The Cost-Effectiveness of Tibial Metaphyseal Cones in Revision Total Knee Arthroplasty.

BACKGROUND: The purpose of this study is to evaluate the cost-effectiveness of tibial cones in revision total knee arthroplasty. METHODS: A Markov model was used for cost-effectiveness analysis. The average cone price was obtained from Orthopedic Network News. The average cone aseptic loosening rate was determined by literature review. Hospitalization costs and baseline re-revision rates were calculated using the PearlDiver Database. RESULTS: The maximum cost-effective cone price varied from $3514 at age 40 to $648 at age 90, compared to the current average selling price of $4201. Cones became cost-effective with baseline aseptic loosening rates of 0.89% annually at age 40 to 4.38% annually at age 90, compared to the current average baseline loosening rate of 0.76% annually. CONCLUSION: For the average patient, tibial cones are not cost-effective, but may become so at lower prices, in younger patients, or in patients at substantially increased risk of aseptic loosening.

Resource utilization and cost effectiveness of treating acute promyelocytic leukaemia using generic arsenic trioxide.

Arsenic trioxide (ATO)-based regimens are the standard of care for treating acute promyelocytic leukaemia (APL) and have replaced chemotherapy-based approaches. However, the cost of "patented" ATO is prohibitive because of patent rights. "Generic" ATO has been used in a few countries, but its implications for health resource utilization (HRU) and cost of treatment are unknown. We hypothesized that treating APL patients using generic ATO (APL-ATO) will be cost effective compared to the chemotherapy-based regimen (APL-CT). In a single-centre retrospective study, we used a bottom-up costing method to compare the direct medical cost of treatment and HRU between APL-ATO and APL-CT. These costs and the survival and relapse probabilities were imputed in a three-state Markov decision model to estimate the cost effectiveness of APL-ATO compared to APL-CT. The mean cost of treatment for APL-ATO (n = 30, $8500 ± 2078) was significantly less than for APL-CT (n = 30, $22 600 ± 5528) (P < 0·001). APL-ATO reduced hospitalization, antibiotic and antifungal usage (P < 0·001). In the Markov model, five-year treatment costs were significantly lower for APL-ATO ($11 131) than for APL-CT ($17 926) (P < 0·001). Treatment cost and health resource utilization were significantly lower for generic ATO-treated APL patients compared to the chemotherapy-based regimen.

A Markov approach for increasing precision in the assessment of data-intensive behavioral interventions.

Health interventions using real-time sensing technology are characterized by intensive longitudinal data, which has the potential to enable nuanced evaluations of individuals' responses to treatment. Existing analytic tools were not developed to capitalize on this opportunity as they typically focus on first-order findings such as changes in the level and/or slope of outcome variables over different intervention phases. This paper introduces an exploratory, Markov-based empirical transition method that offers a more comprehensive assessment of behavioral responses when intensive longitudinal data are available. The procedure projects a univariate time-series into discrete states and empirically determines the probability of transitioning from one state to another. State transition probabilities are summarized separately in phase-specific transition matrices. Comparing transition matrices illuminates intricate, quantifiable differences in behavior between intervention phases. Statistical significance is estimated via bootstrapping techniques. This paper introduces the methodology via three case studies from a secondhand smoke reduction trial utilizing real-time air particle sensors. Analysis enabled the identification of complex phenomena such as avoidance and escape behavior in response to punitive contingencies for tobacco use. Additionally, the largest changes in behavior dynamics were associated with the introduction of behavioral feedback. The Markov approach's ability to elucidate subtle behavioral details has not typically been feasible with standard methodologies, mainly due to historical limitations associated with infrequent repeated measures. These results suggest that the evaluation of intervention effects in data-intensive single-case designs can be enhanced, providing rich information that can ultimately be used to develop interventions uniquely tailored to specific individuals.

Chronic Ampakine Treatments Stimulate Dendritic Growth and Promote Learning in Middle-Aged Rats.

