Gabapentin Add-on for Drug-Resistant Partial Epilepsy.

Gabapentin add-on for drug-resistant partial epilepsy.

Cochrane Database Syst Rev. 2013 Jul 25; 7: CD001415
Al-Bachari S, Pulman J, Hutton JL, Marson AG

The majority of people with epilepsy have a good prognosis and their seizures are well controlled by a single antiepileptic drug, but up to 30% develop drug-resistant epilepsy, especially those with partial seizures. In this review we summarise the current evidence regarding the antiepileptic drug gabapentin, when used as an add-on treatment for drug-resistant partial epilepsy.To evaluate the efficacy and tolerability of gabapentin when used as an add-on treatment for people with drug-resistant partial epilepsy.This is an updated version of the original Cochrane review published in The Cochrane Library 2009, Issue 4. We searched the Cochrane Epilepsy Group’s Specialised Register (14 May 2013), the Cochrane Central Register of Controlled Trials (CENTRAL 2013, Issue 4, The Cochrane Library) (April 2013) and MEDLINE (1946 to 14 May 2013). We imposed no language restrictions.Randomised, placebo-controlled, double-blind, add-on trials of gabapentin in people with drug-resistant partial epilepsy. Trials using an active drug control group or which compared doses of gabapentin were also included in the review.Two review authors independently selected trials for inclusion and extracted the relevant data. We assessed the following outcomes: (a) seizure frequency and seizure freedom; (b) treatment withdrawal (any reason); (c) adverse effects. Primary analyses were intention-to-treat. We also undertook sensitivity best and worst-case analyses. We estimated summary risk ratios for each outcome and evaluated dose-response in regression models.Eleven trials were included representing 2125 randomised participants. We combined data from six trials in meta-analyses of 1206 randomised participants. The overall risk ratio (RR) for 50% or greater reduction in seizure frequency compared to placebo was 1.89 (95% confidence interval (CI) 1.40 to 2.55). Dose regression analysis (for trials in adults) shows increasing efficacy with increasing dose, with 25.3% (19.3 to 32.3) of people responding to 1800 mg of gabapentin compared to 9.7% on placebo, a 15.5% increase in response rate (8.5 to 22.5). The RR for treatment withdrawal compared to placebo was 1.05 (95% CI 0.74 to 1.49). Adverse effects were significantly associated with gabapentin compared to placebo. Risk ratios were as follows: ataxia 2.01 (99% CI 0.98 to 4.11), dizziness 2.43 (99% CI 1.44 to 4.12), fatigue 1.95 (99% CI 0.99 to 3.82) and somnolence 1.93 (99% CI 1.22 to 3.06). No significant differences were found for the adverse effects of headache (RR 0.79, 99% CI 0.46 to 1.35) or nausea (RR 0.95, 99% CI 0.52 to 1.73). Overall the studies together are rated as low/unclear risk of bias due to information on each risk of bias domain not being available.Gabapentin has efficacy as an add-on treatment in people with drug-resistant partial epilepsy. However, the trials reviewed were of relatively short duration and provide no evidence for the long-term efficacy of gabapentin beyond a three-month period. The results cannot be extrapolated to monotherapy or to people with other epilepsy types. HubMed – drug

Monitoring of lipids, enzymes, and creatine kinase in patients on lipid-lowering drug therapy.

Curr Cardiol Rep. 2013 Sep; 15(9): 397
Wiklund O, Pirazzi C, Romeo S

A number of plasma lipid parameters have been used to estimate cardiovascular risk and to be targets for treatment to reduce risk. Most risk algorithms are based on total cholesterol (T-C) or low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), and most intervention trials have targeted the LDL-C levels. Emerging measures, which in some cases may be better for risk calculation and as alternative treatment targets, are apolipoprotein B and non-HDL-C. Other lipid measures that may contribute in risk analysis are triglycerides (TG), lipoprotein(a), and lipoprotein-associated phospholipase A2. The primary treatment target in cardiovascular prevention is LDL-C, and potential alternative targets are apoB and non-HDL-C. In selected individuals at high cardiovascular (CV) risk, TG should be targeted, but HDL-C, Lp(a), and ratios such as LDL-C/HDL-C or apoB/apoAI are not recommended as treatment targets. Lipids should be monitored during titration to targets. Thereafter, lipids should be checked at least once a year or more frequently to improve treatment adherence if indicated. Monitoring of muscle and liver enzymes should be done before the start of treatment. In stable conditions during treatment, the focus should be on clinical symptoms that may alert muscle or liver complications. Routine measurement of CK or ALT is not necessary during treatment with statins. HubMed – drug

Epigenetic Mechanisms and Non-coding RNAs in Osteoarthritis.

Curr Rheumatol Rep. 2013 Sep; 15(9): 353
Barter MJ, Young DA

Osteoarthritis (OA) is a disease typified by the loss of cartilage, the normal integrity of which is maintained by the resident cell, the chondrocyte. Alterations in chondrocyte gene expression with age, injury, loading or predisposing genetics, underpin OA cartilage loss. Cell- and tissue-specific gene expression is determined by epigenetic mechanisms, including DNA methylation, chromatin modifications and non-coding RNAs, including microRNAs and long-non-coding RNAs. A number of epigenetic changes have been identified between OA and normal cartilage, and the enzymes which impart the epigenetic code are increasingly seen as important players in a number of pathologies, including OA. Here, we will describe current and potential new epigenetic studies that are likely to reveal novel aspects of chondrocyte and cartilage biology and potentially help sub-characterise OA phenotypes. Importantly, many of these epigenetic modifiers or non-coding RNAs are proposed drug targets and could represent a therapeutic opportunity for this currently untreatable disease. HubMed – drug

Molecular design and evaluation of biodegradable polymers using a statistical approach.

J Mater Sci Mater Med. 2013 Jul 26;
Lewitus DY, Rios F, Rojas R, Kohn J

The challenging paradigm of bioresorbable polymers, whether in drug delivery or tissue engineering, states that a fine-tuning of the interplay between polymer properties (e.g., thermal, degradation), and the degree of cell/tissue replacement and remodeling is required. In this paper we describe how changes in the molecular architecture of a series of terpolymers allow for the design of polymers with varying glass transition temperatures and degradation rates. The effect of each component in the terpolymers is quantified via design of experiment (DoE) analysis. A linear relationship between terpolymer components and resulting Tg (ranging from 34 to 86 °C) was demonstrated. These findings were further supported with mass-per-flexible-bond analysis. The effect of terpolymer composition on the in vitro degradation of these polymers revealed molecular weight loss ranging from 20 to 60 % within the first 24 h. DoE modeling further illustrated the linear (but reciprocal) relationship between structure elements and degradation for these polymers. Thus, we describe a simple technique to provide insight into the structure property relationship of degradable polymers, specifically applied using a new family of tyrosine-derived polycarbonates, allowing for optimal design of materials for specific applications. HubMed – drug