Data quality predicts care quality: findings from a national clinical audit

Background: Missing clinical outcome data are a common occurrence in longitudinal studies. Data quality in clinical audit is a particular cause for concern. The relationship between departmental levels of missing clinical outcome data and care quality is not known. We hypothesise that completeness of key outcome data in a national audit predicts departmental performance. Methods: The National Clinical Audit for Rheumatoid and Early Inflammatory Arthritis (NCAREIA) collected data on care of patients with suspected rheumatoid arthritis (RA) from early 2014 to late 2015. This observational cohort study collected data on patient demographics, departmental variables, service quality measures including time to treatment, and the key RA clinical outcome measure, disease activity at baseline, and 3 months follow-up. A mixed effects model was conducted to identify departments with high/low proportions of missing baseline disease activity data with the results plotted on a caterpillar graph. A mixed effects model was conducted to assess if missing baseline disease activity predicted prompt treatment. Results: Six thousand two hundred five patients with complete treatment time data and a diagnosis of RA were recruited from 136 departments. 34.3% had missing disease activity at baseline. Mixed effects modelling identified 13 departments with high levels of missing disease activity, with a cluster observed in the Northwest of England. Missing baseline disease activity was associated with not commencing treatment promptly in an adjusted mix effects model, odds ratio 0.50 (95% CI 0.41 to 0.61, p < 0.0001). Conclusions: We have shown that poor engagement in a national audit program correlates with the quality of care provided. Our findings support the use of data completeness as an additional service quality indicator

Targeting Cellular DNA Damage Responses in Cancer: An In Vitro-Calibrated Agent-Based Model Simulating Monolayer and Spheroid Treatment Responses to ATR-Inhibiting Drugs

We combine a systems pharmacology approach with an agent-based modelling approach to simulate LoVo cells subjected to AZD6738, an ATR (ataxia–telangiectasia-mutated and rad3-related kinase) inhibiting anti-cancer drug that can hinder tumour proliferation by targeting cellular DNA damage responses. The agent-based model used in this study is governed by a set of empirically observable rules. By adjusting only the rules when moving between monolayer and multi-cellular tumour spheroid simulations, whilst keeping the fundamental mathematical model and parameters intact, the agent-based model is first parameterised by monolayer in vitro data and is thereafter used to simulate treatment responses in in vitro tumour spheroids subjected to dynamic drug delivery. Spheroid simulations are subsequently compared to in vivo data from xenografts in mice. The spheroid simulations are able to capture the dynamics of in vivo tumour growth and regression for approximately 8 days post-tumour injection. Translating quantitative information between in vitro and in vivo research remains a scientifically and financially challenging step in preclinical drug development processes. However, well-developed in silico tools can be used to facilitate this in vitro to in vivo translation, and in this article, we exemplify how data-driven, agent-based models can be used to bridge the gap between in vitro and in vivo research. We further highlight how agent-based models, that are currently underutilised in pharmaceutical contexts, can be used in preclinical drug development

Non-exercise equations to estimate fitness in white European and South Asian men

Cardiorespiratory fitness is a strong, independent predictor of health, whether it is measured in an exercise test or estimated in an equation. The purpose of this study was to develop and validate equations to estimate fitness in middle-aged white European and South Asian men.Multiple linear regression models (n=168, including 83 white European and 85 South Asian men) were created using variables that are thought to be important in predicting fitness (VO2 max, mL⋅kg⋅min): age (years); BMI (kg·m); resting heart rate (beats⋅min); smoking status (0=never smoked, 1=ex or current smoker); physical activity expressed as quintiles (0=quintile 1, 1=quintile 2, 2=quintile 3, 3=quintile 4, 4=quintile 5), categories of moderate- to vigorous-intensity physical activity (0=&lt;75 min⋅wk, 1=75-150 min⋅wk, 2=&gt;150-225 min⋅wk, 3=&gt;225-300 min⋅wk, 4=&gt;300 min⋅wk), or minutes of moderate- to vigorous-intensity physical activity (min⋅wk); and, ethnicity (0=South Asian, 1=white). The leave-one-out-cross-validation procedure was used to assess the generalizability and the bootstrap and jackknife resampling techniques were used to estimate the variance and bias of the models.Around 70% of the variance in fitness was explained in models with an ethnicity variable, such as: VO2 max = 77.409 - (age*0.374) - (BMI*0.906) - (ex or current smoker*1.976) + (physical activity quintile coefficient) - (resting heart rate*0.066) + (white ethnicity*8.032), where physical activity quintile 1 is 1, 2 is 1.127, 3 is 1.869, 4 is 3.793, and 5 is 3.029. Only around 50% of the variance was explained in models without an ethnicity variable. All models with an ethnicity variable were generalizable and had low variance and bias.These data demonstrate the importance of incorporating ethnicity in non-exercise equations to estimate cardiorespiratory fitness in multi-ethnic populations

Wintering Area DDE Source to Migratory White-Faced Ibis Revealed by Satellite Telemetry and Prey Sampling

