Search

ObjectivesThe aim of our study was to explore the contextual factors that affect the implementation of football injury prevention initiatives and the provision of effective injury management in the Irish Womens National League (WNL).MethodsWe used a criterion-based purposive sampling approach to recruit coaches (n=7), players (n=17) and medical personnel (n=8) representing eight of the nine clubs in the WNL to participate in one-to-one semistructured interviews. Our study was located within an interpretivist, constructivist research paradigm. The interview data were analysed using reflexive thematic analysis.ResultsThe participants identified academic and work pressures, financial challenges, conflict with college football, inadequate facilities and gender inequity as being barriers to the implementation of injury prevention initiatives and the provision of effective injury management. Financial constraints within clubs were perceived to limit the provision of medical care and strength and conditioning (S&C) support and this was deemed to be associated with a heightened risk of injuries.ConclusionSpecific contextual factors were identified which curtail the implementation of injury prevention initiatives and the provision of effective injury management in elite-level womens club football in Ireland. Gender inequity was identified as one of the factors impacting the availability of high-quality medical care, S&C support, as well as access to training and match facilities. Our results provide new insights that could be used to inform the design and implementation of injury prevention and management initiatives for women football players in Ireland., Funding Agencies|Irish Research Council Enterprise Partnership Scheme (Postgraduate) [EPSPG/2019/543]

Medical machine learning algorithms are typically evaluated based on accuracy vs. a clinician-defined ground truth, a reasonable initial choice since trained clinicians are usually better classifiers than ML models. However, this metric does not fully capture the actual clinical task: it neglects the fact that humans, even with perfect accuracy, are subject to non-trivial error from the Poisson statistics of rare events, because clinical protocols often specify a relatively small sample size. For example, to quantitate malaria on a thin blood film a clinician examines only 2000 red blood cells (0.0004 uL), which can yield large Poisson variation in the actual number of parasites present, so that a perfect human's count can differ substantially from the true average load. In contrast, an ML system may be less accurate on an object level, but it may also have the option to examine more blood (e.g. 0.1 uL, or 250x). Then while its parasite identification error is higher, the Poisson variability of its estimate is lower due to larger sample size. To qualify for clinical deployment, an ML system's performance must match current standard of care, typically a very demanding target. To achieve this, it may be possible to offset the ML system's lower accuracy by increasing its sample size to reduce Poisson error, and thus attain the same net clinical performance as a perfectly accurate human limited by smaller sample size. In this paper, we analyse the mathematics of the relationship between Poisson error, classification error, and total error. This mathematical toolkit enables teams optimizing ML systems to leverage a relative strength (larger sample sizes) to offset a relative weakness (classification accuracy). We illustrate the methods with two concrete examples: diagnosis and quantitation of malaria on blood films., Comment: 8 pages + appendix, 4 figures

BackgroundTo manage injuries effectively, players, head coaches, and medical personnel need to have excellent knowledge, attitudes, and behaviours in relation to the identification of risk factors for injuries, the implementation of injury prevention initiatives, as well as the implementation of effective injury management strategies. Understanding the injury context, whereby specific personal, environmental, and societal factors can influence the implementation of injury prevention initiatives and injury management strategies is critical to player welfare. To date, no qualitative research investigating the context of injuries, has been undertaken in elite-level womens football. The aim of our study was to explore the knowledge, attitudes, and behaviours of players, head coaches, and medical personnel in the Irish Womens National League (WNL) to injury prevention and injury management.MethodsWe used qualitative research methods to explore the knowledge, attitudes, and behaviours of players, head coaches, and medical personnel in the Irish WNL to injury prevention and injury management. Semi-structured interviews were undertaken with 17 players, 8 medical personnel, and 7 head coaches in the Irish WNL. The data were analysed using thematic analysis. Our study is located within an interpretivist, constructivist research paradigm.ResultsThe participants had incomplete knowledge of common injuries in elite-level football, and many held beliefs about risk factors for injuries, such as menstrual cycle stage, which lacked evidence to support them. Jumping and landing exercises were commonly used to reduce the risk of injuries but evidence-based injury prevention exercises and programmes such as the Nordic hamstring curl, Copenhagen adduction exercise, and the FIFA 11+ were rarely mentioned. Overall, there was dissatisfaction amongst players with their medical care and strength and conditioning (S & C) support, with resultant inadequate communication between players, he

01 februari 2023, Item does not contain fulltext, BACKGROUND: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. METHODS: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. FINDINGS: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. INTERPRETATION: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implemen

SammanfattningTriply Periodic Minimal Surface (TPMS)-baserade nätverksstrukturer har snabbt blivit populära i flera tillämpningar, exempelvis medicinska implantat, värmeväxlare, stötdämpareoch lättviktskonstruktioner. Gyroidstrukturen är förmodligen den mest kända och använda, men en mängd varianter existerar med extremt goda egenskaper vid additiv tillverkning. Nätverkenkan printas helt utan stödstrukturer och kan erhålla mekaniska egenskaper i nivå̊ med de relativa bulkegenskaperna. I detta projekt skall mekaniska egenskaper för TPMS-baserade provbitar SLS-printade i PA11 undersökas genom dragprov, böjprov, slagseghetsprov och kompressionsprov. Dessutom ska det undersökas om byggriktning och orientering i skrivarens byggkammare har betydelse för materialets mekaniska egenskaper. Utöver detta kommer även en materialmodell byggas upp för analys med hjälp av Abaqus.Slutsatserna från examensarbetet var att både byggriktning och orientering i skrivarens kammare har betydelse för materialegenskaperna. Med resultaten från proverna ges rekommendationen att rikta stavarna från kammarens dörr inåt och med orienteringen liggandes. Även drogs slutsatsen att nätverksstrukturer når upp i nivå med de relativa bulkegenskaperna för trepunkts böjprov, dock endast med en ram runt hela provbiten. Det räckte ej med endast ram under och över, Triply Periodic Minimal Surface (TPMS)-based structures have quickly become popular inmany applications, for example medicinal implants, heat exchangers, shock absorbers and lightweight constructions. The gyroid structure is probably the most known and used, but plenty of variations exist with extremely good properties for additive manufacturing. The networks can be printed completely without support structures and can obtain mechanical properties in line with the relative bulk properties.This project shall evaluate the mechanical properties of TPMS-based test specimens SLSprinted in PA11 through compression testing, tensile testing, impact testing and three-point flexural testing. It shall also be determined if build direction and orientation in the printer’s build chamber effects the material’s mechanical properties. In addition to this will a material model be constructed for finite element analysis in Abaqus.The conclusions from this bachelor’s thesis are that both build direction and orientation in the printer’s build chamber effects the material mechanical properties. Based on the results from the tests the recommendation is given to direct the test specimens inward from the chamber’s door and to orient the specimens flat. The conclusion is also drawn that network structures can reach the relative bulk properties in three-point flexural test, however only with a frame encompassing the entire specimen. A frame only on top and bottom wasn’t enough.

