Impaired pancreatic beta-cell function after a single dose of oral iron: A before-and-after (pre-post) study.

BACKGROUND: Although in vitro and animal studies have shown that iron loading in pancreatic beta cells impairs insulin secretion, no human studies have documented the acute effects of oral iron on beta-cell insulin secretory capacity. In the present study, we determined beta-cell insulin secretory capacity at baseline and after a single oral dose of iron (ferrous sulphate, 120 mg elemental iron) in healthy male individuals. METHODS: Fifteen healthy male volunteers underwent an oral glucose tolerance test (OGTT) to document baseline glucose tolerance and insulin secretion kinetics (baseline OGTT). One week later, the same subjects underwent a second OGTT, 2 h after an oral dose of ferrous sulphate (120 mg of elemental iron) (post-iron OGTT). Changes in disposition index, insulin secretion kinetics, glucose tolerance, insulin resistance, insulin clearance and iron-related parameters in serum were determined. RESULTS: Compared to baseline OGTT, the areas under the curve (AUC) for serum iron and transferrin saturation increased by 125% and 118%, respectively, in the post-iron OGTT. The disposition index decreased by 20% (p = 0.009) and the AUC for glucose concentrations increased by 5.7% (p < 0.001) during the post-iron OGTT. The insulin secretion rate was marginally lower during the first hour (-3.5%, p = 0.63), but became significantly higher during the second hour (22%, p = 0.005) of the post-iron OGTT. Insulin resistance and insulin clearance rate were not affected by iron intake. CONCLUSIONS: The decrease in disposition index and glucose tolerance observed after the oral dose of iron points to an acute iron-induced impairment in pancreatic beta-cell insulin secretory capacity.

Association of dietary patterns and health outcomes by spatial regression analysis of nationally representative survey data from India.

Background: Our aim was to study the regional differences in dietary patterns in India and their association with population-level nutrition-related health indicators such as the prevalence of anemia, overweight, undernutrition, and hyperglycemia. Objectives: To identify and characterize the dietary patterns from publicly available nationally representative survey data on food consumption conducted by the National Sample Survey Office (NSSO) to study the regional differences in dietary patterns. Methods: Dietary patterns were identified by factor analysis of per capita food consumption data from the household consumer expenditure survey (2011). Mean factor scores of dietary patterns were calculated for each district separately for urban and rural regions. Ecological association of factor scores with the district-level percentage prevalence of health indicators from the National Family Health Survey-4 (2015-2016) data was done by the Spatial Durbin Model of spatial regression analysis. Results: Factor analyses revealed four dietary patterns which were similar in terms of the food items that characterized the factors for both rural and urban regions. Direct effects of dietary patterns by spatial regression analyses were observed with several health outcomes after adjusting for differences in socioeconomic development. Prevalence of anemia was positively associated with "Milk and wheat-rich diet" among men in the rural regions but negatively associated with other dietary patterns. Prevalence of overweight and high blood glucose was positively associated with "Rice and meat-rich diet" and "Coconut and seafood rich diet" in the rural regions. "Refined oil and tur dal-rich diet" was positively associated with the prevalence of overweight and hypertension in urban regions and negatively associated with underweight and anemia in men in rural and urban regions. Conclusions: Spatial regression analyses revealed several important associations between dietary patterns and health outcomes, mostly in rural regions and some in urban regions. These results suggest the role of the major food items consumed in different regions and their impact on health outcomes in India and may have implications in tailoring dietary modifications accordingly.

Calculated values of serum LDL-cholesterol (LDL-C) - for better or worse?

BACKGROUND AND AIMS: The use of Friedewald's formula to calculate serum low-density lipoprotein cholesterol (LDL-C) is well-known to have limitations. A modification of it, in 2013, has been proposed to be superior. However, it was not known whether LDL-C values (calculated by the modified formula) meet laboratory performance criteria for their estimation. This study aimed to evaluate this. METHODS AND RESULTS: LDL-C values were calculated for 129,821 lipid profiles, using both Friedewald's formula and its modified version. Kappa statistics and intra-class correlation coefficient (ICC) were used to determine degree of agreement between directly measured and calculated values for LDL-C. Bias and total percentage error of the values were calculated. LDL-C concentrations calculated by the modified formula showed a greater degree of agreement with directly measured values (kappa = 0.713) than those calculated by Friedewald's formula (kappa = 0.595). Both the formulae produced values with negative biases (-3.47 for the modified formula and -7.62 for Friedewald's formula) and total percentage errors above the recommended limit of 12% (15.57% for the modified formula and 21.77% for Friedewald's formula). ICC showed that values calculated by the modified formula showed a greater degree of agreement with directly measured values, across a range of LDL-C values. CONCLUSION: Calculated LDL-C values, using the modified formula, showed better agreement with directly measured values, and less bias and percentage total error than those obtained by use of Friedewald's formula. However, the percentage total error with use of the modified formula exceeded the recommended limit for LDL-C.

