OBJECTIVE: The review was performed to answer the following research question: "In VPNs, are high amounts of arginine in PN, compared with low amounts of arginine, associated with appropriate circulating concentrations of arginine?" Therefore, the aims were to 1) quantify the relationship between parenteral arginine intakes and plasma arginine concentrations in PN-dependent VPNs; 2) identify any features of study design that affect this relationship; and 3) estimate the target parenteral arginine dose to achieve desirable preterm plasma arginine concentrations.
DATA SOURCES: The PubMed, Scopus, Web of Science, and Cochrane databases were searched regardless of study design; review articles were not included.
DATA EXTRACTION: Only articles that discussed amino acid (AA) intake and measured plasma AA profile post PN in VPNs were included. Data were obtained using a data extraction checklist that was devised for the purpose of this review.
DATA ANALYSIS: Twelve articles met the inclusion criteria. The dose-concentration relationship of arginine content (%) and absolute arginine intake (mg/(kg × d)) with plasma arginine concentrations showed a significant positive correlation (P < 0.001).
CONCLUSION: Future studies using AA solutions with arginine content of 17%-20% and protein intakes of 3.5-4.0 g/kg per day may be needed to achieve higher plasma arginine concentrations.
MATERIALS AND METHODS: A cross-sectional study using convenience sampling was conducted among 230 parents with children aged 12 years and below in Malaysia. Data were collected between November 2020 and January 2021 through online platforms.
RESULTS: The majority of respondents were mothers (67.8%) and aged between 40-49 years (43.0%). The results showed that antipyretics were the most commonly used medicines followed by cough and cold medicines, antibiotics, and analgesics. The results further revealed that parents have neutral attitudes toward the use of medicines in children (69.90 ± 12.12 from a total score of 105), and mothers and younger parents having a significantly more positive attitude than fathers and older parents, respectively (p < 0.05).
CONCLUSION: This study provided insights into the types of medicines commonly used in children and parental attitudes towards medicines used in children in Malaysia.
Purpose: To determine the level of adherence to opioid analgesics in patients with cancer pain and to identify factors that may influence the adherence.
Patient and Methods: This was a cross-sectional study conducted from March to June 2018 at two tertiary care hospitals in Malaysia. Study instruments consisted of a set of validated questionnaires; the Medication Compliance Questionnaire, Brief Pain Inventory and Pain Opioid Analgesic Beliefs─Cancer scale.
Results: A total of 134 patients participated in this study. The patients' adherence scores ranged from 52-100%. Factors with a moderate, statistically significant negative correlation with adherence were negative effect beliefs (rs= -0.53, p<0.001), pain endurance beliefs (rs = -0.49, p<0.001) and the use of aqueous morphine (rs = -0.26, p=0.002). A multiple linear regression model on these predictors resulted in a final model which accounted for 47.0% of the total variance in adherence (R2 = 0.47, F (7, 126) = 15.75, p<0.001). After controlling for other variables, negative effect beliefs were the strongest contributor to the model (β = -0.39, p<0.001) and uniquely explained 12.3% of the total variance.
Conclusion: The overall adherence to opioid analgesics among Malaysian patients with cancer pain was good. Negative effects beliefs regarding cancer pain and opioids strongly predicted adherence.
OBJECTIVE: This study aimed to estimate and critically appraise the evidence on the prevalence, causes and severity of medication administration errors (MAEs) amongst neonates in Neonatal Intensive Care Units (NICUs).
METHODS: A systematic review and meta-analysis was conducted by searching nine electronic databases and the grey literature for studies, without language and publication date restrictions. The pooled prevalence of MAEs was estimated using a random-effects model. Data on error causation were synthesised using Reason's model of accident causation.
RESULTS: Twenty unique studies were included. Amongst direct observation studies reporting total opportunity for errors as the denominator for MAEs, the pooled prevalence was 59.3% (95% confidence interval [CI] 35.4-81.3, I2 = 99.5%). Whereas, the non-direct observation studies reporting medication error reports as the denominator yielded a pooled prevalence of 64.8% (95% CI 46.6-81.1, I2 = 98.2%). The common reported causes were error-provoking environments (five studies), while active failures were reported by three studies. Only three studies examined the severity of MAEs, and each utilised a different method of assessment.
CONCLUSIONS: This is the first comprehensive systematic review and meta-analysis estimating the prevalence, causes and severity of MAEs amongst neonates. There is a need to improve the quality and reporting of studies to produce a better estimate of the prevalence of MAEs amongst neonates. Important targets such as wrong administration-technique, wrong drug-preparation and wrong time errors have been identified to guide the implementation of remedial measures.
METHODS AND ANALYSIS: This is a prospective direct observational study that will be conducted in five neonatal intensive care units. A minimum sample size of 820 drug preparations and administrations will be observed. Data including patient characteristics, drug preparation-related and administration-related information and other procedures will be recorded. After each round of observation, the observers will compare his/her observations with the prescriber's medication order, hospital policies and manufacturer's recommendations to determine whether MAE has occurred. To ensure reliability, the error identification will be independently performed by two clinical pharmacists after the completion of data collection for all study sites. Any disagreements will be discussed with the research team for consensus. To reduce overfitting and improve the quality of risk predictions, we have prespecified a priori the analytical plan, that is, prespecifying the candidate predictor variables, handling missing data and validation of the developed model. The model's performance will also be assessed. Finally, various modes of presentation formats such as a simplified scoring tool or web-based electronic risk calculators will be considered.