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Editor-in-chief
Maria Stella Graziani

Deputy Director
Martina Zaninotto

Associate Editors
Ferruccio Ceriotti
Davide Giavarina
Bruna Lo Sasso
Giampaolo Merlini
Martina Montagnana
Andrea Mosca
Paola Pezzati
Rossella Tomaiuolo
Matteo Vidali

EIC Assistant
Francesco Busardò

International Advisory Board Khosrow Adeli Canada
Sergio Bernardini Italy
Marcello Ciaccio Italy
Eleftherios Diamandis Canada
Philippe Gillery France
Kjell Grankvist Sweden
Hans Jacobs The Netherlands
Eric Kilpatrick UK
Magdalena Krintus Poland
Giuseppe Lippi Italy
Mario Plebani Italy
Sverre Sandberg Norway
Ana-Maria Simundic Croatia
Tommaso Trenti Italy
Cas Weykamp The Netherlands
Maria Willrich USA
Paul Yip Canada


Publisher
Biomedia srl
Via L. Temolo 4, 20126 Milano

Responsible Editor
Giuseppe Agosta

Editorial Secretary
Chiara Riva
Biomedia srl
Via L. Temolo 4, 20126 Milano
Tel. 0245498282
email: biochimica.clinica@sibioc.it

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ISSN print: 0393 – 0564
ISSN digital: 0392- 7091



BC: Articoli scritti da A. Carobene

Intra-subject biological variation and reference change value data made available to clinicians: a step toward the interpretation of patient test results
Biochimica Clinica ; 45(4) 427-432
Lettere all'editore - Letters to the editor
 
Ruolo del laboratorio nella diagnostica differenziale di un grave caso di anemia
The role of the clinical laboratory in the differential diagnosis in a patient with severe anemia
M. Seghezzi  |  A. Carobene  |  S. Buoro  | 
<p>A male, 54 years old, presented to the emergency department of Bergamo Papa Giovanni XXIII hospital, with confusion and neurological symptoms.<br />The peripheral blood cells count, performed on the Sysmex XN-20, showed a severe macrocytic anemia: hemoglobin 42 g/L, mean corpuscular volume 107 fL, accompanied by the morphology flag &ldquo;fragments&rdquo;. The morphological evaluation on the blood smear, strongly recommended with a blood cell count showing such values, confirmed the presence of erythroblasts, and revealed several morphological alterations (remarkable anisopoikilocytosis, basophilic stippling, hypersegmented neutrophils). The patient was admitted to the hospital and transfused. Further investigations showed a severe deficiency of vitamin B12, an abnormal lactate dehydrogenase activity, and an undetectable haptoglobin concentration. After the transfusions, the patient recovered quickly, and was able to report about a previous gastric resection; the information was missed at admission because of the patients confusional state. The possibility of metal poisoning or cupper deficiency were not investigated.</p>
Biochimica Clinica ; 45(4) e35
Casi clinici - Case report
 
Tecniche di apprendimento automatico basato sui risultati di esami di medicina di laboratorio nella diagnosi e prognosi per i pazienti COVID-19: una revisione sistematica
Machine Learning based on laboratory medicine test results in diagnosis and prognosis for COVID-19 patients: a systematic review
<p>The rapid detection of SARS-CoV-2 infections is essential for both diagnostic and prognostic reasons: however, the current gold standard for COVID-19 diagnosis, that is the rRT-PCR test, is affected by long turnaround time, potential shortage of reagents, high false-negative rates and high costs. Thus, Machine Learning (ML) based methods have recently attracted increasing interest, especially when applied to digital imaging (x-rays and CT scans).<br />In this article, we review the literature on ML-based diagnostic and prognostic methods grounding on hematochemical parameters. In doing so, we address the gap in the existing literature, which has so far neglected the application of ML to laboratory medicine. We surveyed 20 research articles, extracted from the Scopus and PubMed indexes. These studies were characterized by a large heterogeneity, in terms of considered laboratory and clinical parameters, sample size, reference population, employed ML methods and validation procedures. Most studies were found to be affected by reporting and replicability issues: among the surveyed studies, only three reported complete information regarding the analytic methods (units of measure, analyzing equipment), while nine studies reported no information at all. Furthermore, only six studies reported results on independent external validation. In light of these results, we discuss the importance of a tighter collaboration between data scientists and medicine laboratory professionals, so as to correctly characterize the relevant population, select the most appropriate statistical and analytical methods, ensure reproducibility, enable the correct interpretation of the results, and gain actual usefulness by applying ML methods in clinical practice.</p>
Biochimica Clinica ; 45(4) 348-364
Rassegne - Reviews
 
