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Background: Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2/2019-nCoV). Though many classes of drugs have been advocated/used for the treatment of this disease, vaccines are being targeted for its ultimate prevention. Indian Government has approved Covishield (ChAdOx1 nCoV19 Corona Virus Vaccine-Recombinant) for restricted use in emergency circumstances. Objective: This study is aimed at evaluating the safety profile of the Covishield vaccine among healthcare workers in a tertiary care hospital. Methods: All Adverse Drug Reactions (ADRs) reported to the ADR monitoring centre by healthcare workers who received the Covishield vaccine during the study period of 3 months were analysed on various parameters, and the assessment was done using the WHO-UMC scale. Results: During the study period, a total of 1216 beneficiaries were vaccinated with 1st dose of Covishield, and out of these, 727 beneficiaries also received 2nd dose of the vaccine. Out of the 1216 beneficiaries vaccinated, 69 ADRs were reported in 24 healthcare workers. The most common ADR reported was fever (24.64%), followed by myalgia (18.84%). No death or any serious anaphylactic reaction was observed. None of the healthcare workers experienced any adverse event during the observation period of 30 minutes. Serious reactions were reported in 4 healthcare workers as per the Pharmacovigilance Programme of India (PvPI) criteria of serious AEFI. 92% of healthcare workers recovered from ADRs during the study period. 84% of ADRs were classified as probable as per the WHO-UMC scale. Conclusion: As per the Government of India directives, all the healthcare workers in the institute were encouraged to take both doses of the Covishield vaccine. The beneficiaries were kept under observation for 30 minutes and monitored for any adverse drug reaction following vaccination. The vaccine was found to be safe with a very low incidence of ADRs.

ContextDiabetes or hyperglycemia at admission are established risk factors for adverse outcomes during hospitalization for COVID-19, but the impact of prior glycemic control is not clear.ObjectiveWe aimed to examine the associations between admission variables, including glycemic gap, and adverse clinical outcomes in patients hospitalized with COVID-19 infection.MethodsWe examined the relationship between clinical predictors, including acute and chronic glycemia, and clinical outcomes, including intensive care unit (ICU) admission, mechanical ventilation (MV), and mortality among 1786 individuals with diabetes or hyperglycemia (glucose > 10 mmol/L twice in 24 hours) who were admitted from March 2020 through February 2021 with COVID-19 infection at 5 university hospitals in the eastern United States.ResultsThe cohort was 51.3% male, 53.3% White, 18.8% Black, 29.0% Hispanic, with age = 65.6 ± 14.4 years, BMI = 31.5 ± 7.9 kg/m2, glucose = 12.0 ± 7.5 mmol/L [216 ± 135 mg/dL], and HbA1c = 8.07% ± 2.25%. During hospitalization, 38.9% were admitted to the ICU, 22.9% received MV, and 10.6% died. Age (P < 0.001) and admission glucose (P = 0.014) but not HbA1c were associated with increased risk of mortality. Glycemic gap, defined as admission glucose minus estimated average glucose based on HbA1c, was a stronger predictor of mortality than either admission glucose or HbA1c alone (OR = 1.040 [95% CI: 1.019, 1.061] per mmol/L, P < 0.001). In an adjusted multivariable model, glycemic gap, age, BMI, and diabetic ketoacidosis on admission were associated with increased mortality, while higher estimated glomerular filtration rate (eGFR) and use of any diabetes medication were associated with lower mortality (P < 0.001).ConclusionRelative hyperglycemia, as measured by the admission glycemic gap, is an important marker of mortality risk in COVID-19.

