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To enhance enrollment into randomized clinical trials (RCTs), we proposed electronic health record-based clinical decision support for patient–clinician shared decision-making about care and RCT enrollment, based on “mathematical equipoise.”
As an example, we created the Knee Osteoarthritis Mathematical Equipoise Tool (KOMET) to determine the presence of patient-specific equipoise between treatments for the choice between total knee replacement (TKR) and nonsurgical treatment of advanced knee osteoarthritis.
With input from patients and clinicians about important pain and physical function treatment outcomes, we created a database from non-RCT sources of knee osteoarthritis outcomes. We then developed multivariable linear regression models that predict 1-year individual-patient knee pain and physical function outcomes for TKR and for nonsurgical treatment. These predictions allowed detecting mathematical equipoise between these two options for patients eligible for TKR. Decision support software was developed to graphically illustrate, for a given patient, the degree of overlap of pain and functional outcomes between the treatments and was pilot tested for usability, responsiveness, and as support for shared decision-making.
The KOMET predictive regression model for knee pain had four patient-specific variables, and an r2 value of 0.32, and the model for physical functioning included six patient-specific variables, and an r2 of 0.34. These models were incorporated into prototype KOMET decision support software and pilot tested in clinics, and were generally well received.
Use of predictive models and mathematical equipoise may help discern patient-specific equipoise to support shared decision-making for selecting between alternative treatments and considering enrollment into an RCT.
Trigeminal neuralgia (TN) associated with multiple sclerosis (MS) was first described in Lehrbuch der Nervenkrankheiten für Ärzte und Studirende in 1894 by Hermann Oppenheim, including a pathologic description of trigeminal root entry zone demyelination. Early English-language translations in 1900 and 1904 did not so explicitly state this association compared with the German editions. The 1911 English-language translation described a more direct association. Other later descriptions were clinical with few pathologic reports, often referencing Oppenheim but citing the 1905 German or 1911 English editions of Lehrbuch. This discrepancy in part may be due to the translation differences of the original text.
Campylobacter spp. is a commonly reported food-borne disease with major consequences for morbidity. In conjunction with predicted increases in temperature, proliferation in the survival of microorganisms in hotter environments is expected. This is likely to lead, in turn, to an increase in contamination of food and water and a rise in numbers of cases of infectious gastroenteritis. This study assessed the relationship of Campylobacter spp. with temperature and heatwaves, in Adelaide, South Australia.
We estimated the effect of (i) maximum temperature and (ii) heatwaves on daily Campylobacter cases during the warm seasons (1 October to 31 March) from 1990 to 2012 using Poisson regression models.
There was no evidence of a substantive effect of maximum temperature per 1 °C rise (incidence rate ratio (IRR) 0·995, 95% confidence interval (95% CI) 0·993–0·997) nor heatwaves (IRR 0·906, 95% CI 0·800–1·026) on Campylobacter cases. In relation to heatwave intensity, which is the daily maximum temperature during a heatwave, notifications decreased by 19% within a temperature range of 39–40·9 °C (IRR 0·811, 95% CI 0·692–0·952). We found little evidence of an increase in risk and lack of association between Campylobacter cases and temperature or heatwaves in the warm seasons. Heatwave intensity may play a role in that notifications decreased with higher temperatures. Further examination of the role of behavioural and environmental factors in an effort to reduce the risk of increased Campylobacter cases is warranted.
Bartonellae are blood- and vector-borne Gram-negative bacteria, recognized as emerging pathogens. Whole-blood samples were collected from 58 free-ranging lions (Panthera leo) in South Africa and 17 cheetahs (Acinonyx jubatus) from Namibia. Blood samples were also collected from 11 cheetahs (more than once for some of them) at the San Diego Wildlife Safari Park. Bacteria were isolated from the blood of three (5%) lions, one (6%) Namibian cheetah and eight (73%) cheetahs from California. The lion Bartonella isolates were identified as B. henselae (two isolates) and B. koehlerae subsp. koehlerae. The Namibian cheetah strain was close but distinct from isolates from North American wild felids and clustered between B. henselae and B. koehlerae. It should be considered as a new subspecies of B. koehlerae. All the Californian semi-captive cheetah isolates were different from B. henselae or B. koehlerae subsp. koehlerae and from the Namibian cheetah isolate. They were also distinct from the strains isolated from Californian mountain lions (Felis concolor) and clustered with strains of B. koehlerae subsp. bothieri isolated from free-ranging bobcats (Lynx rufus) in California. Therefore, it is likely that these captive cheetahs became infected by an indigenous strain for which bobcats are the natural reservoir.