Positive allosteric modulators of AMPA-type glutamate receptors (ampakines) have been shown to rescue synaptic plasticity and reduce neuropathology in rodent models of cognitive disorders. Here we tested whether chronic ampakine treatment offsets age-related dendritic retraction in middle-aged (MA) rats. Starting at 10 months of age, rats were housed in an enriched environment and given daily treatment with a short half-life ampakine or vehicle for 3 months. Dendritic branching and spine measures were collected from 3D reconstructions of Lucifer yellow-filled CA1 pyramidal cells. There was a substantial loss of secondary branches, relative to enriched 2.5-month-old rats, in apical and basal dendritic fields of vehicle-treated, but not ampakine-treated, 13-month-old rats. Baseline synaptic responses in CA1 were only subtly different between the two MA groups, but long-term potentiation was greater in ampakine-treated rats. Unsupervised learning of a complex environment was used to assess treatment effects on behavior. Vehicle- and drug-treated rats behaved similarly during a first 30 min session in the novel environment but differed markedly on subsequent measures of long-term memory. Markov sequence analysis uncovered a clear increase in the predictability of serial movements between behavioral sessions 2 and 3 in the ampakine, but not vehicle, group. These results show that a surprising degree of dendritic retraction occurs by middle age and that this can be mostly offset by pharmacological treatments without evidence for unwanted side effects. The functional consequences of rescue were prominent with regard to memory but also extended to self-organization of behavior. SIGNIFICANCE STATEMENT: Brain aging is characterized by a progressive loss of dendritic arbors and the emergence of impairments to learning-related synaptic plasticity. The present studies show that dendritic losses are evident by middle age despite housing in an enriched environment and can be mostly reversed by long-term, oral administration of a positive allosteric modulator of AMPA-type glutamate receptors. Dendritic recovery was accompanied by improvements to both synaptic plasticity and the encoding of long-term memory of a novel, complex environment. Because the short half-life compound had no evident negative effects, the results suggest a plausible strategy for treating age-related neuronal deterioration.

Costs and benefits of automatization in category learning of ill-defined rules.

Learning ill-defined categories (such as the structure of Medin & Schaffer, 1978) involves multiple learning systems and different corresponding category representations, which are difficult to detect. Application of latent Markov analysis allows detection and investigation of such multiple latent category representations in a statistically robust way, isolating low performers and quantifying shifts between latent strategies. We reanalyzed data from three experiments presented in Johansen and Palmeri (2002), which comprised prolonged training of ill-defined categories, with the aim of studying the changing interactions between underlying learning systems. Our results broadly confirm the original conclusion that, in most participants, learning involved a shift from a rule-based to an exemplar-based strategy. Separate analyses of latent strategies revealed that (a) shifts from a rule-based to an exemplar-based strategy resulted in an initial decrease of speed and an increase of accuracy; (b) exemplar-based strategies followed a power law of learning, indicating automatization once an exemplar-based strategy was used; (c) rule-based strategies changed from using pure rules to rules-plus-exceptions, which appeared as a dual processes as indicated by the accuracy and response-time profiles. Results suggest an additional pathway of learning ill-defined categories, namely involving a shift from a simple rule to a complex rule after which this complex rule is automatized as an exemplar-based strategy.

Financial Sustainability of Neuromodulation for Pain.

When considering the financial sustainability of neuromodulation for pain, one needs to consider the varying costs involved with this therapy. These include comparisons between different types of neuromodulation, comparisons between neuromodulation and conventional therapy, and comparisons between neuromodulation and other invasive modalities. In addition, any consideration of cost also needs to take quality into account. Even if a therapy is expensive, it can be considered cost-effective if it leads to significant increase in quality of life and economic productivity of the patient. This review considers these questions, methodologies used to assess them, and variations between different health delivery systems.

Blocking NK1 receptors disrupts the sequential and temporal organization of chain grooming in rats.