Low Serum Hepcidin Levels in Patients with Ulcerative Colitis - Implications for Treatment of Co-existent Iron-Deficiency Anemia.

Ulcerative colitis (UC) is often associated with anemia. Hepcidin, the central regulator of iron homeostasis, is known to be induced by inflammation and suppressed by anemia. It is not clear how hepcidin is affected in those with UC, when both inflammation and anemia may co-exist.Such knowledge may hold implications for treatment. Hematological and iron-related parameters, C-reactive protein (CRP), growth differentiation factor 15 (GDF-15) and erythroferrone (ERFE) (erythroid regulators of hepcidin) levels were estimated in blood from those with UC and in control subjects. Values for hematological and iron-related parameters showed evidence of iron-deficiency and resultant anemia, in patients with UC. The presence of UC was significantly associated with inflammation. Serum levels of ERFE, but not of GDF-15, were significantly higher in patients with UC than in control patients, while hepcidin levels were significantly lower. Serum hepcidin concentrations in patients with UC correlated positively with serum iron, ferritin and GDF-15, and negatively with serum ERFE. The iron status and serum hepcidin levels in UC patients with co-existent anemia were significantly lower and serum ERFE values significantly higher than in those with UC without anemia. The effect of anemia on hepcidin predominated over that of inflammation in patients with UC, resulting in suppressed hepcidin levels. This effect is possibly mediated through erythroferrone. We suggest that a serum hepcidin-guided approach may be useful to guide use of oral iron supplements to treat co-existent iron-deficiency anemia in patients with UC and other chronic inflammatory diseases.

Indian microbiology EQAS registered laboratory's capacity building and infection control practices during the COVID-19 pandemic in India: Lessons learnt and gaps identified.

PURPOSE: The COVID-19 pandemic was unique in the history of outbreaks because of the massive scaling up of resources related to diagnostics, treatment modalities, and vaccines. To understand the impact of the pandemic among laboratory professionals, we aimed to conduct a survey to assess the improvement in the lab capacity post-covid in terms of infrastructure and accreditation status across various levels of hospitals and to determine the changes in the practice of infection control precautions during the pandemic. METHODS: This was an anonymous, online-based survey (using 58 item questionnaire) conducted between July 09, 2021, and August 07, 2021. The survey targeted all EQAS registered diagnostic laboratories located in India. RESULTS: The survey reached out to 1182 participants, out of which 721 (61%) laboratories completed the questionnaire. During pre-COVID times, only 39% (282/721) of the laboratories had an RT-PCR facility. Among these 721 labs, 514 used open system RT-PCR assay, 217 labs used Truenat assay, 188 labs used GeneXpert assay, 31 used Abbott ID Now and 350 labs performed rapid antigen tests. During the pandemic, 55.3% got NABL accreditation and 7.4% were in the process of applying for COVID-19 molecular testing. In this, 80.7% of the laboratories participated in the ICMR - COVID quality control assessment. It was estimated that 41.4% of the laboratory professionals were re-using N95 masks. Overall, the infection prevention and control practices varied across each laboratory and hospital. CONCLUSION: These survey findings helped us to understand the strength and efficiency of laboratories in India in setting up new assays during a crisis time. Based on our findings, we propose to connect this network in a sustained manner to efficiently utilize the existing platforms to adapt to future pandemics.

Transmission Dynamics of COVID-19 and Utility of Contact Tracing in Risk Assessment of Health-Care Worker Exposure during COVID-19 Pandemic.

Background: In the COVID-19 pandemic, the frontline health-care workers (HCWs) are at increased risk of acquiring infection either through household or workplace exposure. Objectives: To assess the risk of acquiring infection after COVID-19 exposure, we evaluated the effectiveness of a contact tracing assessment to identify the high-risk contacts. Materials and Methods: All HCW who tested COVID-19 positive in July 2020 were interviewed to do risk assessment based on their exposure, advised quarantine, and then followed up on day 14 for development of symptoms of COVID-19. Results: Contact tracing identified 2569 HCW contacts for 422 index positive cases, among which 1642 (63.9%) were contactable for follow-up. Among 1642 contacts, 12.97% developed COVID-19 symptoms within 14 days of the exposure. Household contacts comprising (142 out of 956, 14.9%) had a higher risk of becoming symptomatic than workplace contacts (71 out of 686, 10.3%) ([odds ratio 0.66 (confidence interval 0.49-0.89)]. Of these, 76.6% of the household exposure and 55.4% of significant workplace exposure were tested positive for COVID-19. Conclusions: Based on the risk assessment, we found that a HCW is likely to acquire infection at home rather than at the workplace, and hence, an appropriate quarantine policy can help decrease the transmission and mitigate staff shortage.