Background: The price of medicine in India has always been a point of discussion in public domain. The price range of the same drug is very large with more than 100% difference between various brands available in different settings. Aims and Objectives: To assess the price of different drugs at Jan Aushasdhi (JA), AMRIT and Private Chemist and to compare the prices of these three outlets so that the issues. Material and Methods: This institution-based cross-sectional study was carried out from May 2019 to June 2019. A pretested proforma was prepared to compare the prices of 284 different medicines in Jan Aushadhi, AMRIT and private chemist shops. The collected data were entered in an Excel spreadsheet and presented in Proportions, percentages, and mean. Results: The price of 284 medicines were compared from JA (Median(IQR)- 15.18(18.75) INR) and Private chemist shop (Median(IQR)-88(111.5) INR) while 249 medicine from AMRIT (Median(IQR)-61.05(78.33) INR). Although the majority of the AMRIT drugs are cheaper than the chemist shop except for 31% of Antipsychotic drugs, 26.6% of antihypertensives, 25% of respiratory drugs, 25% of steroids, 21.9% of antibiotics. Conclusion: We concluded that JA is providing drugs cheaper than AMRIT and Private chemist . The prices of medicines offered at AMRIT are lower than market pricing but they are costlier when compared to JA prices.

Improving the efficiency of internal combustion engines can result in lower operating costs and enable reduced total cost of vehicle ownership. On the other hand, it is of utmost importance that the development of engine technologies is also directed toward curbing climate-altering and harmful emissions. One such technology is gasoline compression ignition, which can offer increased fuel efficiency and reduced emissions and criteria pollutants. By means of modal analysis methods, this study focuses on characterizing the internal flow behavior of a production, eight-hole, medium-duty diesel injector operating with gasoline-like fuels under typical diesel injection conditions. High-resolution tomographic reconstructions of the injector tip geometry, along with needle motion measurements, were obtained via X-ray measurements. This information was combined with a previously validated computational setup to perform a series of in-nozzle flow computational fluid dynamics (CFD) simulations. The CFD results were analyzed to identify the connection between the injector’s global behavior and relevant flowfields such as velocity and vorticity. The results obtained with the X-ray geometry were then compared against those obtained with a nominal geometry to investigate the effect of the injector’s geometric features on its behavior. Variations to the K-factor and inlet ellipticity of the orifices were explored, and these parameters’ ability to reduce in-orifice cavitation was assessed by analyzing the predicted in-orifice fuel vapor volume fraction. Relatively large and persistent flow structures arising within the injector sac were identified as the main driver for orifice-to-orifice variability, as their location and size impacted the amount of fuel delivered by each orifice. Assessing the extent to which these energetic structures impact the injector performance is of interest; thus, it is desirable to investigate the most energetically significant flowfield structures as a function of modifications to specific features of the injector geometry. Modal decomposition tools, such as space-only proper orthogonal decomposition (POD) and spectral proper orthogonal decomposition (SPOD) were applied to gain insight into dominant coherent structures that persist over the early phase of the needle opening event. It was found that the geometrical modifications applied resulted in variations of the modal energy content, as well as in the leading dominant spatial mode features. Additionally, it was found that the dominant frequency associated with the most significant energetic content was largely invariant to the geometrical modifications, with the difference between realistic and modified geometries being mostly found in the modal energy content.

OBJECTIVE: The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers. METHODS: The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development. RESULTS: This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes. CONCLUSIONS: This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Lack of healthcare insurance is an important factor for poor glycemic control in persons with diabetes. However, a large proportion of insured people also have inadequate glycemic control. This study was conducted to assess factors associated with poor glycemic control in persons with type 2 diabetics (T2D) who received full healthcare coverage through their employer.The study included employees and spouses with T2D who participated in an annual health assessment in 20 and had medical coverage ≥12 consecutive months prior to the assessment. T2D was defined from ICD codes in claims, self-reported physician diagnosis, or having fasting glucose > 125 mg/dL or HbA1C > 6.4%. A stepwise multinomial logistic regression model was used to assess associations of healthcare engagement, diet, smoking and socioeconomic status with glycemic control. The 2,981 participants included 16% (n=484) with HbA1C > 8.5% and 27% (n=800) with HbA1C 7 to 8.5%. We found that HbA1C > 8.5% was associated with age, sex, years since last physical exam, number of complications, number of medications, and physical activity. The regression model results are shown in the figure. We conclude that poor glycemic control is common among persons with T2D despite good healthcare coverage. We identified factors associated with poor glycemic control in this population that may help design strategies to improve glycemic control. Disclosure C.M.Rowland: Employee; Quest Diagnostics, Stock/Shareholder; Quest Diagnostics. J.Z.Louie: None. D.Shiffman: Employee; Quest Diagnostics, Stock/Shareholder; Quest Diagnostics. R.Garg: None. E.Bernal-mizrachi: None. M.J.Mcphaul: Employee; Quest Diagnostics.