Objective To review the literature to establish overall, match and training injury incidence rates (IIRs) in senior (>= 18 years of age) womens football (amateur club, elite club and international). Design Systematic review and meta-analysis of overall, match and training IIRs in senior womens football, stratified by injury location, type and severity. Data sources MEDLINE via PubMed; EMBASE via Ovid; CINAHL via EBSCO and Web of Science were searched from earliest record to July 2021. Eligibility criteria for selecting studies (1) football players participating in a senior womens football league (amateur club or elite club) or a senior womens international football tournament; (2) the study had to report IIRs or provide sufficient data from which this outcome metric could be calculated through standardised equations; (3) a full-text article published in a peer-reviewed journal before July 2021; (4) a prospective injury surveillance study and (5) case reports on single teams were ineligible. Results 17 articles met the inclusion criteria; amateur club (n=2), elite club (n=10), international (n=5). Overall, match and training time-loss IIRs are similar between senior womens elite club football and international football. Time-loss training IIRs in senior womens elite club football and international football are approximately 6-7 times lower than their equivalent match IIRs. Overall time-loss IIRs stratified by injury type in womens elite club football were 2.70/1000 hours (95% CI 1.12 to 6.50) for muscle and tendon, 2.62/1000 hours (95% CI 1.26 to 5.46) for joint and ligaments, and 0.76/1000 hours (95% CI 0.55 to 1.03) for contusions. Due to the differences in injury definitions, it was not possible to aggregate IIRs for amateur club football. Conclusion Lower limb injuries incurred during matches are a substantial problem in senior womens football. The prevention of lower limb joint, ligament, muscle and tendon injuries should be a central focus of injury prev

Aims: There is strong evidence that cribriform morphology indicates a worse prognosis of prostatic adenocarcinoma. Our aim was to investigate its interobserver reproducibility in prostate needle biopsies. Methods and results: A panel of nine prostate pathology experts from five continents independently reviewed 304 digitised biopsies for cribriform cancer according to recent International Society of Urological Pathology criteria. The biopsies were collected from a series of 702 biopsies that were reviewed by one of the panellists for enrichment of high-grade cancer and potentially cribriform structures. A 2/3 consensus diagnosis of cribriform and noncribriform cancer was reached in 90% (272/304) of the biopsies with a mean kappa value of 0.56 (95% confidence interval 0.52–0.61). The prevalence of consensus cribriform cancers was estimated to 4%, 12%, 21%, and 20% of Gleason scores 7 (3 + 4), 7 (4 + 3), 8, and 9–10, respectively. More than two cribriform structures per level or a largest cribriform mass with ≥9 lumina or a diameter of ≥0.5 mm predicted a consensus diagnosis of cribriform cancer in 88% (70/80), 84% (87/103), and 90% (56/62), respectively, and noncribriform cancer in 3% (2/80), 5% (5/103), and 2% (1/62), respectively (all P < 0.01). Conclusion: Cribriform prostate cancer was seen in a minority of needle biopsies with high-grade cancer. Stringent diagnostic criteria enabled the identification of cribriform patterns and the generation of a large set of consensus cases for standardisation.

Background: Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. Methods: Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. Findings: Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. Interpretation: This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical imple

Objectives: The criterion validity of the sphygmomanometer was evaluated, relative to the Force Frame strength testing system. Test-retest reliability was assessed for both hip adduction and abduction strength. Design: Test-retest reliability study and criterion validity study. Participants: 50 asymptomatic, field-sport athletes. Main outcome measures: Maximal isometric hip adduction and abduction strength were measured. Interclass correlation coefficient(ICC2,1) with confidence intervals were calculated to evaluate reliability of peak strength values. A Pearson product-moment correlation coefficient(r) was calculated to examine criterion validity of the sphygmomanometer as a measure of force when compared to the ForceFrame. Results: Intra-rater reliability for bilateral adduction testing using both ForceFrame and sphygmomanometer values revealed good-excellent reliability for both the 0° (ICC2.1 = 0.87–0.90) and 45° (ICC2.1 = 0.81–0.91) positions. ForceFrame values revealed good-excellent reliability for 0° abduction position and 45° abduction position. A good-moderate relationship (Pearson's r = 0.63) for 0° adduction position, and poor relationship (Pearson's r = 0.40) for 45° adduction position, were found between adduction squeeze values on ForceFrame and sphygmomanometer. Conclusion: Excellent reliability in hip adduction squeeze strength testing for both modes. However, there exists a ‘good to moderate’-‘fair’ relationship between the Force Frame and sphygmomanometer.

