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Summary: Background: Arterial hypertension is a major cardiovascular risk factor. Identification of secondary hypertension in its various forms is key to preventing and targeting treatment of cardiovascular complications. Simplified diagnostic tests are urgently required to distinguish primary and secondary hypertension to address the current underdiagnosis of the latter. Methods: This study uses Machine Learning (ML) to classify subtypes of endocrine hypertension (EHT) in a large cohort of hypertensive patients using multidimensional omics analysis of plasma and urine samples. We measured 409 multi-omics (MOmics) features including plasma miRNAs (PmiRNA: 173), plasma catechol O-methylated metabolites (PMetas: 4), plasma steroids (PSteroids: 16), urinary steroid metabolites (USteroids: 27), and plasma small metabolites (PSmallMB: 189) in primary hypertension (PHT) patients, EHT patients with either primary aldosteronism (PA), pheochromocytoma/functional paraganglioma (PPGL) or Cushing syndrome (CS) and normotensive volunteers (NV). Biomarker discovery involved selection of disease combination, outlier handling, feature reduction, 8 ML classifiers, class balancing and consideration of different age- and sex-based scenarios. Classifications were evaluated using balanced accuracy, sensitivity, specificity, AUC, F1, and Kappa score. Findings: Complete clinical and biological datasets were generated from 307 subjects (PA=113, PPGL=88, CS=41 and PHT=112). The random forest classifier provided ∼92% balanced accuracy (∼11% improvement on the best mono-omics classifier), with 96% specificity and 0.95 AUC to distinguish one of the four conditions in multi-class ALL-ALL comparisons (PPGL vs PA vs CS vs PHT) on an unseen test set, using 57 MOmics features. For discrimination of EHT (PA + PPGL + CS) vs PHT, the simple logistic classifier achieved 0.96 AUC with 90% sensitivity, and ∼86% specificity, using 37 MOmics features. One PmiRNA (hsa-miR-15a-5p) and two PSmallMB (C9 and PC ae C38:1) features were found to be most discriminating for all disease combinations. Overall, the MOmics-based classifiers were able to provide better classification performance in comparison to mono-omics classifiers. Interpretation: We have developed a ML pipeline to distinguish different EHT subtypes from PHT using multi-omics data. This innovative approach to stratification is an advancement towards the development of a diagnostic tool for EHT patients, significantly increasing testing throughput and accelerating administration of appropriate treatment. Funding: European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 633983, Clinical Research Priority Program of the University of Zurich for the CRPP HYRENE (to Z.E. and F.B.), and Deutsche Forschungsgemeinschaft (CRC/Transregio 205/1).

Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing’s syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification.

Keywords: MRI, Imaging Sequences, Ultrasound, Mammography, CT, Angiography, Conventional Radiography Published under a CC BY 4.0 license. See also the commentary by Whitman and Vining in this issue.

Background: Clinical gait analysis is widely used to aid the assessment and diagnosis of symptomatic pathologies. Foot function pressure systems such as F-scan and analysis of the spatial-temporal parameters of gait using GAITRite® can provide clinicians with a more comprehensive assessment. There are systems however, such as Strideway™ that can measure these parameters simultaneously but can be expensive. F-Scan in-shoe pressure data is normally collected whilst the person is walking on a hard floor surface. The effects of the softer Gaitrite® mat upon the F-Scan in-shoe sensor pressure data is unknown. This study therefore aimed to assess the agreement between F-Scan pressure measurements taken from a standard walkway (normal hard floor), and those from a GAITRite® walkway to establish whether these two pieces of equipment (in-shoe F-Scan and GAITRite®) can be used simultaneously, as a cost-effective alternative., Method: Twenty-three participants first walked on a standard floor and then on a GAITRite® walkway wearing F-Scan pressure sensor insoles with same footwear. They repeated these walks three times on each surface. Mid gait protocols were utilised by analysing the contact pressure of the first and second metatarsophalangeal joint of the third, fifth and seventh step from each walk. For both joints, 95% Bland-Altman Limits of Agreement was used to determine a level of agreement between the two surfaces, using mean values from pressure data collected from participants who successfully completed all required walks. The intraclass correlation coefficient (ICC) and Lin's concordance correlation coefficient were calculated as indices of reliability., Findings: ICC results for the hard surface and the GAITRrite® walkway at the first and second metatarsophalangeal joints were 0.806 and 0.991 respectively. Lin's concordance correlation coefficient for the first and second metatarsophalangeal joints were calculated to be 0.899 and 0.956 respectively. Both sets of statistics indicate very good reproducibility. Bland-Altman plots revealed good repeatability of data at both joints., Conclusion: The level of agreement in F-Scan plantar pressures observed between walking on a normal hard floor and on a GAITRite® walkway was very high, suggesting that it is feasible to use F-Scan with GAITRite® together in a clinical setting, as an alternative to other less cost-effective standalone systems. Although it is assumed combining F-Scan with GAITRite® does not affect spatiotemporal analysis, this was not validated in this study., (© 2023. The Author(s).)

