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Plenty of studies demonstrate that hospital-acquired anemia (HAA) can increase transfusion rates, mortality, morbidity and cause unnecessary patient burden, including additional length of hospital stay, sleep disruption and venipuncture harms resulting from blood samples unlikely to change clinical management. Beyond patient costs, community costs should also be considered, such as laboratory time and resources waste, environmental impact, increasing pressure on labs and fewer tests available on time for patients who can benefit from them most. Blood over-testing does not support the principles of non-maleficence, justice and respect for patient autonomy, at the expense dubious beneficence. Reducing the number and frequency of orders is possible, to a certain extent, by adopting nudge strategies and raising awareness among prescribing doctors. However, reducing the orders may appear unsafe to doctors and patients. Therefore, reducing blood volume from each order is a better alternative, which is worth implementing through technological, purchasing and organizational arrangements, possibly combined according to need (smaller tubes, adequate analytic platforms, blind dilution, blood conservative devices, aggregating tests and laboratory units)., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

C-reactive protein (CRP) is a cytokine-mediated acute phase reactant with a recognized role in inflammatory conditions and infectious disease. In coronavirus disease 2019 (COVID-19), elevated CRP concentrations in serum were frequently detected and significantly associated with poor outcome in terms of disease severity, need for intensive care, and in-hospital death. For these reasons, the marker was proposed as a powerful test for prognostic classification of COVID-19 patients. In most of available publications, there was however confounding information about how interpretative criteria for CRP in COVID-19 should be derived, including quality of employed assays and optimal cut-off definition. Assuring result harmonization and controlling measurement uncertainty in terms of performance specifications are fundamental to allow worldwide application of clinical information according to specific CRP thresholds and to avoid risk of patient misclassification., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

Appropriateness in Laboratory Medicine has been the object of various types of interventions. From published experiences, it is now clear that to effectively manage the laboratory test demand it is recommended to activate evidence-based preventative strategies stopping inappropriate requests before they can reach the laboratory. To guarantee appropriate laboratory test utilization, healthcare institutions should implement and optimize a computerized provider order entry (CPOE), exploiting the potential of electronic requesting as "enabling factor" for reinforcing appropriateness and sustaining its effects over time. In our academic institution, over the last 15 years, our medical laboratory has enforced various interventions to improve test appropriateness, all directly or indirectly based on CPOE use. The following types of intervention were implemented: (1) applying specific recommendations supported by monitoring by CPOE as well as a continuous consultation with clinicians (tumour markers); (2) removing outdated tests and avoiding redundant duplications (cardiac markers, pancreatic enzymes); (3) order restraints to selected wards and gating policy (procalcitonin, B-type natriuretic peptide, homocysteine); (4) reflex testing (bilirubin fractions, free prostate-specific antigen, aminotransferases, magnesium in hypocalcemia); and (5) minimum retesting interval (D-Dimer, vitamin B 12 , C-reactive protein, γ-glutamyltranspeptidase). In this paper, we reviewed these interventions and summarized their outcomes primarily related to the changes in total test volumes and cost savings, without neglecting patient safety. Our experience confirmed that laboratory professionals have an irreplaceable role as "stewards" in designing, implementing, evaluating, and maintaining interventions focused to improving test appropriateness., (© 2022 the author(s), published by De Gruyter, Berlin/Boston.)

Objectives: The TOP-HOLE (Towards OPtimal glycoHemOgLobin tEsting) project aimed to validate the HbA 1c enzymatic method on the Abbott Alinity c platform and to implement the HbA 1c testing process on the total laboratory automation (TLA) system of our institution., Methods: Three different measuring systems were employed: Architect c4000 stand-alone (s-a), Alinity c s-a, and Alinity c TLA. Eight frozen whole blood samples, IFCC value-assigned, were used for checking trueness. A comparison study testing transferability of HbA 1c results from Architect to Alinity was also performed. The alignment of Alinity TLA vs. s-a was verified and the measurement uncertainty (MU) estimated according to ISO 20914:2019. Turnaround time (TAT) and full time equivalent (FTE) were used as efficiency indicators., Results: For HbA 1c concentrations covering cut-offs adopted in clinical setting, the bias for both Architect and Alinity s-a was negligible. When compared with Architect, Alinity showed a mean positive bias of 0.54 mmol/mol, corresponding to a mean difference of 0.87%. A perfect alignment of Alinity TLA to the Alinity s-a was shown, and a MU of 1.58% was obtained, widely fulfilling the desirable 3.0% goal. After the full automation of HbA 1c testing, 90% of results were released with a maximum TAT of 1 h, 0.30 FTE resource was also saved., Conclusions: The traceability of Alinity HbA 1c enzymatic assay to the IFCC reference system was correctly implemented. We successfully completed the integration of the HbA 1c testing on our TLA system, without worsening the optimal analytical performance. The shift of HbA 1c testing from s-a mode to TLA significantly decreased TAT., (© 2022 Walter de Gruyter GmbH, Berlin/Boston.)

