Utility of 30 and 60 minute cortisol samples after high-dose synthetic ACTH-1-24 injection in the diagnosis of adrenal insufficiency

BACKGROUND: In clinical practise the high dose ACTH stimulation test (HDT) is frequently used in the assessment of adrenal insufficiency (AI). However, there is uncertainty regarding optimal time-points and number of blood samplings. The present study compared the utility of a single cortisol value taken either 30 or 60 minutes after ACTH stimulation with the traditional interpretation of the HDT. METHODS: Retrospective analysis of 73 HDT performed at a single tertiary endocrine centre. Serum cortisol was measured at baseline, 30 and 60 minutes after intravenous administration of 250 µg synthetic ACTH1-24. Adrenal insufficiency (AI) was defined as a stimulated cortisol level <550 nmol/l. RESULTS: There were twenty patients (27.4%) who showed an insufficient rise in serum cortisol using traditional HDT criteria and were diagnosed to suffer from AI. There were ten individuals who showed insufficient cortisol values after 30 minutes, rising to sufficient levels at 60 minutes. All patients revealing an insufficient cortisol response result after 60 minutes also had an insufficient result after 30 minutes. The cortisol value taken after 30 minutes did not add incremental diagnostic value in any of the cases under investigation compared with the 60 minutes' sample. CONCLUSIONS: Based on the findings of the present analysis the utility of a cortisol measurement 30 minutes after high dose ACTH injection was low and did not add incremental diagnostic value to a single measurement after 60 minutes.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Regularity conditions in the realisability problem in applications to point processes and random closed sets

We study existence of random elements with partially specified distributions. The technique relies on the existence of a positive ex-tension for linear functionals accompanied by additional conditions that ensure the regularity of the extension needed for interpreting it as a probability measure. It is shown in which case the extens ion can be chosen to possess some invariance properties. The results are applied to the existence of point processes with given correlation measure and random closed sets with given two-point covering function or contact distribution function. It is shown that the regularity condition can be efficiently checked in many cases in order to ensure that the obtained point processes are indeed locally finite and random sets have closed realisations.

On degeneracy and invariances of random fields paths with applications in Gaussian process modelling

We study pathwise invariances and degeneracies of random fields with motivating applications in Gaussian process modelling. The key idea is that a number of structural properties one may wish to impose a priori on functions boil down to degeneracy properties under well-chosen linear operators. We first show in a second order set-up that almost sure degeneracy of random field paths under some class of linear operators defined in terms of signed measures can be controlled through the two first moments. A special focus is then put on the Gaussian case, where these results are revisited and extended to further linear operators thanks to state-of-the-art representations. Several degeneracy properties are tackled, including random fields with symmetric paths, centred paths, harmonic paths, or sparse paths. The proposed approach delivers a number of promising results and perspectives in Gaussian process modelling. In a first numerical experiment, it is shown that dedicated kernels can be used to infer an axis of symmetry. Our second numerical experiment deals with conditional simulations of a solution to the heat equation, and it is found that adapted kernels notably enable improved predictions of non-linear functionals of the field such as its maximum.

Species interactions and random dispersal rather than habitat filtering drive community assembly during early plant succession

Theory on plant succession predicts a temporal increase in the complexity of spatial community structure and of competitive interactions: initially random occurrences of early colonising species shift towards spatially and competitively structured plant associations in later successional stages. Here we use long-term data on early plant succession in a German post mining area to disentangle the importance of random colonisation, habitat filtering, and competition on the temporal and spatial development of plant community structure. We used species co-occurrence analysis and a recently developed method for assessing competitive strength and hierarchies (transitive versus intransitive competitive orders) in multispecies communities. We found that species turnover decreased through time within interaction neighbourhoods, but increased through time outside interaction neighbourhoods. Successional change did not lead to modular community structure. After accounting for species richness effects, the strength of competitive interactions and the proportion of transitive competitive hierarchies increased through time. Although effects of habitat filtering were weak, random colonization and subsequent competitive interactions had strong effects on community structure. Because competitive strength and transitivity were poorly correlated with soil characteristics, there was little evidence for context dependent competitive strength associated with intransitive competitive hierarchies.