Introduction: Artificial intelligence (AI) applications in healthcare and medicine have increased in recent years. To enable access to personal data, Trusted Research Environments (TREs) (otherwise known as Safe Havens) provide safe and secure environments in which researchers can access sensitive personal data and develop AI (in particular machine learning (ML)) models. However, currently few TREs support the training of ML models in part due to a gap in the practical decision-making guidance for TREs in handling model disclosure. Specifically, the training of ML models creates a need to disclose new types of outputs from TREs. Although TREs have clear policies for the disclosure of statistical outputs, the extent to which trained models can leak personal training data once released is not well understood., Background: We review, for a general audience, different types of ML models and their applicability within healthcare. We explain the outputs from training a ML model and how trained ML models can be vulnerable to external attacks to discover personal data encoded within the model., Risks: We present the challenges for disclosure control of trained ML models in the context of training and exporting models from TREs. We provide insights and analyse methods that could be introduced within TREs to mitigate the risk of privacy breaches when disclosing trained models., Discussion: Although specific guidelines and policies exist for statistical disclosure controls in TREs, they do not satisfactorily address these new types of output requests; i.e., trained ML models. There is significant potential for new interdisciplinary research opportunities in developing and adapting policies and tools for safely disclosing ML outputs from TREs., Competing Interests: The authors whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Dr Esma Mansouri-Benssassi, Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, Scotland. Dr Simon Rogers, Artificial Intelligence Centre of Excellence, NHS National Services Scotland, Glasgow, Scotland. Dr Smarti Reel, Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, Scotland. Maeve Malone, School of Humanities Social Sciences and Law, University of Dundee, Scotland. Prof Jim Smith, School of Computer Science and Creative Technologies, University of West England, Bristol, England. Prof Felix Ritchie, FBL - Accounting, Economics and Finance, University of West England, Bristol, England. Prof Emily Jefferson, Division of Population Health and Genomics, School of Medicine, University of Dundee & HDR UK., (© 2023 The Authors.)

Background: Lower limb venous disease can cause significant pain, loss of mobility, and can be detrimental to an individual's quality of life. Manifestations of venous disease often pose a substantially negative impact on patients and place a high demand on finite healthcare resources. Whilst this problem is internationally recognised, most research and discourse has predominantly focussed on treatment of leg ulceration and prevention of recurrence. Prevention of lower limb venous disease progression to the first ulceration has received far less attention. Overall, the care of this condition appears to rest in the domain of medicine and nursing yet podiatry, a profession with responsibility for the lower limb and foot, is conspicuous by its absence from the literature.  METHODS: An ethnographic approach was used to gather data from 26 participants through observation, semi-structured interviews, and a focus group interview. Qualitative analysis was conducted using the framework approach., Results: The findings revealed an identity crisis within the podiatry profession. Evidence emerged of ritual and routine practices that did not include lower limb venous disease. External control over practice limited the professional autonomy of podiatrists determining their own activities. Inter-professional relationships with nursing, and perceptions of boundaries that venous disease was a nursing role were also found to be limiting factors., Conclusions: This research revealed that podiatry does not occupy a substantive role in contributing to the early identification and prevention of lower limb venous disease. Policy, education, research and practice changes are all required to enhance the contribution of podiatry to reduce the burden of this disease., (© 2022. The Author(s).)

Background: Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches., Results: Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods-Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine-predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL., Conclusions: The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder., (© 2022. The Author(s).)

