Sepsis biomarkers and diagnostic tools with a focus on machine learning.

Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers

Multi-objective improvement of software using co-evolution and smart seeding

Optimising non-functional properties of software is an important part of the implementation process. One such property is execution time, and compilers target a reduction in execution time using a variety of optimisation techniques. Compiler optimisation is not always able to produce semantically equivalent alternatives that improve execution times, even if such alternatives are known to exist. Often, this is due to the local nature of such optimisations. In this paper we present a novel framework for optimising existing software using a hybrid of evolutionary optimisation techniques. Given as input the implementation of a program or function, we use Genetic Programming to evolve a new semantically equivalent version, optimised to reduce execution time subject to a given probability distribution of inputs. We employ a co-evolved population of test cases to encourage the preservation of the program’s semantics, and exploit the original program through seeding of the population in order to focus the search. We carry out experiments to identify the important factors in maximising efficiency gains. Although in this work we have optimised execution time, other non-functional criteria could be optimised in a similar manner

What makes health promotion research distinct?

There have been concerns about the decline of health promotion as a practice and discipline and alongside this, calls for a clearer articulation of health promotion research and what, if anything, makes it distinct. This discussion paper, based on a review of the literature; the authors’ own experiences in the field; and a workshop delivered by two of the authors at the 8th Nordic Health Promotion Conference, seeks to state the reasons why health promotion research is distinctive. While by no means exhaustive, the paper suggests four distinctive features. The paper hopes to be a catalyst to enable health promotion researchers to be explicit in their practice and to begin the process of developing an agreed set of research principles

Measures for assessing practice change in medical practitioners

BACKGROUND: There are increasing numbers of randomised trials and systematic reviews examining the efficacy of interventions designed to bring about a change in clinical practice. The findings of this research are being used to guide strategies to increase the uptake of evidence into clinical practice. Knowledge of the outcomes measured by these trials is vital not only for the interpretation and application of the work done to date, but also to inform future research in this expanding area of endeavour and to assist in collation of results in systematic reviews and meta-analyses. METHODS: The objective of this review was to identify methods used to measure change in the clinical practices of health professionals following an intervention aimed at increasing the uptake of evidence into practice. All published trials included in a recent, comprehensive Health Technology Assessment of interventions to implement clinical practice guidelines and change clinical practice (n = 228) formed the sample for this study. Using a standardised data extraction form, one reviewer (SH), extracted the relevant information from the methods and/or results sections of the trials. RESULTS: Measures of a change of health practitioner behaviour were the most common, with 88.8% of trials using these as outcome measures. Measures that assessed change at a patient level, either actual measures of change or surrogate measures of change, were used in 28.8% and 36.7% of studies (respectively). Health practitioners' knowledge and attitudes were assessed in 22.8% of the studies and changes at an organisational level were assessed in 17.6%. CONCLUSION: Most trials of interventions aimed at changing clinical practice measured the effect of the intervention at the level of the practitioner, i.e. did the practitioner change what they do, or has their knowledge of and/or attitude toward that practice changed? Less than one-third of the trials measured, whether or not any change in practice, resulted in a change in the ultimate end-point of patient health status

Multicentre randomised controlled trial comparing standard and high resolution optical technologies in colorectal cancer screening.

