BackgroundThe suffering from low back pain (LBP) is very common among nurses. The high prevalence rates of LBP are observed in many countries. Many back injuries are due to individual and work-related factors. Our aim is to investigate whether there is an association of occupational factors with LBP among the female nurses who are currently working in tertiary hospitals of Bangladesh.MethodsWe conducted a cross-sectional study with 229 female nurses from two selected tertiary hospitals in Bangladesh. Data was collected through face-to-face interview using a standard structured questionnaire on four different measures of LBP along with questions on socio-demographic, occupational factors, physical and psychological factors.ResultsPrevalence rates of LBP that lasted for at least 1 day, chronic LBP, intense pain and sought medical care because of LBP during the last 12 months were 72.9, 31.8, 24.4 and 36.2%, respectively. The multiple logistic regression analyses indicates that insufficient supporting staffs, overtime working hours and manual lifting in a working environment are associated with LBP. Besides, age and parity are found positively associated with chronic LBP.ConclusionThe prevalence of LBP among nurses in Bangladesh is high and should be actively addressed. Certain occupational factors play a key role in developing LBP among nurses. Nurses to patients ratio should be taken into consideration to reduce the occurrence of LBP among nurses employed in hospitals.
<p>Treatment with chemotherapy is important in limiting the intensity of serous epithelial ovarian cancer. However, not all patients are sensitive to platinum chemotherapy corresponding to longer progression-free survival (PFS >8 months). Koti <em>et al.</em>[1] revealed a set of 204 discriminating genes possessing expression levels, which could influence differential chemotherapy response between the platinum-resistant and platinum-sensitive group of patients. They considered Welch two-sample <em>t</em>-test and non-parametric Mann-Whitney U test to identify the differentially expressed genes. However, both the statistical methods turned out to be unsuitable for microarray data. In this paper, we used three alternative statistical methods to select a combined list of genes and compared the genes that were proposed by Koti <em>et al.</em>[1]. Subsequently, we recommended using sparse principal component analysis (sparse PCA) to identify a final list of genes. Sparse PCA incorporates correlation into account among the genes and helps to draw a biologically important gene discovery. We identified 77 differentially expressed genes, which include 11 new genes that can separate the groups of patients who are platinum-resistant and platinum-sensitive to the chemotherapy. The integrative approach can also be effective in another high dimensional dataset to compare between two groups.</p>
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