Poor socioeconomic status and inadequate insurance coverage may affect an individual’s ability to utilize healthcare services. This study was conducted to evaluate whether the type of insurance coverage is associated with missed appointments for diabetes care. Data analysis included all patients with diabetes mellitus (DM) managed at a major academic center between Jan 2015 and Dec 2020. Association between insurance coverage and proportion of missed appointments was evaluated using analysis of covariance with adjustments for demographic variables and social determinants of health. The relationship between proportion of missed appointments and glycemic control was also evaluated in multivariate analyses. The final dataset included 30,633 patients, out of which 14,064 (46%) reported commercial insurance, 13,376 (44%) reported Medicare and 3,193 (10%) reported Medicaid coverage. Medicaid group was identified to have the highest proportion of Spanish-speakers, African Americans, women, current smokers and single individuals. Proportion of missed appointments was 18.1 ± 18.1% in Medicaid covered patients as compared to 12.1 ± 15.3% among commercially insured and 10.2 ± 14.1% among Medicare covered patients (p Disclosure R.Radhakrishnan: None. W.H.Cade: None. E.Bernal-mizrachi: None. R.Garg: None.

The ADA recommends an A1C 8.5% (poor control) were included. Patients with improved glycemic control (current A1C ≤8.5%) were compared with those with lack of improvement (current A1C >8.5%) . On multivariate logistic regression analysis including all variables in the model, independent predictors of lack of improvement were: younger age (OR 0.89 per 1-SD [12 years]; 95 % CI 0.79 - 1.00) , female gender (1.30, 1.- 1.56) , presence of hypertension (1.29, 1.- 1.55) , Black race (1.32, 1.- 1.68, White as reference) , low income area code (1.86,1.28 - 2.68, high as reference) and insurance coverage other than Medicare (1.32, 1.- 1.66) . Presence of current smoking was associated with a paradoxical improvement in A1C (0.69, 0.47 - 0.99) . We conclude that socioeconomic factors like income, insurance coverage and neighborhood are associated with lack of improvement in A1C. Further studies need to identify specific modifiable socioeconomic factors. Disclosure R. Garg: None. J.Z. Louie: None. D. Shiffman: Employee; Quest Diagnostics. Stock/Shareholder; Quest Diagnostics. C.M. Rowland: Employee; Quest Diagnostics. Stock/Shareholder; Quest Diagnostics. M.J. McPhaul: Employee; Quest Diagnostics. E. Bernal-Mizrachi: None. N. Kenyon: Research Support; Elodon Phamaceutical, Takeda Pharmaceutical Company Limited.