The overlay method is used in forensic podiatry to compare the shape, position, and overall fit of features between questioned and reference footprint evidence. However, the scientific foundation underpinning its validity in the comparison of insole footprints is not fully understood because of a lack of published data defining its statistical operating parameters. A review of literature revealed its subjective nature with little scientific validation, limited only to face validity. The aim of this study investigated strength of agreement between three expert footprint examiners' overlay comparisons of ten reference insole footprints using Cohen's weighted kappa (K w ). Validity of method was explored using measures of sensitivity, specificity, false positive rate (FPR), false negative rate (FNR), receiver operating characteristic (ROC) curve and area under the ROC curve (AUC). Results showed two examiners demonstrated high inter-rater consistency between their overlay comparisons (K w : 0.981; 95 %CI: 0.943 to 1.020 for Rater1 v Rater2) whilst one examiner did not (K w : 0.340; 95 %CI: 0.148 to 0.532 for Rater1 v Rater3; K w : 0.310; 95 %CI: 0.100 to 0.519 for Rater2 v Rater3). Validity was investigated using a conclusion scale in a verbal expressions table to indicate support or rejection of compatibility of footprints between one questioned insole and ten reference insoles. Data analysis indicated validity as follows: Sensitivity: 77.8 %, Specificity: 61.9 %, FPR: 38.1 % and FNR: 22.2 %. ROC analysis corroborated this finding. AUC was calculated at 0.762 or 76.2 % indicating an 'acceptable' measure of overall accuracy of the overlay method for insole footprint comparison. Findings provide novel data supporting previous suggestions that the overlay method should not be used in isolation to compare insole footprints. Data also offers insight into the scientific foundation of this method, whilst highlighting its limitations and providing some implications and recommendations for forensic podiatry practice., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Currently in the UK, if a person is arrested or charged with a recordable offence, they can have prints of their footwear taken whilst in custody. The tread pattern recorded in these prints can be searched for using the National Footwear Database to find out if the same footwear pattern has been recovered at previous crime scenes, generating forensic intelligence. TreadMatch is a digitised system for collecting footwear prints seized from detainees in custody for this purpose. Whilst its use for generating intelligence is accepted, validation experiments have not been conducted to understand its level of performance in assisting in forensic comparison purposes for identification, because in the absence of an incorporated scale, it is not known how well TreadMatch reproduces the pattern size of a tread, threatening the validity of the comparison. If it can be determined that the measurements of TreadMatch scans are consistent with the more commonly used aluminium powder test marks, this could save Police time and resources if the digital scans could be used for preliminary assessment prior to the footwear being physically submitted for evidential comparison. Therefore, this study set out to compare three different types of TreadMatch scans ('dynamic', 'zoomed' and 'rolled') for thirty different pieces of footwear, with test marks of the same footwear using the traditional method (fingerprint powder). Length and width measurements were obtained from each tread pattern using GNU Image Manipulation Program software. The resulting data were analysed to assess for agreement between TreadMatch scans and test marks using 95% Intraclass Correlation Coefficients (ICC) and 95% Bland-Altman plots of Limits of Agreement (LOA). Additionally, an intra-sample study using fifteen repeated measurements of the same piece of footwear for different TreadMatch scanning methods was carried out to support the larger validity study. 95% ICC 3,1 resulted in coefficients ranging from 0.99 to 1.00 across all measurements. 95% LOA displayed close agreement. There was less agreement and more variation displayed between the test marks and the TreadMatch rolled scans for both length and width measurements. This variation for hand-rolled prints must be taken into consideration and a standard approach developed. The study suggests TreadMatch can be used for preliminary assessments in assisting forensic comparisons, particularly for dynamic and zoomed prints., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.)

Ground Truth Data is data that comes from a known source, where the truth about the data is known and not inferred (FSR, 2021). The Forensic Science Regulator requires forensic units (that carry out certain forensic processes) to undertake tests against ground truth data for the purposes of quality assurance/quality control processes such as accreditation. However, the data collected must form a meaningful dataset that will enable relevant tests to be performed that inform the end-user. This technical note discusses how a forensic unit in the UK planned and developed a method for collecting ground truth data for footwear mark evidence. It discusses the materials and variables that were considered when developing the method and the evidence-based, decision-making processes that enabled its creation. Recommendations and considerations are provided to assist other forensic units collect data relevant to their jurisdiction. Whilst the method is not prescriptive, if it is used as a guide, it may facilitate the development of a large and relevant national dataset., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.)

Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the population studied. It occurs due to underlying conditions associated with hormonal excess mainly related to adrenal tumours and sub-categorised: primary aldosteronism (PA), Cushing's syndrome (CS), pheochromocytoma or functional paraganglioma (PPGL). Endocrine hypertension is often misdiagnosed as primary hypertension, causing delays in treatment for the underlying condition, reduced quality of life, and costly antihypertensive treatment that is often ineffective. This study systematically used targeted metabolomics and high-throughput machine learning methods to predict the key biomarkers in classifying and distinguishing the various subtypes of endocrine and primary hypertension. The trained models successfully classified CS from PHT and EHT from PHT with 92% specificity on the test set. The most prominent targeted metabolites and metabolite ratios for hypertension identification for different disease comparisons were C18:1, C18:2, and Orn/Arg. Sex was identified as an important feature in CS vs. PHT classification.

Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing's syndrome (CS), remain undetected. We aimed to establish signatures for the different forms of EHT, investigate potentially confounding effects and establish unbiased disease biomarkers. Plasma samples were obtained from 13 biobanks across seven countries and analyzed using untargeted NMR metabolomics. We compared unstratified samples of 106 PHT patients to 231 EHT patients, including 104 PA, 94 PPGL and 33 CS patients. Spectra were subjected to a multivariate statistical comparison of PHT to EHT forms and the associated signatures were obtained. Three approaches were applied to investigate and correct confounding effects. Though we found signatures that could separate PHT from EHT forms, there were also key similarities with the signatures of sample center of origin and sample age. The study design restricted the applicability of the corrections employed. With the samples that were available, no biomarkers for PHT vs. EHT could be identified. The complexity of the confounding effects, evidenced by their robustness to correction approaches, highlighted the need for a consensus on how to deal with variabilities probably attributed to preanalytical factors in retrospective, multicenter metabolomics studies.

A two-dimensional linear measurement approach for footprints, herein referred to as the "Reel Method," has been shown to be valid and reliable when used on bare footprints, however, few measurement approaches have been examined on sock-clad footprints. The present investigation examines the validity and reliability of the Reel Method as a two-dimensional linear measurement approach for use on sock-clad footprints. A walking, mid-gait footprint was collected from 30 volunteer participants using the Identicator Inkless Shoe Print Model LE 25P system. The width of the ball of the foot, calcaneal width, and distance from the most posterior aspect of the heel to the most distal aspect of the first toe were each measured and compared between and within three raters. The statistical analysis demonstrated high reliability of the Reel Method among these three raters. The data were found to be normally distributed, and measurements were consistent between and within raters. 95% Intraclass Correlation coefficients, 95% Bland-Altman Limits of Agreement and 95% Standard Error of Measurement determined high statistical agreement between and within raters, demonstrating that the Reel Method is reliable and thus valid for the linear measurement of sock-clad footprints., (Copyright © 2021 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.)

Footprints are left, or obtained, in a variety of scenarios from crime scenes to anthropological investigations. Determining the sex of a footprint can be useful in screening such impressions and attempts have been made to do so using single or multi landmark distances, shape analyses and via the density of friction ridges. Here we explore the relative importance of different components in sexing two-dimensional foot impressions namely, size, shape and texture. We use a machine learning approach and compare this to more traditional methods of discrimination. Two datasets are used, a pilot data set collected from students at Bournemouth University (N = 196) and a larger data set collected by podiatrists at Sheffield NHS Teaching Hospital (N = 2677). Our convolutional neural network can sex a footprint with accuracy of around 90% on a test set of N = 267 footprint images using all image components, which is better than an expert can achieve. However, the quality of the impressions impacts on this success rate, but the results are promising and in time it may be possible to create an automated screening algorithm in which practitioners of whatever sort (medical or forensic) can obtain a first order sexing of a two-dimensional footprint., Competing Interests: The authors have declared that no competing interests exist.

With the development of modern high-throughput omic measurement platforms, it has become essential for biomedical studies to undertake an integrative (combined) approach to fully utilise these data to gain insights into biological systems. Data from various omics sources such as genetics, proteomics, and metabolomics can be integrated to unravel the intricate working of systems biology using machine learning-based predictive algorithms. Machine learning methods offer novel techniques to integrate and analyse the various omics data enabling the discovery of new biomarkers. These biomarkers have the potential to help in accurate disease prediction, patient stratification and delivery of precision medicine. This review paper explores different integrative machine learning methods which have been used to provide an in-depth understanding of biological systems during normal physiological functioning and in the presence of a disease. It provides insight and recommendations for interdisciplinary professionals who envisage employing machine learning skills in multi-omics studies., (Copyright © 2021. Published by Elsevier Inc.)