Acquiring large quantities of data and annotations is known to be effective for developing high-performing deep learning models, but is difficult and expensive to do in the healthcare context. Adding synthetic training data using generative models offers a low-cost method to deal effectively with the data scarcity challenge, and can also address data imbalance and patient privacy issues. In this study, we propose a comprehensive framework that fits seamlessly into model development workflows for medical image analysis. We demonstrate, with datasets of varying size, (i) the benefits of generative models as a data augmentation method; (ii) how adversarial methods can protect patient privacy via data substitution; (iii) novel performance metrics for these use cases by testing models on real holdout data. We show that training with both synthetic and real data outperforms training with real data alone, and that models trained solely with synthetic data approach their real-only counterparts. Code is available at https://github.com/Global-Health-Labs/US-DCGAN., Comment: accepted in Simulation and Synthesis in Medical Imaging (SASHIMI)

Through a community-driven competition, the PANDA challenge provides a curated diverse dataset and a catalog of models for prostate cancer pathology, and represents a blueprint for evaluating AI algorithms in digital pathology. Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge-the largest histopathology competition to date, joined by 1,290 developers-to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted kappa, 95% confidence interval (CI), 0.840-0.884) and 0.868 (95% CI, 0.835-0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials., Funding Agencies|Dutch Cancer SocietyKWF Kankerbestrijding [KUN 2015-7970]; Netherlands Organization for Scientific ResearchNetherlands Organization for Scientific Research (NWO) [016.186.152]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [201901466, 2020-00692]; Swedish Cancer Society (CAN)Swedish Cancer Society [2018/741]; Swedish eScience Research Center; Ake Wiberg Foundation; Prostatacancerforbundet; Academy of FinlandAcademy of FinlandEuropean Commission [341967, 335976]; Cancer Foundation Finland; Google LLCGoogle Incorporated; MICCAI board challenge working group; Verily Life Sciences; EIT Health; Karolinska InstitutetKarolinska Institutet; MICCAI 2020 satellite event team; ERAPerMed [334782]

We investigated the pattern of injuries in elite-level womens football in Ireland, during a two-season prospective injury surveillance study in the Womens National League (WNL). Seven out of the eight clubs (271 players) in the WNL were followed prospectively during the 2018 and 2019 seasons. The injury incidence rate in matches (19.2/1000 h) was 7.5 times higher than in training (2.5/1000 h). Players, on average, sustained 0.69 injuries per season (266 injuries/383 player seasons), which equates to 15 time-loss injuries per season for a squad of 22 players. The majority of the injuries sustained by players were lower extremity injuries (85%), of which, 46% had a non-contact injury mechanism. Muscle, ligament, and contusion injuries were the most common injury types, while the ankle, knee, and thigh were the most commonly injured body sites. The most common injuries sustained over the two seasons were lateral ankle sprains (13.9%), hamstring strains (12.4%), knee meniscus/cartilage injuries (7.5%), adductor strains (6%), quadriceps strains (4.5%), and ankle contusions (4.5%). The injuries with the highest injury burden were ACL injuries (59 days lost/1000 h), knee meniscus/cartilage injuries (23/1000 h), lateral ankle sprains (21/1000 h), hamstring strains (12/1000 h), MCL sprains (11/1000 h), and quadriceps strains (11/1000 h). There were 8 ACL tears documented over the 2 seasons, which accounted for 28% of all time lost to injury with a mean days lost per injury of 247. We recommend that clubs in the WNL in Ireland should implement injury risk mitigation strategies, with a particular focus on injuries with a high injury burden., Funding Agencies|Irish Research Council Enterprise Partnership Scheme (Postgraduate) awardIrish Research Council for Science, Engineering and Technology

Poor reporting of medical and healthcare systematic reviews is a problem from which the sports and exercise medicine, musculoskeletal rehabilitation, and sports science fields are not immune. Transparent, accurate and comprehensive systematic review reporting helps researchers replicate methods, readers understand what was done and why, and clinicians and policy-makers implement results in practice. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement and its accompanying Explanation and Elaboration document provide general reporting examples for systematic reviews of healthcare interventions. However, implementation guidance for sport and exercise medicine, musculoskeletal rehabilitation, and sports science does not exist. The Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science (PERSiST) guidance attempts to address this problem. Nineteen content experts collaborated with three methods experts to identify examples of exemplary reporting in systematic reviews in sport and exercise medicine (including physical activity), musculoskeletal rehabilitation (including physiotherapy), and sports science, for each of the PRISMA 2020 Statement items. PERSiST aims to help: (1) systematic reviewers improve the transparency and reporting of systematic reviews and (2) journal editors and peer reviewers make informed decisions about systematic review reporting quality.

Poor reporting of medical and healthcare systematic reviews is a problem from which the sports and exercise medicine, musculoskeletal rehabilitation, and sports science fields are not immune. Transparent, accurate and comprehensive systematic review reporting helps researchers replicate methods, readers understand what was done and why, and clinicians and policy-makers implement results in practice. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement and its accompanying Explanation and Elaboration document provide general reporting examples for systematic reviews of healthcare interventions. However, implementation guidance for sport and exercise medicine, musculoskeletal rehabilitation, and sports science does not exist. The Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science (PERSiST) guidance attempts to address this problem. Nineteen content experts collaborated with three methods experts to identify examples of exemplary reporting in systematic reviews in sport and exercise medicine (including physical activity), musculoskeletal rehabilitation (including physiotherapy), and sports science, for each of the PRISMA 2020 Statement items. PERSiST aims to help: (1) systematic reviewers improve the transparency and reporting of systematic reviews and (2) journal editors and peer reviewers make informed decisions about systematic review reporting quality.

Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological diagnosis and grading of prostate biopsies as example. We digitized 7788 prostate biopsies from 1192 men in the STHLM3 diagnostic study, used for training, and 3059 biopsies from 676 men used for testing. With conformal prediction, 1 in 794 (0.1%) predictions is incorrect for cancer diagnosis (compared to 14 errors [2%] without conformal prediction) while 175 (22%) of the predictions are flagged as unreliable when the AI-system is presented with new data from the same lab and scanner that it was trained on. Conformal prediction could with small samples (N = 49 for external scanner, N = 10 for external lab and scanner, and N = 12 for external lab, scanner and pathology assessment) detect systematic differences in external data leading to worse predictive performance. The AI-system with conformal prediction commits 3 (2%) errors for cancer detection in cases of atypical prostate tissue compared to 44 (25%) without conformal prediction, while the system flags 143 (80%) unreliable predictions. We conclude that conformal prediction can increase patient safety of AI-systems.