While diabetes and admission blood glucose (BG) are established risk factors for adverse outcomes during hospitalization for COVID-19, reports on the impact of prior glycemic control have been variable. We examined the relationship between acute and chronic glycemia on risk of ICU admission, mechanical ventilation (MV) , and mortality among 1,786 patients with diabetes or hyperglycemia (BG > 180 mg/dl twice during any 24-hr period during hospitalization) admitted from March 2020 to February 2021 with COVID-at 5 large university hospitals in the eastern U.S. The cohort was 51.3% male, 53.3% White, 18.8% Black, 29.3% Hispanic, with age = 64.8 ± 13.8 y, BMI = 31.5 ± 7.9 kg/m2, admission BG = 216 ± 134 mg/dl, and HbA1c = 8.1 ± 2.2%. During hospitalization, 38.9% were admitted to the ICU, 22.9% received MV, and 10.6% died. In multivariate regression analysis, among demographic factors, age was the strongest risk factor for in-hospital mortality (OR = 1.per year [95% CI: 1.04, 1.06]) , and Hispanic ethnicity was the greatest risk factor for ICU admission (OR = 1.45 [95% CI: 1.16, 1.80]) and intubation (OR = 1.64 [95% CI: 1.28, 2.10]) . Higher BMI (p = 0.005) and admission BG (p = 0.014) were associated with increased risk of mortality, but HbA1c was not. The glycemic gap (GG) , defined as admission BG minus estimated average BG based on HbA1c, was a stronger predictor of mortality than either admission BG or HbA1c alone. Mortality rate was 5.7% for GG < -20 mg/dl; 12.2% for GG = -20 to < 20 mg/dl; 12.4% for GG = 20 to < 100 mg/dl; and 16.1% for GG ≥ 100 mg/dl (p for trend < 0.001) . Conclusion: Among patients with diabetes or hyperglycemia admitted for COVID-19, in addition to previously established risk factors for poor outcomes (age, Hispanic ethnicity, and BMI) , we found that GG is a stronger predictor of in-hospital mortality than blood glucose alone. This suggests that relative hyperglycemia, as measured by the admission GG, is an important marker of disease severity in COVID-and potentially other serious illnesses. Disclosure M.E.Mcdonnell: Advisory Panel; Everlywell, Inc., Research Support; Lilly, Stock/Shareholder; Abbott Diabetes. G.P.Westcott: None. D.C.Simonson: Stock/Shareholder; GI Windows, Phase V Technologies, Inc. G.Gopalakrishnan: Research Support; Eli Lilly and Company, Spruce Biosciences. R.Garg: None. J.Mitri: Consultant; dairy management, Lnutra. R.S.Weinstock: Research Support; Boehringer Ingelheim International GmbH, Dexcom, Inc., Diasome, Eli Lilly and Company, Insulet Corporation, Kowa Pharmaceuticals America, Inc., Medtronic, Novo Nordisk, Tandem Diabetes Care, Inc., Tolerion, Inc. M.Greenfield: None. N.E.Palermo: Research Support; Dexcom, Inc. R.Radhakrishnan: None. Funding Brigham-TechFoundation, Cambridge, MA 2021

Ocular allergy in the form of Seasonal Allergic Conjunctivitis is one of the most common conditions that ophthalmologists deal with. The signs and symptoms can be distressing and debilitating. The search is still on for the perfect topical drug with maximum efficacy and minimum side effects. We decided to undertake a study to compare and evaluate the efficacy of 3 commonly used drugs, topical Ketorolac tromethamine 0.5%, Ketotifen fumarate 0.05% and Azelastine hydrochloride in patients of Seasonal Allergic Conjunctivitis. 150 patients of Seasonal Allergic Conjunctivitis of both sexes in the age group of 15- 55 years were included. Patients included in the study had bilateral signs and symptoms of Seasonal Allergic Conjunctivitis. Group A patients were given Ketorolac tromethamine 0.5% to be instilled four times a day; Group B patients were given Ketotifen fumarate 0.05% to be instilled two times a day, and Group C patients were given Azelastine hydrochloride 0.05% to be instilled two times a day. The drops were dispensed in identical containers labeled A to C so that the patient did not know the type of drug administered. Informed consent was taken from all the patients. Patients were given the drugs on day 0 and the responses were assessed at 30 minutes (day 0), day 2, day 7, day 14, day 28 and 3 months. The drugs were instilled in both the eyes but the efficacy variables were studied in the eye with greater sign and symptoms. If both eyes had same grades of signs and symptoms, left eye of the patient was assessed. All 3 groups were age and sex matched. On each visit, the patient’s signs and symptoms were graded by the investigator and the total score was noted. During the course of the study, patients were asked regarding any side effects pertaining to the drugs being instilled. Drug A (Ketorolac) had a statistically significant difference as compared to Drug B (Ketotifen) at all follow-up intervals (p< 0.05), except at three month follow up, when there was no significant difference between them (p = 0.07). Also, Drug A had a statistically significant difference as compared to Drug C (Azelastine) throughout the study period (p< 0.05). On comparing Drug B and Drug C, we observed a significant difference from the seventh day onwards. All three drugs had a statistically significant improvement in the total score over baseline from the 30 minute period (p< 0.001).