Context: Identification of patients with endocrine forms of hypertension (EHT) (primary hyperaldosteronism [PA], pheochromocytoma/paraganglioma [PPGL], and Cushing syndrome [CS]) provides the basis to implement individualized therapeutic strategies. Targeted metabolomics (TM) have revealed promising results in profiling cardiovascular diseases and endocrine conditions associated with hypertension., Objective: Use TM to identify distinct metabolic patterns between primary hypertension (PHT) and EHT and test its discriminating ability., Methods: Retrospective analyses of PHT and EHT patients from a European multicenter study (ENSAT-HT). TM was performed on stored blood samples using liquid chromatography mass spectrometry. To identify discriminating metabolites a "classical approach" (CA) (performing a series of univariate and multivariate analyses) and a "machine learning approach" (MLA) (using random forest) were used.The study included 282 adult patients (52% female; mean age 49 years) with proven PHT (n = 59) and EHT (n = 223 with 40 CS, 107 PA, and 76 PPGL), respectively., Results: From 155 metabolites eligible for statistical analyses, 31 were identified discriminating between PHT and EHT using the CA and 27 using the MLA, of which 16 metabolites (C9, C16, C16:1, C18:1, C18:2, arginine, aspartate, glutamate, ornithine, spermidine, lysoPCaC16:0, lysoPCaC20:4, lysoPCaC24:0, PCaeC42:0, SM C18:1, SM C20:2) were found by both approaches. The receiver operating characteristic curve built on the top 15 metabolites from the CA provided an area under the curve (AUC) of 0.86, which was similar to the performance of the 15 metabolites from MLA (AUC 0.83)., Conclusion: TM identifies distinct metabolic pattern between PHT and EHT providing promising discriminating performance., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Endocrine Society.)

This study aimed to systematically review evidence to assess the efficacy of non-pharmacological brief interventions in the emergency department to reduce the incidence, severity and impact of acute behavioural disturbances. The literature search was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 18 articles were identified as meeting the inclusion criteria and read in full. Following a full read and a consensus discussion, it was subsequently considered the studies chosen had not met the inclusion criteria. Research into the use of non-pharmacological brief interventions in the management of acute behavioural disturbance in the emergency department is warranted given the absence of evidence found by this systematic review.

Dynamic bare footprints differ from static bare footprints through the presence of additional, lighter markings around the rear of the heel print and apices of the toe print areas. These images can appropriately be described as inner dark and outer ghosting features. To date, the functional cause of both features has not been understood. To gain such an understanding could potentially allow the further development and use of these features in forensic identification. The aim of this project was to investigate the causes of the inner dark and outer ghosting features seen in dynamic bare footprints through an observational, practice-based action research approach within a gait laboratory. Volunteer male participants provided bare footprints on inkless paper taped to a Kistler force plate with video cameras situated either side. Ground reaction force data were collected as the footprints were formed and the event recorded using video cameras to allow these data to be correlated later. The findings suggest that the ghosting at the heel is the result of splaying of the fibro fatty pad, while that at the toes is the result of the distal ends of the toes coming into contact with the ground as the heel is lifted. Footprint, ground reaction force and video data comparisons showed that the inner dark area of the heel print corresponded with the main body of the heel contacting the ground. Outer ghosting corresponded with a backward splaying of the fat pad and the heel strike transient spike in vertical ground reaction force during increased loading. The inner dark area of the toes corresponded with a longer period of toe contact with the ground. Outer ghosting corresponded with the decreasing vertical ground reaction force and shorter contact time as the toes were leaving the ground towards the end of the contact phase of gait. Although the sample size was limited, these are new appreciations which could facilitate the use of the inner dark features in identification to provide additional points for comparison in cases involving dynamic bare footprints. Further work is now indicated to study these features in different populations and under varying conditions., (Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.)

