Clinical Chemistry and Laboratory Medicine Journal Impact Factor & Information

Publisher: De Gruyter

Journal description

CCLM is an official journal of the Belgian Society of Clinical Chemistry (BVKC/SBCC), the German United Society of Clinical Chemistry and Laboratory Medicine (DGKL), Italian Society of Clinical Biochemistry and Clinical Molecular Biology (SIBioC), and the Slovenian Association for Clinical Chemistry. CCLM keeps you up-to-date with the latest developments in the clinical laboratory sciences. It reports on progress in fundamental and applied research. Areas covered include: clinical biochemistry, molecular medicine, hematology, immunology, microbiology, virology, drug measurement, genetic epidemiology, evaluation of diagnostic markers, new reagents and systems, reference materials, and reference values. CCLM further promotes communication concerning these topics by the publication of news, letters and meeting reports. New teaching and training methods applicable to laboratory medicine are also covered.

Current impact factor: 2.96

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 2.955
2012 Impact Factor 3.009
2011 Impact Factor 2.15
2010 Impact Factor 2.069
2009 Impact Factor 1.886
2008 Impact Factor 1.888
2007 Impact Factor 1.741
2006 Impact Factor 1.725
2005 Impact Factor 1.918
2004 Impact Factor 1.685
2003 Impact Factor 1.523
2002 Impact Factor 1.407
2001 Impact Factor 1.595
2000 Impact Factor 1.744
1999 Impact Factor 1.084
1998 Impact Factor

Impact factor over time

Impact factor
Year

Additional details

5-year impact 2.43
Cited half-life 5.00
Immediacy index 0.58
Eigenfactor 0.01
Article influence 0.57
Website Clinical Chemistry and Laboratory Medicine website
Other titles Clinical chemistry and laboratory medicine (Online)
ISSN 1434-6621
OCLC 41941237
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

De Gruyter

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 12 months embargo
  • Conditions
    • Pre-print and abstract on author's personal website only
    • Author's post-print on funder's repository or funder's designated repository at the funding agencys request or as a result of legal obligation.
    • Publisher's version/PDF may be used, on author's personal website, editor's personal website or institutional repository
    • Authors cannot deposit in subject repositories
    • Published source must be acknowledged
    • Must link to publisher version and article’s DOI must be given
    • Set statement to accompany deposit (see policy)
  • Classification
    ​ yellow

