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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 M. Locatelli

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
 
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
 
Valutazione di IgG e IgM anti-SARS-CoV-2 su Maglumi 800 (Snibe)
Evaluation of Anti-SARS-CoV-2 immunoglobulin G and M on Snibe Maglumi 800
<p>Introduction: the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a due to new beta-coronavirus causing the pandemic called Coronavirus disease 2019 (COVID-19). The evaluation of the presence of immunoglobulin G and M anti-SARS-CoV-2 (IgG and IgM) is important to understand the epidemiology of the disease and to confirm the presence of the disease when clinical signs are present, but RNA is not detected.<br />Methods: leftover serum samples from different types of patients were used: sera from biobank collected in 2018 as negative controls; patients recovering from the disease as positive controls; patients presenting at the Emergency Room with a positive rhino-pharyngeal swab; patients in Intensive Care Units. Anti-SARS-CoV-2 IgG and IgM were measured with MAGLUMI 2019-nCoV IgM/IgG Kits on Maglumi 800.<br />Results: one out of 61 expected negative resulted positive, and 2 were borderline for IgG (95% specificity, 95%CI 89.6-100), 1 positive for IgM (98.4% specificity, 95%CI 95.2-100); one out of 41 expected IgG positive resulted negative (97.6% sensitivity, 95%CI 92.8-100). All the 13 Intensive Care patients were positive for IgG, 11 for IgM. IgG were negative in 50.9% of the 55 swab positive from Emergency Room patients, while IgM were negative in 87.3%.<br />Discussion: sensitivity and specificity of the test appear good for IgG, some false positive is expected and low antibody titles in subjects with no disease story should be rechecked with an alternative method. IgM show a good specificity, but the unexpected low percentage of positivity in Emergency Room patients compared to IgG, pose some relevant doubts on the sensitivity of the test.</p>
Biochimica Clinica ; 44(4) 025-026
COVID-19 - COVID-19
 
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
 
Raccomandazioni per l’identificazione e la gestione dei risultati critici nei laboratori clinici
Recommendations for the detection and management of critical results in clinical laboratories
<p>Critical results, (also known as panic or alarm results) identify a laboratory test result associated with a serious risk for the patient&rsquo;s health, requiring immediate communication to the physician to establish appropriate therapeutic interventions. The adoption of an efficient procedure for the communication of critical values/results is crucial for clinical, ethical, organizational reasons, because it is a requirement for laboratory accreditiation and because of potential legal consequences related to the lack of notification of harmful laboratory results. In 2008, the Italian Society of Clinical Biochemistry and Laboratory Medicine (SIBioC) published its first consensus-based recommendation for the detection and management of critical values in clinical laboratories, with the aim to improve the implementation of standardized and universally accepted procedures, promoting an essential policy toward rational and efficient solutions to this issue. These new recommendations represent a complete review of the first document. Using the same consensus conference method between experts of scientific societies, the main aspects of clinical risk, patient safety and legal liability of health care workers were re-considered. The SIBioC and the Italian Society of Laboratory Medicine (SIPMeL), Intersociety Study Group on Standardization of extra-analytical variability of laboratory results, together with the Italian Society of Ergonomics and Human Factors (SIE) collaboration, issued the present join document.</p>
Biochimica Clinica ; 42(2) 167-179
Documenti SIBioC - SIBioC Documents
 
Armonizzazione in Medicina di Laboratorio
Harmonization in Laboratory Medicine
F. Ceriotti  |  M. Panteghini  |  A. Tosetto  |  V. Valentini  |  L. Politi  |  R. Rolla  |  T. Guastafierro  |  T. Köken  |  E. Capoluongo  |  C. Mazzaccara  |  V. D'Argenio  |  V. D'Argenio  |  G. Lippi  |  M. Plebani  |  D. Giavarina  |  M. Berardi  |   A survey on sample matrix and preanalytical management in clinical laboratories  |  D. Bozzato  |  G. Messeri  |  M. Zaninotto  |  M. Vidali  |  A. Padoan  |  G. Parigi  |  A. Clerico  |  L. Sciacovelli  |  M. Ciaccio  |  G.L. Salvagno  |  G. Barberio  |  G. Barberio  |  G.L. Salvagno  |  M. Pepe  |  M. Panteghini  |  F. Braga  |  G. Gessoni  |  M. Montagnana  |  N. Doğan  |  M. Barberis  |  M. Barberis  |  A. Marchetti  |  F. Borrillo  |  L. Bonfanti  |  P.M. Ness  |  G. Messeri  |  S. Nannini  |  J. Queraltò  |  M. Zaninotto  |  A. Mosca  |  BM. Henry  |  G. Santini  |  A. Coglianese  |  V. D'Argenio  |  E. Fiorio  |  L. Crinò  |  M. A. V. Willrich  |  A. Modenese  |  M. Berardi  |  G. Nordera  |  M. Girelli  |  R. Tomaiuolo  |  D. Giavarina  |  R. Dittadi  |  L. Pighi  |  V. Guaraldo  |  G. Bambagiotti  |  E. Franceschini  |  R. Danesi  |  M. Locatelli  |  F. Balboni  |  D. Cosseddu  |  M. Savoia  |  S. Bernardini  |  C. Domenichini  |  M. Lamonaca  |  M. Perrone  |  M. Perrone  |   per il Gruppo di Studio Intersocietario SIBioC-SIPMeL Diabete Mellito  |  P. Pradella  |  A. Padoan  |  M.T. Sandri  |  L. Belloni  |  A. D'Avolio  |  T. Trenti  |  A. Fortunato  |  T. Trenti  | 
Biochimica Clinica ; 39(6) 546-547
Editoriale - Editorial