Tourette syndrome (TS) as well as its most common comorbidities are associated with a higher propensity for risky behaviour in everyday life. However, it is unclear whether this increased risk propensity in real-life contexts translates into a generally increased attitude towards risk. We aimed to assess decision-making under risk and ambiguity based on prospect theory by considering the effects of comorbidities and medication.

Fifty-four individuals with TS and 32 healthy controls performed risk and ambiguity decision-making tasks under both gains and losses conditions. Behavioural and computational parameters were evaluated using (i) univariate analysis to determine parameters difference taking independently; (ii) supervised multivariate analysis to evaluate whether our parameters could jointly account for between-group differences (iii) unsupervised multivariate analysis to explore the potential presence of sub-groups.

Except for general ‘noisier’ (less consistent) decisions in TS, we showed no specific risk-taking behaviour in TS or any relation with tics severity or antipsychotic medication. However, the presence of comorbidities was associated with distortion of decision-making. Specifically, TS with obsessive–compulsive disorder comorbidity was associated with a higher risk-taking profile to increase gain and a higher risk-averse profile to decrease loss. TS with attention-deficit hyperactivity disorder comorbidity was associated with risk-seeking in the ambiguity context to reduce a potential loss.

Impaired valuation of risk and ambiguity was not related to TS per se. Our findings are important for clinical practice: the involvement of individuals with TS in real-life risky situations may actually rather result from other factors such as psychiatric comorbidities.

Tourette disorder (TD), hallmarks of which are motor and vocal tics, has been related to functional abnormalities in large-scale brain networks. Using a fully data driven approach in a prospective, case–control study, we tested the hypothesis that functional connectivity of these networks carries a neural signature of TD. Our aim was to investigate (i) the brain networks that distinguish adult patients with TD from controls, and (ii) the effects of antipsychotic medication on these networks.

Using a multivariate analysis based on support vector machine (SVM), we developed a predictive model of resting state functional connectivity in 48 patients and 51 controls, and identified brain networks that were most affected by disease and pharmacological treatments. We also performed standard univariate analyses to identify differences in specific connections across groups.

SVM was able to identify TD with 67% accuracy (p = 0.004), based on the connectivity in widespread networks involving the striatum, fronto-parietal cortical areas and the cerebellum. Medicated and unmedicated patients were discriminated with 69% accuracy (p = 0.019), based on the connectivity among striatum, insular and cerebellar networks. Univariate approaches revealed differences in functional connectivity within the striatum in patients v. controls, and between the caudate and insular cortex in medicated v. unmedicated TD.

SVM was able to identify a neuronal network that distinguishes patients with TD from control, as well as medicated and unmedicated patients with TD, holding a promise to identify imaging-based biomarkers of TD for clinical use and evaluation of the effects of treatment.

The association between long QT interval and sudden infant death syndrome has been clearly established. Several studies have been conducted to determine the evolution of the QT interval in childhood from birth, but only in full-term newborns. However, data on the QT interval in pre-term infants are extremely scarce. The objective was to describe the development of the QT interval in premature infants.

In a prospective monocentric study in a neonatal intensive care unit, pre-term newborns born before 37 weeks of gestation without congenital heart disease, family history of long QT, unstable haemodynamic status, or administration of drugs inducing QT interval prolongation were included with parental consent. An electrocardiogram was recorded in similar conditions weekly until discharge in each child. The corrected QT was calculated with Bazett's formula.

In all, 309 echocardiograms were recorded in 87 children, with gestational age ranging from 24–36 weeks. QT first increased after birth in very premature infants – less than 30 weeks of gestation – and then started to decrease, whereas it only decreased in more mature infants. When plotted against postmenstrual age, QT first increased, and then decreased after 32 weeks.

Our data suggest that the QT interval varies with postmenstrual age in very premature infants, reaching a peak at 32 weeks. These developmental changes may induce specific vulnerability to QT-lengthening medications in premature infants. This study underlines the need for specific pharmacological studies in this population.

Owing to systemic inflammatory response syndrome, the diagnosis of post-operative infection after cardiopulmonary bypass is difficult to assess in children with the usual clinical and biological tools. Procalcitonin could be informative in this context.

Retrospective study in a paediatric intensive care unit. Blood samples were collected as soon as infection was clinically suspected and a second assay was performed 24 hours later. Using referenced criteria, children were retrospectively classified into two groups: infected and non-infected.

Out of the 95 children included, 14 were infected. Before the third post-operative day, procalcitonin median concentration was significantly higher in the infected group than in the non-infected group – 20.24 nanograms per millilitre with a 25th and 75th interquartile of 15.52–35.71 versus 0.72 nanograms per millilitre with a 25th and 75th interquartile of 0.28 to 5.44 (p = 0.008). The area under the receiver operating characteristic curve was 0.89 with 95% confidence intervals from 0.80 to 0.97. The best cut-off value to differentiate infected children from healthy children was 13 nanograms per millilitre with 100% sensitivity – 95% confidence intervals from 51 to 100 – and 85% specificity – 95% confidence intervals from 72 to 91. After the third post-operative day, procalcitonin was not significantly higher in infected children – 2 nanograms per millilitre with a 25th and 75th interquartile of 0.18 to 12.42 versus 0.37 nanograms per millilitre with a 25th and 75th interquartile of 0.24 to 1.32 (p = 0.26). The area under the receiver operating characteristic curve was 0.62 with 95% confidence intervals from 0.47 to 0.77. A procalcitonin value of 0.38 nanograms per millilitre provided a sensitivity of 70% with 95% confidence intervals from 39 to 89 for a specificity of 52% with 95% confidence intervals from 34 to 68. After the third post-operative day, a second assay at a 24-hour interval can improve the sensitivity of the test.

Procalcitonin seems to be a discriminating marker of bacterial infection during the post-operative days following cardiopulmonary bypass in children.