Publications in this journal

  • Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0303
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    ABSTRACT: Appropriate quality of test results is fundamental to the work of the medical laboratory. How to define the level of quality needed is a question that has been subject to much debate. Quality specifications have been defined based on criteria derived from the clinical applicability, validity of reference limits and reference change values, state-of-the-art performance, and other criteria, depending on the clinical application or technical characteristics of the measurement. Quality specifications are often expressed as the total error allowable (TEA) - the total amount of error that is medically, administratively, or legally acceptable. Following the TEA concept, bias and imprecision are combined into one number representing the "maximum allowable" error in the result. The commonly accepted method for calculation of the allowable error based on biological variation might, however, have room for improvement. In the present paper, we discuss common theories on the determination of quality specifications. A model is presented that combines the state-of-the-art with biological variation for the calculation of performance specifications. The validity of reference limits and reference change values are central to this model. The model applies to almost any test if biological variation can be defined. A pragmatic method for the design of internal quality control is presented.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1146
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    ABSTRACT: The non-vitamin K antagonist oral anticoagulants (NOACs) apixaban, dabigatran, and rivaroxaban are being administered in fixed doses without routine monitoring of anticoagulant activities. Despite this key advantage over vitamin K antagonists (VKAs), assessment of anticoagulant intensities is required in various clinical circumstances. We developed a multi-analyte approach for mass spectrometric analysis of NOACs in human plasma. Plasma samples were precipitated with acetonitrile. Separation was achieved by liquid chromatography using a C18 column and a gradient elution within a run time of 2.5 min. Positive electrospray ionization was used and ion transitions monitored by a triple quadrupole mass spectrometer. Stable-isotope-labeled analogues of analytes were employed as internal standards for quantitative analysis. Certified external quality control samples were obtained for external validation. For all analytes, linearity could be demonstrated over the concentration range of 1-500 μg/L (R2>0.999), and the calculated limits of quantification were <1 μg/L. Results for inter- and intra-day assay precision and trueness were obtained using internal quality control samples and remained within the acceptance criterion of ±15%. External quality control samples were measured at the specified nominal values with inter- and intra-day precisions <14%. Matrix effects were fully compensated by co-eluting internal standards, which in turn did not relevantly influence ionization efficiency. The method enables rapid and reliable simultaneous determination of NOAC concentrations in human plasma. It was successfully introduced into clinical practice; a case with rivaroxaban overdose is presented to exemplify the method's applicability.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1108
  • Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0109
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    ABSTRACT: The routine use of brain natriuretic peptide (BNP) in pediatric cardiac surgery remains controversial. Our aim was to test whether BNP adds information to predict risk in pediatric cardiac surgery. In all, 587 children undergoing cardiac surgery (median age 6.3 months; 1.2-35.9 months) were prospectively enrolled at a single institution. BNP was measured pre-operatively, on every post-operative day in the intensive care unit, and before discharge. The primary outcome was major complications and length ventilator stay >15 days. A first risk prediction model was fitted using Cox proportional hazards model with age, body surface area and Aristotle score as continuous predictors. A second model was built adding cardiopulmonary bypass time and arterial lactate at the end of operation to the first model. Then, peak post-operative log-BNP was added to both models. Analysis to test discrimination, calibration, and reclassification were performed. BNP increased after surgery (p<0.001), peaking at a mean of 63.7 h (median 36 h, interquartile range 12-84 h) post-operatively and decreased thereafter. The hazard ratios (HR) for peak-BNP were highly significant (first model HR=1.40, p=0.006, second model HR=1.44, p=0.008), and the log-likelihood improved with the addition of BNP at 12 h (p=0.006; p=0.009). The adjunction of peak-BNP significantly improved the area under the ROC curve (first model p<0.001; second model p<0.001). The adjunction of peak-BNP also resulted in a net gain in reclassification proportion (first model NRI=0.089, p<0.001; second model NRI=0.139, p=0.003). Our data indicates that BNP may improve the risk prediction in pediatric cardiac surgery, supporting its routine use in this setting.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1084
  • Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0066
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    ABSTRACT: Urokinase plasminogen activator receptor (uPAR) is a key component of the fibrinolytic system involved in extracellular matrix remodeling and angiogenesis. Novel animal models supported the key role of uPAR not only in fibrosis but also in systemic sclerosis (SSc)-related microvascular abnormalities. The aim of this study was to investigate plasma soluble uPAR (suPAR) levels in SSc, and their association with organ-specific involvement. suPAR concentrations were measured by ELISA in SSc patient (n=83) and in healthy controls (n=29). Simultaneously, CRP and ESR were assessed. Detailed clinical data including skin, lung, heart and microvascular characteristics were evaluated at sampling. suPAR values were higher in SSc patients than in controls. Subgroup analysis showed higher suPAR values in diffuse cutaneous- than in limited cutaneous SSc and correlated with anti-Scl-70+. suPAR levels also associated with pulmonary function test parameters of fibrosis, presence of microvascular lesions (e.g., Raynaud phenomenon, naifold capillaroscopic abnormalities and digital ulcers) and arthritis. Our data indicate that suPAR might be a valuable early diagnostic marker of SSc which also correlates with disease severity.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0079
