Hand hygiene is a simple, low-cost intervention that may lead to substantial population-level effects in suppressing acute respiratory infection epidemics. However, quantification of the efficacy of hand hygiene on respiratory infection in the community is lacking. We searched PubMed for randomised controlled trials on the effect of hand hygiene for reducing acute respiratory infections in the community published before 11 March 2021. We performed a meta-regression analysis using a Bayesian mixed-effects model. A total of 105 publications were identified, out of which six studies reported hand hygiene frequencies. Four studies were performed in household settings and two were in schools. The average number of handwashing events per day ranged from one to eight in the control arms, and four to 17 in the intervention arms. We estimated that a single hand hygiene event is associated with a 3% (80% credible interval (−1% to 7%)) decrease in the daily probability of an acute respiratory infection. Three of these six studies were potentially at high risk of bias because the primary outcome depended on self-reporting of upper respiratory tract symptoms. Well-designed trials with an emphasis on monitoring hand hygiene adherence are needed to confirm these findings.

Background: A quantitative understanding of the impact of delays to concordant antibiotic treatment on patient mortality is important for designing hospital antibiotic policies. Acinetobacter spp are among the most prevalent pathogens causing multidrug-resistant hospital-acquired infections in developing countries. We aimed to determine the causal effect of delays in concordant antibiotic treatment on 30-day survival of patients with hospital-acquired Acinetobacter spp bacteremia in a resource-limited setting. Methods: We included patients with Acinetobacter spp–related hospital-acquired bacteremia (HAB) in a hospital in Thailand over a 13-year period. We classified patients into 4 groups: those with no delays to concordant antibiotic treatment; those with a 1-day delay; those with 2-day delays; and those with >2 days of delay. We adopted an analytical approach that aimed to emulate a randomized controlled trial and compared the expected potential outcomes of patients between the exposure groups using a marginal structural model with inverse-probability weightings to adjust for confounders and immortal time bias. Results: Between January 2003 and December 2015, 1,203 patients had HAB with Acinetobacter spp., of which 682 patients (56.7%) had ≥1 days of delay in concordant antibiotic treatment. These delays were associated with an absolute increase in 30-day mortality of 6.6% (95% CI 0.2%-13.0%), from 33.8% to 40.4%. Among the 1,203 patients, 521 had no delays to concordant antibiotic treatment (i.e. concordant therapy on the day of blood collection), 224 patients had a 1-day delay, 119 had a 2-day delay, and 339 had a delay of ≥3 days. The crude 30-day mortality was substantially lower in patients with ≥3 days of delay in concordant treatment compared to those with 1 to 2-days of delays. After adjusting for measured confounders and immortal time bias, the expected probability of dying in the hospital within 30-days of blood collection if patient had no delays in concordant therapy was 39.7% (95% CI: 32.3-47.2%), for a 1-day delay it was 42.7% (95% CI: 29.8-55.7%), for a 2-day delay it was 51.0% (95% CI: 38.9-63.2%), and for a ≥3 days was 40.9% (36.0-45.7%).

Conclusions: Delays to concordant antibiotic therapy are linked to increased mortality among patients with HAB due to Acinetobacter spp. Accounting for confounders and immortal time bias is necessary when attempting to estimate causal effects of delayed concordant treatment and, in this case, it helped resolve paradoxical results in crude data.

Funding: The Mahidol Oxford Tropical Medicine Research Unit (MORU) is funded by the Wellcome Trust [grant number 106698/Z14/Z]. CL is funded by a Wellcome Trust Research Training Fellowship [grant number 206736/Z/17/Z]. MY is supported by a Singapore National Medical Research Council Research Fellowship [grant number NMRC/Fellowship/0051/2017]. BSC is funded by the UK Medical Research Council and Department for International Development [grant number MR/K006924/1]. DL is funded by a Wellcome Trust Intermediate Training Fellowship [grant number 101103]. The funder has no role in the design and conduct of the study, data collection, or in the analysis and interpretation of the data.

