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Non-typhoidal Salmonella (NTS) serovars, sequences types and antimicrobial susceptibility profiles have specific associations with animal and human infections in Vietnam. Antimicrobial resistance may have an effect on the manifestation of human NTS infections, with isolates from asymptomatic individuals being more susceptible to antimicrobials than those associated with animals and human diarrhoea.
Infants with prenatally diagnosed CHD are at high risk for adverse outcomes owing to multiple physiologic and psychosocial factors. Lack of immediate physical postnatal contact because of rapid initiation of medical therapy impairs maternal–infant bonding. On the basis of expected physiology, maternal–infant bonding may be safe for select cardiac diagnoses.
This is a single-centre study to assess safety of maternal–infant bonding in prenatal CHD.
In total, 157 fetuses with prenatally diagnosed CHD were reviewed. On the basis of cardiac diagnosis, 91 fetuses (58%) were prenatally approved for bonding and successfully bonded, 38 fetuses (24%) were prenatally approved but deemed not suitable for bonding at delivery, and 28 (18%) were not prenatally approved to bond. There were no complications attributable to bonding. Those who successfully bonded were larger in weight (3.26 versus 2.6 kg, p<0.001) and at later gestation (39 versus 38 weeks, p<0.001). Those unsuccessful at bonding were more likely to have been delivered via Caesarean section (74 versus 49%, p=0.011) and have additional non-cardiac diagnoses (53 versus 29%, p=0.014). There was no significant difference regarding the need for cardiac intervention before hospital discharge. Infants who bonded had shorter hospital (7 versus 26 days, p=0.02) and ICU lengths of stay (5 versus 23 days, p=0.002) and higher survival (98 versus 76%, p<0.001).
Fetal echocardiography combined with a structured bonding programme can permit mothers and infants with select types of CHD to successfully bond before ICU admission and intervention.
We present an interesting and rare case of traumatic Gerbode ventricular septal defect and complete heart block. The multimodality images illustrate the diagnosis well. This case is an excellent demonstration of the diagnostic utility of multimodality imaging.
Fontan survivors have depressed cardiac index that worsens over time. Serum biomarker measurement is minimally invasive, rapid, widely available, and may be useful for serial monitoring. The purpose of this study was to identify biomarkers that correlate with lower cardiac index in Fontan patients.
Methods and results
This study was a multi-centre case series assessing the correlations between biomarkers and cardiac magnetic resonance-derived cardiac index in Fontan patients ⩾6 years of age with biochemical and haematopoietic biomarkers obtained ±12 months from cardiac magnetic resonance. Medical history and biomarker values were obtained by chart review. Spearman’s Rank correlation assessed associations between biomarker z-scores and cardiac index. Biomarkers with significant correlations had receiver operating characteristic curves and area under the curve estimated. In total, 97 cardiac magnetic resonances in 87 patients met inclusion criteria: median age at cardiac magnetic resonance was 15 (6–33) years. Significant correlations were found between cardiac index and total alkaline phosphatase (−0.26, p=0.04), estimated creatinine clearance (0.26, p=0.02), and mean corpuscular volume (−0.32, p<0.01). Area under the curve for the three individual biomarkers was 0.63–0.69. Area under the curve for the three-biomarker panel was 0.75. Comparison of cardiac index above and below the receiver operating characteristic curve-identified cut-off points revealed significant differences for each biomarker (p<0.01) and for the composite panel [median cardiac index for higher-risk group=2.17 L/minute/m2 versus lower-risk group=2.96 L/minute/m2, (p<0.01)].
Higher total alkaline phosphatase and mean corpuscular volume as well as lower estimated creatinine clearance identify Fontan patients with lower cardiac index. Using biomarkers to monitor haemodynamics and organ-specific effects warrants prospective investigation.
This short piece highlights a current spurt in queer researcher–practitioners doing practice as research (PaR) in higher education and explores potential reasons why PaR is so vital, appealing, useful and strategic for queer research. As a starting point, we offer the idea of messiness and messing things up as a way of describing the methods of PaR. Queer mess is to do with asserting the value and pleasure of formations of knowledge that sit outside long-standing institutional hierarchies of research. The latter places what Robin Nelson calls ‘hard knowledge’ above tacit, quotidian, haptic and embodied knowledge. The methodological and philosophical impulses of PaR make space for a range of research methods inherently bound up with the researcher as an individual and the materiality of lived experience within research. Yet, in our experience, although each PaR project is individual, PaR projects follow certain shared modes evolving largely from embodied and heuristic research methods adapted from social sciences, such as (auto)ethnography, participant observation, phenomenology and action research. PaR methodology in theatre and performance is composed of a bricolage of these openly embodied methods, which makes PaR, as an embodied resistance to sanitary boundaries, somewhat queer in academic terms already. It is unsurprising, then, that PaR is so attractive to queer practitioner–researchers bent on queering normative hierarchies of knowledge.