Locations of contaminant exposure for nesting migratory species are difficult to fully understand because of possible additional sources encountered during migration or on the wintering grounds. A portion of the migratory white-faced ibis (Plegadis chihi) nesting at Carson Lake, Nevada continues to be exposed to dichloro-diphenyl-dichloroethylene (DDE) with no change, which is unusual, observed in egg concentrations between 1985 and 2000. About 45 to 63% of the earliest nesting segment shows reduced reproductive success correlated with elevated egg concentrations of \u3e 4 µg/g wet weight (ww). Local prey (primarily earthworms) near nests contained little DDE so we tracked the migration and wintering movements of 20 adult males during 2000-2004 to determine the possible source. At various wintering sites, we found a correlation (r2 = 0.518, P = 0.0125, N = 11) between DDE in earthworm composites and DDE in blood plasma of white-faced ibis wintering there, although the plasma was collected on their breeding grounds soon after arrival. The main source of DDE was wintering areas in the Mexicali Valley of Baja California Norte, Mexico, and probably the adjacent Imperial Valley, California, USA. This unusual continuing DDE problem for white-face ibis is associated with: the long-term persistence in soil of DDE; the earthworms’ ability to bioconcentrate DDE from soil; the proclivity of white-faced ibis to feed on earthworms in agricultural fields; the species extreme sensitivity to DDE in their eggs; and perhaps its life history strategy of being a “capital breeder”. We suggest surveying and sampling white-faced ibis eggs at nesting colonies, especially at Carson Lake, to monitor the continuing influence of DDE

Teaching Applications and Implications of Blockchain via Project-Based Learning: A Case Study

This paper presents student projects analyzing or using blockchain technologies, created by students enrolled in courses dedicated to teaching blockchain, at two different universities during the 2018-2019 academic year. Students explored perceptions related to storing private healthcare information on a blockchain, managing the security of Internet of Things devices, maintaining public governmental records, and creating smart contracts. The course designs, which were centered around project-based learning, include self-regulated learning and peer feedback as ways to improve student learning. Students either wrote a research paper or worked in teams on a programming project to build and deploy a blockchain-based application using Solidity, a programming language for writing smart contracts on various blockchain platforms. For select student papers, this case study describes research methods and outcomes and how students worked together or made use of peer feedback to improve upon drafts of research questions and abstracts. For a development project in Solidity, this study presents the issues at hand along with interview results that guided the implementation. Teams shared lessons learned with other teams through a weekly status report to the whole class. While available support for the Solidity teams was not ideal, students learned to use available online resources for creating and testing smart contracts. Our findings suggest that a project-based learning approach is an effective way for students to expand and develop their knowledge of emerging technologies, like blockchain, and apply it in a variety of industrie

Seeking and applying diagnostic information in a health care setting

Many studies have shown that people have difficulty judging the diagnostic value of conditional probability information with respect to one or more hypotheses. The present research addressed two aspects of performing the diagnostic task in a health care decision: (a) recognition of the information's importance, and (b) correct usage of that information. In experiment 1, health care providers, who are trained in, and regularly exposed, to conditional probabilities imparting diagnostic information, exhibited at least a rudimentary recognition of the need for this information in assessing diagnosticity. Experiment 2 indicated that health care and layperson subjects had difficulty in actually applying the information, however. This difficulty prompts a need for judgment aids and caution in using diagnostic information.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28644/1/0000459.pd

Independent and Interactive Influences of Environmental UVR, Vitamin D Levels, and Folate Variant MTHFD1-rs2236225 on Homocysteine Levels

Elevated homocysteine (Hcy) levels are a risk factor for vascular diseases. Recently, increases in ultraviolet radiation (UVR) have been linked to decreased Hcy levels. This relationship may be mediated by the status of UVR-responsive vitamins, vitamin D and folate, and/or genetic variants influencing their levels; however, this has yet to be examined. Therefore, the independent and interactive influences of environmental UVR, vitamin D and folate levels and related genetic variants on Hcy levels were examined in an elderly Australian cohort (n = 619). Red blood cell folate, 25-hydroxyvitamin D (25(OH)D), and plasma Hcy levels were determined, and genotyping for 21 folate and vitamin D-related variants was performed. Erythemal dose rate accumulated over six-weeks (6W-EDR) and four-months (4M-EDR) prior to clinics were calculated as a measure of environmental UVR. Multivariate analyses found interactions between 6W-EDR and 25(OH)D levels (pinteraction = 0.002), and 4M-EDR and MTHFD1-rs2236225 (pinteraction = 0.006) in predicting Hcy levels. The association between 6W-EDR and Hcy levels was found only in subjects within lower 25(OH)D quartiles (<33.26 ng/mL), with the association between 4M-EDR and Hcy occurring only in subjects carrying the MTHFD1-rs2236225 variant. 4M-EDR, 6W-EDR, and MTHFD1-rs2236225 were also independent predictors of Hcy. Findings highlight nutrient–environment and gene–environment interactions that could influence the risk of Hcy-related outcomes