Notes

Specialized medical popular features of genetically indicated kinds of innate angioedema with standard C1 chemical: a systematic report on qualitative evidence.
Pre-amplification facilitated the detection of all assayed miRNAs with an overall cycle threshold (C
) improvement of 6.6 ± 0.89 (P < 0.05). Excellent ICCs (> 0.90) were found between data for preamplified and not preamplified miR-16, miR-21 and miR-146a. However, these correlations for low expressed miR-190b were moderate (0.79 in maternal; 0.61 in cord plasma) and poor for miR-1537 (0.49 in maternal; no correlation in cord plasma).

Pre-amplification is a useful, necessary step in the analysis of miR-1537 and miR-190b as a reliable procedure facilitating extracellular miRNA expression detection in human plasma by real-time PCR quantification.
Pre-amplification is a useful, necessary step in the analysis of miR-1537 and miR-190b as a reliable procedure facilitating extracellular miRNA expression detection in human plasma by real-time PCR quantification.
High prolactin (PRL) concentrations are found in laboratory test results of patients on majority of antipsychotic drugs. Prevalence rates and degrees of severity of hyperprolactinemia (HPRL) based on PRL concentration may depend on the presence of macroprolactin in the serum. The aim of the study was to investigate the difference between PRL concentrations before and after precipitation of macroprolactin and to examine if there were any changes in the categorization of HPRL between samples prior and after precipitation.

Total of 98 female patients (median age 33; range 19-47 years) diagnosed with a psychotic disorder, proscribed antipsychotic drugs, and with HPRL were included. Total PRL concentration and PRL concentration after macroprolactin precipitation with polyethylene glycol (postPEG-PRL) were determined by the chemiluminometric method on the Beckman Coulter Access2 analyser.

Total PRL concentrations (median 1471; IQC 1064-2016 mlU/L) and postPEG-PRL concentrations (median 1453; IQC 979-1955 mlU/resence in the serum on the categorization of patients according to severity of HPRL.
The intraindividual variability in urinary creatinine excretion is notoriously large. The aims of this study were to investigate the variability of duplicate consecutive 24-hour urinary creatinine excretions in patients and to develop a model for the detection and correction of discrepant creatinine excretions.

A group of 270 patients (82 men and 188 women) were included in the study. We collected the following data urinary 24-hour volumes (volumetric/gravimetric) and urinary creatinine concentrations (Jaffé/enzymatic) on both collection days. We performed specific calculations to detect discrepant creatinine excretions.

In 60 patients (22%) discrepant collections were found. Among the remaining 78%, 22% of the patients collected very accurately (almost identical urinary creatinine excretions). In this subgroup the volume ratios and the creatinine concentration ratios behave inversely as in a dilution curve. A theoretical model and six collection scenarios were developed to detect, interpret and correct discrepant collections. Practical examples are given to illustrate the use of the model in successful correction of creatinine and other analytes for under- or overcollection.

We conclude that missed or overcollected urine volumes are the largest source of variation in creatinine excretion. Discrepancies in consecutive duplicate 24-hour creatinine excretions can be detected and corrected with specific calculations by means of the presented model. The effectiveness of these corrections is demonstrated with examples from daily practice. These calculations can be easily automated.
We conclude that missed or overcollected urine volumes are the largest source of variation in creatinine excretion. Discrepancies in consecutive duplicate 24-hour creatinine excretions can be detected and corrected with specific calculations by means of the presented model. The effectiveness of these corrections is demonstrated with examples from daily practice. These calculations can be easily automated.
To interpret test results correctly, understanding of the variations that affect test results is essential. The aim of this study is 1) to evaluate the clinicians' knowledge and opinion concerning biological variation (BV), and 2) to investigate if clinicians use BV in the interpretation of test results.

This study uses a questionnaire comprising open-ended and close-ended questions. Questions were selected from the real-life numerical examples of interpretation of test results, the knowledge about main sources of variations in laboratories and the opinion of clinicians on BV. A total of 399 clinicians were interviewed, and the answers were evaluated using a scoring system ranked from A (clinician has the highest level of knowledge and the ability of using BV data) to D (clinician has no knowledge about variations in laboratory). The results were presented as number (N) and percentage (%).

Altogether, 60.4% of clinicians have knowledge of pre-analytical and analytical variations; but only 3.5% of them have knowledge related to BV. The number of clinicians using BV data or reference change value (RCV) to interpret measurements results was zero, while 79.4% of clinicians accepted that the difference between two measurements results located within the reference interval may be significant.

Clinicians do not use BV data or tools derived from BV such as RCV to interpret test results. It is recommended that BV should be included in the medical school curriculum, and clinicians should be encouraged to use BV data for safe and valid interpretation of test results.
Clinicians do not use BV data or tools derived from BV such as RCV to interpret test results. It is recommended that BV should be included in the medical school curriculum, and clinicians should be encouraged to use BV data for safe and valid interpretation of test results.
We investigated the interference of haemolysis on ethanol testing carried out with the Synchron assay kit using an AU680 autoanalyser (Beckman Coulter, Brea, USA).

