The oxyhaemoglobin dissociation curve is generally left-shifted in COVID-19 patients at admission to hospital, and this is associated with lower mortality.

Lung damage caused by SARS-Cov-2 virus results in marked arterial hypoxia, accompanied in many cases by hypocapnia. The literature is inconclusive as to whether these conditions induce alteration of the affinity of haemoglobin for oxygen. We studied the oxyhaemoglobin dissociation curves (ODCs) of 517 patients hospitalized with coronavirus disease 2019 (COVID-19) for whom arterial blood gas analysis (BGA) was performed upon hospitalization (i.e., before treatment). With respect to a conventional normal p50 (pO2 at 50% saturation of haemoglobin) of 27 mmHg, 76% had a lower standardized p50 (p50s) and 85% a lower in vivo p50 (p50i). In a 33-patient subgroup with follow-up BGAs after 3, 6, 9, 12, 15 and 18 days' treatment, p50s and p50i exhibited statistically significant differences between baseline values and values recorded at all these time points. The 30-day Kaplan-Meier survival curves of COVID-19 patients stratified by p50i level show a higher probability of survival among patients who at admission had p50 values below 27 mmHg (p = 0.012). Whether the observed alteration of the affinity of haemoglobin for oxygen in COVID-19 patients is a direct or indirect effect of the virus on haemoglobin is unknown.

Blood eosinophil count as predictor of asthma exacerbation. A meta-analysis.

BACKGROUND: Evidence about the association of high blood eosinophil count with asthma exacerbation is inconsistent and unclear. The objective of this meta-analysis was to determine whether elevated blood eosinophil count predicts asthma exacerbation. METHODS: We searched MEDLINE, EMBASE, and additional databases, without any language restriction. We also checked the reference lists of the included studies and of relevant systematic reviews. The main outcome was the occurrence of asthma exacerbation. We calculated global pooled odds ratios (ORs) and their 95% confidence intervals (CIs) and performed predefined subgroup analyses. We appraised the quality of the studies using Newcastle-Ottawa Scale, examined the heterogeneity between studies, assessed publication bias, and carried out sensitivity analyses. RESULTS: Among 1567 retrieved publications, 23 observational studies comprising 155,772 participants met the inclusion criteria. High blood eosinophil count was associated with higher odds of asthma exacerbation [OR: 1.31 (95% CI: 1.16, 1.49)], specifically with asthma-related outpatient visits [OR: 1.46 (95% CI: 1.25, 1.70)] and emergency department visits [OR: 1.63 (95% CI: 1.29, 2.07)]. A significant association was observed starting from an eosinophils' cutoff value of 200 cells/µl. The association was observed for cohort studies [OR: 1.30 (95%CI: 1.13, 1.49)], North American studies [OR: 1.43 (95%CI: 1.31, 1.57)], Asian populations [OR: 1.67 (95%CI: 1.34, 2.08)], children [OR: 1.38 (95%CI: 1.22, 1.56)], and studies that adjusted for inhaled corticosteroids therapy [OR: 1.42 (95%CI: 1.28, 1.56)]. CONCLUSIONS: Blood eosinophil counts ≥ 200 cells/µL are associated with asthma exacerbation. Blood eosinophil count is a modifiable factor that could be addressed in asthma management strategies.

Impact of Mean Cell Hemoglobin on Hb A1c-Defined Glycemia Status.

BACKGROUND: Several hematological alterations are associated with altered hemoglobin A1c (Hb A1c). However, there have been no reports of their influence on the rates of exceeding standard Hb A1c thresholds by patients for whom Hb A1c determination is requested in clinical practice. METHODS: The initial data set included the first profiles (complete blood counts, Hb A1c, fasting glucose, and renal and hepatic parameters) of all adult patients for whom such a profile was requested between 2008 and 2013 inclusive. After appropriate exclusions, 21844 patients remained in the study. Linear and logistic regression models were adjusted for demographic, hematological, and biochemical variables excluded from the predictors. RESULTS: Mean corpuscular hemoglobin (MCH) and mean corpuscular volume (MCV) correlated negatively with Hb A1c. Fasting glucose, MCH, and age emerged as predictors of Hb A1c in a stepwise regression that discarded sex, hemoglobin, MCV, mean corpuscular hemoglobin concentration (MCHC), serum creatinine, and liver disease. Mean Hb A1c in MCH interdecile intervals fell from 6.8% (51 mmol/mol) in the lowest (≤27.5 pg) to 6.0% (43 mmol/mol) in the highest (>32.5 pg), with similar results for MCV. After adjustment for fasting glucose and other correlates of Hb A1c, a 1 pg increase in MCH reduced the odds of Hb A1c-defined dysglycemia, diabetes and poor glycemia control by 10%-14%. CONCLUSIONS: For at least 25% of patients, low or high MCH or MCV levels are associated with increased risk of an erroneous Hb A1c-based identification of glycemia status. Although causality has not been demonstrated, these parameters should be taken into account in interpreting Hb A1c levels in clinical practice.

At-admission HbA1c levels in hospitalized COVID-19 participants with and without known diabetes.