The basal ganglia are a group of sub-cortical structures believed to play a critical role in action selection and sequencing. The striatum is the largest input structure of the basal ganglia and contains the neuropeptide substance P in abundance. Recent computational work has suggested that substance P could play a critical role in action sequence performance and acquisition, but this has not been tested experimentally before. The aim of the present study was to test how blocking substance P's main NK1-type receptors affected the sequential and temporal organization of spontaneous behavioral patterns. We did this in rats by focusing on the grooming chain, an innate and highly stereotyped ordered sequence. We performed an open field experiment in which the NK1 receptor antagonist L-733,060 was injected intraperitoneally in rats at two doses (2 and 4 mg/kg/ml), in a within-subject counterbalanced design. We used first order transition probabilities, Variable Length Markov Models, entropy metrics and T-pattern analysis to evaluate the effects of L-733,060 on sequential and temporal aspects of spontaneously ordered behavioral sequences. Our results suggest that blocking NK1 receptors made the transitions between the grooming chain elements significantly more variable, the transition structure of the grooming bouts simpler, and it increased the probability of transitioning from active to inactive states. Overall, this suggest that blocking substance P receptors led to a general break down in the fluency of spontaneous behavioral sequences, suggesting that substance P could be playing a key role in the implementation of sequential patterns.

Reliability modelling of redundant safety systems without automatic diagnostics incorporating common cause failures and process demand.

Redundant safety systems are commonly used in the process industry to respond to hazardous events. In redundant systems composed of identical units, Common Cause Failures (CCFs) can significantly influence system performance with regards to reliability and safety. However, their impact has been overlooked due to the inherent complexity of modelling common cause induced failures. This article develops a reliability model for a redundant safety system using Markov analysis approach. The proposed model incorporates process demands in conjunction with CCF for the first time and evaluates their impacts on the reliability quantification of safety systems without automatic diagnostics. The reliability of the Markov model is quantified by considering the Probability of Failure on Demand (PFD) as a measure for low demand systems. The safety performance of the model is analysed using Hazardous Event Frequency (HEF) to evaluate the frequency of entering a hazardous state that will lead to an accident if the situation is not controlled. The utilisation of Markov model for a simple case study of a pressure protection system is demonstrated and it is shown that the proposed approach gives a sufficiently accurate result for all demand rates, durations, component failure rates and corresponding repair rates for low demand mode of operation. The Markov model proposed in this paper assumes the absence of automatic diagnostics, along with multiple stage repair strategy for CCFs and restoration of the system from hazardous state to the "as good as new" state.

Statistical properties of sleep-wake behavior in the rat and their relation to circadian and ultradian phases.

STUDY OBJECTIVES: To examine the statistical characteristics of short-term sleep-wake architecture and to evaluate their dependence on ultradian and circadian phase. DESIGN: Observational, time series. SETTING: Laboratory. PARTICIPANTS: Ten male adult Sprague-Dawley rats. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: States of wakefulness (WAKE), rapid eye movement sleep (REM) and nonrapid eye movement sleep (NREM) were recorded in 5-sec epochs over 7 consecutive days. State bout durations were analyzed using parametric regression of survival curves, comparing exponential, biexponential, and power law models. WAKE survival curves were best fit by biexponential models, suggesting that there are two statistically distinct stochastic mechanisms generating two types of WAKE--"brief" WAKE and "long" WAKE. Exponential time constants varied as a function of circadian and ultradian phase, with "long" WAKE showing the largest effect. NREM survival curves exhibited biexponential and monoexponential distributions in light and dark, respectively, with weak effects of ultradian phase. REM survival curves approximated a monoexponential distribution that varied with circadian but not ultradian phase. χ(2) analysis was used in a three-state Markov model to evaluate whether conditional state transition probabilities exhibit the property of first-order dependence. This was partially confirmed, but only after accounting for heterogeneity associated with circadian and ultradian phase. However, there was evidence of residual second-order dependence indicating that additional sources of statistical heterogeneity may remain to be identified. CONCLUSIONS: Sleep-wake state is regulated over short timescales by stochastic mechanisms. When the major sources of heterogeneity are taken into account, including two-component WAKE and NREM states, the sleep-wake system of the rat behaves, to a reasonable approximation, as a Markovian system that is modulated over ultradian and circadian timescales.