Designing and evaluating complex interventions to improve health care

Complex interventions are “built up from a number of components, which may act both independently and interdependently.”1 2 Many health service activities should be considered as complex. Evaluating complex interventions can pose a considerable challenge and requires a substantial investment of time. Unless the trials illuminate processes and mechanisms they often fail to provide useful information. If the result is negative, we are left wondering whether the intervention is inherently ineffective (either because the intervention was inadequately developed or because all similar interventions are ineffective), whether it was inadequately applied or applied in an inappropriate context, or whether the trial used an inappropriate design, comparison groups or outcomes. If there is a positive effect, it can be hard to judge how the results of the trial might be applied to a different context (box 1)

Role of International Medical Graduates in Kentucky Medicine: Implications For Workforce Planning and Medical Education

An argument for International Medical Graduates (IMGs) as part of a state’s physician workforce is that they “fill the gap” created by the shortage of United States Medical Graduates (USMGs) required to meet the demand for physician services, especially primary care physicians in rural areas. The purpose of this study is to examine the overall impact of IMGs on Kentucky’s physician workforce and determine whether they overcome the shortage of USMGs. Information from the Kentucky Board of Medical Licensure (KBML) was used to examine the distribution and practice patterns of IMGs and USMGs. IMGs are similar to USMGs in terms of gender, age, and average hours worked. IMGs were not any more likely than USMGs to practice in a primary care specialty. They were more likely to practice in a rural county and a county with a critical access hospital. In conclusion, IMGs do not completely “fill the gap” in physician shortages in most Kentucky counties. More programs to attract and retain physicians should be developed, especially in rural areas. Additional residency programs at regional medical centers is one recommendation to accomplish this

Autoimmune-autoinflammatory rheumatoid arthritis overlaps: a rare but potentially important subgroup of diseases

At the population level, rheumatoid arthritis (RA) is generally viewed as autoimmune in nature with a small subgroup of cases having a palindromic form or systemic autoinflammatory disorder (SAID) phenotype. Herein, we describe resistant cases of classical autoantibody associated RA that had clinical, genetic and therapeutic responses indicative of coexistent autoinflammatory disease. Five patients with clinically overlapping features between RA and SAID including polysynovitis and autoantibody/shared epitope positivity, and who had abrupt severe self-limiting attacks including fevers and serositis, are described. Mutations or single nucleotide polymorphisms in recognised autoinflammatory pathways were evident. Generally, these cases responded poorly to conventional Disease-modifying anti-rheumatic drugs (DMARD) treatment with some excellent responses to colchicine or interleukin 1 pathway blockade. A subgroup of RA cases have a mixed autoimmune-autoinflammatory phenotype and genotype with therapeutic implications

State-Dependent Architecture of Thalamic Reticular Subnetworks

Behavioral state is known to influence interactions between thalamus and cortex, which are important for sensation, action, and cognition. The thalamic reticular nucleus (TRN) is hypothesized to regulate thalamo-cortical interactions, but the underlying functional architecture of this process and its state dependence are unknown. By combining the first TRN ensemble recording with psychophysics and connectivity-based optogenetic tagging, we found reticular circuits to be composed of distinct subnetworks. While activity of limbic-projecting TRN neurons positively correlates with arousal, sensory-projecting neurons participate in spindles and show elevated synchrony by slow waves during sleep. Sensory-projecting neurons are suppressed by attentional states, demonstrating that their gating of thalamo-cortical interactions is matched to behavioral state. Bidirectional manipulation of attentional performance was achieved through subnetwork-specific optogenetic stimulation. Together, our findings provide evidence for differential inhibition of thalamic nuclei across brain states, where the TRN separately controls external sensory and internal limbic processing facilitating normal cognitive function.National Institute of Neurological Disorders and Stroke (U.S.) (NIH Pathway to Independence Career Award K99 NS 078115)Brain & Behavior Research Foundation (Young Investigator Award)National Institutes of Health (U.S.) ( Transformative R01 Award TR01-GM10498)National Institutes of Health (U.S.) (Grant R01-MH061976

Pseudospin SU(2) Symmetry Breaking, Charge Density Wave and Superconductivity in the Hubbard Model

In this paper, we discuss physical consequences of pseudospin SU(2) symmetry breaking in the negative-U Hubbard model at half-filling. If pseudospin symmetry is spontaneously broken while its unique subgroup U(1) remains invariant, it will lead to the charge density wave (CDW) ground state. Furthermore, if the U(1) symmetry is also broken, the ground state will have the off-diagonal long range order (ODLRO), signaling a superconductor. In this case, CDW and superconductivity coexist to form a supersolid. Finally, we show that CDW suppresses, but does not destroy superconductivity.Comment: 7 page

Assessing Neuronal Interactions of Cell Assemblies during General Anesthesia

Understanding the way in which groups of cortical neurons change their individual and mutual firing activity during the induction of general anesthesia may improve the safe usage of many anesthetic agents. Assessing neuronal interactions within cell assemblies during anesthesia may be useful for understanding the neural mechanisms of general anesthesia. Here, a point process generalized linear model (PPGLM) was applied to infer the functional connectivity of neuronal ensembles during both baseline and anesthesia, in which neuronal firing rates and network connectivity might change dramatically. A hierarchical Bayesian modeling approach combined with a variational Bayes (VB) algorithm is used for statistical inference. The effectiveness of our approach is evaluated with synthetic spike train data drawn from small and medium-size networks (consisting of up to 200 neurons), which are simulated using biophysical voltage-gated conductance models. We further apply the analysis to experimental spike train data recorded from rats' barrel cortex during both active behavior and isoflurane anesthesia conditions. Our results suggest that that neuronal interactions of both putative excitatory and inhibitory connections are reduced after the induction of isoflurane anesthesia.National Institutes of Health (U.S.) (NIH Grants DP1-OD003646