BACKGROUND: To examine glycaemic status, and the impact of at-admission HbA1c levels on outcome, in a large group of participants hospitalized for COVID-19. METHODS: We inclued 515 participants with confirmed COVID-19 infection, with or without known diabetes, who met the following additional criteria: 1) age > 18 years, 2) HbA1c was determined at admission; 3) fasting plasma glucose was determined in the week of admission, and 4) discharge or death was reached before the end of the study. We examined attributes of participants at admission and 3-6 months post-discharge. To assess the associations of pre-admission attributes with in-hospital mortality, logistic regression analyses were performed. RESULTS: Mean age was 70 years, 98.8% were of white race, 49% were female, 31% had known diabetes (KD), an additional 7% met the HbA1c criterion for diabetes, and 13.6% died. In participants with KD, FPG and HbA1c levels were not associated with mortality in adjusted analyses; however, in participants without KD, whereas FPG showed direct association with mortality, HbA1c showed slight inverse association. CONCLUSIONS: There was a very high prevalence of people without KD with HbA1c levels above normal at-admission. This alteration does not seem to have been related to blood glucose levels.

Progression of nephropathy in type 2 diabetes: the glycation gap is a significant predictor after adjustment for glycohemoglobin (Hb A1c).

BACKGROUND: The glycation gap has been proposed as an index of nonglycemic determinants of glycated hemoglobin (Hb A(1c)). We investigated whether it predicts progression of nephropathy in type 2 diabetic patients. METHODS: We recorded albumin excretion rate, Hb A(1c), and serum fructosamine in 2314 patients over an average of 6.5 years. Hb A(1c) was regressed on fructosamine by using a repeated-measures longitudinal regression model and data for all visits of all patients; the raw glycation gap gg was calculated at each visit, as measured by Hb A(1c) minus the value predicted by the regression; and the mean glycation gap (GG) was defined for each patient as the mean of the values for the raw glycation gap (gg) calculated at each visit. The study group was divided into high-, medium- and low-GG groups of equal sizes, which were compared for progression of nephropathy by Cox regression analyses controlling for age, sex, duration of diabetes, initial nephropathy status, therapy, baseline Hb A(1c), mean Hb A(1c), and mean fructosamine. The design of the study was a retrospective cohort study with follow-up for 6.5 (SD 4.2) years. RESULTS: The gg exhibited considerable stability over time. In the high- and medium-GG groups, the risk of progression of nephropathy was respectively 2.5 and 1.6 times that of the low-GG group (P < 0.0001 and P = 0.001, respectively) after adjustment as described above. CONCLUSIONS: GG predicts the progression of nephropathy in type 2 diabetic patients independently of fructosamine and even after adjustment for Hb A(1c). The joint use of the glycation gap and fructosamine as measures of nonglycemic and glycemic determinants of glycation, respectively, may improve evaluation of the risk of nephropathy and of the glycemic control desirable for the individual patient.

Prediabetes defined by HbA1c and by fasting glucose: differences in risk factors and prevalence.

AIMS: To investigate, in a sample of nondiabetic adults from a Spanish community, the differences between prediabetes as defined by HbA1c ("H-prediabetes") and by fasting plasma glucose (FPG) ("F-prediabetes") in regard to prevalence and the influence of potential risk factors, adjusting the latter for confounders. METHODS: A total of 1328 nondiabetic participants aged ≥ 18 years were classified as normoglycemic, H-prediabetic [HbA1c 5.7-6.4% (39-47 mmol/mol)] or F-prediabetic (FPG 5.6-6.9 mmol/L). Multivariable analyses were used to compare the impacts of risk factors on the prevalence of H-prediabetes, F-prediabetes and their conjunctive and disjunctive combinations ("HaF-prediabetes" and "HoF-prediabetes," respectively). RESULTS: Some 29.9% of participants were HoF-prediabetic, 21.7% H-prediabetic, 16.3% F-prediabetic and only 8.1% HaF-prediabetic. Whatever the definition of prediabetes, increasing age, fasting insulin and LDL cholesterol were each a risk factor after adjustment for all other variables. Increasing BMI and decreasing mean corpuscular hemoglobin (MCH) were additional risk factors for H-prediabetes; male sex and increasing uric acid for F-prediabetes and increasing BMI for HaF-prediabetes. The participants satisfying the compound condition "hypertension or hyperlipidemia or obesity or hyperuricemia" (59.9% of the whole study group) included 83.1% of all subjects with HoF-prediabetes. CONCLUSIONS: In this population, the most sensitive risk factor for detection of prediabetes was age, followed by fasting insulin, LDL cholesterol, BMI, MCH, male sex and uric acid, with differences depending on the definition of prediabetes. MCH, an indirect measure of erythrocyte survival, significantly influences the prevalence of HbA1c-defined prediabetes. This study suggests that screening of individuals with selected risk factors may identify a high proportion of prediabetic persons.

Postprandial glycemic response in a non-diabetic adult population: the effect of nutrients is different between men and women.