Changing trends in foodborne disease are influenced by many factors, including temperature. Globally and in Australia, warmer ambient temperatures are projected to rise if climate change continues. Salmonella spp. are a temperature-sensitive pathogen and rising temperature can have a substantial effect on disease burden affecting human health. We examined the relationship between temperature and Salmonella spp. and serotype notifications in Adelaide, Australia. Time-series Poisson regression models were fit to estimate the effect of temperature during warmer months on Salmonella spp. and serotype cases notified from 1990 to 2012. Long-term trends, seasonality, autocorrelation and lagged effects were included in the statistical models. Daily Salmonella spp. counts increased by 1·3% [incidence rate ratio (IRR) 1·013, 95% confidence interval (CI) 1·008–1·019] per 1 °C rise in temperature in the warm season with greater increases observed in specific serotype and phage-type cases ranging from 3·4% (IRR 1·034, 95% CI 1·008–1·061) to 4·4% (IRR 1·044, 95% CI 1·024–1·064). We observed increased cases of S. Typhimurium PT9 and S. Typhimurium PT108 notifications above a threshold of 39 °C. This study has identified the impact of warm season temperature on different Salmonella spp. strains and confirms higher temperature has a greater effect on phage-type notifications. The findings will contribute targeted information for public health policy interventions, including food safety programmes during warmer weather.
To assess the impact of Bordetella pertussis infections in South Australia during an epidemic and determine vulnerable populations, data from notification reports for pertussis cases occurring between July 2008 and December 2009 were reviewed to determine the distribution of disease according to specific risk factors and examine associations with hospitalizations. Although the majority (66%) of the 6230 notifications for pertussis occurred in adults aged >24 years, the highest notification and hospitalization rate occurred in infants aged <1 year. For these infants, factors associated with hospitalization included being aged <2 months [relative risk (RR) 2·3, 95% confidence interval (CI) 1·60–3·32], Indigenous ethnicity (RR 1·7, 95% CI 1·03–2·83) and receiving fewer than two doses of pertussis vaccine (RR 4·1, 95% CI 1·37–12·11). A combination of strategies aimed at improving direct protection for newborns, vaccination for the elderly, and reducing transmission from close contacts of infants are required for prevention of severe pertussis disease.
Binary brown dwarfs are important because their dynamical masses can be determined in a model-independent way. If a main sequence star is also involved, the age and metallicity for the system can be determined, making it possible to break the sub-stellar mass-age degeneracy. The most suitable benchmark system for intermediate age T dwarfs is ε Indi Ba,b, two T dwarfs (spectral types T1 and T6; McCaughrean et al. (2004)) orbiting a K4.5V star, ε Indi A, at a projected separation of 1460AU. At a distance of 3.6224pc (HIPPARCOS distance to ε Indi A; van Leeuwen (2007)), these are the closest brown dwarfs to the Earth, and thus both components are bright and the system is well-resolved. The system has been monitored astrometrically with NACO and FORS2 on the VLT since June 2004 and August 2005, respectively, in order to determine the system and individual masses independent of evolutionary models. We have obtained a preliminary system mass of 121±1MJup. We have also analysed optical/near-IR spectra (0.6-5.0μm at a resolution up to R~5000; King et al. (2009)) allowing us to determine bolometric luminosities, compare and calibrate evolutionary and atmospheric models of T dwarfs at an age of 4-8Gyr.
Infections due to Salmonella enteritidis are increasing worldwide. In the United States, between 1985 and 1989. 78% of the S. enteritidis outbreaks in which a food vehicle was identified implicated a food containing raw or lightly cooked shell eggs.
Under a US Department of Agriculture regulation published in 1990, eggs implicated in human food-borne S. enteritidis outbreaks were traced back to the source flock. The flock environment and the internal organs of a sample of hens were tested for S. enteritidis. We compared the S. enteritidis phage types of isolates from 18 human, egg-associated outbreaks and the 15 flocks implicated through traceback of these outbreaks. The predominant human outbreak phage type was recovered from the environment in 100% of implicated flocks and from the internal organs of hens in 88% of implicated flocks we tested. The results support the use of phage typing as a tool to identify flocks involved in human S. enteritidis outbreaks.
