Serial hemodynamic measurements were performed in 13 women on two occasions before conception and then at monthly intervals throughout pregnancy. Cardiac output (CO) was measured by Doppler and cross-sectional echocardiography at the aortic, pulmonary, and mitral valves. Cardiac chamber size and ventricular function were investigated by M-mode echocardiography. CO increased from a mean of 4.88 l/min before the conception to a maximum of 7.21 l/min at 32 wk, the increase being significant by 5 wk after the last menstrual period. Heart rate and left ventricular performance increased during the first trimester. Heart rate increased further during the second trimester, during which left atrial and left ventricular end-diastolic dimensions increased, suggesting an increase in venous return. Derived values of total peripheral vascular resistance fell during the first 20 wk. These changes were associated with a progressive increase in valve orifice area and left ventricular wall thickness during pregnancy.

The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The biochemical data are intrinsically stochastic and tend to be observed by means of discrete-time sampling systems, which are often limited in their completeness. In this paper we explore how to make Bayesian inference for the kinetic rate constants of regulatory networks, using the stochastic kinetic Lotka-Volterra system as a model. This simple model describes behaviour typical of many biochemical networks which exhibit auto-regulatory behaviour. Various MCMC algorithms are described and their performance evaluated in several data-poor scenarios. An algorithm based on an approximating process is shown to be particularly efficient.

Objectives-To test the validity and reliability of scales for measuring patients' experiences of and satisfaction with nursing care; to test the ability of the scales to detect differences between hospitals and wards; and to investigate whether place of completion, hospital, or home influences response. Design-Sample survey. Setting-20 wards in five hospitals in the north east of England. Patients-2078 patients in general medical and surgical wards. Main measures-Experiences of and satisfaction with nursing care. Results-75% of patients approached to complete the questionnaires did so. Construct validity and internal consistency were both satisfactory. Both the experience and satisfaction scales were found to detect differences between randomly selected wards and hospitals. A sample of patients (102) were sent a further questionnaire to complete at home. 73% returned this; no significant differences were found in either experience or satisfaction scores between questionnaires given in hospital or at home. Conclusion-Scales to measure patients' experiences of and satisfaction with nursing in acute care have been developed and found to be valid, reliable, and able to detect differences between hospitals and wards. Questionnaires can be given before patients leave hospital or at home without affecting scores, but those given at home have a lower response rate.

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Serial measurements ofcardiac output and mean arterial pressure were performed in 15 women during the first stage of labour and at one and 24 hours after delivery. Cardiac output was measured by Doppler and cross sectional echocardiography at the pulmonary valve. Basal cardiac output (between uterine contractions) increased from a prelabour mean of 6-99 V/min to 7-88 V/min at >s8 cm of cervical dilatation as a result of an increase in stroke volume. Over the same period basal mean arterial pressure also increased. During uterine contractions there was a further increase in cardiac output as a result of increases in both stroke volume and heart rate. The increment in cardiac output during contractions became progressively greater as labour advanced. At s8 cm of dilatation cardiac output increased from a basal mean of 7 88 l/min to 10-57 /min during contractions. There were also further increases in mean blood pressure during contractions. One hour after delivery heart rate and cardiac output had returned to prelabour values, though mean arterial pressure and stroke volume remained raised. By 24 hours after delivery all haemodynamic variables had returned to prelabour values.Haemodynamic changes of the magnitude found in this series are of considerable clinical relevance in managing mothers with complicated cardiovascular function.

Thirty-eight healthy women undergoing elective Caesarean section under spinal anaesthesia at term were allocated randomly to receive boluses of either phenylephrine 100 micrograms or ephedrine 5 mg for maintenance of maternal arterial pressure. The indication for administration of vasopressor was a reduction in systolic pressure to < or = 90% of baseline values. Maternal arterial pressure (BP) and heart rate (HR) were measured every minute by automated oscillometry. Cardiac output (CO) was measured by cross-sectional and Doppler echocardiography before and after preloading with 1500 ml Ringer lactate solution and then every 2 min after administration of bupivacaine. Umbilical artery pulsatility index (PI) was measured using Doppler before and after spinal anaesthesia. The median (range) number of boluses of phenylephrine and ephedrine was similar; 6 (1-10) vs 4 (1-8) respectively. Maternal systolic BP and CO changes were similar in both groups, but the mean [95% CI] maximum percentage change in maternal HR was larger in the phenylephrine group (-28.5 [-24.2, -32.9]%) than in the ephedrine group (-14.4 [-10.6, -18.2]%). As a consequence atropine was required in 11/19 women in the phenylephrine group compared with 2/19 in the ephedrine group (P < 0.01). Mean umbilical artery pH [95% CI] was higher in the phenylephrine group (7.29 [7.28-7.30]) than in the ephedrine group (7.27 [7.25-7.28]). The results of the present study support the use of phenylephrine for maintenance of maternal arterial pressure during spinal anaesthesia for elective Caesarean section.

In recent years there has been a rapid growth in the amount of DNA being sequenced and in its availability through genetic databases. Statistical techniques which identify structure within these sequences can be of considerable assistance to molecular biologists particularly when they incorporate the discrete nature of changes caused by evolutionary processes. This paper focuses on the detection of homogeneous segments within heterogeneous DNA sequences. In particular, we study an intron from the chimpanzee -fetoprotein gene; this protein plays an important role in the embryonic development of mammals. We present a Bayesian solution to this segmentation problem using a hidden Markov model implemented by Markov chain Monte Carlo methods. We consider the important practical problem of specifying informative prior knowledge about sequences of this type. Two Gibbs sampling algorithms are contrasted and the sensitivity of the analysis to the prior speci®cation is investigated. Model selection and possible ways to overcome the label switching problem are also addressed. Our analysis of intron 7 identi®es three distinct homogeneous segment types, two of which occur in more than one region, and one of which is reversible.

We consider the task of generating discrete-time realisations of a nonlinear multivariate diffusion process satisfying an Itô stochastic differential equation conditional on an observation taken at a fixed future time-point. Such realisations are typically termed diffusion bridges. Since, in general, no closed form expression exists for the transition densities of the process of interest, a widely adopted solution works with the Euler-Maruyama approximation, by replacing the intractable transition densities with Gaussian approximations. However, the density of the conditioned discrete-time process remains intractable, necessitating the use of computationally intensive methods such as Markov chain Monte Carlo. Designing an efficient proposal mechanism which can be applied to a noisy and partially observed system that exhibits nonlinear dynamics is a challenging problem, and is the focus of this paper. By partitioning the process into two parts, one that accounts for nonlinear dynamics in a deterministic way, and another as a residual stochastic process, we develop a class of novel constructs that bridge the residual process via a linear approximation. In addition, we adapt a recently proposed construct to a partial and noisy observation regime. We compare the performance of each new construct with a number of existing approaches, using three applications.