Identificazione di positività al SARS-CoV-2 attraverso metodi di Machine Learning sui dati dell’esame emocromocitometrico: validazione esterna di modelli allo stato dell'arte
Identification of SARS-CoV-2 positivity using machine learning methods on blood count data: external validation of state-of-the-art models.
<p>Introduction: The aim of the paper is to present the results from the process of external validation of a number of machine learning (ML) models that had been previously developed to detect SARS-CoV-2 virus positivity on both symptomatic and asymptomatic patients on the basis of the complete blood count (CBC) test.<br />Methods: Briefly, models were trained using a dataset of 816 COVID-19 positive and 920 negative cases collected at the emergency departments of IRCCS Hospital San Raffaele and IRCCS Istituto Ortopedico Galeazzi. 21 parameters, including the results of the CBC analysis, age [60.9 (0.9) years], gender (57% males) and the presence of COVID-19 related symptoms were used. The validation regarded the evaluation of the error rate (through different metrics, including accuracy, sensitivity, specificity and the area under the curve (AUC)) of the models considered. This external validation was conducted on two well balanced datasets coming from two different hospitals in Northern Italy: Desio hospital and Bergamo Papa Giovanni XXIII hospital. 163 positive and 174 true negative patients from Desio, and 104 positive and 145 true negative from Bergamo were included in the validation.<br />Results: The performance of the predictive models is satisfactory as we can report an average AUC of 95% for both external datasets.<br />Conclusion: ML models have been applied to hematological parameters for a more rapid and cost-effective detection of the COVID-19 disease. We make the point that validated models may be useful in the management and early detection of potential COVID-19 patients.</p>
Biochimica Clinica ; 45(3) 281-289
Contributi Scientifici - Scientific Papers
 
Utilizzo della differenza critica per una corretta interpretazione dei valori di creatinina sierica
A. Carobene  |  M. Vidali  | 
Biochimica Clinica ; 45(3) s104-s106
Lettere all'editore - Letters to the editor
 
Valutazione critica e meta-analisi delle stime di variabilità biologica degli analiti relativi alle patologie renali
Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes
<p>Objective: Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma; albumin, creatinine, cystatin C, chloride, potassium, sodium and urea.&nbsp;&nbsp;<br />Content: Relevant studies were identified from a historical BV database as well as by systematic literature searches. Retrieved publications were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Metaanalyses of BIVAC compliant studies with similar design were performed to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV estimates. Out of the 61 identified papers, three received a BIVAC grade A, four grade B, 48 grade C, five grade D grade and one was not appraised as it did not report numerical BV estimates. Most studies were identified for creatinine (n=48). BV estimates derived from the meta-analysis were in general lower than previously reported estimates for all analytes except urea. For some measurands, BV estimates may be influenced by age or states of health, but further data are required.&nbsp;&nbsp;<br />Summary: This review provides updated global BV estimates for kidney related measurands. For all measurands except for urea, these estimates were lower than previously reported.&nbsp;&nbsp;<br />Outlook: For the measurands analyzed in this review, there are sufficient well-designed studies available to publish a trustworthy estimate of BV. However, for a number of newly appearing kidney markers no suitable data is available and additional studies are required.&nbsp;&nbsp;</p>
Biochimica Clinica ; 45(3) s060-s070
Contributi Scientifici - Scientific Papers
 
