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* Context.--A relevant portion of coronavirus disease 2019 (COVID-19) patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk. Objective.--To evaluate 6 serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin, and cardiac troponin T) for predicting COVID-19 severity and to define related cutoffs able to aid clinicians in risk stratification of hospitalized patients. Design.--A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: nonsurvivors versus survivors and patients admitted to an intensive care unit versus others. Receiver operating characteristic curves and likelihood ratios were employed to define predictive cutoffs for evaluated markers. Results.--Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, whereas only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cutoffs for death prediction were greater than 731 U/L for lactate dehydrogenase and 18 g/L or lower for albumin, whereas a lactate dehydrogenase activity lower than 425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment. Conclusions.--Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cutoffs for their use. doi: 10.5858/arpa.2020-0389-SA, At the end of 2019, an outbreak of atypical pneumonia of unknown cause was detected in Wuhan, the capital of the province of Hubei, China. (1) The etiologic agent of [...]

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). [ABSTRACT FROM AUTHOR]

The letter addresses concerns regarding the inaccurate definition of Bence Jones proteinuria (BJP) in the EFLM European Urinalysis Guideline 2023. The authors argue that the guideline's terminology does not accurately reflect the characteristics of BJP, which is defined as monoclonal free light chains of immunoglobulins. They caution against using total proteinuria as a screening method for BJP, as it may not be sensitive enough to detect clinically significant concentrations. The authors emphasize the importance of using strict and accurate definitions in guidelines and recommend urine immunofixation as the gold standard test for detecting BJP. [Extracted from the article]

The letter published in the Annals of Clinical Biochemistry discusses the impact of the Hub & Spoke organization on the measurement of plasma ammonia levels. The study conducted a retrospective analysis comparing results from outpatients and inpatients, revealing differences in haemolysis index values and sample handling protocols. As a result of the findings, the authors revised their ammonia testing procedures within the organization to ensure efficient sample delivery, rapid analysis, and appropriate result reporting. Age-related reference intervals will also be implemented in the future. [Extracted from the article]

This study systematically examined the influence of carbohydrate (sucrose), sodium, and caffeine on the fluid retention potential of beverages under euhydrated conditions, using the beverage hydration index method. Three cohorts, each of 12 young, healthy, active men, ingested 1 L of beverages containing four different concentrations of a single component (sucrose, sodium, or caffeine) in a double-blind, crossover manner. Urine output was collected for the subsequent 4 hr. Cumulative urine output was lower and net fluid balance was higher after 10 and 20% sucrose beverages than 0 and 5% sucrose beverages (p <.05), and after 27 and 52 mmol/L sodium beverages than 7 and 15 mmol/L sodium beverages (p <.05). No difference in urine output or net fluid balance was apparent following ingestion of caffeine at concentrations of 0–400 mg/L (p =.83). Consequently, the calculated beverage hydration index was greater in beverages with higher sucrose or sodium content, but caffeine had no effect. No difference was observed in arginine vasopressin or aldosterone between any trials. These data highlight that the key drivers promoting differences in the fluid retention potential of beverages when euhydrated are energy density, likely through slowed fluid delivery to the circulation (carbohydrate content effect), or electrolyte content through improved fluid retention (sodium content effect). These data demonstrate that beverage carbohydrate and sodium content influence fluid delivery and retention in the 4 hr after ingestion, but caffeine up to 400 mg/L does not. Athletes and others can use this information to guide their daily hydration practices. [ABSTRACT FROM AUTHOR]

Results are automatically calculated by the system as follows: HbA SB 1c sb (mmol/mol)=[HbA SB 1c sb ( mol/L)/total haemoglobin (mol/L)] × 1,000. A bias >1 mmol/mol for Alinity became however evident only in samples with HbA SB 1c sb values >=69 mmol/mol. Keywords: clinical governance; diabetes; HbA1c; metrological traceability; total laboratory automation EN clinical governance diabetes HbA1c metrological traceability total laboratory automation 441 450 10 02/07/22 20220201 NES 220201 Introduction There are approximately 500 million people living with diabetes mellitus (DM) worldwide [[1]]. Alinity showed a mean positive absolute bias of 0.54 mmol/mol (range: -0.4 to 2.6 mmol/mol), corresponding to a mean percentage difference of 0.87% (range: -1.13 to 2.74%). [Extracted from the article]