have reported the association between diet quality and glycemic parameters among known diabetic subjects. Its influence in individuals with borderline diabetes (i.e. pre-diabetes) or unknown diabetes is still unclear. OBJECTIVE: The objective of this study was to assess the association between diet quality evaluated by healthy eating index (HEI) with the glucose outcome in individuals with distinct diabetes progression stages, as well as to identify causal factors in relation to their diabetes status. METHOD: A cross-sectional study was conducted at clinical care setting in Universiti Sains Malaysia (USM) between October 2018-March 2019. Normoglycemic controls (n = 47), at-risk of pre-diabetes (n = 58), pre-diabetes (n = 24) as well as individuals with undiagnosed diabetes (n = 18) were queried about their habitual diet by using Food Frequency Questionnaire (FFQ). Correlation analyses were performed to examine the relationship between HEI score and 1) Fasting plasma glucose (FPG) 2) postprandial blood glucose (2-HPP) and glycosylated hemoglobin (HbA1c). Multinomial regression was performed to identify predictors associated with diabetes status of study participants. RESULT: Overall, diet quality of study participants was unsatisfactory with the mean score of 58.05 ± 9.07 that need improvement. Total HEI score was negatively correlated with the 2-HPP levels in pre-diabetic patients (r = - 0.45, p = 0.05). No significant association was revealed between glycemic parameters and total HEI score among other groups. Age, body mass index (BMI), triglycerides and female gender were positively correlated with the risk of pre-diabetes, at-risk of pre-diabetes and undiagnosed diabetes (p < 0.01). CONCLUSION: Diet quality was not strongly associated with glycemic parameters among study participants. Age, BMI, triglycerides and female gender are crucial factors, that needed to be prioritized by primary care providers when managing pre-diabetes/diabetes to achieve possible reversion. Further in-depth investigations with large sample are warranted to confirm study findings.