Chemical Composition, Antioxidant, Antibacterial, and Antibiofilm Activities of Backhousia citriodora Essential Oil.

The essential oil of Backhousia citriodora, commonly known as lemon myrtle oil, possesses various beneficial properties due to its richness in bioactive compounds. This study aimed to characterize the chemical profile of the essential oil isolated from leaves of Backhousia citriodora (BCEO) and its biological properties, including antioxidant, antibacterial, and antibiofilm activities. Using gas chromatography-mass spectrometry, 21 compounds were identified in BCEO, representing 98.50% of the total oil content. The isomers of citral, geranial (52.13%), and neral (37.65%) were detected as the main constituents. The evaluation of DPPH radical scavenging activity and ferric reducing antioxidant power showed that BCEO exhibited strong antioxidant activity at IC50 of 42.57 µg/mL and EC50 of 20.03 µg/mL, respectively. The antibacterial activity results showed that BCEO exhibited stronger antibacterial activity against Gram-positive bacteria (Staphylococcus aureus and Staphylococcus epidermidis) than against Gram-negative bacteria (Escherichia coli and Klebsiella pneumoniae). For the agar disk diffusion method, S. epidermidis was the most sensitive to BCEO with an inhibition zone diameter of 50.17 mm, followed by S. aureus (31.13 mm), E. coli (20.33 mm), and K. pneumoniae (12.67 mm). The results from the microdilution method showed that BCEO exhibited the highest activity against S. epidermidis and S. aureus, with the minimal inhibitory concentration (MIC) value of 6.25 µL/mL. BCEO acts as a potent antibiofilm agent with dual actions, inhibiting (85.10% to 96.44%) and eradicating (70.92% to 90.73%) of the biofilms formed by the four tested bacteria strains, compared with streptomycin (biofilm inhibition, 67.65% to 94.29% and biofilm eradication, 49.97% to 89.73%). This study highlights that BCEO can potentially be a natural antioxidant agent, antibacterial agent, and antibiofilm agent that could be applied in the pharmaceutical and food industries. To the best of the authors' knowledge, this is the first report, on the antibiofilm activity of BCEO against four common nosocomial pathogens.

Determinants of Inadequate Empiric Antimicrobial Therapy in ICU Sepsis Patients in Al-Madinah Al-Munawwarah, Saudi Arabia: A Comparison of Artificial Neural Network and Regression Analysis.

In the management of sepsis, providing adequate empiric antimicrobial therapy is one of the most important pillars of sepsis management. Therefore, it is important to evaluate the adequacy of empiric antimicrobial therapy (EAMT) in sepsis patients admitted to intensive care units (ICU) and to identify the determinants of inadequate EAMT. The aim of this study was to evaluate the adequacy of empiric antimicrobial therapy in patients admitted to the ICU with sepsis or septic shock, and the determinants of inadequate EAMT. The data of patients admitted to the ICU units due to sepsis or septic shock in two tertiary healthcare facilities in Al-Madinah Al-Munawwarah were retrospectively reviewed. The current study used logistic regression analysis and artificial neural network (ANN) analysis to identify determinants of inadequate empiric antimicrobial therapy, and evaluated the performance of these two approaches in predicting the inadequacy of EAMT. The findings of this study showed that fifty-three per cent of patients received inadequate EAMT. Determinants for inadequate EAMT were APACHE II score, multidrug-resistance organism (MDRO) infections, surgical history (lower limb amputation), and comorbidity (coronary artery disease). ANN performed as well as or better than logistic regression in predicating inadequate EAMT, as the receiver operating characteristic area under the curve (ROC-AUC) of the ANN model was higher when compared with the logistic regression model (LRM): 0.895 vs. 0.854. In addition, the ANN model performed better than LRM in predicting inadequate EAMT in terms of classification accuracy. In addition, ANN analysis revealed that the most important determinants of EAMT adequacy were the APACHE II score and MDRO. In conclusion, more than half of the patients received inadequate EAMT. Determinants of inadequate EAMT were APACHE II score, MDRO infections, comorbidity, and surgical history. This provides valuable inputs to improve the prescription of empiric antimicrobials in Saudi Arabia going forward. In addition, our study demonstrated the potential utility of applying artificial neural network analysis in the prediction of outcomes in healthcare research.

Factors influencing parents' hesitancy to vaccinate their children aged 5-11 years old against COVID-19: results from a cross-sectional study in Malaysia.

