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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., (© 2020 College of American Pathologists.)

Unaccustomed strenuous physical exertion in hot environments can result in heat stroke and acute kidney injury (AKI). Both exercise-induced muscle damage and AKI are associated with the release of interleukin-6, but whether muscle damage causes AKI in the heat is unknown. We hypothesized that muscle-damaging exercise, before exercise in the heat, would increase kidney stress. Ten healthy euhydrated men underwent a randomized, crossover trial involving both a 60-min downhill muscle-damaging run (exercise-induced muscle damage; EIMD), and an exercise intensity-matched non-muscle-damaging flat run (CON), in random order separated by 2 wk. Both treatments were followed by heat stress elicited by a 40-min run at 33°C. Urine and blood were sampled at baseline, after treatment, and after subjects ran in the heat. By design, EIMD induced higher plasma creatine kinase and interleukin-6 than CON. EIMD elevated kidney injury biomarkers (e.g., urinary neutrophil gelatinase-associated lipocalin (NGAL) after a run in the heat: EIMD-CON, mean difference [95% CI]: 12 [5, 19] ng/ml) and reduced kidney function (e.g., plasma creatinine after a run in the heat: EIMD-CON, mean difference [95% CI]: 0.2 [0.1, 0.3] mg/dl), where CI is the confidence interval. Plasma interleukin-6 was positively correlated with plasma NGAL (r = 0.9, P = 0.001). Moreover, following EIMD, 5 of 10 participants met AKIN criteria for AKI. Thus for the first time we demonstrate that muscle-damaging exercise before running in the heat results in a greater inflammatory state and kidney stress compared with non-muscle-damaging exercise. Muscle damage should therefore be considered a risk factor for AKI when performing exercise in hot environments.

Elevated copeptin, a surrogate marker of vasopressin, is linked to low water intake and increased diabetes risk. Water supplementation in habitual low-drinkers with high copeptin significantly lowers both fasting plasma (fp) copeptin and glucose. This study aims at investigating possible underlying mechanisms. Thirty-one healthy adults with high copeptin (> 10.7 pmol·L−1 (men), > 6.1 pmol−1 (women)) and 24-h urine volume of < 1.5L and osmolality of > 600 mOsm·kg−1 were included. The intervention consisted of addition of 1.5 L water daily for 6 weeks. Fp-adrenocorticotropic hormone (ACTH), fp-cortisol, 24-h urine cortisol, fasting and 2 h (post oral glucose) insulin and glucagon were not significantly affected by the water intervention. However, decreased (Δ baseline-6 weeks) fp-copeptin was significantly associated with Δfp-ACTH (r = 0.76, p < 0.001) and Δfp-glucagon (r = 0.39, p = 0.03), respectively. When dividing our participants according to baseline copeptin, median fp-ACTH was reduced from 13.0 (interquartile range 9.2–34.5) to 7.7 (5.3–9.9) pmol L−1, p = 0.007 in the top tertile of copeptin, while no reduction was observed in the other tertiles. The glucose lowering effect from water may partly be attributable to decreased activity in the hypothalamic–pituitary–adrenal axis. ClinicalTrials.gov: NCT03574688. [ABSTRACT FROM AUTHOR]

Purpose: Growing evidence suggests hydration plays a role in metabolic dysfunction, however data in humans are scarce. This study examined the cross-sectional association between hydration and metabolic dysfunction in a representative sample of the US population. Methods: Data from 3961 adult NHANES (National Health and Nutrition Examination Survey) participants (49.8% female; age 46.3 ± 0.5 years) were grouped by quartile of urine specific gravity (USG, 2007–2008 cohort) or urine osmolality (UOsm, 2009–2010 cohort) as measures of hydration. Metabolic dysfunction was assessed by glycemic and insulinemic endpoints and by components of the metabolic syndrome. Multivariate-adjusted linear and logistic regression models were used. Results: Increasing quartiles of USG but not UOsm was associated with higher fasting plasma glucose (FPG), glycated hemoglobin (all P < 0.01), HOMA-IR and elevated insulin (all P < 0.05). Compared with the lowest quartile, those with the highest USG but not UOsm had greater risk of metabolic syndrome (Q4 vs. Q1, OR (99% CI): 1.6 (1.0, 2.7), P = 0.01) and diabetes (Q4 vs. Q1, OR: 1.8 (1.0, 3.4), P < 0.05). Additionally, those with USG > 1.013 or UOsm > 500 mOsm/kg, common cut-off values for optimal hydration based on retrospective analyses of existing data, had less favorable metabolic markers. In a subset of participants free from diabetes mellitus, impaired kidney function, hypertension and diuretic medication, USG remained positively associated with FPG (P < 0.01) and elevated FPG (P < 0.05). Conclusion: These analyses provide population-based evidence that USG as a proxy for hydration is associated with glucose homeostasis in NHANES 2007–2008. The same association was not significant when UOsm was used as a proxy for hydration in the 2009–2010 wave. Clinical trial registry: Not applicable, as this was a reanalysis of existing NHANES data. [ABSTRACT FROM AUTHOR]