The pathophysiology of global ischemia and reperfusion
Brian J. O'Neil, Department of Emergency Medicine, William Beaumont Hospital, Royal Oak, MI, USA,
Raymond C. Koehler, Department of Anesthesiology, Johns Hopkins University, Baltimore, MD, USA,
Robert W. Neumar, Department of Emergency Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA,
Uwe Ebmeyer, Klinik für Anaesthesiologie und Intensivtherapie, Otto-von-Guericke Universität, Magdeburg, Germany,
Gary S. Krause, Department of Emergency Medicine, Wayne State University, Detroit, MI, USA
Sudden, unexpected death claims nearly 1000 lives each day in the United States and is the fifth leading cause of all deaths in the western world. Cardiac arrest occurs over 300 000 times per year both in the United States and Europe with the risk for persons 35 years and older estimated at 1 per 1000. In those patients resuscitated from cardiac arrest, nearly 60% die from a neurological cause. Despite every effort, only 3%–10% of all resuscitated patients are able to resume their former lifestyles.
To date, there are no clinically effective pharmacologic tools for amelioration of brain damage by ischemia and reperfusion. Clinical trials conducted more than a decade ago utilizing postresuscitation treatment with barbiturates or calcium antagonists were disappointing. More recently, clinical treatment of stroke with a radical scavenger (trilazad), intercellular adhesion molecule-1 antagonist (Enlimomab), glutamate receptor antagonist (Aptiganel, gavestinel), glutamate release inhibitor (Lubeluzole), ganglioside administration (GM1), calcium channel blockade, or upregulation of the GABA receptor (Clomethiazole) were all found ineffective. This suggests that our understanding of the mechanisms involved in damage and repair in neurons remains incomplete and further therapeutic progress will require the delineation of the primary mechanisms involved in neuronal injury and repair.
Although the picture is still incomplete, a few things are clear.
The majority of damage occurs not during ischemia but during reperfusion. Nevertheless, the two processes work sequentially to increase neuronal damage (i.e., lipolysis during ischemia potentiates the radicalmediated peroxidation of polyunsaturated fatty acids (PUFAs) during reperfusion).
Manipulations that draw attention to extensional or set-based considerations are neither sufficient nor necessary for enhanced use of base rates in intuitive judgments. Frequency formats are only one part of the puzzle of base-rate use and neglect. The conditions under which these and other manipulations promote base-rate use may be more parsimoniously organized under the broader notion of case-based judgment.
In this chapter, we explore a classic problem in psychology: How do individuals draw on their previous experience in an uncertain environment to make a prediction or diagnosis on the basis of a set of informational cues? Intuitive predictions based on multiple cues are often highly sensitive to environmental contingencies yet at the same time often exhibit pronounced and consistent biases.
Our research has focused on judgments of the probability of an outcome based on binary cues (e.g., present/absent), in which the diagnostic value of those cues has been learned from direct experience in an uncertain environment. For example, in medical diagnosis, we might predict which disease a patient has based on a symptom that a patient does or does not exhibit. We have developed a model that captures both the strengths and weaknesses of intuitive judgments of this kind (the Evidential Support Accumulation Model, ESAM; Koehler, White, & Grondin, 2003). The model assumes that the frequency with which each cue is observed to have co-occurred with the outcome variable of interest is stored. The perceived diagnostic value of each cue, based on these frequencies, is calculated in a normatively appropriate fashion and integrated with the prior probability of the outcome to arrive at a final probability judgment for a given outcome.
ESAM is designed to account for people's behavior in uncertain environments created in the lab that are, effectively by definition, sampled without bias.
we accept sunstein's claim that people often use moral heuristics to make judgments and decisions. however, in situations that include a risk of betrayal, we disagree with sunstein about when the relevant moral heuristic may be said to “misfire.” we suggest that the moral heuristic people apply to avoid the possibility of safety-product betrayal may be reasonable.
The Very Large Telescope (VLT) Observatory on Cerro Paranal (2635
m) in Northern Chile is approaching completion. After the four 8-m
Unit Telescopes (UT) individually saw first light in the last years,
two of them were combined for the first time on October 30, 2001 to
form a stellar interferometer, the VLT Interferometer. The remaining
two UTs will be integrated into the interferometric array later this
year, so that any two UTs can be used for interferometry. In this
article, we will describe the subsystems of the VLTI and the planning
for the following years.
Both laypeople and experts are often called upon to evaluate the probability of uncertain events such as the outcome of a trial, the result of a medical operation, the success of a business venture, or the winner of a football game. Such assessments play an important role in deciding, respectively, whether to go to court, undergo surgery, invest in the venture, or bet on the home team. Uncertainty is usually expressed in verbal terms (e.g., unlikely or probable), but numeric estimates are also common. Weather forecasters, for example, often report the probability of rain (Murphy, 1985), and economists are sometimes required to estimate the chances of recession (Zarnowitz, 1985). The theoretical and practical significance of subjective probability has inspired psychologists, philosophers, and statisticians to investigate this notion from both descriptive and prescriptive standpoints.