BACKGROUND: Individual differences in children eating behaviours have been linked with childhood overweight and obesity. The determinants of childhood eating behaviours are influenced by a complex combination of hereditary and ecological factors. This study examines if key ecological predictors of childhood overweight; maternal socio-economic status (SES), children's screen time, and childcare arrangements, are associated with eating behaviours in children aged 5-years-old. METHODS: This is secondary, cross-sectional analysis of the ROLO (Randomized COntrol Trial of LOw glycemic diet in pregnancy) study, using data from the 5-year follow-up (n = 306). Weight, height, and body mass index (BMI) were obtained from mothers and children at the 5-year follow-up. Children's BMI z-scores were calculated. SES was determined using maternal education level and neighborhood deprivation score. Information on children's screen time and childcare arrangements were collected using lifestyle questionnaires. Children's eating behaviours were measured using the Children's Eating Behaviour Questionnaire (CEBQ). Multiple linear regression, adjusted for potential confounders, assessed associations between maternal SES, screen time and children's eating behaviours. One-way ANOVA, independent sample t-tests and Spearman's correlation examined childcare exposure and children's eating behaviour. RESULTS: Mothers in the lowest SES group had higher BMI and were younger than those in the highest SES group (p = < 0.001, p = 0.03 respectively). In adjusted analysis, the lowest SES group was associated with a 0.463-point higher mean score for 'Desire to Drink' (95% CI = 0.054,0.870, p = 0.027) and higher 'Slowness to Eat' (B = 0.388, 95% CI = 0.044,0.733, p = 0.027) when compared with the highest SES group. Screen time (hours) was associated with higher 'Food Fussiness' (B = 0.032, 95% CI = 0.014,0.051, p = 0.001). Those who attended childcare had higher scores for 'Desire to Drink'(p = 0.046). N

Automated malaria diagnosis is a difficult but high-value target for machine learning (ML), and effective algorithms could save many thousands of children's lives. However, current ML efforts largely neglect crucial use case constraints and are thus not clinically useful. Two factors in particular are crucial to developing algorithms translatable to clinical field settings: (i) Clear understanding of the clinical needs that ML solutions must accommodate; and (ii) task-relevant metrics for guiding and evaluating ML models. Neglect of these factors has seriously hampered past ML work on malaria, because the resulting algorithms do not align with clinical needs. In this paper we address these two issues in the context of automated malaria diagnosis via microscopy on Giemsa-stained blood films. First, we describe why domain expertise is crucial to effectively apply ML to malaria, and list technical documents and other resources that provide this domain knowledge. Second, we detail performance metrics tailored to the clinical requirements of malaria diagnosis, to guide development of ML models and evaluate model performance through the lens of clinical needs (versus a generic ML lens). We highlight the importance of a patient-level perspective, interpatient variability, false positive rates, limit of detection, and different types of error. We also discuss reasons why ROC curves, AUC, and F1, as commonly used in ML work, are poorly suited to this context. These findings also apply to other diseases involving parasite loads, including neglected tropical diseases (NTDs) such as schistosomiasis., Comment: 17 pages, 5 figures

Objectives: To evaluate the adoption of and opinions on the Doha agreement meeting classification in groin pain in athletes. Design: Delphi survey and e-survey. Methods: A 2-round Delphi survey among the Doha agreement meeting expert group, and a separate international e-survey among clinicians who regularly assess athletes with groin pain. Clinical cases were presented, and participants provided their preferred terms for the diagnoses. All participants reported if they had adopted the Doha agreement meeting classification system in their practice. The Doha agreement meeting experts also shared opinions on amendments to the classification system, and reported their level of agreement with suggested statements. Results: In the Delphi survey, the Doha agreement meeting experts (n = 21) reported 8–11 different terms for their primary diagnosis of each presented case. The Doha agreement meeting terminology was used by 50–67% of these experts. In the international e-survey (n = 51), 12–15 different diagnostic terms were reported in each clinical case, and 43–55% of clinicians used the Doha agreement meeting terminology. Adoption of the Doha agreement classification system in practice was reported by 73–82% of the Doha agreement meeting experts and 57–69% of the clinicians in the international e-survey. The experts suggested 49 statements regarding amendments to the classification system. Seven of these reached >75% agreement or disagreement. Conclusions: Five years after publication, the majority of the Doha agreement expert group and independent international clinicians report adopting the Doha agreement meeting classification system. There is still considerable heterogeneity in diagnostic terminology when clinical cases are presented, and disagreement on statements related to amendments of the current classification system.

Lateral ankle sprains are a commonly incurred injury in sports. They have a high recurrence rate and can lead to the development of persistent injury associated symptoms. We performed a quantitative synthesis of published case reports documenting the kinematics of acute lateral ankle sprains and episodes of 'giving-way' of the ankle joint to provide a comprehensive description of the mechanisms. A systematic literature search was conducted to screen records within MEDLINE® and EMBASE®. Additional strategies included manual search of specific journals, as well as contacting researchers in relevant communities to retrieve unpublished data. Twenty-four cases were included in the quantitative synthesis, 11 from individual case reports and 13 from four separate case series. Two authors independently reviewed all the articles and extracted ankle joint kinematic data. Excessive ankle inversion was the most pronounced kinematic pattern observed across all included cases, with a mean peak inversion angle of 67.5° (range 2.0 to 142) and a mean peak inversion velocity of 974°/s (range 468 to 1752). This was followed by internal rotation and plantar flexion, respectively. A homogeneous linear function revealed a mean inversion velocity across all cases of 337°/s (range 117 to 1400; R2 = 0.78; p