Variabilità biologica dei parametri dell’esame emocromocitometrico in soggetti sani
Biological variation estimates of complete blood count parameters in healthy subjects
<p>Background: the complete blood count (CBC) is the test more frequently requested in clinical practice. Therefore, estimating the biological variation (BV) of CBC parameters is essential for assessing the analytical performance of hematological analyzers and for enabling accurate data interpretation and appropriate clinical management. This study was aimed to define BV estimates and reference change value (RCV) of CBC parameters.<br />Methods: the study population consisted of 21 healthy volunteers, who had BV of CBC parameters assessed with Sysmex XN. The study protocol, the analytical measurements and the statistical analysis were carried out according to current recommendations of the European Federation for Clinical Chemistry and Laboratory Medicine (EFLM).<br />Results: Within-subject BV ranged between 0,3% for mean cell hemoglobin (MCH) and 19,7% for immature granulocytes (IG), whilst between-subjects BVs ranged between 0,9% for mean corpuscolar haemoglobin concentration (MCHC) and 66,6% for microcytic red blood cells (Micro-R). The RCV ranged between 2,3% for MCH and 73,5% for IG.<br />Conclusion: This study has allowed the estimation of BV of many CBC parameters, some of which have not been currently explored, thus leading the way to use RCV calculated according to time of monitoring and/or differentiated by sex.</p>
Biochimica Clinica ; 43(4) 384-393
Contributi Scientifici - Scientific Papers
 
Protocollo operativo per la verifica della comparabilità dei risultati di laboratorio ottenuti su più procedure analitiche
Protocol to verify the comparability of quantitative laboratory results obtained with different measurementprocedures.
<p>With the growth and merging of clinical laboratories, very frequently analytical tests are performed onmultiple instruments within one or multiple locations. In these situations, there is the need of verifying thecomparability of patient results obtained with different analysers and/or different measurement procedures. Theimportance of this verification is further emphasised when considering that it is included into the ISO 15189specifications. This protocol provides step-by-step guidance on how to assess results comparability in differentscenarios. Up to four experimental designs are presented to meet laboratories&rsquo; needs, with details and examples onfrequency of testing, definition of acceptability criteria, samples selection, sample size calculation, statistical analysisand reporting.</p>
Biochimica Clinica ; 43(2) 228-243
Documenti SIBioC - SIBioC Documents
 
Importanza dell’utilizzo di Biological Variation Data Critical Appraisal Checklist nel disegno sperimentale di studi di variabilità biologica. Valutazione a confronto di due pubblicazioni sulla variabilità biologica della proteina S100βe dell’enolasi neu
The importance of the Biological Variation Data Critical Appraisal Checklist when designing experimental studies on biological variation. Comparison of two papers reporting biological variation results for S100-β and neuron-specific enolase proteins
<p>The Biological Variation Data Critical Appraisal Checklist (BIVAC) has been designed to evaluate biological variation (BV) studies and the reliability of the associated BV estimates. To illustrate its utility, two studies delivering within-subject BV (CVI) data for S100-&beta; protein and neuron-specific enolase (NSE), markers typically used for melanoma and neuroendocrine tumors, respectively, were appraised using BIVAC. Data from the European Biological Variation Study (EuBIVAS) and the recently published Johnson et al. study (ref n 11) were scored using the 14 BIVAC quality items (QI), with alternatives A, B, C and/or D to verify whether the elements required to obtain reliable BV data, were present and appropriately documented. Grade A indicates compliance with all the QIs and D indicates non compliance. The sizes of the confidence interval (CI) around the CVI estimates were also compared. Johnson&rsquo;s study received a BIVAC grade C, EuBIVAS a grade A. EuBIVAS is a large scale study, with&nbsp;1609 and 1728 results for NSE and S100-&beta;, respectively. In Johnson&rsquo;s study, only 40 results were available. The EuBIVAS CVI estimates [NSE, 10.9% (10.3-11.5); S100-&beta; , 10.2% (9.6-10.7)] were clearly lower than Johnson&rsquo;s CVIs [NSE, 22.1% (9.9-34.3); S100-&beta;, 18.9% (8.5-29.4)]. The overlapping CI between the two estimates are caused by Johnson&rsquo;s CI being about 20 times larger than the corresponding EuBIVAS CI. It is likely that studies that do not comply with all BIVAC QI deliver less reliable, and possibly too high, CVI estimates. Adherence to the BIVAC ensures safe clinical application of BV estimates.</p><p>&nbsp;</p>
Biochimica Clinica ; 43(1) 059-066
Contributi Scientifici - Scientific Paper
 