Objectives: Previous studies reported lipase elevations in serum of COVID-19 patients trying to establish a causal link between SARS-CoV-2 infection and pancreatic damage. However, the degree and prevalence of hyperlipasemia was not uniform across studies., Methods: We retrospectively evaluated 1,092 hospitalized patients with COVID-19 and at least one available lipase result. The number and frequency of patients with lipase above the upper reference limit (URL), >3 URL, and >6 URL were estimated. Correlations between lipase values and other biomarkers of organ or tissue damage were performed to identify possible extra-pancreatic sources of lipase release. The potential prognostic role of lipase to predict death and intensive care unit (ICU) admission during hospitalization was also evaluated., Results: Lipase was >URL in 344 (31.5%) of COVID-19 patients. Among them, 65 (5.9%) and 25 (2.3%) had a peak lipase >3 URL and >6 URL, respectively. In the latter group, three patients had acute pancreatitis of gallstone or drug-induced etiology. In others, the etiology of lipase elevations appeared multifactorial and could not be directly related to SARS-CoV-2 infection. No correlation was found between lipase and other tested biomarkers of organ and tissue damage. Lipase concentrations were not different between survivors and non-survivors; however, lipase was significantly increased (p<0.001) in patients admitted to the ICU, even if the odds ratio for lipase as predictor of ICU admission was not significant., Conclusions: Lipase was elevated in ∼1/3 of COVID-19 patients, but the clinical significance of this finding is unclear and irrelevant to patient prognosis during hospitalization., (© 2021 Simone Caruso et al., published by De Gruyter, Berlin/Boston.)

Objectives: Procalcitonin (PCT) has been proposed for differentiating viral vs. bacterial infections. In COVID-19, some preliminary results have shown that PCT testing could act as a predictor of bacterial co-infection and be a useful marker for assessment of disease severity., Methods: We studied 83 COVID-19 hospitalized patients in whom PCT was specifically ordered by attending physicians. PCT results were evaluated according to the ability to accurately predict bacterial co-infections and death in comparison with other known biomarkers of infection and with major laboratory predictors of COVID-19 severity., Results: Thirty-three (39.8%) patients suffered an in-hospital bacterial co-infection and 44 (53.0%) patients died. In predicting bacterial co-infection, PCT showed a relatively low accuracy (area under receiver-operating characteristic [ROC] curve [AUC]: 0.757; 95% confidence interval [CI]: 0.651-0.845), with a strength for detecting the outcome not significantly different from that of white blood cell count and C-reactive protein (CRP). In predicting patient death, PCT showed an AUC of 0.815 (CI: 0.714-0.892), not better than those of other more common laboratory tests, such as blood lymphocyte percentage (AUC: 0.874, p=0.19), serum lactate dehydrogenase (AUC: 0.860, p=0.47), blood neutrophil count (AUC: 0.845, p=0.59), and serum albumin (AUC: 0.839, p=0.73)., Conclusions: Procalcitonin (PCT) testing, even when appropriately ordered, did not provide a significant added value in COVID-19 patients when compared with more consolidated biomarkers of infection and poor clinical outcome. The major application of PCT in COVID-19 is its ability, associated with a negative predictive value >90%, to exclude a bacterial co-infection when a rule-out cut-off (<0.25 μg/L) is applied.

Background Blood loss for laboratory testing may contribute to hospital-acquired anemia. When implementing the core laboratory (core-lab) section, we consolidated first-line tests decreasing the number of tubes previously dispatched to different sites. Here, hypothesized benefits of the amount of blood volume drawn were explored. Methods We retrieved, using a laboratory information system (LIS), the number of tubes received by laboratories interested in the change from all clinical wards in a year-based period, i.e. 2013 for pre-core-lab and 2015 for core-lab system, respectively. Data were expressed as the overall number of tubes sent to laboratories, the corresponding blood volume, and the number of laboratory tests performed, normalized for the number of inpatients. Results After consolidation, the average number of blood tubes per inpatient significantly decreased (12.6 vs. 10.7, p < 0.001). However, intensive care units (ICUs) did not reduce the number of tubes per patient, according to the needs of daily monitoring of their clinical status. The average blood volume sent to laboratories did not vary significantly because serum tubes for core-lab required higher volumes for testing up to 55 analytes in the same transaction. Finally, the number of requested tests per patient during the new osystem slightly decreased (-2.6%). Conclusions Total laboratory automation does not automatically mean reducing iatrogenic blood loss. The new system affected the procedure of blood drawing in clinical wards by significantly reducing the number of handled tubes, producing a benefit in terms of costs, labor and time consumption. Except in ICUs, this also slightly promoted some blood saving. ICUs which engage in phlebotomizing patients daily, did not take advantage from the test consolidation.