281 research outputs found

    Pre-analytical stability of coagulation parameters in plasma stored at room temperature

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    Introduction: Haemostasis testing is influenced by many pre-analytical variables, such as storage time and temperature, which can affect the stability of coagulation factors and influence the results of coagulation assays. We investigated the stability of haemostasis tests after storage of aliquoted plasma at RT, including the variability of measurement principle and reagent used for determination. Methods: Blood samples from 20 healthy volunteers were obtained, processed to PPP and aliquoted. Aliquots were stored at RT for 0 hour, 2 hours, 4 hours, 6 hours, 8 hours, 12 hours, 24 hours and 48 hours. PT, aPTT, fibrinogen, D-Dimers and coagulation factors (FII, FV, FVII, FX, FVIII, FIX, FXI, FXII) were determined by STA-R Max (R) and ACL-TOP (R). VWF:Ag and vWF:RCo were determined by AcuStar (R). Clinically relevant changes, compared to the initial measurement, were denoted as a percentage change of > 10% according to the 99% CI. Results: For both analysers, a clinically relevant change of > 10% was observed for FV after 2 hours, FVIII after 4 hours and for aPTT, FII, FVII, FX and FXII after 48 hours of storage at RT. Statistically significant, but no clinically relevant differences were observed after 48-hours storage for PT, fibrinogen and FIX. D-Dimers, FXI, vWF: Ag and vWF: RCo were found stable up to 48 hours at RT. Conclusion: Overall, compared to the limits given by the current CLSI guidelines, for most coagulation parameters investigated in this study a longer storage period could be accepted. Time intervals for FVIII and FV dosage were shorter than recommended by the CLSI guidelines. For PT determination, our findings were consistent

    Nutritional status, growth and disease management in children with single and dual diagnosis of type 1 diabetes mellitus and coeliac disease

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    Background: The consequences of subclinical coeliac disease (CD) in Type 1 diabetes mellitus (T1DM) remain unclear. We looked at growth, anthropometry and disease management in children with dual diagnosis (T1DM + CD) before and after CD diagnosis.<p></p> Methods: Anthropometry, glycated haemoglobin (HbA1c) and IgA tissue transglutaminase (tTg) were collected prior to, and following CD diagnosis in 23 children with T1DM + CD. This group was matched for demographics, T1DM duration, age at CD diagnosis and at T1DM onset with 23 CD and 44 T1DM controls.<p></p> Results: No differences in growth or anthropometry were found between children with T1DM + CD and controls at any time point. Children with T1DM + CD, had higher BMI z-score two years prior to, than at CD diagnosis (p <0.001). BMI z-score change one year prior to CD diagnosis was lower in the T1DM + CD than the T1DM group (p = 0.009). At two years, height velocity and change in BMI z-scores were similar in all groups. No differences were observed in HbA1c between the T1DM + CD and T1DM groups before or after CD diagnosis. More children with T1DM + CD had raised tTg levels one year after CD diagnosis than CD controls (CDx to CDx + 1 yr; T1DM + CD: 100% to 71%, p = 0.180 and CD: 100% to 45%, p < 0.001); by two years there was no difference.<p></p> Conclusions: No major nutrition or growth deficits were observed in children with T1DM + CD. CD diagnosis does not impact on T1DM glycaemic control. CD specific serology was comparable to children with single CD, but those with dual diagnosis may need more time to adjust to gluten free diet

    Thawing times and haemostatic assessment of fresh frozen plasma thawed at 37°C and 45°C using water bath methods