Disclosures: None

OBJECTIVES/SPECIFIC AIMS: Women with GDM have a 7-fold higher risk of developing T2DM, and rates of GDM are higher among racial and ethnic minorities and women of lower socio-economic status. There are no data on postpartum diabetes screening after the first postpartum year or among women receiving care in FQHCs. We aim to address this gap in the literature by (1) defining the rates of follow-up screening for T2DM at 6–12 weeks and 1–3 years postpartum and (2) characterizing patient, provider, and healthcare system attributes that are associated with lack of follow-up screening for T2DM in a population of low-income women with GDM. METHODS/STUDY POPULATION: This is a retrospective cohort study of women with GDM during pregnancy receiving care in Missouri FQHCs from 2010 to 2015. Electronic health records (EHR) data from 26 FQHCs is housed in a central repository through the Missouri Primary Care Association (MPCA). This includes patient demographic, lab, and medication information as well as encounter level patient and provider data for the prenatal and postpartum period. EHR data does not include accurate delivery information, however. Pregnancies during the study time frame were identified using CPT and ICD9/10 codes. Deidentified data on individuals with a pregnancy was utilized to identify a subpopulation of “GDM candidates,” using a broad definition of glucose abnormalities as follows: ICD-9/ICD-10 codes for diabetes, medications and testing supplies used for diabetes, infant birth weight ≥4000 g or 8 lb or 13 oz, or abnormal glucose labs [defined as fasting glucose≥95, gestational glucose screen≥130, 1 h test≥130 (or ≥180 if 2 h test and 3 h test recorded on same day), 2 h test≥155, 3 h test≥140, A1C≥6, any glucose≥130, or any positive urine glucose]. This subpopulation was then linked to Medicaid administrative claims data [housed at the University of Missouri Office of Social and Economic Development Analysis (OSEDA)], providing detailed information on delivery, to further characterize patients with GDM in the time frame and provide all dates necessary to classify pregnancy and postpartum periods. RESULTS/ANTICIPATED RESULTS: From the de-identified pregnancy data set including 45,810 individuals, we identified 8008 “GDM candidates.” EHR data were linked to Medicaid claims data for these individuals from 2010 to 2015. Utilizing the enhanced data set, we are defining a pregnancy for each individual by the delivery date in the Medicaid record and an algorithm using lab and ultrasound record dates to define gestational age at delivery. This will result in a pregnancy level data set linked with individual encrypted identifiers with each record representing 1 pregnancy and postpartum period. GDM in pregnancy will be defined as having a baby with birth weight≥4000 g or 8 lb or 13 oz, ICD-9 or ICD-10 code for GDM during pregnancy or at delivery, or an oral glucose tolerance test (oGTT) 12–16 weeks before delivery with 2 or more abnormal results by Carpenter and Coustan criteria. We anticipate that our final GDM data set will include 2000–3000 individuals. We will then calculate the percentage of individuals receiving recommended screening tests at 6–12 weeks (fasting glucose or 2 h oGTT) and 1–3 years postpartum (fasting glucose, 2 h oGTT, HbA1C). We will use multivariable regression techniques to identify risk factors for lack of screening. We will be able to incorporate predictors not previously evaluated including distance from home to health center, access to public transport, specialty and training of the patient’s providers, pregnancy weight gain, postpartum appointment time of day, and number of various types of office visits. DISCUSSION/SIGNIFICANCE OF IMPACT: The creation of a linked data set of pregnancies complicated by GDM in women receiving care in FQHCs in Missouri is the first step toward better characterizing follow-up diabetes screening rates in this population and understanding patient, provider, and healthcare system variables that affect postpartum screening. The ultimate goal is to translate evidence-based patient-centered sustainable interventions into practice for low-income women with a history of GDM and improve population outcomes with the ability to track progress prospectively over time.

Acknowledgements: The authors thank Susan Wilson (MPCA), Jill Lucht, and Bhawani Mishra (OSEDA).

During puberty young people undergo significant hormonal changes which affect metabolism and, subsequently, health. Evidence suggests there is a period of transient pubertal insulin resistance, with this effect greater in girls than boys. However, the response to everyday high and low glycaemic index (GI) meals remains unknown. Following ethical approval, forty adolescents consumed a high GI or low GI breakfast, in a randomised cross-over design. Capillary blood samples were taken during a 2-h postprandial period, examining the glycaemic and insulinaemic responses. Maturity offset and homoeostatic model assessment (HOMA) were also calculated. The glycaemic response to the breakfasts was similar between boys and girls, as shown by similar peak blood glucose concentrations and incremental AUC (IAUC) following both high and low GI breakfasts (all P>0·05). Girls exhibited a higher peak plasma insulin concentration 30 min post-breakfast following both high GI (P=0·043, g=0·69) and low GI (P=0·010, g=0·84) breakfasts, as well as a greater IAUC following high GI (P=0·041, g=0·66) and low GI (P=0·041, g=0·66) breakfasts. HOMA was positively correlated with the insulinaemic responses (all P<0·0005) and maturity offset (P=0·037). The findings of the present study suggest that pubertal insulin resistance affects the postprandial insulinaemic responses to both high and low GI meals. Specifically, girls exhibit a greater insulinaemic response than boys to both meals, despite similar glycaemic responses. This study is the first to report the glycaemic and insulinaemic responses to everyday meals in boys and girls, supporting the recommendation for young people to base their diet on low GI carbohydrates.

The ethics of high frequency trading are obscure, due in part to the complexity of the practice. This article contributes to the existing literature of ethics in financial markets by examining a recent trend in regulation in high frequency trading, the prohibition of deception. We argue that in the financial markets almost any regulation, other than the most basic, tends to create a moral hazard and increase information asymmetry. Since the market’s job is, at least in part, price discovery, we argue that simplicity of regulation and restraint in regulation are virtues to a greater extent than in other areas of finance. This article proposes criteria for determining which high-frequency trading strategies should be regulated.

Background: The Hospital Anxiety and Depression Scale (HADS) is widely used but evaluation of its psychometric properties has produced equivocal results. Little is known about its structure in non-clinical samples of older people.

Methods: We used data from four cohorts in the HALCyon collaborative research program into healthy aging: the Caerphilly Prospective Study, the Hertfordshire Ageing Study, the Hertfordshire Cohort Study, and the Lothian Birth Cohort 1921. We used exploratory factor analysis and confirmatory factor analysis with multi-group comparisons to establish the structure of the HADS and test for factorial invariance between samples.

Results: Exploratory factor analysis showed a bi-dimensional structure (anxiety and depression) of the scale in men and women in each cohort. We tested a hypothesized three-factor model but high correlations between two of the factors made a two-factor model more psychologically plausible. Multi-group confirmatory factor analysis revealed that the sizes of the respective item loadings on the two factors were effectively identical in men and women from the same cohort. There was more variation between cohorts, particularly those from different parts of the U.K. and in whom the HADS was administered differently. Differences in social-class distribution accounted for part of this variation.

Conclusions: Scoring the HADS as two subscales of anxiety and depression is appropriate in non-clinical populations of older men and women. However, there were differences between cohorts in the way that individual items were linked with the constructs of anxiety and depression, perhaps due to differences in sociocultural factors and/or in the administration of the scale.