Background and objectives: The UK bowel cancer screening programme (BCSP) has been established for the early detection of colorectal cancer offering colonoscopy to patients screened positive by faecal occult blood tests. In this multisite, prospective, randomised controlled trial, we aimed to compare the performance of Standard Definition Olympus Lucera (SD-OL) with Scope Guide and the High Definition Pentax HiLine (HD-PHL). Patients and methods: Subjects undergoing a colonoscopy as part of the UK National BCSP at four UK sites were randomised to an endoscopy list run using either SD-OL or HD-PHL. Primary endpoints were polyp and adenoma detection rate (PDR and ADR, respectively) as well as polyp size, morphology and histology characteristics. Results: 262 subjects (168 males, mean age 66.3±4.3 years) were colonoscoped (133 patients with HD-PHL while 129 with SD-OL). PDR and ADR were comparable within the two optical systems. The HD-PHL group resulted in a PDR 55.6% and ADR 43.6%; the SD-OL group had PDR 56.6% and ADR 45.7%. HD-PHL was significantly superior to SD-OL in detection of flat adenomas (18.6% vs 5.2%, p<0.001), but not detection of pedunculated or sessile polyps. Patient comfort, use of sedation and endoscopist perception of procedural difficulty resulted similar despite the use of Scope Guide with SD-OL. Conclusion: PDR and ADR were not significantly different between devices. The high-resolution colonoscopy system HD-PHL may improve polyp detection as compared with standard resolution technology in detecting flat adenomas. This advantage may have clinically significant implications for missed lesion rates and post-colonoscopy interval colorectal cancer rates

Investigating the experience of Moodle adoption through expert voices

Virtual learning environments (VLEs) such as Moodle are now widely used in universities and other organisations. One crucial factor in the successful employment of such platforms is the ability and commitment of teaching staff to adopt the system. Despite the importance of this role, there has been little work to examine the experience of using VLEs in practice. This paper presents initial, qualitative research aimed at understanding how Moodle is being used and the different experiences and perspectives of the staff involved. To generate themes and areas of interest for future investigation this paper uses interview data from two “expert witnesses” who have a deep understanding of how the platform is used. Emergent themes include: divergence between confident and basic users; the spread of usage within an academic community; lack of progression to innovative teaching methods

Physician Practice Patterns and Variation in the Delivery of Preventive Services

BACKGROUND: Strategies to improve preventive services delivery (PSD) have yielded modest effects. A multidimensional approach that examines distinctive configurations of physician attributes, practice processes, and contextual factors may be informative in understanding delivery of this important form of care. OBJECTIVE: We identified naturally occurring configurations of physician practice characteristics (PPCs) and assessed their association with PSD, including variation within configurations. DESIGN: Cross-sectional study. PARTICIPANTS: One hundred thirty-eight family physicians in 84 community practices and 4,046 outpatient visits. MEASUREMENTS: Physician knowledge, attitudes, use of tools and staff, and practice patterns were assessed by ethnographic and survey methods. PSD was assessed using direct observation of the visit and medical record review. Cluster analysis identified unique configurations of PPCs. A priori hypotheses of the configurations likely to perform the best on PSD were tested using a multilevel random effects model. RESULTS: Six distinct PPC configurations were identified. Although PSD significantly differed across configurations, mean differences between configurations with the lowest and highest PSD were small (i.e., 3.4, 7.7, and 10.8 points for health behavior counseling, screening, and immunizations, respectively, on a 100-point scale). Hypotheses were not confirmed. Considerable variation of PSD rates within configurations was observed. CONCLUSIONS: Similar rates of PSD can be attained through diverse physician practice configurations. Significant within-configuration variation may reflect dynamic interactions between PPCs as well as between these characteristics and the contexts in which physicians function. Striving for a single ideal configuration may be less valuable for improving PSD than understanding and leveraging existing characteristics within primary care practices

A Spoonful of Math Helps the Medicine Go Down: An Illustration of How Healthcare can Benefit from Mathematical Modeling and Analysis