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    BACKGROUND: The Barkey Plasmatherm (BP; Barkey GmbH & Co. KG) can thaw plasma at 37°C and 45°C. No studies have assessed thawing times or hemostatic qualities of plasma thawed at 45°C with BP. This study assessed fresh frozen plasma (FFP) thawing times with use of BP at 37°C and 45°C and Thermogenesis ThermoLine (TT; Helmer Scientific) at 37°C and compared the hemostatic quality of LG-Octaplas (Octapharma) with use of BP at 37°C and 45°C with TT at 37°C. STUDY DESIGN AND METHODS: The thawing time of FFP (pairs or fours) was assessed using BP at 37°C and 45°C (not prewarmed and prewarmed) and TT at 37°C. Hemostasis was assessed in LG-Octaplas at 5 minutes, 24 hours, 48 hours, and 120 hours after thawing with use of the three methods. RESULTS: Thawing time for two units was 13.44 minutes using TT, the same as using BP at 37°C (12.94 min not prewarmed; 12.20 min prewarmed) or 45°C (12.38 min not prewarmed), but longer than using BP prewarmed to 45°C (11.31 min, p < 0.001). Thawing time for four units was 13.41 minutes using TT, shorter than using BP at 37°C (17.19 min not prewarmed, 18.47 min prewarmed; both p < 0.001) or 45°C (15.03 min not prewarmed, p = 0.012; 15.22 min prewarmed, p = 0.004). There was no reduction in hemostatic markers in LG-Octaplas with use of BP at 37°C or 45°C compared to TT. CONCLUSION: BP is quicker than TT by 2 minutes when thawing two units of FFP if it is prewarmed to 45°C. BP is slower than TT by at least 2 minutes when thawing four units of FFP at 37o C. There was no significant difference in the hemostatic qualities of plasma whether thawed at 37°C or 45°C

    Comparison of clinical methods with the faecal gluten immunogenic peptide to assess gluten intake in coeliac disease

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    Objectives: Detection of faecal gluten immunogenic peptides (GIP) is a biomarker of recent gluten consumption. GIP levels can be used to monitor gluten intake and compliment clinical methods to evaluate compliance to gluten free diet (GFD). In this study, recent gluten intake was measured by GIP in CD children and compared to routine clinical measures to evaluate GFD compliance. Methods: GIP was measured in 90 samples from 63 CD children (44 previously and 19 newly diagnosed with follow-up samples at 6 and 12 months on GFD). Compliance to GFD was evaluated based on clinical assessment, tTG levels and Biagi score. Results: GIP was detectable in 16% of patients with previous CD diagnosis on GFD. BMI z-score (p=0.774), height z-score (p=0.723), haemoglobin concentration (p=0.233), age (p=0.448), gender (p=0.734) or disease duration (p=0.488) did not differ between those with detectable and non-detectable GIP. In newly diagnosed patients, on gluten containing diet, GIP was detectable in 95% of them. Following GFD initiation, GIP decreased (p&lt;0.001); 17% and 27% had detectable levels at 6 and 12 months, respectively. Compared to GIP, the Biagi score, tTG and clinical assessment presented sensitivity of 17%, 42% and 17%. Likewise, GIP was detectable in 16%, 16%, 14% of patients evaluated as GFD compliant according to the Biagi score, tTG and clinical assessment. A combination of methods did not improve identification of patients who were non-compliant. Conclusions: Inclusion of faecal GIP measurements is likely to improve identification of GFD recent noncompliance in CD management and could be incorporated into current follow-up strategies

    Alterations in intestinal microbiota of children with celiac disease at time of diagnosis and on a gluten-free diet

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    Background &amp; Aims: It is not clear whether alterations in the intestinal microbiota of children with celiac disease cause the disease or are a result of disease and/or its treatment with gluten-free diet (GFD). Methods: We obtained 167 fecal samples from 141 children (20 with new-onset celiac disease, 45 treated with a GFD, 57 healthy children, and 19 unaffected siblings of children with celiac disease) in Glasgow, Scotland. Samples were analyzed by 16S rRNA sequencing and diet-related metabolites were measured by gas chromatography. We obtained fecal samples from 13 of the children with new-onset CD after 6 and 12 months on GFD. Relationships between microbiota with diet composition, gastrointestinal function, and biomarkers of GFD compliance were explored. Results: Microbiota α diversity did not differ among groups. Microbial dysbiosis was not observed in children with new-onset celiac disease. In contrast, 2.8% (Bray-Curtis dissimilarity index, P=.025) and 2.5% (UniFrac distances, P=.027) of the variation in microbiota composition could be accounted for by the GFD. Between 3% to 5% of all taxa differed among all group comparisons. Eleven distinctive operational taxonomic units composed a microbe signature specific to celiac disease with high diagnostic probability. Most of the operational taxonomic units that differed between patients on GFD with new-onset celiac disease vs healthy children were associated with nutrient and food group intake (from 75% to 94%), and with biomarkers of gluten ingestion. Fecal levels of butyrate and ammonia decreased during the GFD. Conclusions: Although several alterations in the intestinal microbiota of children with established celiac disease appear to be effects of a GFD, there are specific bacteria that are distinct biomarkers of celiac disease. Studies are needed to determine whether these bacteria contribute to pathogenesis of celiac disease
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