BACKGROUNDThere is considerable variation in disease behavior among patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 . Genomewide association analysis may allow for the identification of potential genetic factors involved in the development of Covid-19. METHODSWe conducted a genomewide association study involving 1980 patients with Covid-19 and severe disease (defined as respiratory failure) at seven hospitals in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe. After quality control and the exclusion of population outliers, 835 patients and 1255 control participants from Italy and 775 patients and 950 control participants from Spain were included in the final analysis. In total, we analyzed 8,582,968 single-nucleotide polymorphisms and conducted a meta-analysis of the two case-control panels. RESULTSWe detected cross-replicating associations with rs11385942 at locus 3p21.31 and with rs657152 at locus 9q34.2, which were significant at the genomewide level (P<5×10 −8 ) in the meta-analysis of the two case-control panels (odds ratio, 1.77; 95% confidence interval [CI], 1.48 to 2.11; P = 1.15×10 −10 ; and odds ratio, 1.32; 95% CI, 1.20 to 1.47; P = 4.95×10 −8 , respectively). At locus 3p21.31, the association signal spanned the genes SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6 and XCR1. The association signal at locus 9q34.2 coincided with the ABO blood group locus; in this cohort, a blood-group-specific analysis showed a higher risk in blood group A than in other blood groups (odds ratio, 1.45; 95% CI, 1.20 to 1.75; P = 1.48×10 −4 ) and a protective effect in blood group O as compared with other blood groups (odds ratio, 0.65; 95% CI, 0.53 to 0.79; P = 1.06×10 −5 ). CONCLUSIONSWe identified a 3p21.31 gene cluster as a genetic susceptibility locus in patients with Covid-19 with respiratory failure and confirmed a potential involvement of the ABO blood-group system. (Funded by Stein Erik Hagen and others.

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Background: The problem of medical errors has recently received a great deal of attention, which will probably increase. In this minireview, we focus on this issue in the fields of laboratory medicine and blood transfusion. Methods: We conducted several MEDLINE queries and searched the literature by hand. Searches were limited to the last 8 years to identify results that were not biased by obsolete technology. In addition, data on the frequency and type of preanalytical errors in our institution were collected. Results: Our search revealed large heterogeneity in study designs and quality on this topic as well as relatively few available data and the lack of a shared definition of “laboratory error” (also referred to as “blunder”, “mistake”, “problem”, or “defect”). Despite these limitations, there was considerable concordance on the distribution of errors throughout the laboratory working process: most occurred in the pre- or postanalytical phases, whereas a minority (13–32% according to the studies) occurred in the analytical portion. The reported frequency of errors was related to how they were identified: when a careful process analysis was performed, substantially more errors were discovered than when studies relied on complaints or report of near accidents. Conclusions: The large heterogeneity of literature on laboratory errors together with the prevalence of evidence that most errors occur in the preanalytical phase suggest the implementation of a more rigorous methodology for error detection and classification and the adoption of proper technologies for error reduction. Clinical audits should be used as a tool to detect errors caused by organizational problems outside the laboratory.

New facts have recently enhanced interest in the topic of reference intervals. In particular, the International Organization for Standardization standard 15189, requesting that 'biological reference intervals shall be periodically reviewed', and the directive of the European Union on in vitro diagnostic medical devices asking manufacturers to provide detailed information on reference intervals, have renewed interest in the subject. This review presents an update on the topic, discussing the theoretical aspects and the most critical issues. The basic approach to the definition of reference intervals proposed in the original International Federation of Clinical Chemistry documents still remain valid. The use of data mining to obtain reference data from existing databases has severe limitations. New statistical approaches to discard outliers and to compute reference limits have been recommended. On the other hand, perspectives opened by the improvement in standardization through the implementation of the concept of traceability suggest new models to define 'common' reference intervals that can be transferred and adopted by different clinical laboratories in order to decrease the proliferation of different reference intervals not always justified by differences in population characteristics or in analytical methodology.

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BACKGROUND:Reference intervals for serum creatinine remain relevant despite the current emphasis on the use of the estimated glomerular filtration rate for assessing renal function. Many studies on creatinine reference values have been published in the last 20 years. Using criteria derived from published IFCC documents, we sought to identify universally applicable reference intervals for creatinine via a systematic review of the literature.

Objectives: The management of healthcare workers (HCWs) exposed to confirmed cases of coronavirus disease 2019 (COVID-19) is still a matter of debate. We aimed to assess in this group the attack rate of asymptomatic carriers and the symptoms most frequently associated with infection. Methods: Occupational and clinical characteristics of HCWs who underwent nasopharyngeal swab testing for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a university hospital from 24 February 2020 to 31 March 2020 were collected. For those who tested positive and for those who tested positive but who were asymptomatic, we checked the laboratory and clinical data as of 22 May to calculate the time necessary for HCWs to then test negative and to verify whether symptoms developed thereafter. Frequencies of positive tests were compared according to selected variables using multivariable logistic regression models. Results: There were 139 positive tests (8.8%) among 1573 HCWs (95% confidence interval, 7.5e10.3), with a marked difference between symptomatic (122/503, 24.2%) and asymptomatic (17/1070, 1.6%) workers (p < 0.001). Physicians were the group with the highest frequency of positive tests (61/582, 10.5%), whereas clerical workers and technicians had the lowest frequency (5/137, 3.6%). The likelihood of testing positive for COVID-19 increased with the number of reported symptoms; the strongest predictors of test positivity were taste and smell alterations (odds ratio ¼ 76.9) and fever (odds ratio ¼ 9.12). The median time from first positive test to a negative test was 27 days (95% confidence interval, 24e30). Conclusions: HCWs can be infected with SARS-CoV-2 without displaying any symptoms. Among symptomatic HCWs, the key symptoms to guide diagnosis are taste and smell alterations and fever. A median of almost 4 weeks is necessary before nasopharyngeal swab test results are negative.

For AST and ALT, the implementation of common RIs appears to be possible, because no differences between regions were observed. However, a common RI for GGT that is applicable worldwide appears unlikely due to differences among populations.