Purpose: An increasing body of evidence suggests that excreting a generous volume of diluted urine is associated with short- and long-term beneficial health effects, especially for kidney and metabolic function. However, water intake and hydration remain under-investigated and optimal hydration is poorly and inconsistently defined. This review tests the hypothesis that optimal chronic water intake positively impacts various aspects of health and proposes an evidence-based definition of optimal hydration. Methods: Search strategy included PubMed and Google Scholar using relevant keywords for each health outcome, complemented by manual search of article reference lists and the expertise of relevant practitioners for each area studied. Results: The available literature suggest the effects of increased water intake on health may be direct, due to increased urine flow or urine dilution, or indirect, mediated by a reduction in osmotically -stimulated vasopressin (AVP). Urine flow affects the formation of kidney stones and recurrence of urinary tract infection, while increased circulating AVP is implicated in metabolic disease, chronic kidney disease, and autosomal dominant polycystic kidney disease. Conclusion: In order to ensure optimal hydration, it is proposed that optimal total water intake should approach 2.5 to 3.5 L day−1 to allow for the daily excretion of 2 to 3 L of dilute (< 500 mOsm kg−1) urine. Simple urinary markers of hydration such as urine color or void frequency may be used to monitor and adjust intake. [ABSTRACT FROM AUTHOR]

Purpose: This investigation had three purposes: (a) to evaluate changes in hydration biomarkers in response to a graded rehydration intervention (GRHI) following 3 days of water restriction (WR), (b) assess within-day variation in urine concentrations, and (c) quantify the volume of fluid needed to return to euhydration as demonstrated by change in Ucol. Methods: 115 adult males and females were observed during 1 week of habitual fluid intake, 3 days of fluid restriction (1000 mL day−1), and a fourth day in which the sample was randomized into five different GRHI groups: no additional water, CON; additional 500 mL, G+0.50; additional 1000 mL, G+1.00; additional 1500 mL, G+1.50; additional 2250 mL, G+2.25. All urine was collected on 1 day of the baseline week, during the final 2 days of the WR, and during the day of GRHI, and evaluated for urine osmolality, color, and specific gravity. Results: Following the GRHI, only G+1.50 and G+2.25 resulted in all urinary values being significantly different from CON. The mean volume of water increase was significantly greater for those whose Ucol changed from > 4 to < 4 (+ 1435 ± 812 mL) than those whose Ucol remained ≥ 4 (+ 667 ± 722 mL, p < 0.001). Conclusions: An additional 500 mL of water is not sufficient, while approximately 1500 mL of additional water (for a total intake between 2990 and 3515 mL day−1) is required to return to a urine color associated with adequate water intake, following 3 days of WR. [ABSTRACT FROM AUTHOR]

Background Epidemiological studies in humans show increased concentrations of copeptin, a surrogate marker of arginine vasopressin (AVP), to be associated with increased risk for type 2 diabetes. Objectives To examine the acute and independent effect of osmotically stimulated AVP, measured via the surrogate marker copeptin, on glucose regulation in healthy adults. Methods Sixty subjects (30 females) participated in this crossover design study. On 2 trial days, separated by ≥7 d (males) or 1 menstrual cycle (females), subjects were infused for 120 min with either 0.9% NaCl [isotonic (ISO)] or 3.0% NaCl [hypertonic (HYPER)]. Postinfusion, a 240-min oral-glucose-tolerance test (OGTT; 75 g) was administered. Results During HYPER, plasma osmolality and copeptin increased (P  < 0.05) and remained elevated during the entire 6-h protocol, whereas renin-angiotensin-aldosterone system hormones were within the lower normal physiological range at the beginning of the protocol and declined following infusion. Fasting plasma glucose did not differ between trials (P  > 0.05) at baseline and during the 120 min of infusion. During the OGTT the incremental AUC for glucose from postinfusion baseline (positive integer) was greater during HYPER (401.5 ± 190.5 mmol/L·min) compared with the ISO trial (354.0 ± 205.8 mmol/L·min; P <  0.05). The positive integer of the AUC for insulin during OGTT did not differ between trials (HYPER 55,850 ± 36,488 pmol/L·min compared with ISO 57,205 ± 31,119 pmol/L·min). Baseline values of serum glucagon were not different between the 2 trials; however, the AUC of glucagon during the OGTT was also significantly greater in HYPER (19,303 ± 3939 ng/L·min) compared with the ISO trial (18,600 ± 3755 ng/L·min; P  < 0.05). Conclusions The present data indicate that acute osmotic stimulation of copeptin induced greater hyperglycemic responses during the oral glucose challenge, possibly due to greater glucagon concentrations. This study was registered at clinicaltrials.gov as NCT02761434. [ABSTRACT FROM AUTHOR]