INTRODUCTION: Variable eligibility criteria across studies on plantar heel pain may result in compromising the generalisability of meta-analyses when heterogeneity is not accounted for. We aimed to explore: (i) heterogeneity of participant eligibility criteria in studies that have investigated plantar heel pain, and (ii) associations between key eligibility criteria and the characteristics of the participants included in the study. METHODS: In this systematic review with narrative synthesis, we extracted participant eligibility criteria, and participants' age, body mass index (BMI), symptom duration and pain level from published studies on plantar heel pain. We performed a content analysis of criteria and aligned overarching criteria to the International Classification of Functioning, Disability and Health (ICF). We pooled studies that used the same thresholds for participant eligibility criteria into sub-groups. We also pooled and reported studies that did not have any eligibility criteria for the quantitative characteristics to use their data for reference values and pooled studies that did not have any eligibility criteria for the characteristics as reference. RESULTS: Two hundred and fourteen articles were included. The most reported participant eligibility criteria (as aligned to the ICF) related to body structures/function and personal factors. Age, BMI, symptom duration and pain level were used with various ranges and/or thresholds across studies (age was reported in 23 different ways across 97 studies; BMI 7/13; symptom duration 14/100; and pain level 8/31). When eligibility criteria included thresholds close to the reference value of a participant characteristic, characteristics were associated with criteria (e.g., younger participants when an upper age threshold was used). CONCLUSION: Participant eligibility criteria in studies on plantar heel pain vary widely; studies differed substantially in their use of quantitative thresholds. Participant character

Poor reporting of medical and healthcare systematic reviews is a problem from which the sports and exercise medicine, musculoskeletal rehabilitation, and sports science fields are not immune. Transparent, accurate and comprehensive systematic review reporting helps researchers replicate methods, readers understand what was done and why, and clinicians and policy-makers implement results in practice. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement and its accompanying Explanation and Elaboration document provide general reporting examples for systematic reviews of healthcare interventions. However, implementation guidance for sport and exercise medicine, musculoskeletal rehabilitation, and sports science does not exist. The Prisma in Exercise, Rehabilitation, Sport medicine and SporTs science (PERSiST) guidance attempts to address this problem. Nineteen content experts collaborated with three methods experts to identify examples of exemplary reporting in systematic reviews in sport and exercise medicine (including physical activity), musculoskeletal rehabilitation (including physiotherapy), and sports science, for each of the PRISMA 2020 Statement items. PERSiST aims to help: (1) systematic reviewers improve the transparency and reporting of systematic reviews and (2) journal editors and peer reviewers make informed decisions about systematic review reporting quality.

Contains fulltext : 238871.pdf (Publisher’s version ) (Open Access), Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the high grading variability among pathologists leads to the potential for under- and overtreatment. Artificial intelligence (AI) systems have shown promise in assisting pathologists to perform Gleason grading, which could help address this problem. In this mini-review, we highlight studies reporting on the development of AI systems for cancer detection and Gleason grading, and discuss the progress needed for widespread clinical implementation, as well as anticipated future developments. PATIENT SUMMARY: This mini-review summarizes the evidence relating to the validation of artificial intelligence (AI)-assisted cancer detection and Gleason grading of prostate cancer in biopsies, and highlights the remaining steps required prior to its widespread clinical implementation. We found that, although there is strong evidence to show that AI is able to perform Gleason grading on par with experienced uropathologists, more work is needed to ensure the accuracy of results from AI systems in diverse settings across different patient populations, digitization platforms, and pathology laboratories.

BACKGROUND AND PURPOSE: Hip fracture guidelines emphasize mobilization within 48 hours of surgery. The aims of this audit were to determine the proportion of patients with hip fracture who mobilize within 48 hours, identify factors associated with delayed mobilization, and identify barriers to mobilization. METHODS: Single-site prospective audit of 100 consecutive patients (age 82 ± 9 years) admitted for surgical management of hip fracture. Data collected included time to mobilization, factors that may impact mobilization (age, weight-bearing status, additional injuries, premorbid mobility status, time to surgery, dementia, delirium, and postoperative complications), and barriers to mobilization as identified by the physical therapist. RESULTS AND DISCUSSION: Mobilization within 48 hours of surgery was achieved by 43% of patients. Multivariate logistic regression demonstrated odds of mobilizing early increased with higher New Mobility Scores, representing better premorbid mobility (odds ratio [OR] = 1.30; 95% confidence interval [CI], 1.06-1.60); odds reduced if delirium was present on day 1 or 2 (OR = 0.25; 95% CI, 0.08-0.79). New Mobility Scores 5 or more, which indicate independent premorbid mobility inside and outside the house, best predicted early mobilization in patients who did not develop delirium. No cutoff score was identified for those with delirium. Identified barriers to mobilization included patient confusion, manual handling risk, patient declined, and hypotension. CONCLUSIONS: Less than half of this cohort achieved the guideline of mobilization within 48 hours of surgery. Patients who develop delirium within the first 2 days of surgery or who had premorbid mobility limitation were less likely to mobilize. Identification of patients likely to have delayed mobilization will assist physical therapists with delivering appropriate management to patients with hip fracture during their acute hospital stay.

BACKGROUND: Early mobilization after surgery is a key recommendation for people with hip fracture, however this is achieved by only 50% of people. Recumbent bike riding has been used in other populations with limited mobility and has potential to allow early exercise in people post hip fracture. The primary aim of this pilot trial was to demonstrate the feasibility of a trial protocol designed to determine the effect of early post-operative cycling in bed on outcomes in people with hip fracture. METHODS: Single-blinded, multi-site randomized controlled pilot trial. Fifty-one people with hip fracture were recruited within 4 days of surgery from two sites in Victoria. Participants were randomly allocated to receive either usual care (n = 25) or usual care plus active cycling in bed (n = 26). The cycling intervention was delivered on weekdays until the participant could walk 15 m with assistance of one person. The primary outcomes were trial feasibility and safety. Clinical outcomes, including mobility (Modified Iowa Level of Assistance Scale) and delirium were measured at day seven post-operatively and at hospital discharge by an assessor blinded to group. Additional outcomes at discharge included gait speed, cognition and quality of life. RESULTS: The intervention was safe, feasible and acceptable to patients and staff. Delivery of the intervention was ceased on (median) day 9.5 (IQR 7, 12); 73% of scheduled sessions were delivered; (median) 4 sessions (IQR 2.0, 5.5) were delivered per participant with (median) 9 min 34 s (IQR 04:39, 17:34) of active cycling per session. The trial protocol was feasible, however at day seven 75% of participants had not met the criterion (able to walk 15 m with assistance of one person) to cease the cycling intervention.. CONCLUSION: In bed cycling is feasible post-operatively following hip fracture, however seven days post-operatively is too early to evaluate the impact of the cycling intervention as many participants were still recei

Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67-0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization.

Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the high grading variability among pathologists leads to the potential for under-and overtreatment. Artificial intelligence (AI) systems have shown promise in assisting pathologists to perform Gleason grading, which could help address this problem. In this mini-review, we highlight studies reporting on the development of AI systems for cancer detection and Gleason grading, and discuss the progress needed for widespread clinical implementation, as well as anticipated future developments. Patient summary: This mini-review summarizes the evidence relating to the validation of artificial intelligence (AI)-assisted cancer detection and Gleason grading of prostate cancer in biopsies, and highlights the remaining steps required prior to its widespread clinical implementation. We found that, although there is strong evidence to show that AI is able to perform Gleason grading on par with experienced uropathologists, more work is needed to ensure the accuracy of results from AI systems in diverse settings across different patient populations, digitization platforms, and pathology laboratories.

Automated data-driven modeling, the process of directly discovering the governing equations of a system from data, is increasingly being used across the scientific community. PySINDy is a Python package that provides tools for applying the sparse identification of nonlinear dynamics (SINDy) approach to data-driven model discovery. In this major update to PySINDy, we implement several advanced features that enable the discovery of more general differential equations from noisy and limited data. The library of candidate terms is extended for the identification of actuated systems, partial differential equations (PDEs), and implicit differential equations. Robust formulations, including the integral form of SINDy and ensembling techniques, are also implemented to improve performance for real-world data. Finally, we provide a range of new optimization algorithms, including several sparse regression techniques and algorithms to enforce and promote inequality constraints and stability. Together, these updates enable entirely new SINDy model discovery capabilities that have not been reported in the literature, such as constrained PDE identification and ensembling with different sparse regression optimizers.

We consider the data-driven discovery of governing equations from time-series data in the limit of high noise. The algorithms developed describe an extensive toolkit of methods for circumventing the deleterious effects of noise in the context of the sparse identification of nonlinear dynamics (SINDy) framework. We offer two primary contributions, both focused on noisy data acquired from a system x' = f(x). First, we propose, for use in high-noise settings, an extensive toolkit of critically enabling extensions for the SINDy regression method, to progressively cull functionals from an over-complete library and yield a set of sparse equations that regress to the derivate x'. These innovations can extract sparse governing equations and coefficients from high-noise time-series data (e.g. 300% added noise). For example, it discovers the correct sparse libraries in the Lorenz system, with median coefficient estimate errors equal to 1% - 3% (for 50% noise), 6% - 8% (for 100% noise); and 23% - 25% (for 300% noise). The enabling modules in the toolkit are combined into a single method, but the individual modules can be tactically applied in other equation discovery methods (SINDy or not) to improve results on high-noise data. Second, we propose a technique, applicable to any model discovery method based on x' = f(x), to assess the accuracy of a discovered model in the context of non-unique solutions due to noisy data. Currently, this non-uniqueness can obscure a discovered model's accuracy and thus a discovery method's effectiveness. We describe a technique that uses linear dependencies among functionals to transform a discovered model into an equivalent form that is closest to the true model, enabling more accurate assessment of a discovered model's accuracy., Comment: Body 21 pages. Total length with Appendix 32 pages. 17 Figures, 8 Tables

Background Despite being the most commonly incurred sports injury with a high recurrence rate, there are no guidelines to inform return to sport (RTS) decisions following acute lateral ankle sprain injuries. We aimed to develop a list of assessment items to address this gap. Methods We used a three-round Delphi survey approach to develop consensus of opinion among 155 globally diverse health professionals working in elite field or court sports. This involved surveys that were structured in question format with both closed-response and open-response options. We asked panellists to indicate their agreement about whether or not assessment items should support the RTS decision after an acute lateral ankle sprain injury. The second and third round surveys included quantitative and qualitative feedback from the previous round. We defined a priori consensus being reached at >70% agree or disagree responses. Results Sixteen assessment items reached consensus to be included in the RTS decision after an acute lateral ankle sprain injury. They were mapped to five domains with 98% panellist agreement - PAASS: Pain (during sport participation and over the last 24 hours), Ankle impairments (range of motion; muscle strength, endurance and power), Athlete perception (perceived ankle confidence/reassurance and stability; psychological readiness), Sensorimotor control (proprioception; dynamic postural control/balance), Sport/functional performance (hopping, jumping and agility; sport-specific drills; ability to complete a full training session). Conclusion Expert opinion indicated that pain severity, ankle impairments, sensorimotor control, athlete perception/readiness and sport/functional performance should be assessed to inform the RTS decision following an acute lateral ankle sprain injury. Trial registration number ACTRN12619000522112.

