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Cognition refers to a set of mental actions or processes by which we create, use or store knowledge. We can conceptualise a global measure of overall cognitive ability, however, it is possible to distinguish a range of individual components or core cognitive domains. This is informative as cognitive disorders often selectively affect some functions, while sparing others. As well as providing diagnostic help, cognitive assessment can be valuable in monitoring progression or improvement of a disorder. It is particularly powerful used in combination with information from clinical interview and measurement of biomarkers (e.g., through brain imaging, or CSF examination).
English law reports between 1550 and 1650 seem far more accessible today than the “year books” that preceded them. This is not because they were produced differently, for a different readership or by a different kind of reporter, but because the legal system itself had changed. We also encounter in the Tudor period the first reports written by eminent lawyers, two of whom (Plowden and Coke) saw a selection of them through the press in their lifetimes. Recent editorial work on the better reports has revealed something of the way they were compiled, and also of what was omitted when contemporary notes were turned into printed volumes.
Coke's reports are the most famous, traditionally cited simply as The Reports. Work has just begun on an edition of the underlying notebooks (first discovered just forty years ago), which will probably require at least six volumes. Coke's reporting style was controversial, and his alleged subjectivity was seized upon by Francis Bacon as one of the grounds for bringing him down in 1616. However, Bacon's scheme of 1617 to engage professional reporters, paid by the crown, seems to have collapsed after a few years. Law reporting was thus to remain a matter of private initiative until the end of the eighteenth century, and many of the best reports – even those written by judges – have still not been published. Anyone seeking to trace the evolution of a legal doctrine or practice before about 1700 must regard manuscript reports as an essential recourse.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
Predicting recurrent Clostridium difficile infection (rCDI) remains difficult. METHODS. We employed a retrospective cohort design. Granular electronic medical record (EMR) data had been collected from patients hospitalized at 21 Kaiser Permanente Northern California hospitals. The derivation dataset (2007–2013) included data from 9,386 patients who experienced incident CDI (iCDI) and 1,311 who experienced their first CDI recurrences (rCDI). The validation dataset (2014) included data from 1,865 patients who experienced incident CDI and 144 who experienced rCDI. Using multiple techniques, including machine learning, we evaluated more than 150 potential predictors. Our final analyses evaluated 3 models with varying degrees of complexity and 1 previously published model.
Despite having a large multicenter cohort and access to granular EMR data (eg, vital signs, and laboratory test results), none of the models discriminated well (c statistics, 0.591–0.605), had good calibration, or had good explanatory power.
Our ability to predict rCDI remains limited. Given currently available EMR technology, improvements in prediction will require incorporating new variables because currently available data elements lack adequate explanatory power.