Copeptin as a serum biomarker of febrile seizures.

BACKGROUND AND OBJECTIVES: Accurate diagnosis of febrile seizures in children presenting after paroxysmal episodes associated with fever, is hampered by the lack of objective postictal biomarkers. The aim of our study was to investigate whether FS are associated with increased levels of serum copeptin, a robust marker of arginine vasopressin secretion. METHODS: This was a prospective emergency-setting cross-sectional study of 161 children between six months and five years of age. Of these, 83 were diagnosed with febrile seizures, 69 had a febrile infection without seizures and nine had epileptic seizures not triggered by infection. Serum copeptin and prolactin levels were measured in addition to standard clinical, neurophysiological, and laboratory assessment. CLINICAL TRIAL REGISTRATION: NCT01884766. RESULTS: Circulating copeptin was significantly higher in children with febrile seizures (median [interquartile range] 18.9 pmol/L [8.5-36.6]) compared to febrile controls (5.6 pmol/L [4.1-9.4]; p < 0.001), with no differences between febrile and epileptic seizures (21.4 pmol/L [16.1-46.6]; p = 0.728). In a multivariable regression model, seizures were the major determinant of serum copeptin (beta 0.509; p < 0.001), independently of clinical and baseline laboratory indices. The area under the receiver operating curve for copeptin was 0.824 (95% CI 0.753-0.881), significantly higher compared to prolactin (0.667 [0.585-0.742]; p < 0.001). The diagnostic accuracy of copeptin increased with decreasing time elapsed since the convulsive event (at 120 min: 0.879 [0.806-0.932] and at <60 min: 0.975 [0.913-0.997]). CONCLUSIONS: Circulating copeptin has high diagnostic accuracy in febrile seizures and may be a useful adjunct for accurately diagnosing postictal states in the emergency setting.

Association of smoking and nicotine dependence with pre-diabetes in young and healthy adults.

INTRODUCTION: Several studies have shown an increased risk of type 2 diabetes among smokers. Therefore, the aim of this analysis was to assess the relationship between smoking, cumulative smoking exposure and nicotine dependence with pre-diabetes. METHODS: We performed a cross-sectional analysis of healthy adults aged 25-41 in the Principality of Liechtenstein. Individuals with known diabetes, Body Mass Index (BMI) >35 kg/m² and prevalent cardiovascular disease were excluded. Smoking behaviour was assessed by self-report. Pre-diabetes was defined as glycosylated haemoglobin between 5.7% and 6.4%. Multivariable logistic regression models were done. RESULTS: Of the 2142 participants (median age 37 years), 499 (23.3%) had pre-diabetes. There were 1,168 (55%) never smokers, 503 (23%) past smokers and 471 (22%) current smokers, with a prevalence of pre-diabetes of 21.2%, 20.9% and 31.2%, respectively (p <0.0001). In multivariable regression models, current smokers had an odds ratio (OR) of pre-diabetes of 1.82 (95% confidential interval (CI) 1.39; 2.38, p <0.0001). Individuals with a smoking exposure of <5, 5-10 and >10 pack-years had an OR (95% CI) for pre-diabetes of 1.34 (0.90; 2.00), 1.80 (1.07; 3.01) and 2.51 (1.80; 3.59) (p linear trend <0.0001) compared with never smokers. A Fagerström score of 2, 3-5 and >5 among current smokers was associated with an OR (95% CI) for pre-diabetes of 1.27 (0.89; 1.82), 2.15 (1.48; 3.13) and 3.35 (1.73; 6.48) (p linear trend <0.0001). DISCUSSION: Smoking is strongly associated with pre-diabetes in young adults with a low burden of smoking exposure. Nicotine dependence could be a potential mechanism of this relationship.