Introduction: The syndrome of Relative Energy Deficiency in Sport (RED-S) consensus statements recognise that male athletes might have impaired fertility in terms of the Exercise Hypogonodal Male Condition (ExHMC). Thus, the aims of this study were to (1) identify risk of ExHMC in active males in various sports and (2) determine if associations between risk of ExHMC and health problems interfering with training and competition exist. Methods: A questionnaire was distributed online (November 2018–January 2019) using questions derived from the “Androgen Deficiency in the Aging Male Questionnaire” (ADAM-Q) to assess risk of ExHMC. Additional questions were included to collect information on participant demographics, injury and illness history and dietary habits. Logistic regression analyses explored differences between groups. Results: Risk of ExHMC was identified in 23.3% (n = 185) of 794 questionnaire participants. Following multivariate analyses, risk of ExHMC was independently associated with a lower than normal sex drive rating within the last month (OR 7.62, 95%CI 4.99–11.63) and less than three morning erections per week within the last month (OR: 4.67, 95%CI 3.23–6.76). Risk of ExHMC was associated with 15–21 days absence from training or competition during the previous 6 months due to overload injuries in the univariate analysis (OR = 2.69, 95% CI = 1.24–5.84). Conclusion: Risk of ExHMC and associated symptoms in this heterogeneous sample may be indicative of RED-S. Confounding factors such as over-training, medication use, fatigue and psychological stress need to be considered. Identification of male athletes exhibiting physiological symptoms associated with RED-S requires more research.

BACKGROUND: Lateral ankle sprains are common in indoor sports. High shoe-surface friction is considered a risk factor for non-contact lateral ankle sprains. Spraino is a novel low-friction patch that can be attached to the outside of sports shoes to minimise friction at the lateral edge, which could mitigate the risk of such injury. We aimed to determine preliminary effectiveness (incidence rate and severity) and safety (harms) of Spraino to prevent lateral ankle sprains among indoor sport athletes.METHODS: In this exploratory, parallel-group, two-arm pilot randomised controlled trial, 510 subelite indoor sport athletes with a previous lateral ankle sprain were randomly allocated (1:1) to Spraino or 'do-as-usual'. Allocation was concealed and the trial was outcome assessor blinded. Match and training exposure, number of injuries and associated time loss were captured weekly via text messages. Information on harms, fear-of-injury and ankle pain was also documented.RESULTS: 480 participants completed the trial. They reported a total of 151 lateral ankle sprains, of which 96 were categorised as non-contact, and 50 as severe. All outcomes favoured Spraino with incidence rate ratios of 0.87 (95% CI 0.62 to 1.23) for all lateral ankle sprains; 0.64 (95% CI 0.42 to 0.98) for non-contact lateral ankle sprains; and 0.47 (95% CI 0.25 to 0.88) for severe lateral ankle sprains. Time loss per injury was also lower in the Spraino group (1.8 vs 2.8 weeks, p=0.014). Six participants reported minor harms because of Spraino.CONCLUSION: Compared with usual care, athletes allocated to Spraino had a lower risk of lateral ankle sprains and less time loss, with only few reported minor harms.TRIAL REGISTRATION NUMBER: NCT03311490.

We have read with interest the recent debate between Drs Varma and Epstein regarding the grading of intraductal carcinoma of the prostate.$^{1}$ Unfortunately, the arguments as presented do little to abate the confusion surrounding this so-called diagnostic entity.

Background An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatment and undertreatment of prostate cancer. To alleviate these problems, we aimed to develop an artificial intelligence (AI) system with clinically acceptable accuracy for prostate cancer detection, localisation, and Gleason grading. Methods We digitised 6682 slides from needle core biopsies from 976 randomly selected participants aged 50–69 in the Swedish prospective and population-based STHLM3 diagnostic study done between May 28, 2012, and Dec 30, 2014 (ISRCTN84445406), and another 271 from 93 men from outside the study. The resulting images were used to train deep neural networks for assessment of prostate biopsies. The networks were evaluated by predicting the presence, extent, and Gleason grade of malignant tissue for an independent test dataset comprising 1631 biopsies from 246 men from STHLM3 and an external validation dataset of 330 biopsies from 73 men. We also evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology. We assessed discriminatory performance by receiver operating characteristics and tumour extent predictions by correlating predicted cancer length against measurements by the reporting pathologist. We quantified the concordance between grades assigned by the AI system and the expert urological pathologists using Cohen's kappa. Findings The AI achieved an area under the receiver operating characteristics curve of 0·997 (95% CI 0·994–0·999) for distinguishing between benign (n=910) and malignant (n=721) biopsy cores on the independent test dataset and 0·986 (0·972–0·996) on the external validation dataset (benign n=108, malignant n=222). The correlation between cancer length predicted by the AI and

AIMS: Perineural invasion (PNI) by prostatic adenocarcinoma is debated as a prognostic parameter. This study investigates the prognostic predictive value of PNI in a series of patients with locally advanced prostate cancer treated with radiotherapy and androgen deprivation using 10 years outcome data from the TROG 03.04 RADAR trial. METHODS: Diagnostic prostate biopsies from 976 patients were reviewed and the presence of PNI noted. Patients were followed for 10 years according to the trial protocol or until death. The primary endpoint for the study was time to bone metastasis. Secondary endpoints included time to soft tissue metastasis, transition to castration resistance, prostate cancer-specific mortality and all-cause mortality. RESULTS: PNI was detected in 449 cases (46%), with 234 cases (24%) having PNI in more than one core. The presence of PNI was significantly associated with higher ISUP grade, clinical T staging category, National Comprehensive Cancer Network risk group, and percent positive biopsy cores. The cumulative probability of bone metastases according to PNI status was significant over the 10 years follow-up interval of the study (log-rank test P < 0.0001). PNI was associated with all endpoints on univariable analysis. After adjusting for baseline clinicopathological and treatment factors, bone metastasis was the only endpoint in which PNI retained its prognostic significance (hazard ratio 1.42, 95% confidence interval 1.05-1.92, P = 0.021). CONCLUSIONS: The association between PNI and the development of bone metastases supports the inclusion of this parameter as a component of the routine histology report. Further this association suggests that evaluation of PNI may assist in selecting those patients who should be monitored more closely during follow-up.