Background: Monitoring of test imprecision is one of the most important quality indicators in clinical laboratories. Imprecision goals should be derived from biological variation. The aim of this study was to evaluate the imprecision of eight tumour biomarker assays routinely measured on the Modular E170 system. Methods: Method coefficient of variations (CVs) were obtained by an appropriate Internal Quality Control programme based on the measurement every working day of a fresh-frozen human serum pool with biomarkers concentrations around the clinical cut-offs. We evaluated data collected along the whole year 2008 (n range: 21-461); monthly CVs and their cumulative means were calculated and compared with corresponding goals. Results: Biomarkers concentration means and average yearly CVs (desirable goals in parentheses) were as follows: α-fetoprotein, 9.6 μg/L, 3.9% (6.0%); CA125, 41.2 U/L, 2.8% (12.4%); CA15.3, 32.7 U/L, 3.1% (3.1%); CA19.9, 35.1 U/L, 2.8% (8.0%); CEA, 7.7 μg/L, 4.3% (6.4%); prostate-specific antigen (PSA), 4.1 μg/L, 4.3% (9.1%); CYFRA 21.1, 2.4 μg/L, 5.7% (11.3%); and ferritin, 64.5 μg/L, 4.0% (7.1%). Conclusions: Our study shows that in routine laboratory practice and over a clinically and analytically relevant time-span, the imprecision of the tumour biomarker measurements on the Roche Modular E170 fulfills desirable goals. For four assays (CA125, CA19.9, PSA and CYFRA 21.1) the optimum CV can even be achieved. [ABSTRACT FROM AUTHOR]

Background Automatic photometric determination of the hemolysis index (HI) on serum and plasma samples is central to detect potential interferences of in vitro hemolysis on laboratory tests. When HI is above an established cut-off for interference, results may suffer from a significant bias and undermine clinical reliability of the test. Despite its undeniable importance for patient safety, the analytical performance of HI estimation is not usually checked in laboratories. Here we evaluated for the first time the random source of measurement uncertainty of HI determination on the two Abbott Architect c16000 platforms in use in our laboratory. Methods From January 2016 to September 2017, we collected data from daily photometric determination of HI on a fresh-frozen serum pool with a predetermined HI value of ~ 100 (corresponding to ~ 1 g/L of free hemoglobin). Monthly and cumulative CVs were calculated. Results During 21 months, 442 and 451 measurements were performed on the two platforms, respectively. Monthly CVs ranged from 0.7% to 2.7% on c16000–1 and from 0.8% to 2.5% on c16000-2, with a between-platform cumulative CV of 1.82% (corresponding to an expanded uncertainty of 3.64%). Mean HI values on the two platforms were just slightly biased (101.3 vs. 103.1, 1.76%), but, due to the high precision of measurements, this difference assumed statistical significance (p < 0.0001). Conclusions Even though no quality specifications are available to date, our study shows that the HI measurement on Architect c16000 platform has nice reproducibility that could be considered in establishing the state of the art of the measurement. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: Chromogranin A (CgA) and neuron-specific enolase (NSE) are biomarkers for neuroendocrine tumors. Although the knowledge of their biological variation (BV) is critical, only one study for CgA and no data for NSE are available. We report a definitive assessment of BV components of these biomarkers in the same cohort of subjects by an accurately experimental protocol. Design and methods: We collected five blood specimens from each of 22 healthy volunteers (10 men and 12 women, 23–54years) on the same day every two weeks for two months. Serum specimens were stored at −80°C until analysis and analyzed in a single run in duplicate. Data were analyzed by ANOVA. Results: Serum CgA concentrations were significantly higher for women than for men (P=0.01), whereas no difference was found for NSE. Intra-individual variance was not different between genders for both biomarkers. Within- and between-subject CVs were 16.3% and 33.5% for CgA and 13.6% and 11.5% for NSE, respectively. CgA showed marked individuality, suggesting that the use of population-based reference limits is inadequate for its interpretation. Conversely, the low individuality of NSE allows the use of a single reference interval. Reference change values were 46% for CgA and 39% for NSE. Desirable analytical goals for imprecision, bias, and total error were <8.2%, ±9.3%, and ±22.8% for CgA, and <6.8%, ±4.5%, and ±15.7% for NSE, respectively. Conclusion: In this study, we defined BV components of serum CgA and NSE and derived indices that may improve the clinical use of these biomarkers. [Copyright &y& Elsevier]