A PK–PD model of ketamine-induced high-frequency oscillations

Objective. Ketamine is a widely used drug with clinical and research applications, and also known to be used as a recreational drug. Ketamine produces conspicuous changes in the electrocorticographic (ECoG) signals observed both in humans and rodents. In rodents, the intracranial ECoG displays a high-frequency oscillation (HFO) which power is modulated nonlinearly by ketamine dose. Despite the widespread use of ketamine there is no model description of the relationship between the pharmacokinetic–pharmacodynamics (PK–PDs) of ketamine and the observed HFO power. Approach. In the present study, we developed a PK–PD model based on estimated ketamine concentration, its known pharmacological actions, and observed ECoG effects. The main pharmacological action of ketamine is antagonism of the NMDA receptor (NMDAR), which in rodents is accompanied by an HFO observed in the ECoG. At high doses, however, ketamine also acts at non-NMDAR sites, produces loss of consciousness, and the transient disappearance of the HFO. We propose a two-compartment PK model that represents the concentration of ketamine, and a PD model based in opposing effects of the NMDAR and non-NMDAR actions on the HFO power. Main results. We recorded ECoG from the cortex of rats after two doses of ketamine, and extracted the HFO power from the ECoG spectrograms. We fit the PK–PD model to the time course of the HFO power, and showed that the model reproduces the dose-dependent profile of the HFO power. The model provides good fits even in the presence of high variability in HFO power across animals. As expected, the model does not provide good fits to the HFO power after dosing the pure NMDAR antagonist MK-801. Significance. Our study provides a simple model to relate the observed electrophysiological effects of ketamine to its actions at the molecular level at different concentrations. This will improve the study of ketamine and rodent models of schizophrenia to better understand the wide and divergent range of effects that ketamine has.National Institutes of Health (U.S.) (Pioneer Award DP1-OD003646)Burroughs Wellcome Fund (Career Award at the Scientific Interface)National Institutes of Health (U.S.) (Grant 5R01MH061976)National Institutes of Health (U.S.) (New Innovator Award DP2-OD006454

Anderson-Yuval approach to the multichannel Kondo problem

We analyze the structure of the perturbation expansion of the general multichannel Kondo model with channel anisotropic exchange couplings and in the presence of an external magnetic field, generalizing to this case the Anderson-Yuval technique. For two channels, we are able to map the Kondo model onto a generalized resonant level model. Limiting cases in which the equivalent resonant level model is solvable are identified. The solution correctly captures the properties of the two channel Kondo model, and also allows an analytic description of the cross-over from the non Fermi liquid to the Fermi liquid behavior caused by the channel anisotropy.Comment: 23 pages, ReVTeX, 4 figures av. on reques

Discerning Applicants\u27 Interests in Rural Medicine: A Textual Analysis of Admission Essays

BACKGROUND: Despite efforts to construct targeted medical school admission processes using applicant-level correlates of future practice location, accurately gauging applicants\u27 interests in rural medicine remains an imperfect science. This study explores the usefulness of textual analysis to identify rural-oriented themes and values underlying applicants\u27 open-ended responses to admission essays. METHODS: The study population consisted of 75 applicants to the Rural Physician Leadership Program (RPLP) at the University of Kentucky College of Medicine. Using WordStat, a proprietary text analysis program, applicants\u27 American Medical College Application Service personal statement and an admission essay written at the time of interview were searched for predefined keywords and phrases reflecting rural medical values. From these text searches, derived scores were then examined relative to interviewers\u27 subjective ratings of applicants\u27 overall acceptability for admission to the RPLP program and likelihood of practicing in a rural area. RESULTS: The two interviewer-assigned ratings of likelihood of rural practice and overall acceptability were significantly related. A statistically significant relationship was also found between the rural medical values scores and estimated likelihood of rural practice. However, there was no association between rural medical values scores and subjective ratings of applicant acceptability. CONCLUSIONS: That applicants\u27 rural values in admission essays were not related to interviewers\u27 overall acceptability ratings indicates that other factors played a role in the interviewers\u27 assessments of applicants\u27 acceptability for admission

Classification and Stability of Phases of the Multicomponent One-Dimensional Electron Gas

The classification of the ground-state phases of complex one-dimensional electronic systems is considered in the context of a fixed-point strategy. Examples are multichain Hubbard models, the Kondo-Heisenberg model, and the one-dimensional electron gas in an active environment. It is shown that, in order to characterize the low-energy physics, it is necessary to analyze the perturbative stability of the possible fixed points, to identify all discrete broken symmetries, and to specify the quantum numbers and elementary wave vectors of the gapless excitations. Many previously-proposed exotic phases of multichain Hubbard models are shown to be unstable because of the ``spin-gap proximity effect.'' A useful tool in this analysis is a new generalization of Luttinger's theorem, which shows that there is a gapless even-charge mode in any incommensurate N-component system.Comment: 15 pages revtex. Final version as publishe