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    ABSTRACT: Quality in healthcare is ideally at an optimal benchmark, but must be at least above the minimal standards for care. While laboratory quality is ideally judged in clinical terms, laboratory medicine has also used biological variations and state-of-the-art criteria when, as is often the case, clinical outcome studies or clinical consensus are not available. The post-analytical phase involves taking quality technical results and providing the means for clinical interpretation in the report. Reference intervals are commonly used as a basis for data interpretation; however, laboratories vary in the reference intervals they use, even when analysis is similar. Reference intervals may have greater clinical value if they are both optimised to account for physiological individuality, as well as if they are harmonised through professional consensus. Clinical decision limits are generally superior to reference intervals as a basis for interpretation because they address the specific clinical concern in any patient. As well as providing quality data and interpretation, the knowledge of laboratory experts can be used to provide targeted procedural knowledge in a patient report. Most profoundly critically abnormal results should to be acted upon to minimise the risk of mortality. The three steps in quality report interpretation, (i) describing the abnormal data, (ii) interpreting the clinical information within that data and (iii) providing knowledge for clinical follow-up, highlight that the quality of all laboratory testing is reflected in its impact on clinical management and improving patient outcomes.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0016
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    ABSTRACT: Allowable total error is derived in many ways, often from data on biological variation in normal individuals. We present a new principle for evaluating allowable total error: What are the diagnostic consequences of allowable total errors in terms of errors in likelihood ratio (LR)? Glycated hemoglobin A1c in blood (HbA1c) in diagnosing diabetes mellitus is used as an example. Allowable total error for HbA1c is 3.0% derived from data on biological variation compared to 6.0% as defined by National Glycohemoglobin Standardization Program (NGSP). We estimated a function for LR of HbA1c in diagnosing diabetes mellitus using logistic regression with a clinical database (n=572) where diabetes status was defined by WHO criteria. Then we estimated errors in LR that correspond to errors in the measurement of HbA1c. Measuring HbA1c 3% too low at HbA1c of 6.5 percentage points (the suggested diagnostic limit) gives a LR of 0.36 times the correct LR, while measuring HbA1c 3% too high gives a LR of 2.77 times the correct LR. The corresponding errors in LR for allowable total error of 6% are 0.13 and 7.69 times the correct LR, respectively. These principles of evaluating allowable total error can be applied to any diagnostically used analyte where the distribution of the analyte's concentration is known in patients with and without the disease in a clinically relevant population. In the example used, the allowable total error of 6% leads to very erroneous LRs, suggesting that the NGSP limits of ±6% are too liberal.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1125
  • Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0027
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    ABSTRACT: Biological variation (BV) data enable assessment of the significance of changes in serial measurements observed within a subject and are used to set analytical quality specifications. This data is available in a database held in Westgard website (http://www.westgard.com/biodatabase1.htm). Some limitations of this data, however, have been identified in recent published reviews. The aim of this paper is to show the reliability of the published BV data and to identify ongoing works to address some of its limitations. The BV data currently hosted on the Westgard website was examined. Distribution of measurands stratified by the number of cited references upon which the database entry is based and the distribution of papers stratified by publication year, are shown. Moreover, BV data available in literature for glycated hemoglobin, C-reactive protein, glycated albumin, alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transferase are evaluated. The results obtained show that most BV data come just from a few papers or only one paper and that a lot of publications are dated, therefore this data is too obsolete to be used. Furthermore critical review of the BV database highlights a number of factors that might impact on the reliability of the BV data entries and translation into current practice. A number of issues clearly undermine the value of the current database. These issues are being considered by the European Federation of Clinical Chemistry and Laboratory Medicine, biological variation working group, in collaboration with a Spanish group responsible for the database updating.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1133
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    ABSTRACT: External Quality Assurance (EQA) is a vital tool in laboratory medicine to assess individual laboratory analytical performance and also the differences between the results from different laboratories. This information is also useful for professional bodies and manufacturers as part of post-market surveillance. The process involves the measurement of one or more samples by many laboratories and then assessment of the results. Individual results are generally assessed by how far they lie from a target, which may be established using reference methods or a median of some or all of the submitted results. The distance of a result from the target is compared with analytical performance specifications in order to assess the analytical quality. One of the uses of the Stockholm hierarchy of performance goals is to set the performance specifications for analysis of EQA results. Fifteen years after the Stockholm consensus meeting, EQA analytical performance specifications appear to still vary widely between EQA providers. This can be due to a range of factors, including the rationale for setting the criteria, the expected response to a failure to meet the specified performance, the clinical meaning behind meeting the specifications, and the possible need for further analytical improvements. There are also differences in the models chosen to set the criteria, usually either state of the art or biological variation, and then differences in how these are applied. While harmonisation of EQA performance specifications may be some time off, all EQA providers should define the nature of their specifications and the basis for their selection and make this information available to customers.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1268
