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<p><b></b>To carry out phylogenetic analysis for drug-resistance genes from clinical isolates of Helicobacter pylori (Hp) among patients with gastric diseases from Tibet, China.</p><p><b>METHODS</b>Hp strains were isolated and cultured from saliva and gastric mucosal tissues derived from patients with gastric diseases. Nine strains (including 5 isolated from oral tissues, 1 isolated from gastric tissues, and 3 representative strains of SS international standard strains used for animal models) were tested for common antibiotic resistance. Together with an ACTT 11637 international standard strain, these were subjected to re-sequencing to obtain drug-resistance genes. Such genes from various sources were compared with the resistance genes of Hp strains recorded by the NCBI website. Combined with results of drug-resistance experiments, correlation between molecular evolution and drug-resistance was analyzed.</p><p><b>RESULTS</b>Testing of gastric mucosal tissues and salivary samples from 217 patients has found 89 Hp strains, which yielded a total infection rate of 41.01%. The resistance rates of 9 representative Hp strains for clarithromycin, amoxicillin, metronidazole, levofloxacin and tetracycline were 77.8%, 77.8%, 44.4%, 77.8%, and 77.8%, respectively. Compared with the reference strain, the similarity between clarithromycin-resistance genes was 99%, and that between amoxicillin- and metronidazole-resistance genes was 96%-97%. A2143G mutation was also found in clarithromycin-resistant genes of three Hp strains.</p><p><b>CONCLUSION</b>The sensitivity of Hp to metronidazole is much higher in patients from Tibet region, and the sensitivity of Hp to clarithromycin, amoxicillin, levofloxacin and tetracycline is poor. Resistance mutations are consistent with drug resistance.</p>
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Objective To verify and monitor the performance of accuracy, precision and comparability of 26 clinical biochemical analytes (29 methods) in the six centers involved in multi-centers reference intervals research, and to ensure the reliability of theirmeasurement results.Methods During the period of the systems evaluating, two levels of commercial quality control materials and fresh frozen human serum reference materials were applied to verify the performance of inter-laboratory precision and accuracy of analysis systems. During the period of samples testing, the commercial quality control materials were measured whenever samples were analysed, the fresh frozen serum reference materials were measured once a month.The coefficient of variations (CVs), bias and total errors were calculated to assess the precision, accuracy and comparability.Results Verification of precision and accuracy: ( 1 ) the ranges of CVs of 29 methods in the six laboratory laboratories were 0.4%-6.0%, the CVs of all 29 methods met the criterion . (2) The overall average bias of the analysis systems of 21 analytes (24 methods) ranged from -5.15%( ALT) to 4.46% ( Ur ) .Among 24 methods the overall average bias of TP, Glu-GOD, Ur, Cl, Ca exceeded the acceptable range.The quality assessment during the period of samples testing:(1) The overall average bias ranged from -1.95%(Ca) to 2.92%(Ur), median 1.26%, they all met the requirements of relevant standards.( 2 ) When commercial control materials were tested, the requirements of CVs were fulfilled for most methods in the six laboratories,and the CVs of TP, Alb, Cl, Ca exceeded the acceptable range.The overall average TE of all methods met the quality specification for the C-N controls material.For the C-P control material, only the overall average TE of TP (5.05%) exceeded thearceptable range while the other methods met the requirement in criterion.Conclusions The performance of precision and accuracy of the analysis systems used in the six laboratories passed the verification.During the period of sample testing, the performance of precision and accuracy of the most methods in the 6 laboratories met the requirements of quality specifications, and the overall performance was good.Because of the limitation of current technology the performance of some methods didn't fulfill the requirement of specifications, and need to be improved.
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Objective To evaluate the reference change values (RCV),individual indexes of TSH,T4,T3,FT3,and FT4 and the limitations of population-based reference ranges.Furthermore,to determine the quality standards based on the biological varia-tion.Methods Acorrding to intra-and inter-individual biological variations,and analytical variations ,RCV and individual indexes of TSH,T4,T3,free T3,and free T4 were calculated,and analytical variations of quality standards based on biological variation were induced.Results RCV of TSH,T4,T3,FT3,and FT4 is 54.0%,16.8%,26.8%,42.8%,23.8%,respectively.Individ-uality index is 0.78,0.45,0.49,0.47,0.45,respectively,and satisfied analytical variation based on biological variation is less than 9.6%,2.5%,4.4%,2.9%,4.0%,respectively.Conclusion When monitoring thyroid functions,the RCV values should be considered.It is important to recognize population-based reference ranges limitations for use in individuals.Quality standards based on biological variation should be meeted when laboratory analysis of variance is determined.
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Objective The main purpose is to establish a simple method of analytical run length definition through combination of control-based quality control(QC) and average of normals method(AON).Methods Eight test items with different analytical performance were chosen.First,the individualized control-based quality control strategy was designed in the direction of sigma metrics,and the suitable AON rules were selected for each analyte.Then,the selected AON rules were applied to the patient data of successive five workdays.Meanwhile,new individualized control-based QC procedures were also used at 8:00,10:00,12:00 and 14:00 in those days.At last,AON QC result were compared with control-based QC result to define the analytical run for 8 items and the strategy through which laboratory can optimize analytical run length.Results The error detection power of AON algorithms was as good as control-based QC whose performance was excellent.Analytical run length for 8 items involved in this study were defined as follows:triglyceride,potassium,total protein: 8 hours,Chlorine: 6 hours,magnesium:4 hours,calcium,carbon dioxide combining power,sodium: 2 hours.Conclusions For the items with performance above 3.5 sigma,the analytical run was defined mainly depending upon control-based QC,and AON QC was just used to validate control-based result.For the items with performance below 3.5 sigma,the analytical run was defined mainly depending upon AON QC.
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Objective To apply sigma metrics to assess key indicators designed in the laboratory improvement plan to find problems and promote quality improvement.Methods Sigma metrics were calculated to reflect the performance of analytic phase including imprecision,inaccuracy and Turn around time(TAT).The quality control strategy was designed accordingly.Quality goal index(QGI)was calculated to find the cause of any error for the items exceeding 6 sigma.Quality of pre-,post-analytic and total analytic phase,such as quality of specimen,TAT,panic value notification and satisfaction of physicians and patients were measured in sigma metrics too.Results The average sigma metric of analytic phase was 4.44,while sigma metric for 8 of 27 test items were above 6?.The main cause of performance under 6o" was poor precision.The sigma metrics of quality of specimen,panic value notification,satisfaction of customer and emergent/routine TAT were 4.9,2.9,5.6,2.8,and 2.9 respectively.Conclusion Sigma metrics provide the objective marker for the evaluation of performance in each stage of analytic process.