BACKGROUND: There is a growing interest in the pathopysiological consequences of postprandial hyperglycemia. It is well known that in diabetic patients 2 h plasma glucose is a better risk predictor for coronary heart disease than fasting plasma glucose. Data on the glycemic response in healthy people are scarce. OBJECTIVE: To evaluate the effect of macronutrients (carbohydrates, fats, and proteins) and fiber on postprandial glycemic response in an observational study of a non-diabetic adult population. DESIGN: Cross-sectional study. 150 non-diabetic adults performed continuous glucose monitoring for 6 days. During this period they recorded food and beverage intake. The participants were instructed not to make changes in their usual diet and physical exercise.Variables analyzed included clinical parameters (age, sex, body weight, height, body mass index, blood pressure, and waist measurement), meal composition (calories, carbohydrates, fats, proteins, and fiber) and glycemic postprandial responses separated by sexes.The study period was defined from the start of dinner to 6 h later. RESULTS: A total of 148 (51% women) subjects completed all study procedures. Dinner intake was higher in males than in females (824 vs 531 kcal). Macronutrient distribution was similar in both sexes. No significant differences were found in fiber intake between men and women (5.5 g vs 4.5 g).In both sexes, the higher intake of carbohydrates corresponded to a significantly higher glycemic response (p = 0.0001 in women, p = 0.022 in men). Moreover, in women, as fat intake was higher, a flattening of the postprandial glycemic curve was observed (p = 0.003). With respect to fiber, a significantly lower glycemic response was observed in the group of women whose fiber intake at dinner was higher (p = 0.034). CONCLUSIONS: Continuous glucose monitoring provides important information about glucose levels after meals. In this study, the postprandial glycemic response in women was different from that of men, and carbohydrates were the main determinant of elevated postprandial glucose levels.

Empagliflozin reduces the levels of CD36 and cardiotoxic lipids while improving autophagy in the hearts of Zucker diabetic fatty rats.

The EMPA-REG OUTCOME (Empagliflozin, Cardiovascular Outcome Event Trial in patients with Type 2 Diabetes Mellitus (T2DM)) trial made evident the potentiality of pharmacological sodium-glucose cotransporter 2 (SGLT2) inhibition for treating patients with diabetes and cardiovascular disease. Since the effect of empagliflozin or other SGLT2 inhibitors on the whole cardiac metabolic profile was never analysed before, and with the purpose to contribute to elucidate the benefits at cardiac level of the use of empagliflozin, we explored the effect of the treatment with empagliflozin for six weeks on the cardiac metabolomic profile of Zucker diabetic fatty rats, a model of early stage T2DM, using untargeted metabolomics approach. Empagliflozin reduced significantly the cardiac content of sphingolipids (ceramides and sphingomyelins) and glycerophospholipids (major bioactive contributing factors linking insulin resistance to cardiac damage) and decreased the cardiac content of the fatty acid transporter cluster of differentiation 36 (CD36); induced significant decreases of the cardiac levels of essential glycolysis intermediaries 2,3-bisphosphoglycerate and phosphoenolpyruvate, and regulated the abundance of several amino acids of relevance as tricarboxylic acid suppliers and/or in the metabolic control of the cardiac function as glutamic acid, gamma-aminobutyric acid and sarcosine. Empagliflozin treatment activated the cardioprotective master regulator of cellular energyhomeostasis AMP-activatedproteinkinase (AMPK) and enhanced autophagy at cardiac level, while it decreased significantly the cardiac mRNA levels of the pro-inflammatory cytokines interleukin-6 (IL-6), chemerin, TNF-α and MCP-1, reinforcing the hypothesis of a direct role for empagliflozin in attenuating cardiac inflammation. Our results provide an advancement on the knowledge of the mechanisms linking the therapy with empagliflozin with protective effects on the development of cardiometabolic diseases whose course is associated with remarkable cardiac bioenergetics dysregulation and disarrangement in cardiac metabolome and lipidome.

Continuous glucose monitoring is more sensitive than HbA1c and fasting glucose in detecting dysglycaemia in a Spanish population without diabetes.

AIMS: To investigate whether continuous glucose monitoring (CGM) reveals patterns of glycaemic behaviour, the detection of which might improve early diagnosis of dysglycaemia. METHODS: A total 1521 complete days of valid CGM data were recorded under real-life conditions from a healthy sample of a Spanish community, as were matching FPG and HbA1C data. No participant was pregnant, had a history of kidney or liver disease, or was taking drugs known to affect glycaemia. RESULTS: CGM and fingerstick measurements showed a mean relative absolute difference of 6.9 ±â€¯2.2%. All subjects were normoglycaemic according to FPG and HbA1C except 21% who were prediabetic. The normoglycaemic subjects had a 24-hour mean blood glucose concentration (MBG) of 5.7 ±â€¯0.4 mmol/L, spending a median of 97% of their time within the target range (3.9-7.8 mmol/L). 73% of them experienced episodes with blood glucose levels above the threshold for impaired glucose tolerance, and 5% levels above the threshold for diabetes. These normoglycaemic participants with episodes of high glycaemia had glycaemic variabilities similar to those of prediabetic subjects with episodes of similar intensity or combined duration. CONCLUSIONS: CGM is a better indicator of possible early dysglycaemia than either FPG or HbA1c.