Breast cancer risk factor knowledge among nurses in teaching hospitals of Karachi, Pakistan: a cross-sectional study

BACKGROUND: Breast cancer is the most common cancer among women in both the developed and the developing world. The incidence of breast cancer in Karachi, Pakistan is 69.1 per 100,000 with breast cancer presentation in stages III and IV being common (≥ 50%). The most pragmatic solution to early detection lies in breast cancer education of women. Nurses constitute a special group having characteristics most suited for disseminating breast cancer information to the women. We assessed the level of knowledge of breast cancer risk factors among registered female nurses in teaching hospitals of Karachi. We also identified whether selected factors among nurses were associated with their knowledge of breast cancer risk factors, so that relevant measures to improve knowledge of nurses could be implemented. METHODS: A cross-sectional survey was conducted in seven teaching hospitals of Karachi using stratified random sampling with proportional allocation. A total of 609 registered female nurses were interviewed using a structured questionnaire adapted from the Stager's Comprehensive Breast Cancer Knowledge Test. Knowledge of breast cancer risk factors was categorized into good, fair and poor categories. Ordinal regression was used to identify factors associated with risk knowledge among nurses. RESULTS: Thirty five percent of nurses had good knowledge of risk factors. Graduates from private nursing schools (aOR = 4.23, 95% CI: 2.93, 6.10), nurses who had cared for breast cancer patients (aOR = 1.41, 95% CI: 1.00, 1.99), those having received a breast examination themselves (aOR = 1.56, 95% CI: 1.08, 2.26) or those who ever examined a patient's breast (aOR = 1.87, 95% CI: 1.34, 2.61) were more likely to have good knowledge. CONCLUSION: A relatively small proportion of the nursing population had good level of knowledge of the breast cancer risk factors. This knowledge is associated with nursing school status, professional breast cancer exposure and self history of clinical breast examination. Since only about one-third of the nurses had good knowledge about risk factors, there is a need to introduce breast cancer education in nursing schools particularly in the public sector. Continuing nursing education at the workplace can be of additional benefit

Left ventricular volume: an optimal parameter to detect systolic dysfunction on prospectively triggered 64-multidetector row computed tomography: another step towards reducing radiation exposure

In this study, we define the correlation between LV volumes (both LV end-diastolic volume [LVEDV] and LV end-systolic volume [LVESV]) and ejection fraction (EF) on 64 slice multi-detector computed tomography (MDCT). We also determine the accuracy of all the LV volume (LVV) parameters to detect LV systolic dysfunction (LVSD) and investigate the feasibility of using LVV as a surrogate of LVSD on prospectively gated imaging to prevent the radiation exposure of retrospective imaging. 568 patients undergoing 64-detector MDCT were divided into 2 groups: Group 1—subjects without any heart disease and LVEF ≥ 50%; and Group 2—patients with coronary artery disease and LVEF < 50% (defined as LVSD). The LVV (LV cavity only) and Total LV volume (cavity + LV mass) at end-systole and end-diastole (LVESV, Total LVESV, LVEDV and Total LVEDV) were measured. The upper limit values (mean + 2 SD) of all LVV parameters in Group 1 were used as the reference criterion to diagnose LVSD in Group 2. An exponential correlation was found between LVEF and all the LVV parameters. The specificity to detect LVSD in Group 2 was >90% and the sensitivity was 88.9, 83.3, 61.3 and 74.9% by using LVESV, Total LVESV, LVEDV and Total LVEDV, respectively. Systolic and diastolic LV volumes had a high correlation with LVEF and a high accuracy to detect LVSD. Thus, on prospectively triggered imaging, ventricular volumes can predict patients with reduced LVEF, and appropriate referrals can be made

Expression and Function of Serotonin 2A and 2B Receptors in the Mammalian Respiratory Network

Neurons of the respiratory network in the lower brainstem express a variety of serotonin receptors (5-HTRs) that act primarily through adenylyl cyclase. However, there is one receptor family including 5-HT2A, 5-HT2B, and 5-HT2C receptors that are directed towards protein kinase C (PKC). In contrast to 5-HT2ARs, expression and function of 5-HT2BRs within the respiratory network are still unclear. 5-HT2BR utilizes a Gq-mediated signaling cascade involving calcium and leading to activation of phospholipase C and IP3/DAG pathways. Based on previous studies, this signal pathway appears to mediate excitatory actions on respiration. In the present study, we analyzed receptor expression in pontine and medullary regions of the respiratory network both at the transcriptional and translational level using quantitative RT-PCR and self-made as well as commercially available antibodies, respectively. In addition we measured effects of selective agonists and antagonists for 5-HT2ARs and 5-HT2BRs given intra-arterially on phrenic nerve discharges in juvenile rats using the perfused brainstem preparation. The drugs caused significant changes in discharge activity. Co-administration of both agonists revealed a dominance of the 5-HT2BR. Given the nature of the signaling pathways, we investigated whether intracellular calcium may explain effects observed in the respiratory network. Taken together, the results of this study suggest a significant role of both receptors in respiratory network modulation

Background Traffic Load Aware Video Class-lecture Client Admission in a Bandwidth Constrained Campus Network

Video class-lecture streaming is regarded as a popular means in improving quality of teaching and learning in schools and universities. Several research findings reveal that, recorded lecture videos (streamed over the Internet) are a useful supplement to non-classroom learning. Despite knowing this importance, some schools or universities are reluctant to use video lecture streaming service in their campus network, thinking video streaming service would impose additional traffic load in their network. In fact, in a bandwidth constrained campus network, other regular traffic flows may experience lower throughput, packet drop and delay due to presence of class lecture video streaming traffic, resulting in deteriorating Quality of Experience (QoE) of campus users. In this paper, we propose video streaming service model for the bandwidth constrained campus networks. We refer to our solution as Class Lecture on Demand (CLD) service that can be easily adopted in a campus. CLD de nes the policies for admitting number of clients that request for video stream- ing service taking into account peak hour and o -peak hour background tra c load. This paper provides a detailed procedures, showing how a network administrator in a bandwidth constrained campus network can measure the maximum number class lecture streaming requests that a video streaming server should accommodated at di erent part of a day without affecting other traffic flows. Additionally, we provide an insightful discussion (policies) in order to make video lecture streaming in a bandwidth constrained campus network easily adopted