Utility of electrophysiological studies to predict arrhythmic events

AIM To evaluate the prognostic value of electrophysiological stimulation (EPS) in the risk stratification for tachyarrhythmic events and sudden cardiac death (SCD). METHODS We conducted a prospective cohort study and analyzed the long-term follow-up of 265 consecutive patients who underwent programmed ventricular stimulation at the Luzerner Kantonsspital (Lucerne, Switzerland) between October 2003 and April 2012. Patients underwent EPS for SCD risk evaluation because of structural or functional heart disease and/or electrical conduction abnormality and/or after syncope/cardiac arrest. EPS was considered abnormal, if a sustained ventricular tachycardia (VT) was inducible. The primary endpoint of the study was SCD or, in implanted patients, adequate ICD-activation. RESULTS During EPS, sustained VT was induced in 125 patients (47.2%) and non-sustained VT in 60 patients (22.6%); in 80 patients (30.2%) no arrhythmia could be induced. In our cohort, 153 patients (57.7%) underwent ICD implantation after the EPS. During follow-up (mean duration 4.8 ± 2.3 years), a primary endpoint event occurred in 49 patients (18.5%). The area under the receiver operating characteristic curve (AUROC) was 0.593 (95%CI: 0.515-0.670) for a left ventricular ejection fraction (LVEF) < 35% and 0.636 (95%CI: 0.563-0.709) for inducible sustained VT during EPS. The AUROC of EPS was higher in the subgroup of patients with LVEF ≥ 35% (0.681, 95%CI: 0.578-0.785). Cox regression analysis showed that both, sustained VT during EPS (HR: 2.26, 95%CI: 1.22-4.19, P = 0.009) and LVEF < 35% (HR: 2.00, 95%CI: 1.13-3.54, P = 0.018) were independent predictors of primary endpoint events. CONCLUSION EPS provides a benefit in risk stratification for future tachyarrhythmic events and SCD and should especially be considered in patients with LVEF ≥ 35%.

The utility of preoperative six-minute-walk distance in lung transplantation

RATIONALE The use of 6-minute-walk distance (6MWD) as an indicator of exercise capacity to predict postoperative survival in lung transplantation has not previously been well studied. OBJECTIVES To evaluate the association between 6MWD and postoperative survival following lung transplantation. METHODS Adult, first time, lung-only transplantations per the United Network for Organ Sharing database from May 2005 to December 2011 were analyzed. Kaplan-Meier methods and Cox proportional hazards modeling were used to determine the association between preoperative 6MWD and post-transplant survival after adjusting for potential confounders. A receiver operating characteristic curve was used to determine the 6MWD value that provided maximal separation in 1-year mortality. A subanalysis was performed to assess the association between 6MWD and post-transplant survival by disease category. MEASUREMENTS AND MAIN RESULTS A total of 9,526 patients were included for analysis. The median 6MWD was 787 ft (25th-75th percentiles = 450-1,082 ft). Increasing 6MWD was associated with significantly lower overall hazard of death (P < 0.001). Continuous increase in walk distance through 1,200-1,400 ft conferred an incremental survival advantage. Although 6MWD strongly correlated with survival, the impact of a single dichotomous value to predict outcomes was limited. All disease categories demonstrated significantly longer survival with increasing 6MWD (P ≤ 0.009) except pulmonary vascular disease (P = 0.74); however, the low volume in this category (n = 312; 3.3%) may limit the ability to detect an association. CONCLUSIONS 6MWD is significantly associated with post-transplant survival and is best incorporated into transplant evaluations on a continuous basis given limited ability of a single, dichotomous value to predict outcomes.

The clinical utility of basophil activation testing in diagnosis and monitoring of allergic disease

The basophil activation test (BAT) has become a pervasive test for allergic response through the development of flow cytometry, discovery of activation markers such as CD63 and unique markers identifying basophil granulocytes. Basophil activation test measures basophil response to allergen cross-linking IgE on between 150 and 2000 basophil granulocytes in <0.1 ml fresh blood. Dichotomous activation is assessed as the fraction of reacting basophils. In addition to clinical history, skin prick test, and specific IgE determination, BAT can be a part of the diagnostic evaluation of patients with food-, insect venom-, and drug allergy and chronic urticaria. It may be helpful in determining the clinically relevant allergen. Basophil sensitivity may be used to monitor patients on allergen immunotherapy, anti-IgE treatment or in the natural resolution of allergy. Basophil activation test may use fewer resources and be more reproducible than challenge testing. As it is less stressful for the patient and avoids severe allergic reactions, BAT ought to precede challenge testing. An important next step is to standardize BAT and make it available in diagnostic laboratories. The nature of basophil activation as an ex vivo challenge makes it a multifaceted and promising tool for the allergist. In this EAACI task force position paper, we provide an overview of the practical and technical details as well as the clinical utility of BAT in diagnosis and management of allergic diseases.

GSAMPLE: Stata module to draw a random sample

gsample draws a random sample from the data in memory. Simple random sampling (SRS) is supported, as well as unequal probability sampling (UPS), of which sampling with probabilities proportional to size (PPS) is a special case. Both methods, SRS and UPS/PPS, provide sampling with replacement and sampling without replacement. Furthermore, stratified sampling and cluster sampling is supported.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.