Two tubes of plasma samples were collected from 20 volunteers. Mechanical haemolysis was performed in one tube, and no other intervention was performed in the other tube. After centrifugation, haemolysed and non-haemolysed samples were diluted to obtain samples with the desired free haemoglobin (Hb) values (0, 1, 2, 5, 10 g/L). A portion of these samples was then separated, and ethanol was added to the separated sample to obtain a concentration of 86.8 mmol/L ethanol. After that, these samples were diluted with ethanol-free samples with the same Hb concentration to obtain samples containing 43.4, 21.7, and 10.9 mmol/L. Each group was divided into 20 equal parts, and an ethanol test was carried out. The coefficient of variation (CV), bias, and total error (TE) values were calculated.

The TE values of haemolysis-free samples were approximately 2-5%, and the TE values of haemolysed samples were approximately 10-18%. The bias values of haemolysed samples ranged from nearly - 6.2 to - 15.7%.

Haemolysis led to negative interference in all samples. However, based on the 25% allowable total error value specified for ethanol in the Clinical Laboratory Improvement Amendments (CLIA 88) criteria, the TE values did not exceed 25%. Consequently, ethanol concentration can be measured in samples containing free Hb up to 10 g/L.
Haemolysis led to negative interference in all samples. However, based on the 25% allowable total error value specified for ethanol in the Clinical Laboratory Improvement Amendments (CLIA 88) criteria, the TE values did not exceed 25%. Consequently, ethanol concentration can be measured in samples containing free Hb up to 10 g/L.
It is often quoted that 70% of clinical decisions are based on laboratory results, but the evidence to substantiate this claim is lacking. Since clinical guidelines aim to document best-practice decision making for specific disease conditions, inclusion of any laboratory test means that the best available evidence is recommending clinicians use it. Cardiovascular disease (CVD) is the world's most common cause of mortality, so this study reviewed all CVD guidelines published by five national/international authorities to determine what proportion of them recommended laboratory testing.

Five leading CVD guidelines were examined, namely the European Society of Cardiology (ESC), the UK National Institute for Health and Clinical Excellence (NICE), the American College of Cardiology (ACC), the Australian Heart Foundation (AHF) and the Cardiac Society of Australia and New Zealand (CSANZ).

A total of 101 guidelines were reviewed. Of the 33 individual ESC guidelines relating to CVD, 24/33 made a direct reference to the use of clinical laboratory tests in either diagnosis or follow-up treatment. The same applied to 15/20 of NICE guidelines, 24/32 from the ACC and 15/16 from the AHF/CSANZ. Renal function and blood count testing were the most recommended (39 and 26 times), with lipid, troponin and natriuretic peptide measurement advocated 25, 19 and 19 times respectively.

This study has shown that laboratory testing is advocated by between 73% and 94% of individual CVD guideline recommendations from five national/international authorities. This provides an index to assess the potential value of laboratory medicine to healthcare.
This study has shown that laboratory testing is advocated by between 73% and 94% of individual CVD guideline recommendations from five national/international authorities. This provides an index to assess the potential value of laboratory medicine to healthcare.
Intensive physical activity causes functional and metabolic changes in the athlete's organism. The study aimed to verify the common national available reference intervals (RIs) for common inflammatory and screening coagulation tests in a population of healthy young female athletes.

One hundred and twenty-one female athletes (age range 16-34), from various sports disciplines (water polo, handball, volleyball, football, basketball), were included in the study. All participants completed the international physical activity short-form questionnaire. Blood samples were collected between 8-10 am, after an overnight fast, before any physical activity. Reference intervals were determined according to Clinical & Laboratory Standards Institute EP28-A3C Guidelines.

Calculated RIs for white blood cell count (WBC), prothrombin time (PT), and activated partial thromboplastin time (APTT) ratio were in accordance with the common national RIs. Calculated RI for C-reactive protein (CRP) was lower (< 2.9 mg/L) thanE diagnosis exclusion in a group of healthy young female athletes.
The accurate estimation of low-density lipoprotein cholesterol (LDL) is crucial for management of patients at risk of cardiovascular events due to dyslipidemia. The LDL is typically calculated using the Friedewald equation and/or direct homogeneous assays. However, both methods have their own limitations, so other equations have been proposed, including a new equation developed by Sampson. The aim of this study was to evaluate Sampson equation by comparing with the Friedewald and Martin-Hopkins equations, and with a direct LDL method.

Results of standard lipid profile (total cholesterol (CHOL), high-density lipoprotein cholesterol (HDL) and triglycerides (TG)) were obtained from two anonymized data sets collected at two laboratories, using assays from different manufacturers (Beckman Coulter and Roche Diagnostics). The second data set also included LDL results from a direct assay (Roche Diagnostics). Passing-Bablok and Bland-Altman analysis for method comparison was performed.

A total of 64,345 and 37,783 results for CHOL, HDL and TG were used, including 3116 results from the direct LDL assay.
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