<p>Abstract</p> <p>Objectives</p> <p>A recent joint report from the Institute of Medicine and the National Academy of Engineering, highlights the benefits of--indeed, the need for--mathematical analysis of healthcare delivery. Tools for such analysis have been developed over decades by researchers in Operations Research (OR). An OR perspective typically frames a complex problem in terms of its essential mathematical structure. This article illustrates the use and value of the tools of operations research in healthcare. It reviews one OR tool, queueing theory, and provides an illustration involving a hypothetical drug treatment facility.</p> <p>Method</p> <p>Queueing Theory (QT) is the study of waiting lines. The theory is useful in that it provides solutions to problems of waiting and its relationship to key characteristics of healthcare systems. More generally, it illustrates the strengths of modeling in healthcare and service delivery.</p> <p>Queueing theory offers insights that initially may be hidden. For example, a queueing model allows one to incorporate randomness, which is inherent in the actual system, into the mathematical analysis. As a result of this randomness, these systems often perform much worse than one might have guessed based on deterministic conditions. Poor performance is reflected in longer lines, longer waits, and lower levels of server utilization.</p> <p>As an illustration, we specify a queueing model of a representative drug treatment facility. The analysis of this model provides mathematical expressions for some of the key performance measures, such as average waiting time for admission.</p> <p>Results</p> <p>We calculate average occupancy in the facility and its relationship to system characteristics. For example, when the facility has 28 beds, the average wait for admission is 4 days. We also explore the relationship between arrival rate at the facility, the capacity of the facility, and waiting times.</p> <p>Conclusions</p> <p>One key aspect of the healthcare system is its complexity, and policy makers want to design and reform the system in a way that affects competing goals. OR methodologies, particularly queueing theory, can be very useful in gaining deeper understanding of this complexity and exploring the potential effects of proposed changes on the system without making any actual changes.</p

Health-related quality of life in Huntington’s Disease patients: a comparison of proxy assessment and patient self-rating using the disease-specific Huntington’s Disease health-related quality of life questionnaire (HDQoL)

Huntington’s disease (HD) is a fatal, neurodegenerative disease for which there is no known cure. Proxy evaluation is relevant for HD as its manifestation might limit the ability of persons to report their health-related quality of life (HrQoL). This study explored patient–proxy ratings of HrQoL of persons at different stages of HD, and examined factors that may affect proxy ratings. A total of 105 patient–proxy pairs completed the Huntington’s disease health-related quality of life questionnaire (HDQoL) and other established HrQoL measures (EQ-5D and SF-12v2). Proxy–patient agreement was assessed in terms of absolute level (mean ratings) and intraclass correlation. Proxies’ ratings were at a similar level to patients’ self-ratings on an overall Summary Score and on most of the six Specific Scales of the HDQoL. On the Specific Hopes and Worries Scale, proxies on average rated HrQoL as better than patients’ self-ratings, while on both the Specific Cognitive Scale and Specific Physical and Functional Scale proxies tended to rate HrQoL more poorly than patients themselves. The patient’s disease stage and mental wellbeing (SF-12 Mental Component scale) were the two factors that primarily affected proxy assessment. Proxy scores were strongly correlated with patients’ self-ratings of HrQoL, on the Summary Scale and all Specific Scales. The patient–proxy correlation was lower for patients at moderate stages of HD compared to patients at early and advanced stages. The proxy report version of the HDQoL is a useful complementary tool to self-assessment, and a promising alternative when individual patients with advanced HD are unable to self-report

Subcellular localization of MC4R with ADCY3 at neuronal primary cilia underlies a common pathway for genetic predisposition to obesity.

Most monogenic cases of obesity in humans have been linked to mutations in genes encoding members of the leptin-melanocortin pathway. Specifically, mutations in MC4R, the melanocortin-4 receptor gene, account for 3-5% of all severe obesity cases in humans1-3. Recently, ADCY3 (adenylyl cyclase 3) gene mutations have been implicated in obesity4,5. ADCY3 localizes to the primary cilia of neurons 6 , organelles that function as hubs for select signaling pathways. Mutations that disrupt the functions of primary cilia cause ciliopathies, rare recessive pleiotropic diseases in which obesity is a cardinal manifestation 7 . We demonstrate that MC4R colocalizes with ADCY3 at the primary cilia of a subset of hypothalamic neurons, that obesity-associated MC4R mutations impair ciliary localization and that inhibition of adenylyl cyclase signaling at the primary cilia of these neurons increases body weight. These data suggest that impaired signaling from the primary cilia of MC4R neurons is a common pathway underlying&nbsp;genetic causes of obesity in humans