Anatomic and physiologic changes in lower extremity venous hemodynamics associated with pregnancy

AbstractPurpose: The purpose of this study was to describe the physiologic effects of pregnancy on lower extremity venous hemodynamics.Methods: Eight pregnant women, six with no known venous disease (NVD) and two with documented deep venous obstruction (DVO), were identified in the first trimester (TM) and studied monthly until delivery and once postpartum (pp) by air plethysmography and duplex scan.Results: None of six women in the NVD group (12 extremities) had obstruction or elevated ambulatory venous pressures as estimated by air plethysmography. In addition, despite significant increases in common femoral vein and saphenofemoral junction diameters, no woman in the NVD group had reflux by either test. Venous filling index increased significantly during pregnancy and decreased significantly pp, but all values remained within the normal range (0.55 ± 0.2 ml/sec first TM, 1.01 ± 0.38 ml/sec late third TM, 0.58 ± 0.08 ml/sec pp; p < 0.03 both comparisons). Common femoral vein diameters increased and decreased in similar fashion (0.99 ± 0.25 cm first TM, 1.21 ± 0.25 cm late third TM, 0.80 ± 0.11 cm pp; p < 0.0005 first vs late third TM, p < 0.005 late third TM vs pp). Saphenofemoral junction vein diameters similarly increased and decreased in size (0.46 ± 0.07 cm first TM, 0.68 ± 0.19 cm late third TM, 0.50 ± 0.10 cm pp; p < 0.01 first vs late third TM, p < 0.03 late third TM vs pp). Neither of the two women in the DVO group showed deterioration of outflow fraction or venous filling index as pregnancy progressed, and neither had thromboembolic complications despite moderate to severe preexisting obstruction. Both women in the DVO group delivered uneventfully. No woman in either group developed varicose veins.Conclusion: Pregnancy-induced changes in lower extremity venous hemodynamics in the NVD and DVO groups were detected but were small. Hormonal or other systemic factors must play a significant role in the development of postpartum varicose veins. (J Vasc Surg 1996;24:763-7.

"Depression Is A Medical Condition": Exploring the Medicalization of Depression on SSRI Websites

ABSTRACT “DEPRESSION IS A MEDICAL CONDITION”: EXPLORING THE MEDICALIZATION OF DEPRESSION ON SSRI WEBSITES Sociologists of medicine have become increasingly interested in mental health over the last two decades (Pilgrim and Rogers, 2005). Known as the “common cold” of mental illness, depression affects millions around the globe. The social understanding of depression has been shaped by a phenomenon known as medicalization, where an unusual behavior or state of being is labeled illness or disorder or disease, and addressed through rationalized medical intervention. The medicalization of depression is particularly evident on SSRI websites. SSRIs (Selective Serotonin Reuptake Inhibitors) are a popular class of antidepressants used to treat depression. Pharmaceutical companies who manufacture these medications now advertise their products on the Internet, an increasingly popular source for health information. This thesis is a critical, empirical investigation of the medicalization of depression on SSRI websites. Five major research questions guide this study. First, how is depression portrayed on the websites? Second, what are the means used to construct this portrayal? Third, who is the apparent target audience? Fourth, what assumptions are made about this audience? Finally, what is absent from or silent in the websites? These questions are answered using an analytical framework called Critical Discourse Analysis (CDA). This framework is both a theoretical orientation and a methodological process (Fairclough, 1992). This study reveals that medicalization has a strong impact on the portrayal of depression on the websites, and is the major perspective from which the issue is approached. The depressed person is seen to be affected by depression in a variety of ways, including being ill with a medical condition and at risk for further difficulty if treatment is not handled properly. A variety of means are used to construct the portrayal of depression, including structural means such as interactional controls, linguistic means such as word choices and meanings, and visual means such as the use of diagrams and caricatures. Embedded in the text are a number of indicators which highlight some apparent assumptions about the targeted audience, such as insurance coverage and general literacy. Absences or silences in the texts include a failure to discuss the prevention of depression. The most significant finding concerns “the symptom/side-effect” problem; this dilemma highlights the lack of clarity around definitions of recovery and mental health as well as the purpose of taking medications. It also reveals that, while the application of the medicalized perspective to depression is certainly useful given the efficacy of antidepressant drugs for many people, it is not infallible and requires careful critical consideration