Low energy availability (EA) underpins the female and male athlete triad and relative energy deficiency in sport (RED-S). The condition arises when insufficient calories are consumed to support exercise energy expenditure, resulting in compromised physiological processes, such as menstrual irregularities in active females. The health concerns associated with longstanding low EA include menstrual/libido, gastrointestinal and cardiovascular dysfunction and compromised bone health, all of which can contribute to impaired sporting performance. This narrative review provides an update of our previous review on the prevalence and risk of low EA, within-day energy deficiency, and the potential impact of low EA on performance. The methods to assess EA remain a challenge and contribute to the methodological difficulties in identifying "true" low EA. Screening female athletic groups using a validated screening tool such as the Low Energy Availability in Females Questionnaire (LEAF-Q) has shown promise in identifying endurance athletes at risk of low EA. Knowledge of RED-S and its potential implications for performance is low among coaches and athletes alike. Development of sport and gender-specific screening tools to identify adolescent and senior athletes in different sports at risk of RED-S is warranted. Education initiatives are required to raise awareness among coaches and athletes of the importance of appropriate dietary strategies to ensure that sufficient calories are consumed to support training.

Background: The detection of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI is; however, labor intensive. In the study we aimed to develop an algorithm based on deep neural networks to aid pathologists in this task. Methods: We collected, digitized and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7,406 men who underwent biopsy in the prospective and diagnostic STHLM3 trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n=8,318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build deep neural networks, and the remaining 20% were used to evaluate the performance of the algorithm. Results: For the detection of PNI in prostate biopsy cores the network had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97-0.99) based on 106 PNI positive cores and 1,652 PNI negative cores in the independent test set. For the pre-specified operating point this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. For localizing the regions of PNI within a slide we estimated an average intersection over union of 0.50 (CI: 0.46-0.55). Conclusion: We have developed an algorithm based on deep neural networks for detecting PNI in prostate biopsies with apparently acceptable diagnostic properties. These algorithms have the potential to aid pathologists in the day-to-day work by drastically reducing the number of biopsy cores that need to be assessed for PNI and by highlighting regions of diagnostic interest., Comment: 20 pages, 5 figures

Two decades of U.S. government legislative outcomes, as well as the policy preferences of rich people, the general population, and diverse interest groups, were captured in a detailed dataset curated and analyzed by Gilens, Page et al. (2014). They found that the preferences of the rich correlated strongly with policy outcomes, while the preferences of the general population did not, except via a linkage with rich people's preferences. Their analysis applied the tools of classical statistical inference, in particular logistic regression. In this paper we analyze the Gilens dataset using the complementary tools of Random Forest classifiers (RFs), from Machine Learning. We present two primary findings, concerning respectively prediction and inference: (i) Holdout test sets can be predicted with approximately 70% balanced accuracy by models that consult only the preferences of rich people and a small number of powerful interest groups, as well as policy area labels. These results include retrodiction, where models trained on pre-1997 cases predicted "future" (post-1997) cases. The 20% gain in accuracy over baseline (chance), in this detailed but noisy dataset, indicates the high importance of a few wealthy players in U.S. policy outcomes, and aligns with a body of research indicating that the U.S. government has significant plutocratic tendencies. (ii) The feature selection methods of RF models identify especially salient subsets of interest groups (economic players). These can be used to further investigate the dynamics of governmental policy making, and also offer an example of the potential value of RF feature selection methods for inference on datasets such as this., Comment: 13 pages, 2 figures

n/a

n/a

Despite the widespread acknowledgement of the importance of academic reading, much research tends to focus on academic writing. The role of academic writing in the development of academic and professional identities is generally accepted. In contrast, the role of academic reading has been less visible in the literature, and when discussed, it tends to be conceptualised as a generic skill. In this paper, we explore the role of reading in emergent academic identities in undergraduates. We reflect on research with our own Nursing and Midwifery students that highlighted the role of reading in the development of ‘writing capital.’ Drawing on this and wider evidence we explore how, through academic reading, students begin to recognise, and then participate in the scholarly conversations that construct knowledge within disciplines. We argue that academic reading, like academic writing, is a complex ongoing process that involves multiple transitions, rather than a skill that can, and should, be mastered early on. We contend that educators need to consider how and where academic reading is addressed within academic programmes. Moreover, we suggest ways to make room for it within our curricula and engage students in conversations about the nature of scholarship within their disciplines.

Introduction Systematic reviews fulfil a vital role in modern medicine.1 However, the results of systematic reviews are only as valid as the studies they include.2 Pooling flawed, or biased, results from different studies can compromise the credibility of systematic review findings. Bias is a systematic deviation from the truth in the results of a research study that

The Gleason Grading system has been used for over 50 years to prognosticate and guide the treatment for patients with prostate cancer. At consensus conferences in 2005 and 2014 under the guidance of the International Society of Urological Pathology (ISUP), the system has undergone major modifications to reflect modern diagnostic and therapeutic practices. The 2014 consensus conference yielded recommendations regarding cribriform, mucinous, glomeruloid and intraductal patterns, the most significant of which was the removal of any cribriform pattern from Gleason grade 3. Furthermore, a Gleason score grouping system was endorsed which consisted of five grades where Gleason score 6 (3+3) was classified as grade 1 which better reflected the mostly indolent behaviour of these tumours. Another issue discussed at the meeting and subsequently endorsed was that in Gleason score 7 cases, the percentage pattern 4 should be recorded. This is especially important in situations where modern active surveillance protocols expand to include men with low volume pattern 4. While major progress was made at the conference, several issues were either not resolved or not discussed at all. Most of these items relate to details of assignment of Gleason score and ISUP grade in specific specimen types and grading scenarios. This detailed review looks at the 2014 ISUP conference results and subsequent literature from an international perspective and proposes several recommendations. The specific issues addressed are percentage pattern 4 in Gleason score 7 tumours, percentage patterns 4 and 5 or 4/5 in Gleason score 8-10 disease, minor (≤5%) high grade patterns when either 2 or 3 patterns are present, level of reporting (core, specimen, case), dealing with grade diversity among site (highest and composite scores) and reporting scores in radical prostatectomy specimens with multifocal disease. It is recognised that for many of these issues, a strong evidence base does not exist, and further resea