Background: An investigation was undertaken to compare the effect of multi-component compression bandages and compression hosiery kits on individuals' range of ankle motion whilst wearing typical and medical footwear, and barefoot., Methods: A convenience sample of 30 healthy individuals recruited from the staff and student population at the University of Huddersfield, UK. Plantarflexion/dorsiflexion range of ankle motion (ROAM) was measured in participants over 6 steps in every combination of typical, medical and no footwear; and multi-component bandages, compression hosiery and no garments., Results: Controlling for age, gender and garments, the use of typical footwear was associated with a mean increase in ROAM of 2.54° at best estimate compared with barefoot; the use of medical footwear was associated with a mean decrease in ROAM of 1.12° at best estimate compared with barefoot. Controlling for age, gender and footwear, the use of bandaging was associated with a mean decrease in ROAM of 2.51° at best estimate compared with no garments. Controlling for age, gender and footwear, the use of hosiery was not associated with a significant change in ROAM compared with no garments., Conclusions: Bandages appear to restrict ROAM more than hosiery when used in conjunction with a variety of footwear types.

Background and Aims: Obesity combined with hypertension places patients at greater risk for target-organ damage and cardiovascular disease. The purpose of this secondary analysis was to identify physician- and patient-levels determinants of blood pressure (BP) values and predictors of uncontrolled BP through subgroup analysis by body mass index (BMI)., Methods and Results: We conducted a subgroup analysis of 3006 patients with High-BMI (BMI >25 kg/m(2); n=2124) and Normal-BMI (BMI<25 kg/m(2); n=882) treated by 504 physicians and enrolled in PREVIEW, a Belgian prospective, multi-center, pharmaco-epidemiological study of 90-day second-line treatment with valsartan. Physician- and patient-level determinants of BP values and BP control were identified by means of hierarchical linear and logistic regression. Blood pressure values and control after 90 days of treatment were consistently lower for the High-BMI group. The 25.5% of variance in 90-day systolic and 28.3% of the variance in 90-day diastolic BP were attributable to physician-level determinants for the High-BMI group; versus 27.3% and 29.8% for the Normal-BMI group (ICC=0.273 and 0.298, respectively). Determinants of 90-day BP values and predictors of uncontrolled BP varied considerably by BMI status., Conclusion: Several common and unique patient- and physician-level determinants of BP values and control were identified for the High-BMI and Normal-BMI groups. These findings highlight the need for differentiating healthcare interventions to account for patient and physician variables, particularly with respect to effective BP management in vulnerable populations., (Copyright © 2011 Elsevier B.V. All rights reserved.)

The ability to estimate accurately from known parameters is a fundamental aspect of science and is evident as an emerging approach in the area of footprints and stature estimation within the field of forensic identification. There are numerous foot dimensions that have been measured in the literature to predict stature with varying degrees of confidence but few studies have tried to link the strength of estimation to anatomical landmarks. Such an approach is utilised in this study which estimates stature from the right footprints of sixty one adult male and female UK participants. Static and dynamic footprints were taken from each volunteer using the 'inkless paper system'. The prints were digitised and twelve length, width and angle measurements were chosen for the analysis. The highest correlations with stature were shown to be the heel to fourth toe print for the static group of footprints (r=0.786, p<0.01), and the heel to fifth toe print in the dynamic footprints (r=0.858, p<0.01). Collinearity statistics suggest the heel to fifth toe print length measurement is independent and not influenced by any other variables in the estimation of stature for the dynamic prints. Linear regression equations for this measurement presented the smallest standard error of estimate (SEE) and highest shared variance (R(2)) of all included variables (SEE 4.16, R(2) 0.74). Our study discusses a potential anatomical explanation as to why the lateral border of the foot and hence the impression it makes upon a hard surface, is a more stable indicator in the estimation of stature. The investigation recommends the use of Calc&#95;A4 and Calc&#95;A5 length measurements when estimating stature from footprint impressions., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