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    ABSTRACT: In the general classical model for diagnoses based on a single analytic component, distributions of healthy and diseased are compared and several investigations of varying analytical performance on the percentage of misclassifications have been published. A new concept based on an alternative type of diagnosing, based on sharp decision limits has been introduced in diagnostic guidelines, but only a few publications on investigation of analytical performance have been seen. The two diagnostic models (bimodal and unimodal) based on natural logarithmic Gaussian distributions are simulated. In the bimodal model it is possible to evaluate the influence of prevalence of disease in combination with varying analytical performances. In the unimodal model the prevalence is pre-decided by the chosen decision limit. In this model the influence of analytical performance is investigated for diagnosing diabetes using haemoglobin A1c (HbA1c), and for patients with high and low risk for coronary heart disease defined by serum-cholesterol concentrations. For HbA1c the guidelines and recommendations define a maximum inter-laboratory coefficient of variation of 3.5%, but this is in DCCT units (without a true zero-point), so after transformation to IFCC units (which are proportional) it was 5.2%, which allows for analytical bias as high as approximately ±9%. Consequently, analytical quality specifications should be separated as maximum bias and imprecision.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1138
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    ABSTRACT: Analytical performance specifications can be based on three different models: the effect of analytical performance on clinical outcome, based on components of biological variation of the measurand or based on state-of-the-art. Models 1 and 3 may to some degree be combined by using case histories presented to a large number of clinicians. The Norwegian Quality Improvement of Primary Care Laboratories (Noklus) has integrated vignettes in its external quality assessment programme since 1991, focusing on typical clinical situations in primary care. Haemoglobin, erythrocyte sedimentation rate (ESR), HbA1c, glucose, u-albumin, creatinine/estimated glomerular filtration rate (eGFR), and Internationl Normalised Ratio (INR) have been evaluated focusing on critical differences in test results, i.e., a change from a previous result that will generate an "action" such as a change in treatment or follow-up of the patient. These critical differences, stated by physicians, can translate into reference change values (RCVs) and assumed analytical performance can be calculated. In general, assessments of RCVs and therefore performance specifications vary both within and between groups of doctors, but with no or minor differences regarding specialisation, age or sex of the general practitioner. In some instances state-of-the-art analytical performance could not meet clinical demands using 95% confidence, whereas clinical demands were met using 80% confidence in nearly all instances. RCVs from vignettes should probably not be used on their own as a basis for setting analytical performance specifications, since clinicians seem "uninformed" regarding important principles. They could rather be used as a background for focus groups of "informed" physicians in discussions of performance specifications tailored to "typical" clinical situations.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1280
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    ABSTRACT: Circulating cell-free DNA (ccfDNA) has been confirmed as a useful biomarker in cancer and pre-natal clinical practice. One of the main critical points in using ccfDNA is a lack of standardisation for sample processing methods, storage conditions, procedures for extraction, and quantification that can affect ccfDNA quality and quantity. We report the results obtained from the SPIDIA-DNAplas, one of the EU SPIDIA (Standardisation and improvement of generic pre-analytical tools and procedures for in vitro diagnostics) subprojects based on the implementation of an External Quality Assessment scheme for the evaluation of the influence of the pre-analytical phase on ccfDNA. This is the first reported quality control scheme targeting ccfDNA for pre-analytical phase studies. Fifty-six laboratories throughout Europe were recruited. The participating laboratories received the same plasma sample and extracted ccfDNA by using their own procedures, at defined plasma storage conditions, and sent the isolated ccfDNA to the SPIDIA facility for analyses. Laboratory performance was evaluated by using specific quality parameters such as ccfDNA integrity (by multiplex PCR) and yield (by qPCR). The analysis of the ccfDNA extracted by the laboratories showed that most of them (53 of 56) were able to recover ccfDNA but only 12.5% recovered non-fragmented ccfDNA. Extraction methods specifically designed for ccfDNA preserved the integrity profile. The evidence-based results of the SPIDIA-DNAplas EQA have been proposed as a basis for the development of a Technical Specification by the European Committee for standardisation (CEN).
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2014-1161
  • Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0197
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    ABSTRACT: The term "qualitative test" is ambiguous and should not be used for nominal (classification) or ordinal (grading) tests. Characteristics for nominal and ordinal scale test results, such as traceability and uncertainty, remains to be established before general performance criteria can be agreed upon. For ordinal binary test with a quantitative back ground scale an assay could be characterized with the three quantities "C5", "C50", and "C95". The C50-value, or the equivalence point, ought to be declared by the manufacturers of diagnostic products. For the correct understanding and communication of results from ordinal and nominal tests the way of expressing the results also need to be harmonized.
    Clinical Chemistry and Laboratory Medicine 04/2015; DOI:10.1515/cclm-2015-0005