The paper "Antimicrobial Resistance Patterns of Gram-Negative Bacilli Bloodstream Isolates" is an excellent example of a research paper on biology. Antimicrobial resistance is the prime public health problem, particularly in developing nations, where there is relatively easy access to antibiotics and high medicine consumption (Kumar et al, 2013; Spellberg et al, 2013). As established by Khalili et al (2012), incidences of antibiotic resistance have risen rapidly over the past decade, with between 50 and 80 percent of the hospital-acquired infections resulting from the resistant strains. The contributing factors to the infections from resistant microorganisms include the use of antibiotics (Mushi, 2013).
Indeed, studies have established that antibiotic resistance is triggered for comorbidity, mortality, as well as higher cost of treatment (Magnet et al 2013; Tan et al, 2012; Gupta, 2011). Among the most significant causes of a hospital, infections are Gram-negative bacilli (GNB), which is a cause of early- and late-onset neonatal sepsis that has a high mortality rate (Toroglu et al, 2005). Apart from the innate and chromosomally mediated methods of resistance, the advancement of drug resistance in GNB is also encouraged by the acquisition of integrons, plasmids, and transposons that transmit resistance genes (Soge et al, 2009- Paterson, 2008).
These genes are characteristically an outcome of selective antimicrobial strain compelled by long-term use of antibiotics. Hence, averting the increase of resistant organisms is vital for mitigating hospital infections. The incidence of antimicrobial resistance ranges in varied settings (Navaneeth & Belwadi, 2002). At the same time, past and current studies have to indicate that information on the patterns of antimicrobial resistance is critical, specifically in hospitals (Paramythiotou et al, 2004; Velasco et al, 2012). To this end, the proposed question is: “ what are the antimicrobial resistance patterns of GNB bloodstream isolates in a hospital and their potential causes to patients when significant changes take place? ” The research question directs an inquiry into the antimicrobial resistance patterns in hospitals as this will help the healthcare practitioners to select appropriate antibiotic therapy that can improve reduce mortality and morbidity, reduce treatment care and improve treatment outcomes. 2.0 Methodology Data were mainly collected using the Google search engine and search into open-access databases such as Google Scholar and Medline.
The keywords employed for the search included antibiotic resistance, antimicrobial resistance, Gram-negative bacilli (GNB) among others. Articles targeted were those that combined observational and randomized controlled trial (RCTs), systematic review as well as those supporting, and not supporting the hypothesis.