Indeed, the question of whether degree of belief can, or should be, represented by the calculus of chance has been the focus of a long and lively debate. In contrast to the Bayesian school, which represents degree of belief by an additive probability measure, there are many skeptics who question the possibility and the wisdom of quantifying subjective uncertainty and are reluctant to apply the laws of chance to the analysis of belief. Besides the Bayesians and the skeptics, there is a growing literature on what might be called revisionist models of subjective probability.
A great deal of psychological research has addressed the nature and quality of people's intuitive judgments of likelihood. Much of this work has sought to characterize the simple mental operations, often termed heuristics, that govern people's assessments of probabilities and frequencies. The heuristics initially identified by Daniel Kahneman and Amos Tversky – availability, representativeness, and anchoring, among others – describe and explain many phenomena in judgment under uncertainty. These heuristics have been particularly helpful in identifying conditions under which people closely conform to, or radically deviate from, the requirements of probability theory.
Support theory, a formal descriptive account of subjective probability introduced by Tversky and Koehler (1994), offers the opportunity to weave together the different heuristics into a unified account. The theory can accommodate many mechanisms (such as the various heuristics) that influence subjective probability, but integrates them via the construct of support. Consequently, support theory can account for numerous existing empirical patterns in the literature on judgment under uncertainty.
The original works describing the major heuristics underlying likelihood judgments are presented in Kahneman, Slovic, and Tversky (1982). Previous chapters of this book contain selections from the initial statements of support theory that invoke several heuristics to account for various properties of support. Our goal in this chapter is twofold: to summarize recent developments in support theory, and to suggest some possible directions for future research.
The study of how people use subjective probabilities is a remarkably modern concern, and was largely motivated by the increasing use of expert judgment during and after World War II (Cooke, 1991). Experts are often asked to quantify the likelihood of events such as a stock market collapse, a nuclear plant accident, or a presidential election (Ayton, 1992; Baron, 1998; Hammond, 1996). For applications such as these, it is essential to know how the probabilities experts attach to various outcomes match the relative frequencies of those outcomes; that is, whether experts are properly “calibrated.” Despite this, relatively few studies have evaluated how well descriptive theories of probabilistic reasoning capture the behavior of experts in their natural environment. In this chapter, we examine the calibration of expert probabilistic predictions “in the wild” and assess how well the heuristics and biases perspective on judgment under uncertainty can account for the findings. We then review alternate theories of calibration in light of the expert data.
Calibration and Miscalibration
Miscalibration presents itself in a number of forms. Figure 39.1 displays four typical patterns of miscalibrated probability judgments. The solid diagonal line, identity line, or line of perfect calibration, indicates the set of points at which judged probability and relative frequency coincide. The solid line marked A, where all judgments are higher than the corresponding relative frequency, represents overprediction bias. The solid line B, where all judgments are lower than the corresponding relative frequency, represents underprediction bias.
Aneuploidy is a crucial issue in human reproductive biology, accounting for both a significant
proportion of miscarriages and, among liveborns, multiple congenital malformation syndromes such
as Down Syndrome. Although the etiology of human aneuploidy remains poorly understood, recent
studies have elucidated certain fundamental correlates of meiotic nondisjunction, such as altered
recombination. These features are extraordinarily similar to those associated with chromosome
misbehavior in Drosophila melanogaster females. Furthermore, these organisms also share a
significant level of achiasmate chromosome nondisjunction. Here we describe in detail the processes
of achiasmate chromosome segregation in Drosophila and discuss how they may be most effectively
applied to our understanding of the etiology of human aneuploidy. In particular, we examine the
possibility that similar “backup” mechanisms of chromosome segregation might function in
mammalian meiosis, particularly mammalian females. Drawing upon observations made in flies, we
also propose a new model for the segregation of achiasmate chromosomes in humans.
I agree with Gibbs that the message of the base
rate literature reads differently depending on which null hypothesis
is used to frame the issue. But I argue that the normative null
hypothesis, H0: “People use base rates in a
Bayesian manner,” is no longer appropriate. I also challenge
Adler's distinction between unused and ignored base
rates, and criticize Goodie's reluctance to shift
research attention to the field. Macchi's arguments
about textual ambiguities in traditional base rate problems suggest
that empirical testing is needed to tease apart the effects of problem
clarification and problem framing. Macdonald's,
Fletcher's and Snow's skepticism about
the value of Bayesian methods in real world judgment tasks is treated
as a challenge for the next generation of empirical base rate