Gender-specific determinants of blood pressure (BP) values and control have not been the focus of clinical hypertension research. The purpose of this analysis was to identify gender-specific and multi-level (physician and patient) determinants of BP values and predictors of uncontrolled BP. We completed a subgroup analysis comparing men and women who participated in the Belgian PREVIEW study of second-line treatment effectiveness of valsartan, applying two-level hierarchical modelling of 90-day BP values and guideline-defined BP control. In total, 1665 women and 1525 men were treated by 504 general practitioners. Fewer women than men reached systolic BP (SBP) (P=0.015) and combined BP targets at 90 days (P=0.007). More than 26% of the variance in 90-day SBP (intra-class correlation coefficient (ICC)=0.270) and diastolic BP (DBP) (ICC=0.262) was attributable to physician-level factors for men; the physician-level ICCs for SBP and DBP were 0.259 and 0.268, respectively, for women. Determinants of 90-day BP values and predictors of uncontrolled BP varied considerably by gender. Many of the multi-level determinants of BP by gender are amenable to intervention, and the remainder can serve as warning signs to clinicians that patients may remain vulnerable to poor outcomes associated with sub-optimal BP control.

Purpose: To evaluate and compare the drug-drug interaction (DDI) knowledge of pharmacy, medical, and nurse practitioner (NP) students who are beginning supervised clinical practice., Data Sources: This study utilized a prospective evaluation of DDI knowledge among healthcare professional students who were currently enrolled in their final didactic year at the University of Arizona Colleges of Medicine, Pharmacy, or Nursing's NP program. Students were asked to assess 15 drug pairs and to select an appropriate management strategy for each pair. The primary outcome measure was the ability to correctly categorize each drug pair into one of the five management responses. The secondary outcome measure was the number of clinically significant DDIs recognized., Conclusions: Pharmacy students demonstrated significantly better knowledge than medical and NP students with respect to identifying and selecting management strategies for possible DDIs. However, there is much room for improvement for all groups., Implications for Practice: An increase in curricular content that focuses on DDIs has the potential to better prepare medical, pharmacy, and NP students for practice situations involving DDI alerts, and to increase the quality of patient care., (©2011 The Author(s) Journal compilation ©2011 American Academy of Nurse Practitioners.)

Background: It is essential that current and future health professionals be able to evaluate for possible clinically significant drug-drug interactions (DDIs) and when detected, determine appropriate management strategies to prevent patient harm., Objective: Assess the validity of a DDI knowledge assessment instrument in a health professional student population., Methods: This study recruited health professional students (medical, nurse practitioner, and pharmacy) beginning experiential training at the University of Arizona. Students were given a knowledge assessment instrument that included 15 medication pairings selected on the basis of clinical importance and were asked to select the most appropriate DDI management strategy for each pair by selecting "avoid combination," "usually avoid combination," "take precautions," or "no special precautions." Data were analyzed in 2 ways because of the subjective nature of classifying DDIs into specific management categories. In the first analysis, respondents were given credit for a correct item only if they selected the management strategy deemed appropriate (management strategy analysis). In another analysis, students were given credit for an item only if they correctly identified specific DDIs (DDI recognition analysis). Rasch analysis was used to assess the validity of the knowledge instrument., Results: A total of 165 of the 226 eligible health professional students completed the DDI knowledge assessment (73% response rate). The mean score for management strategy analysis was 3.82 out of 15, whereas DDI recognition analysis produced a higher average (mean=6.55). Good reliability was demonstrated in both strategies, and no ceiling or floor effects were observed. Some construct underrepresentation occurred with both scoring strategies, and some mistargeting was identified when analyzing the management strategy., Conclusions: Although improvements in construct representation may be beneficial, the instrument used demonstrated good reliability and validity and could be used by educators to assess and improve DDI knowledge. The ability of the participants to identify DDIs and select an appropriate management strategy was low. These results support the need for additional DDI education in this institution's health curricula., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Although footprint evidence can be taken from the scene of a crime, the science underpinning such measurement in forensic science has not been fully explored. A literature search revealed various measuring approaches, all of which demonstrated either little or no measurement rigour in terms of reliability. The aim of this study was to apply a robust measurement approach for testing the reliability of two-dimensional footprint impressions. Three dynamic and three static footprints were taken from the right foot of thirty female and thirty one male volunteers using the 'Inkless Shoeprint Kit'. The images were digitised. Lengths, widths and angles were measured using a selection of currently employed methods. An investigation of the reliability of the chosen measuring method suggested high intra-rater agreement: for example, the length measurement suggested an intraclass correlation coefficient (ICC) 0.99, 95% Confidence Interval (CI) -0.28 to 0.01, standard error of measurement (SEM) 0.07, Limits of Agreement (LOA) -0.91 to 0.65. Inter-rater reliability between three operators was also high: SEM ranged from 0.05 mm to 0.07 mm, ICC 0.99. Our study has established a reliable two-dimensional measuring technique that could be used for footprint comparison in further research., (Copyright © 2009 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.)

