Prevalence and barriers to HIV testing among mothers at a tertiary care hospital in Phnom Penh, Cambodia. Barriers to HIV testing in Phnom Penh, Cambodia

<p>Abstract</p> <p>Background</p> <p>One-third of all new HIV infections in Cambodia are estimated to be due to mother-to-child transmission. Although the Ministry of Health adopted a policy of provider-initiated HIV testing and counseling (PITC), nearly a quarter of pregnant mothers were not tested in 2007. Greater acceptance of HIV testing is a challenge despite Cambodia's adoption of the PITC policy.</p> <p>Methods</p> <p>A hospital-based quantitative and cross-sectional survey was conducted to assess the prevalence of and barriers to HIV testing among mothers after delivery at the National Maternal and Child Health Center in Phnom Penh. The Center is one of the largest maternal and child care hospitals in the country to offer PITC services. All 600 eligible mothers who were admitted to the hospital after delivery from October to December 2007 were approached and recruited. Data were collected via a semi-structured questionnaire.</p> <p>Results</p> <p>The prevalence of HIV testing among women who delivered at the hospital was 76%. In multivariate logistic regression, factors such as the perceived need to obtain a partner's permission to be tested (OR=0.27, 95% CI=0.14-0.51, p<0.01), the lack of knowledge about HIV prevention and treatment (OR=0.38, CI=0.22-0.66, p<0.01), and the lack of access to ANC services (OR=0.35, 95% CI=0.21-0.58, p<0.01) were found to be the main barriers to HIV testing.</p> <p>Conclusion</p> <p>To achieve greater acceptance of HIV testing, counseling on HIV prevention and treatment must be provided not only to mothers but also to their partners. In addition, utilization of non-laboratory staff such as midwives to provide HIV testing services in rural health facilities could lead to the greater acceptance of HIV testing.</p

Image quality and diagnostic accuracy of unenhanced SSFP MR angiography compared with conventional contrast-enhanced MR angiography for the assessment of thoracic aortic diseases

The purpose of this study was to determine the image quality and diagnostic accuracy of three-dimensional (3D) unenhanced steady state free precession (SSFP) magnetic resonance angiography (MRA) for the evaluation of thoracic aortic diseases. Fifty consecutive patients with known or suspected thoracic aortic disease underwent free-breathing ECG-gated unenhanced SSFP MRA with non-selective radiofrequency excitation and contrast-enhanced (CE) MRA of the thorax at 1.5 T. Two readers independently evaluated the two datasets for image quality in the aortic root, ascending aorta, aortic arch, descending aorta, and origins of supra-aortic arteries, and for abnormal findings. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were determined for both datasets. Sensitivity, specificity, and diagnostic accuracy of unenhanced SSFP MRA for the diagnosis of aortic abnormalities were determined. Abnormal aortic findings, including aneurysm (n = 47), coarctation (n = 14), dissection (n = 12), aortic graft (n = 6), intramural hematoma (n = 11), mural thrombus in the aortic arch (n = 1), and penetrating aortic ulcer (n = 9), were confidently detected on both datasets. Sensitivity, specificity, and diagnostic accuracy of SSFP MRA for the detection of aortic disease were 100% with CE-MRA serving as a reference standard. Image quality of the aortic root was significantly higher on SSFP MRA (P &lt; 0.001) with no significant difference for other aortic segments (P &gt; 0.05). SNR and CNR values were higher for all segments on SSFP MRA (P &lt; 0.01). Our results suggest that free-breathing navigator-gated 3D SSFP MRA with non-selective radiofrequency excitation is a promising technique that provides high image quality and diagnostic accuracy for the assessment of thoracic aortic disease without the need for intravenous contrast material

Biological effects of exposure to magnetic resonance imaging: an overview

The literature on biological effects of magnetic and electromagnetic fields commonly utilized in magnetic resonance imaging systems is surveyed here. After an introduction on the basic principles of magnetic resonance imaging and the electric and magnetic properties of biological tissues, the basic phenomena to understand the bio-effects are described in classical terms. Values of field strengths and frequencies commonly utilized in these diagnostic systems are reported in order to allow the integration of the specific literature on the bio-effects produced by magnetic resonance systems with the vast literature concerning the bio-effects produced by electromagnetic fields. This work gives an overview of the findings about the safety concerns of exposure to static magnetic fields, radio-frequency fields, and time varying magnetic field gradients, focusing primarily on the physics of the interactions between these electromagnetic fields and biological matter. The scientific literature is summarized, integrated, and critically analyzed with the help of authoritative reviews by recognized experts, international safety guidelines are also cited

Patient Safety in Radiology

AbstractMedical imaging (in short radiology) includes diagnostic and interventional procedures and has an essential role in the diagnosis and treatment of diseases. The objective in this field of medicine is focused on providing diagnostic and therapeutic benefit to the patients along with protecting them from the possible hazards associated with the procedures. By continuously upgrading imaging technologies and improving imaging modalities, such as ultrasound imaging, X-ray-based imaging (radiography, fluoroscopy, and computed tomography), magnetic resonance imaging (MRI), and interventional radiology, safety has become more and more crucial. The potential hazards in radiology for the patients and the staff are multidimensional and will be discussed in the chapter

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks