Monitoring salivary lamotrigine concentrations

Lamotrigine concentrations were measured simultaneously (as far as was feasible) in stimulated and unstimulated saliva samples, and in plasma, from seven adult volunteers over a 32 h period following a single 50 mg dose of the drug, and in 20 children and adolescents during the course of routine antiepileptic therapy. In individuals there was a close correlation between the measurements at least 2 It after ingestion of the drug. Concentrations in stimulated and unstimulated saliva were similar; the stimulation produced little change in the saliva secretion rate. The saliva-to-plasma concentration ratio increased linearly by 0.78% for each 1 mg/L plasma lamotrigine concentration, with a mean value of 48.8% at a plasma lamotrigine concentration of 10 mg/L. With appropriate precautions as to the timing of saliva collections, and a single plasma lamotrigine concentration measurement to calibrate the salivary values in the individual, salivary lamotrigine concentration measurement appears to be a practicable approach to therapeutic drug monitoring. This has significant implications for the elucidation of the pharmacokinetics of lamotrigine in the paediatric population.

High-precision TIMS U-series and AMS C-14 dating of a coral reef lagoon sediment core from southern South China Sea

Accurate dating of lagoon sediments has been a difficult problem, although lagoon profiles, usually with high deposition rates, have a great potential for high-resolution climate reconstruction. We report 26 high-precision TIMS U-series dates (on 25 coral branches) and five AMS C-14 dates (on foraminifera) for a 15.4-m long lagoon core from Yongshu Reef, Nansha area, southern South China Sea. All the dates are in the correct stratigraphical sequence, providing the best chronology so far reported for lagoon deposits. The results reveal a similar to 4000-a continuous depositional history, with sedimentation rates varying from 0.8 to 24.6 mm a(-1), with an average of 3.85 mm a(-1), which corresponds to an average net carbonate accumulation rate of similar to 2700 g CaCO3 m(-2) a(-1), significantly higher than the mean value (800 +/- 400 g CaCO3 m(-2) a(-1)) used for lagoons in general in previous studies of global carbonate budget. Episodes of accelerated depositions within the last 1000 years correlate well with strong storm events identified by U-series dates of storm-transported coral blocks in the area. However, in the longer term, the sedimentation rates during the past 1000 years were much higher than earlier on, probably due to more vigorous wave-reef interaction as a result of relative sea-level fall since 500 AD and expansion of reef flat area, supplying more sediments. The coral TIMS U-series ages and foraminifera AMS 14C dates reveal intriguing apparent radiocarbon reservoir ages (R) from 572 to 1052 years, which are much higher than global mean values of similar to 400 years. (c) 2006 Elsevier Ltd. All rights reserved.

The prognostic value of a nomogram for exercise capacity in women

BACKGROUND: Recent studies have demonstrated that exercise capacity is an independent predictor of mortality in women. Normative values of exercise capacity for age in women have not been well established. Our objectives were to construct a nomogram to permit determination of predicted exercise capacity for age in women and to assess the predictive value of the nomogram with respect to survival. METHODS: A total of 5721 asymptomatic women underwent a symptom-limited, maximal stress test. Exercise capacity was measured in metabolic equivalents (MET). Linear regression was used to estimate the mean MET achieved for age. A nomogram was established to allow the percentage of predicted exercise capacity to be estimated on the basis of age and the exercise capacity achieved. The nomogram was then used to determine the percentage of predicted exercise capacity for both the original cohort and a referral population of 4471 women with cardiovascular symptoms who underwent a symptom-limited stress test. Survival data were obtained for both cohorts, and Cox survival analysis was used to estimate the rates of death from any cause and from cardiac causes in each group. RESULTS: The linear regression equation for predicted exercise capacity (in MET) on the basis of age in the cohort of asymptomatic women was as follows: predicted MET = 14.7 - (0.13 x age). The risk of death among asymptomatic women whose exercise capacity was less than 85 percent of the predicted value for age was twice that among women whose exercise capacity was at least 85 percent of the age-predicted value (P<0.001). Results were similar in the cohort of symptomatic women. CONCLUSIONS: We have established a nomogram for predicted exercise capacity on the basis of age that is predictive of survival among both asymptomatic and symptomatic women. These findings could be incorporated into the interpretation of exercise stress tests, providing additional prognostic information for risk stratification.

Regression to the mean: what it is and how to deal with it

Background Regression to the mean (RTM) is a statistical phenomenon that can make natural variation in repeated data look like real change. It happens when unusually large or small measurements tend to be followed by measurements that are closer to the mean. Methods We give some examples of the phenomenon, and discuss methods to overcome it at the design and analysis stages of a study. Results The effect of RTM in a sample becomes more noticeable with increasing measurement error and when follow-up measurements are only examined on a sub-sample selected using a baseline value. Conclusions RTM is a ubiquitous phenomenon in repeated data and should always be considered as a possible cause of an observed change. Its effect can be alleviated through better study design and use of suitable statistical methods.

Using extreme value theory to measure value-at-risk for daily electricity spot prices

The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.