Methodological and Reporting Quality of Systematic Reviews Published in the Highest Ranking Journals in the Field of Pain.

BACKGROUND: Systematic reviews (SRs) are important for making clinical recommendations and guidelines. We analyzed methodological and reporting quality of pain-related SRs published in the top-ranking anesthesiology journals. METHODS: This was a cross-sectional meta-epidemiological study. SRs published from 2005 to 2015 in the first quartile journals within the Journal Citation Reports category Anesthesiology were analyzed based on the Journal Citation Reports impact factor for year 2014. Each SR was assessed by 2 independent authors using Assessment of Multiple Systematic Reviews (AMSTAR) and Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA) tools. Total score (median and interquartile range, IQR) on checklists, temporal trends in total score, correlation in total scores between the 2 checklists, and variability of those results between journals were analyzed. RESULTS: A total of 446 SRs were included. Median total score of AMSTAR was 6/11 (IQR: 4-7) and of PRISMA 18.5/27 (IQR: 15-22). High compliance (reported in over 90% SRs) was found in only 1 of 11 AMSTAR and 5 of 27 PRISMA items. Low compliance was found for the majority of AMSTAR and PRISMA individual items. Linear regression indicated that there was no improvement in the methodological and reporting quality of SRs before and after the publication of the 2 checklists (AMSTAR: F(1,8) = 0.22; P = .65, PRISMA: F(1,7) = 0.22; P = .47). Total scores of AMSTAR and PRISMA had positive association (R = 0.71; P < .0001). CONCLUSIONS: Endorsement of PRISMA in instructions for authors was not a guarantee of compliance. Methodological and reporting quality of pain-related SRs should be improved using relevant checklists. This can be remedied by a joint effort of authors, editors, and peer reviewers.

Determining the adulteration of spices with Sudan I-II-II-IV dyes by UV-visible spectroscopy and multivariate classification techniques.

We propose a very simple and fast method for detecting Sudan dyes (I, II, III and IV) in commercial spices, based on characterizing samples through their UV-visible spectra and using multivariate classification techniques to establish classification rules. We applied three classification techniques: K-Nearest Neighbour (KNN), Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA). A total of 27 commercial spice samples (turmeric, curry, hot paprika and mild paprika) were analysed by chromatography (HPLC-DAD) to check that they were free of Sudan dyes. These samples were then spiked with Sudan dyes (I, II, III and IV) up to a concentration of 5 mg L(-1). Our final data set consisted of 135 samples distributed in five classes: samples without Sudan dyes, samples spiked with Sudan I, samples spiked with Sudan II, samples spiked with Sudan III and samples spiked with Sudan IV. Classification results were good and satisfactory using the classification techniques mentioned above: 99.3%, 96.3% and 90.4% of correct classification with PLS-DA, KNN and SIMCA, respectively. It should be pointed out that with SIMCA, there are no real classification errors as no samples were assigned to the wrong class: they were just not assigned to any of the pre-defined classes.

Uncertainty in aflatoxin B1 analysis using information from proficiency tests.

We describe how to calculate uncertainty in the determination of aflatoxin B(1) in nuts and maize using an HPLC method with prederivatisation with trifluoroacetic acid and fluorescence detection. The uncertainty is easily calculated using the information obtained from the participation in several proficiency tests. All the sources of uncertainty are grouped in two terms: (1) matrix variability, intermediate precision and sample heterogeneity, and (2) method concordance. This methodology has the advantage that no extra work needs to be done because all the information to calculate uncertainty comes from proficiency tests. The uncertainty values were calculated using samples whose concentration ranged between 2 and 20 microg L(-1). The relative standard uncertainty computed for aflatoxin B(1) was 16.3%.

Qualitative method for determination of aflatoxin B1 in nuts.

The proper characterization of a commercial qualitative method for determining aflatoxin B1 in some nuts is described. A qualitative method that provides binary responses of the yes/no type means that the performance parameters have been properly adapted and defined. Performance characteristics such as the cut-off limit, the detection limit, sensitivity, specificity, false-positive and negative rates, and the unreliability or uncertainty region are defined and then estimated by means of the performance characteristic curves. The commercial test kit showed the cut-off limit at 1.6 ng/g, with a sensitivity rate of 95% and a false-negative rate of zero. A modification can be performed to shift the cut-off to 2.0 ng/g, keeping the same values for the sensitivity and false-negative rate.