Maximum recovery after knee replacement - the MARKER study rationale and protocol

Background There is little scientific evidence to support the usual practice of providing outpatient rehabilitation to patients undergoing total knee replacement surgery (TKR) immediately after discharge from the orthopaedic ward. It is hypothesised that the lack of clinical benefit is due to the low exercise intensity tolerated at this time, with patients still recovering from the effects of major orthopaedic surgery. The aim of the proposed clinical trial is to investigate the clinical and cost effectiveness of a novel rehabilitation strategy, consisting of an initial home exercise programme followed, approximately six weeks later, by higher intensity outpatient exercise classes. Methods/Design In this multicentre randomised controlled trial, 600 patients undergoing primary TKR will be recruited at the orthopaedic pre-admission clinic of 10 large public and private hospitals in Australia. There will be no change to the medical or rehabilitative care usually provided while the participant is admitted to the orthopaedic ward. After TKR, but prior to discharge from the orthopaedic ward, participants will be randomised to either the novel rehabilitation strategy or usual rehabilitative care as provided by the hospital or recommended by the orthopaedic surgeon. Outcomes assessments will be conducted at baseline (pre-admission clinic) and at 6 weeks, 6 months and 12 months following randomisation. The primary outcomes will be self-reported knee pain and physical function. Secondary outcomes include quality of life and objective measures of physical performance. Health economic data (health sector and community service utilisation, loss of productivity) will be recorded prospectively by participants in a patient diary. This patient cohort will also be followed-up annually for five years for knee pain, physical function and the need or actual incidence of further joint replacement surgery. Discussion The results of this pragmatic clinical trial can be directly implemented into clinical practice. If beneficial, the novel rehabilitation strategy of utilising outpatient exercise classes during a later rehabilitation phase would provide a feasible and potentially cost-effective intervention to optimise the physical well-being of the large number of people undergoing TKR.

Generalized binomial Tau-leap method for biochemical kinetics incorporating both delay and intrinsic noise

The delay stochastic simulation algorithm (DSSA) by Barrio et al. [Plos Comput. Biol.2, 117–E (2006)] was developed to simulate delayed processes in cell biology in the presence of intrinsic noise, that is, when there are small-to-moderate numbers of certain key molecules present in a chemical reaction system. These delayed processes can faithfully represent complex interactions and mechanisms that imply a number of spatiotemporal processes often not explicitly modeled such as transcription and translation, basic in the modeling of cell signaling pathways. However, for systems with widely varying reaction rate constants or large numbers of molecules, the simulation time steps of both the stochastic simulation algorithm (SSA) and the DSSA can become very small causing considerable computational overheads. In order to overcome the limit of small step sizes, various τ-leap strategies have been suggested for improving computational performance of the SSA. In this paper, we present a binomial τ- DSSA method that extends the τ-leap idea to the delay setting and avoids drawing insufficient numbers of reactions, a common shortcoming of existing binomial τ-leap methods that becomes evident when dealing with complex chemical interactions. The resulting inaccuracies are most evident in the delayed case, even when considering reaction products as potential reactants within the same time step in which they are produced. Moreover, we extend the framework to account for multicellular systems with different degrees of intercellular communication. We apply these ideas to two important genetic regulatory models, namely, the hes1 gene, implicated as a molecular clock, and a Her1/Her 7 model for coupled oscillating cells.

Modeling intrinsic noise and delays in chemical kinetics of coupled autoregulated oscillating cells

Delays are an important feature in temporal models of genetic regulation due to slow biochemical processes, such as transcription and translation. In this paper, we show how to model intrinsic noise effects in a delayed setting by either using a delay stochastic simulation algorithm (DSSA) or, for larger and more complex systems, a generalized Binomial τ-leap method (Bτ-DSSA). As a particular application, we apply these ideas to modeling somite segmentation in zebra fish across a number of cells in which two linked oscillatory genes (her1 and her7) are synchronized via Notch signaling between the cells.