Between 1270 and 1870 Britain slowly progressed from the periphery of the European economy to centre-stage of an integrated world economy. In the process it escaped from Malthusian constraints and by the eighteenth century had successfully reconciled rising population with rising living standards. This final chapter reflects upon this protracted but profound economic transformation from the perspective of the national income estimates assembled in Part I and analysed in Part II of this book. Because Britain’s economic rise did not unfold in isolation, account is taken of the broader comparative context provided by the national income reconstructions now available for several other Eurasian countries: Spain from 1282, Italy from 1310 and Holland from 1348, plus Japan from 725, China from 980 and India from 1600. All are output-based estimates but have been derived via a range of alternative approaches according to the nature of the available historical evidence. Several make ingenious use of real wage rates and urbanisation ratios (Malanima, 2011; Álvarez-Nogal and Prados de la Escosura, 2013), two economic indicators often used as surrogates for estimates of GDP per head. Only the GDP estimates for Holland, like these for Britain, have been made the hard way, by summing the weighted value-added outputs of the agricultural, industrial and service sectors and then dividing the results by estimates of total population obtained by reconciling time-series and cross-sectional demographic data. Methodologically, the British and Dutch national income estimates are therefore the most directly comparable. Each is free from overdependence upon any single or narrow range of data series and, instead, they encapsulate variations in the wide range of economic indicators, appropriately weighted in line with their importance in overall economic activity, from which they have been reconstructed.
Agriculture was for long the single largest component of the English and British economies, both in terms of its share of employment and the value of its output. The latter was a function of the amount of land under cultivation, the uses to which it was put, the productivities of crops and animals and their respective prices. The main purpose of this chapter is to describe the methods used to derive the areas under arable and grass and, in particular, the total sown acreage. The crops produced and animals stocked are the subjects of the following chapter. Along the way, it will be demonstrated that claims that the peak arable area in the medieval period may have exceeded 20 million acres (Clark, 2007a: 124) are unrealistic, since, on the best available evidence, the combined total under field crops and fallow could not have been more than 12.75 million acres. In the absence of significant food imports, this limited both the population that could be supported and the supply of kilocalories per head needed for survival. It also shaped the production choices made by agricultural producers.
Comprehensive national agricultural statistics were collected annually from 1866 and provide the starting point for calculating the acreages of arable and grass (Anon, 1968; Coppock, 1984). Together with the tithe files, which provide a precise but incomplete guide to the share of land in each county devoted to arable production during the 1830s (Kain, 1986; Overton, 1986), they are used to provide a nineteenth-century benchmark. The chapter proceeds as follows. After a discussion of the potential agricultural area of England in Section 2.2, Section 2.3 reviews the arable acreage by county from the tithe files of the 1830s and from the agricultural statistics of 1871. Section 2.4 then examines changes in land use between 1290 and 1871, while Section 2.5 presents county-level estimates of the arable acreage in 1290. Section 2.6 provides a further cross-check by examining changes in land use between 1086 and 1290. Finally, Section 2.7 provides estimates of land use for a number of benchmark years between 1270 and 1871.
Economic growth can be either extensive or intensive. Extensive growth arises where more output is produced in line with a growing population but living standards remain constant, while intensive growth arises where more output is produced by each person. In the former case, there is no economic development, as the economy simply reproduces itself on a larger scale: in the latter, living standards rise as the economy goes through a process of economic development. To understand the long-run growth of the British economy reaching back to the thirteenth century therefore requires knowledge of the trajectories followed by both population and GDP. Of particular interest is whether periods of intensive growth, distinguished by rising GDP per head, were accompanied by expanding or contracting population. For it is one thing for living standards to rise during a period of population decline, such as that induced by the recurrent plagues of the second half of the fourteenth century, when survivors found themselves able to add the land and capital of those who had perished to their own stocks, but quite another for living standards and population to rise together, particularly given the emphasis of Malthus  on diminishing returns. Indeed, Kuznets (1966: 34–85) identified simultaneous growth of population and income per head (i.e. the concurrence of intensive and extensive growth) as one of the key features that distinguished modern from pre-industrial economic growth.