FNS and HEIV: relating two vision parameter estimation frameworks

©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Problems requiring accurate determination of parameters from image-based quantities arise often in computer vision. Two recent, independently developed frameworks for estimating such parameters are the FNS and HEIV schemes. Here it is shown that FNS and a core version of HEIV are essentially equivalent, solving a common underlying equation via different means. The analysis is driven by the search for a non-degenerate form of a certain generalised eigen-value problem, and effectively leads to a new derivation of the relevant case of the HEIV algorithm. This work may be seen as an extension of previous efforts to rationalise and inter-relate a spectrum of estimators, including the renormalisation method of Kanatani and the normalised eight-point method of Hartley.Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, Darren Gawle

On the fitting of surfaces to data with covariances

Copyright © 2000 IEEEWe consider the problem of estimating parameters of a model described by an equation of special form. Specific models arise in the analysis of a wide class of computer vision problems, including conic fitting and estimation of the fundamental matrix. We assume that noisy data are accompanied by (known) covariance matrices characterizing the uncertainty of the measurements. A cost function is first obtained by considering a maximum-likelihood formulation and applying certain necessary approximations that render the problem tractable. A Newton-like iterative scheme is then generated for determining a minimizer of the cost function. Unlike alternative approaches such as Sampson's method or the renormalization technique, the new scheme has as its theoretical limit the minimizer of the cost function. Furthermore, the scheme is simply expressed, efficient, and unsurpassed as a general technique in our testing. An important feature of the method is that it can serve as a basis for conducting theoretical comparison of various estimation approaches.Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel and Darren Gawle

From FNS to HEIV: A link between two vision parameter estimation methods

Copyright © 2004 IEEEProblems requiring accurate determination of parameters from imagebased quantities arise often in computer vision. Two recent, independently developed frameworks for estimating such parameters are the FNS and HEIV schemes. Here, it is shown that FNS and a core version of HEIV are essentially equivalent, solving a common underlying equation via different means. The analysis is driven by the search for a nondegenerate form of a certain generalized eigenvalue problem and effectively leads to a new derivation of the relevant case of the HEIV algorithm. This work may be seen as an extension of previous efforts to rationalize and interrelate a spectrum of estimators, including the renormalization method of Kanatani and the normalized eight-point method of Hartley.Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, and Darren Gawle

What value covariance information in estimating vision parameters?

©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Many parameter estimation methods used in computer vision are able to utilise covariance information describing the uncertainty of data measurements. This paper considers the value of this information to the estimation process when applied to measured image point locations. Covariance matrices are first described and a procedure is then outlined whereby covariances may be associated with image features located via a measurement process. An empirical study is made of the conditions under which covariance information enables generation of improved parameter estimates. Also explored is the extent to which the noise should be anisotropic and inhomogeneous if improvements are to be obtained over covariance-free methods. Critical in this is the devising of synthetic experiments under which noise conditions can be precisely controlled. Given that covariance information is, in itself, subject to estimation error tests are also undertaken to determine the impact of imprecise covariance information upon the quality of parameter estimates. Finally, an experiment is carried out to assess the value of covariances in estimating the fundamental matrix from real imagesBrooks, M.J. Chojnacki, W. Gawley, D. van den Hengel, A

Revisiting Hartley's normalized eight-point algorithm

Copyright © 2003 IEEEHartley's eight-point algorithm has maintained an important place in computer vision, notably as a means of providing an initial value of the fundamental matrix for use in iterative estimation methods. In this paper, a novel explanation is given for the improvement in performance of the eight-point algorithm that results from using normalized data. It is first established that the normalized algorithm acts to minimize a specific cost function. It is then shown that this cost function I!; statistically better founded than the cost function associated with the nonnormalized algorithm. This augments the original argument that improved performance is due to the better conditioning of a pivotal matrix. Experimental results are given that support the adopted approach. This work continues a wider effort to place a variety of estimation techniques within a coherent framework.Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel and Darren Gawle