Introduction: Vaccination programs have been rolled out across the globe to contain and mitigate the spread of the COVID-19 infection. Until recently, such programs were limited to adults and the older population, thereby limiting children from getting vaccinated. Recently, the Malaysian government rolled out vaccination for children aged 5-11 years. However, there are certain factors that might affect vaccination uptake among children. This study explores factors influencing parents' hesitancy to vaccinate children in Malaysia. Method: A nationwide online cross-sectional convenience sampling survey from April 21, 2022 to June 3, 2022 was conducted. The study used descriptive statistics to inform about vaccine hesitancy among parents. Cross-tabulation was performed to calculate the frequency and percentage of vaccine hesitancy, quality of life, e-health literacy, and the 5C psychological antecedents of vaccination among parents with children 5-11 years in Malaysia. Graphical methods were used to portray the levels of e-health literacy and levels of 5C psychological antecedents of vaccination. The study used both bi-variate and multivariate analysis to understand the relationship between vaccine hesitancy and the socio-demo-economic factors, quality of life, e-health literacy and 5C psychological antecedents. Results: Of 382 participants, almost one-third (33%) of participants reported vaccine hesitancy for their children. For 5C's psychological antecedents of vaccination, around one quarter (26.96%) reported disagreement for confidence in vaccination, almost half (52.36%) reported disagreement for vaccination complacency, three-fifths (60.99%) reported vaccination constraint, one quarter (25.92%) reported calculation antecedent, and almost one-third reported disagreement over collective responsibility antecedent (25.92%). Chi-square test revealed that gender, employment status, and parents' COVID-19 vaccination status were significantly associated (p<0.05) with vaccine hesitancy among parents. Assessing the influence of transactional e-health literacy, only the communication component contained a significant association (p<0.05). Among the 5C psychological antecedents, confidence, calculation, and collective responsibility were significantly associated (p<0.05) with vaccine hesitancy. Parents with secondary [OR: 8.80; CI: 2.44-31.79, (p<0.05)], post-secondary [OR: 5.21; CI: 2.10-13.41, (p<0.05)], and tertiary education [OR: 6.77; CI: 2.25-20.35, (p<0.05)] had significantly higher likelihood of vaccine hesitancy than those with primary education. Conclusion: Highly educated parents are more skeptical and are more likely to perceive the vaccine as unsafe and ineffective for their children. It is critical to disseminate the required information about the vaccine safety to the educated group.

Adapted digital health literacy and health information seeking behavior among lower income groups in Malaysia during the COVID-19 pandemic.

Background: Misinformation has had a negative impact upon the global COVID-19 vaccination program. High-income and middle-income earners typically have better access to technology and health facilities than those in lower-income groups. This creates a rich-poor divide in Digital Health Literacy (DHL), where low-income earners have low DHL resulting in higher COVID-19 vaccine hesitancy. Therefore, this cross-sectional study was undertaken to assess the impact of health information seeking behavior on digital health literacy related to COVID-19 among low-income earners in Selangor, Malaysia. Methods: A quantitative cross-sectional study was conducted conveniently among 381 individuals from the low-income group in Selangor, Malaysia. The remote data collection (RDC) method was used to gather data. Validated interviewer-rated questionnaires were used to collect data via phone call. Respondents included in the study were 18 years and older. A normality of numerical variables were assessed using Shapiro-Wilk test. Univariate analysis of all variables was performed, and results were presented as means, mean ranks, frequencies, and percentages. Mann-Whitney U test or Kruskal Wallis H test was applied for the comparison of DHL and health information seeking behavior with characteristics of the participants. Multivariate linear regression models were applied using DHL as dependent variable and health information seeking behavior as independent factors, adjusting for age, gender, marital status, educational status, employment status, and household income. Results: The mean age of the study participants was 38.16 ± 14.40 years ranging from 18 to 84 years. The vast majority (94.6%) of participants stated that information seeking regarding COVID-19 was easy or very easy. Around 7 percent of the respondents cited reading information about COVID-19 on the internet as very difficult. The higher mean rank of DHL search, content, reliability, relevance, and privacy was found among participants who were widowed, had primary education, or unemployed. An inverse relationship was found between overall DHL and confidence in the accuracy of the information on the internet regarding COVID-19 (ß = -2.01, 95% CI = -2.22 to -1.79). Conclusion: It is important to provide support to lower-income demographics to assist access to high-quality health information, including less educated, unemployed, and widowed populations. This can improve overall DHL.