Achieving guideline-recommended blood pressure targets is difficult in older adults with hypertension. We completed a subgroup analysis of patients 65 years of age or older enrolled in PREVIEW, a prospective, multicenter, pharmacoepidemiological study of the determinants and outcomes of second-line antihypertensive treatment with valsartan in Belgium. Multilevel modeling was used to identify physician- and patient-level determinants of blood pressure values and practice guideline-derived definitions of blood pressure control. Data on 1560 patients and 504 physicians were used in this analysis. Blood pressure control rates for patients age 65 and over were lower for systolic (34.2% vs. 38.6%) and combined systolic/diastolic blood pressure (31.2% vs. 34.4%) compared to the entire PREVIEW sample. Twenty-seven percent of the variability in systolic, and 32% in diastolic pressure after 90 days of treatment were attributable to such variables as physicians' knowledge and adherence to evidence-based guidelines, practice patterns, and experience; with the remaining variance attributable to various demographic, behavioral, and clinical patient-related factors. Several independent predictors of uncontrolled blood pressure after 90 days of treatment were identified, largely confirming factors identified as determinants of blood pressure values. Recommendations for managing hypertension in the elderly are made in view of these findings., (Copyright 2009 Elsevier Ireland Ltd. All rights reserved.)

Background: Data on the state of information systems infrastructures used in the clinical research enterprise of academic medical centers are limited and mostly anecdotal. What has been published is slowly beginning to make important distinctions, such as clinical trials as a specialized form of clinical research and between "Informatics" in an academic setting from health care information technology. However, this field continues to undergo fundamental changes, accelerated by the National Institutes of Health's creation of Clinical and Translational Science Awards to build a new "home" for biomedical research., Methods: We surveyed all Clinical Research Forum member institutions regarding their enterprise infrastructure and use of information systems in support of clinical research. The questions in this on-line study expanded on one first done in 2005. Of the 52 sites invited, 19 (37%) responded. We analyzed the responses and also made matched comparisons for those organizations that participated in both surveys., Results: Although there continues to be conceptual agreement on information system elements for the clinical research enterprise, no single institution achieved the ideal, a similar result to the 2005 survey. Indeed, little progress was made over the past 2 years at most locations other than in information technology planning, strategy, and governance., Conclusions: There is increased recognition of the importance of information systems infrastructure and expertise for biomedical research, but the needs are accelerating much faster than institutions can build or pay for. A much greater realization of and innovative solution for this growing chasm is urgently required.

The notion of social capital focuses attention on social connectedness within communities and the ways that this connectedness may affect health and well-being. There are many competing definitions of social capital but most suggest that it involves trust, social networks and reciprocity within communities, not necessarily geographically defined. The usefulness of social capital and related theories that help in understanding the function of nurses in rural communities are explored in this paper. Nurses and health service planners are becoming increasingly aware of the potential contribution of community nurses in rural and/or remote areas, as evidenced in the development of nurse practitioners. Through their interrelational role and status in rural communities, nurses are often 'immersed' or 'embedded' in the social networks that make up the fabric of rural life and may therefore be important contributors to social capital. For a concept such as social capital to be useful in nursing research, it must have distinct attributes, delineated boundaries, and well-described preconditions and outcomes in multiple contexts.

Background: The World Health Organisation HEALTH21 strategy has firmly placed families and family oriented services at the core of health care delivery., Objective: In this article we argue that a fundamental reorganisation of primary health care practices in remote and rural Australia needs to be undertaken., Discussion: Nurses have been shown to be equally effective and less costly than general practitioners. Family nurse practitioners should be a first point of contact, and family health nurses should be responsible for responding to problems of multiple deprivation and social exclusion in remote and rural areas. These practitioners would, in their respective areas of responsibility, identify, diagnose, refer or treat individuals, families and communities. In effect they would act as gatekeepers to health and social care services. Family health nurses would also aim to support the community in developing and sustaining the capacity to take responsibility for its own health and social care. The main obstacles to these initiatives are concerns of general practitioners and nurses, the inertia of large organisations when faced with the need to undertake radical change and the highly unionised and rule bound nature of Australian nursing.