MyMedR

Displaying all 2 publications

Abstract:

Sort:

Fulltext Knowledge about the administration and regulation of high alert medications among nurses in Palestine: a cross-sectional study

Zyoud SH, Khaled SM, Kawasmi BM, Habeba AM, Hamadneh AT, Anabosi HH, et al.

BMC Nurs, 2019;18:11.
PMID: 30936779 DOI: 10.1186/s12912-019-0336-0

Background: Medication errors (MEs) are unintended failures in the drug treatment process that can occur during prescription, dispensing, storing, preparation or administration of medications. High alert medications (HAMs) are defined as those medications that bear the highest risk of causing significant patient harm when used incorrectly, either due to their serious adverse events or to a narrow therapeutic window. Nurses are responsible for administration of HAMs; incorrect administration can have a significant clinical outcome. This study aimed to assess the level of knowledge of HAMs among nurses in government hospitals in West Bank, Palestine.
Methods: A cross-sectional study was conducted in 2015, in West Bank, Palestine. Data were collected via a face to face interview questionnaire, which was taken from a previous study. Data were collected by convenient sampling. The questionnaire consisted of four parts: demographic characteristics of the nurses, drug administration knowledge (10 true-false questions), drug regulation knowledge (10 true-false questions), and self-evaluation.
Results: A total of 280 nurses participated in the study; these nurses were working in the emergency room (ER), intensive care unit (ICU), paediatric or medical ward. The response rate was 93%. Nurses were found to have insufficient knowledge about HAMs; 67.1% of participants had a score of less than 70%, with a mean total score of 59.9 ± 15.1. Factors associated with sufficient knowledge among nurses were HAMs training and ICU training, both with p-values of 0.002. Nurses with a master degree, those working in the ICU ward, head nurses, and male nurses were the most knowledgeable groups, with a p-values
Fulltext 1H-NMR-Based Metabolomics: An Integrated Approach for the Detection of the Adulteration in Chicken, Chevon, Beef and Donkey Meat

Akhtar MT, Samar M, Shami AA, Mumtaz MW, Mukhtar H, Tahir A, et al.

Molecules, 2021 Jul 30;26(15).
PMID: 34361796 DOI: 10.3390/molecules26154643

Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing of high-price meat species with low-quality/-price meat. This work aimed to differentiate different meat samples on the basis of metabolites. The metabolic difference between various meat samples was investigated through Nuclear Magnetic Resonance spectroscopy coupled with multivariate data analysis approaches like principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). In total, 37 metabolites were identified in the gluteal muscle tissues of cow, goat, donkey and chicken using 1H-NMR spectroscopy. PCA was found unable to completely differentiate between meat types, whereas OPLS-DA showed an apparent separation and successfully differentiated samples from all four types of meat. Lactate, creatine, choline, acetate, leucine, isoleucine, valine, formate, carnitine, glutamate, 3-hydroxybutyrate and α-mannose were found as the major discriminating metabolites between white (chicken) and red meat (chevon, beef and donkey). However, inosine, lactate, uracil, carnosine, format, pyruvate, carnitine, creatine and acetate were found responsible for differentiating chevon, beef and donkey meat. The relative quantification of differentiating metabolites was performed using one-way ANOVA and Tukey test. Our results showed that NMR-based metabolomics is a powerful tool for the identification of novel signatures (potential biomarkers) to characterize meats from different sources and could potentially be used for quality control purposes in order to differentiate different meat types.

Filters

Please provide feedback to Administrator ([email protected])

External Links