La variabilità biologica: le basi teoriche e l’esperienza dei Gruppi di Lavoro della Federazione Europea di Chimica Clinica e Medicina di Laboratorio
Biological Variation: theoretical bases and the experience of the EFLM working groups
A. Carobene  | 
<p>In laboratory medicine, the test results of a subject vary over the time due to three factors: pre-analytical variation, analytical variation, and intra-individual biological variation (BV) that depends on the subject physiology. Appropriately, quantified and characterized BV data have many applications. Besides the setting of performance specifications, the data can also be used to define significance of change between measurements within a subject, and to assess the utility of conventional population-based reference intervals. Given the importance of BV data, it is clear that the access to them is essential for the clinical laboratory, and that users should be confident that they are well characterized and fit for purpose. To make the data accessible, a BV database has been made available via the Westgard website. However, in recent years, concerns have been raised about the quality of the published BV data. To address some of the concerns, the EFLM Task and Finish Group on Biological Variation has developed the Biological Variation Data Critical Appraisal Checklist (BIVAC), with the aim to verify whether publications in the field have included all essential elements that may influence the veracity of associated BV estimates. Moreover, to address the need to deliver new reliable data, the EFLM Working Group on BV has designed and initiated the European Biological Variation Study (EuBIVAS) to obtain high-quality BV estimates for the highest possible number of measurands. The aim of this review, in addition to an overview about the theory of BV, is to describe BIVAC rationale and to present new BV estimates obtained by EuBIVAS.</p>
Biochimica Clinica ; 42(1) 15-25
Rassegne - Reviews
 
Il progetto pilota SIBioC di VEQ della misura dell’emoglobina glicata
Pilot SIBioC EQAS project on glycated hemoglobin measurement
<p>Two fresh blood samples collected with EDTA&nbsp;were distributed by courier in December 2014 to 206 Italian laboratories asking for the determination of their HbA<sub>1c</sub> concentrations. Target HbA<sub>1c</sub> values were assigned by the IFCC reference measurement procedure based on HPLC capillary&nbsp;electrophoresis. The results, collected from 193 laboratories using analytical systems mainly from five&nbsp;manufacturers (Bio-Rad Laboratories, A. Menarini Diagnostics, Roche Diagnostics, Sebia and Tosoh), showed a&nbsp;global variability (in terms of CV) of 5.3% and 3.8% at HbA<sub>1c</sub> values of 37.4 mmol/mol (sample 1) and 62.0 mmol/mol&nbsp;(sample 2), respectively. Globally, 84% of the participants reported HbA<sub>1c</sub> results within the total allowable error (TE)&nbsp;of 8.6% (sample 1) and 93% for sample 2. These percentages decreased to 70% and 77%, respectively, when using&nbsp;a goal for the allowable TE of 6.0% as criterion. Inter-laboratory CVs, calculated per group of methods, were between&nbsp;3.3% and 5.0% and between 2.2% and 3.7% for sample 1 and 2, respectively. Tosoh users registered the smaller&nbsp;inter-laboratory CV in sample 1 and Sebia&rsquo;s in sample 2. With regard to trueness, all methods had a mean bias &le;2.8%&nbsp;respect to the target values, with the exception of Tosoh (bias of +6.1% and +5.8%, for samples 1 and 2, respectively).</p>
Biochimica Clinica ; 39(6) 568-574
Contributi scientifici - Scientific Papers
 