Chapter 6 has argued that workers responded to changes in real wage rates by adapting how hard they worked so as to maintain their earnings. Household incomes therefore tracked GDP per head rather than real wage rates and progressively improved over time, doubling between the early fourteenth and late seventeenth centuries and doubling again over the course of the industrial revolution. Higher incomes translated into changing patterns of consumption and the forms these consumption choices took are the subjects of this chapter. Section 7.2 reconstructs the kilocalorie value and composition of diets based on the agricultural-output estimates presented in Chapter 3, augmented by information on imported foodstuffs. Given that populations require an average daily food intake per head of 2,000 kilocalories (Livi-Bacci, 1991: 27) to provide sufficient nourishment for both economic and biological reproduction, these calculations also provide a useful cross-check on the consistency of the agricultural-output and population estimates. Section 7.3 then considers non-food consumption drawing upon early modern evidence of material culture as revealed by probate inventories. Again, these trends need to be consistent with those of industrial output reconstructed in Chapter 4.
Price, habit, fashion and status all shaped the budgetary decisions taken by households. Demand for food was inelastic up to the point where basic subsistence needs had been met, but as incomes rose there were clear trade-offs to be obtained between increasing consumption of cheap sources of kilocalories such as pottage, potatoes and salted herrings on the one hand, or indulging in more expensive refined bread, quality ale and beer, dairy produce and meat, plus the imported luxuries of wine, sugar, tea, cocoa and tobacco, on the other. In effect, higher incomes allowed more households to trade up to a respectability basket of foodstuffs providing a more varied and processed diet but not necessarily more kilocalories. The changing relative prices of arable, livestock and luxury products influenced these consumption decisions, while the relative cheapness or dearness of food determined how much disposable income could be devoted to the increasingly varied and tempting array of non-food consumer goods (Figure 5.02).
Income distribution in England between 1270 and 1870, as elsewhere in Western Europe, was profoundly unequal due to entrenched inequalities in access to the land, capital, education and political power upon which personal wealth depended. Gender, rank and servility and their differential legal rights were determined at birth. Privilege, patronage and position ensured that rent-seeking was rife, while warfare created opportunities for ransom and plunder to the enrichment of those in command and impoverishment of the vanquished. Everywhere, as a result, there were rich men in their castles and poor men at their gates. Moreover, as van Zanden (1995) and Milanovic and others (2007) have demonstrated, the effect of economic growth was to magnify rather than mitigate these inequalities and widen the income gap between those at the top and bottom of the social pyramid.
The rich became richer as average wealth grew because the more wealth there was the greater the opportunities for those with power and privilege to enrich themselves at the expense of the weak and disadvantaged majority. In Holland one legacy of the prosperity achieved during the Dutch Golden Age was a greatly increased inequality of incomes, which was more marked in towns than rural villages and greatest of all in major cities (van Zanden, 1995). In England, similarly, Milanovic and others (2007) claim that inequality rose with average incomes between 1688 and 1801/03, thereby confirming Kuznets’ (1955) observation that income inequality typically increased during the early stages of economic growth and only declined relatively late in the modernisation process. Prior to 1870, therefore, increasing inequality can be treated, like urbanisation, as a characteristic and unavoidable manifestation of economic growth.
This chapter provides annual estimates of output in agriculture, which was the largest sector of the economy during the middle ages, and continued to play an important role throughout the period under consideration. The approach builds on the study of Overton and Campbell (1996), which tracked long-run trends in agricultural output and labour productivity, but was restricted to estimates for a small number of benchmark years. To provide annual estimates, heavy reliance has been made on three datasets assembled for the late-medieval, early modern and modern periods. For the period c.1250 to c.1500, a Medieval Accounts Database has been assembled by Campbell (2000, 2007), drawing upon the archival labours of a number of other historians, including David Farmer, John Langdon and Jan Titow. The information on arable yields and animal stocking densities is taken largely from manorial accounts, but is supplemented by information on the non-manorial sector from tithes. For the period c.1550 to c.1750, an Early Modern Probate Inventories Database has been assembled by Overton, which provides animal stocking densities and indirect estimates of arable yields from the valuation of the assets left by farmers (Overton and others, 2004). From the early eighteenth century, use is made of the Modern Farm Accounts Database assembled by Turner, Beckett and Afton (2001).
The chapter proceeds as follows. Section 3.2 provides a brief introduction to the main data sources for the three periods. Estimates of output for the arable sector are then given in Section 3.3, followed by estimates of livestock-sector output in Section 3.4. The arable and livestock outputs are combined in Section 3.5 to provide estimates of overall agricultural output, while Section 3.6 concludes.