Valutazione dell’impatto del processo di standardizzazione sulla qualità della misura della creatininemia nei laboratori italiani
Evaluation of the impact of standardization process on the quality of serum creatinine determination in Italian laboratories
<p style="text-align: justify;">Evaluation of the impact of standardization process on the quality of serum creatinine determination in Italian laboratories. Creatinine determination in serum is a key indicator of kidney glomerular function. A reference measurement system for standardization of creatinine measurements is now available and virtually all IVD manufacturers have aligned their creatinine assays to this system. The aim of this work was to verify if and how these standardization efforts have improved the state of the art of creatinine determination in Italy through the analysis of Prolarit EQAS results using control materials with target values assigned by a traceable method (enzymatic assay calibrated against the NIST SRM 967). Results obtained during 2006, 2010, and 2011 schemes by participating laboratories showed a general good alignment at creatinine concentrations <span style="font-family: symbol;">&#61566;</span>2.00 mg/dL, with 2011 results &#8211; except for one method group &#8211; well inside the desirable bias (<span style="font-family: symbol;">&#61617;</span>4%). At higher concentrations, whereas the overall bias was small in 2010, for some groups using alkaline picrate (AP) methods it became significantly negative in 2011. The performance markedly worsens at creatinine physiologic concentrations, where a significant positive bias (up to <span style="font-family: symbol;">&#61566;</span>20%) is still present for most of the AP-based analytical systems. Unexpectedly, with few exceptions, no evident improvement in individual assay bias was noted from pre- (2006) to post-standardization (2011) periods. The enzymatic method groups were the only always presenting an acceptable bias for all concentration levels, in addition to showing the lowest between-laboratory variability. The number of laboratories using enzymatic methods, however, still remains only 7% of the total. In conclusion, our EQAS performance data indicate that most of the current "standardized" creatinine methods based on AP reaction do not perform well, mainly at the lower creatinine concentrations. This inaccuracy of creatinine measurements can adversely impact the estimation of glomerular filtration rate by equations and the evaluation of kidney function in pediatrics.</p>
Biochimica Clinica ; 36(6) 414-424
Contributi Scientifici - Scientific Papers
 
Big data e intelligenza artificiale in medicina di laboratorio: una indagine SiBioC nei i laboratori clinici italiani
A survey on Artificial Intelligence and Big Data utilisation in Italian Clinical Laboratories
<p>Objectives: the Italian Society of Clinical Biochemistry and Clinical Molecular Biology (SIBioC) Big Data and Artificial Intelligence (BAI) Working Group promoted a survey to frame the knowledge, skills, and technological predisposition in Clinical Laboratories. Methods: questionnaire, focusing on digitization, IT infrastructures, data accessibility, and BAI projects underway was sent to 1351 SIBioC participants. The responses were evaluated using SurveyMonkey software and Google Sheets. Results: the 227 respondents (17%) from all over Italy (47% of 484 labs), mainly biologists, laboratory physicians and managers, mostly from laboratories of public hospitals, revealed lack of hardware, software and corporate Wi-Fi, and dearth of PCs. Only 25% work daily on clouds, while 65%-including Laboratory Directors-cannot acquire health data from sources other than laboratories. Only 50% of those with access can review a clinical patient&rsquo;s health record, while the other access only to laboratory information. The integration of laboratory data with other health data is mostly incomplete, which limits BAI-type analysis. Many are unaware of integration platforms. Over 90% report pulling data from the LIS, with varying degrees of autonomy. Very few have already undertaken BAI projects, frequently relying on IT partnerships. The majority consider BAI as crucial in helping professional judgments, indicating a growing interest. Conclusions: the questionnaire received relevant feedback from SIBioC participants. It highlighted the level of expertise and interest in BAI applications. None of the obstacles stands out more than the others, emphasising the need to allaround work: IT infrastructures, data warehouses, BAI analysis software acquisition, data accessibility and training.</p>
Biochimica Clinica ; 17(1)
Contributi Scientifici - Scientific Papers
 
Standardizzazione e armonizzazione dell’albuminuria: a che punto siamo?
M. Mussap  |  A. Carobene  | 
Biochimica Clinica ; 17(1)
Lettere all'Editore - Letters to the Editors