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The Society for Cardiovascular Magnetic Resonance (SCMR) last published its comprehensive expert panel report of clinical indications for CMR in 2004. This new Consensus Panel report brings those indications up to date for 2020 and includes the very substantial increase in scanning techniques, clinical applicability and adoption of CMR worldwide. We have used a nearly identical grading system for indications as in 2004 to ensure comparability with the previous report but have added the presence of randomized controlled trials as evidence for level 1 indications. In addition to the text, tables of the consensus indication levels are included for rapid assimilation and illustrative figures of some key techniques are provided. ispartof: JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE vol:22 issue:1 ispartof: location:England status: published

The promise of precision medicine as a model to customize health care to the individual patient is heavily dependent upon new genetic tools to classify and characterize diseases and their hosts. Liquid biopsies serve as a safe alternative to solid biopsies and are thus a useful and critical component to fully realizing personalized medicine. The International Liquid Biopsy Standardization Alliance (ILSA) comprises organizations and foundations that recognize the importance of working towards the global use of liquid biopsy in oncology practice to support clinical decision making and regulatory considerations and seek to promote it in their communities. This manuscript provides an overview of the independent liquid biopsy- and standardization-based programs engaged with ILSA, their objectives and progress to date, and the tools and resources each is developing to contribute to the field. It also describes the unique areas of effort as well as synergy found within the group.

While they account for one-fifth of new cancer cases, rare cancers are difficult to study. A higher than average degree of uncertainty should be accommodated for clinical as well as for population-based decision making. Rules of rational decision making in conditions of uncertainty should be rigorously followed and would need widely informative clinical trials. In principle, any piece of new evidence would need to be exploited in rare cancers. Methodologies to explicitly weigh and combine all the available evidence should be refined, and the Bayesian logic can be instrumental to this end. Likewise, Bayesian-design trials may help optimize the low number of patients liable to be enrolled in clinical studies on rare cancers, as well as adaptive trials in general, with their inherent potential of flexibility when properly applied. While clinical studies are the mainstay to test hypotheses, the potential of electronic patient records should be exploited to generate new hypotheses, to create external controls for future studies (when internal controls are unpractical), to study effectiveness of new treatments in real conditions. Framework study protocols in specific rare cancers to stepwisely test sets of new agents, as from the early post-phase I development stage, should be encouraged. Also the compassionate and the off-label settings should be exploited to generate new evidence, and flexible regulatory innovations such as adaptive licensing could convey new agents early to rare cancer patients, while generating evidence. Though validation of surrogate end points is problematic in rare cancers, the use of an updated notion of tumor response may be of great value in the single patient to optimize the use of therapies, all the more the new ones. Disease-based communities, involving clinicians and patients, should be regularly consulted by regulatory bodies when setting their policies on drug approval and reimbursement in specific rare cancers ., While they account for one-fifth of new cancer cases, rare cancers are difficult to study. A higher than average degree of uncertainty should be accommodated for clinical as well as for population-based decision making. Rules of rational decision making in conditions of uncertainty should be rigorously followed and would need widely informative clinical trials. In principle, any piece of new evidence would need to be exploited in rare cancers. Methodologies to explicitly weigh and combine all the available evidence should be refined, and the Bayesian logic can be instrumental to this end. Likewise, Bayesian-design trials may help optimize the low number of patients liable to be enrolled in clinical studies on rare cancers, as well as adaptive trials in general, with their inherent potential of flexibility when properly applied. While clinical studies are the mainstay to test hypotheses, the potential of electronic patient records should be exploited to generate new hypotheses, to create external controls for future studies (when internal controls are unpractical), to study effectiveness of new treatments in real conditions. Framework study protocols in specific rare cancers to sequentially test sets of new agents, as from the early post-phase I development stage, should be encouraged. Also the compassionate and the off-label settings should be exploited to generate new evidence, and flexible regulatory innovations such as adaptive licensing could convey new agents early to rare cancer patients, while generating evidence. Though validation of surrogate end points is problematic in rare cancers, the use of an updated notion of tumor response may be of great value in the single patient to optimize the use of therapies, all the more the new ones. Disease-based communities, involving clinicians and patients, should be regularly consulted by regulatory bodies when setting their policies on drug approval and reimbursement in specific rare cancers.

Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology is used to assess and report certainty of evidence and strength of recommendations. This GRADE concept article is not GRADE guidance but introduces certainty of net benefit, defined as the certainty that the balance between desirable and undesirable health effects is favourable. Determining certainty of net benefit requires considering certainty of effect estimates, the expected importance of outcomes and variability in importance, and the interaction of these concepts. Certainty of net harm is the certainty that the net effect is unfavourable. Guideline panels using or testing this approach might limit strong recommendations to actions with a high certainty of net benefit or against actions with a moderate or high certainty of net harm. Recommendations may differ in direction or strength from that suggested by the certainty of net benefit or harm when influenced by cost, equity, acceptability or feasibility.

Background The second part of this study reanalyzes Ponce and Lozano's (2010) list of classics to create a new list of “foundational” articles in neurosurgery. Ponce and Lozano (2010) previously published a list of 106 neurosurgery classics, as defined by Garfield and his 400 citation criterion. Methods We used the Web of Science citation reports to create graphs for each study showing the total citations it received as a function of time. Each graph was subjectively analyzed independently and scored as “foundational” or “classic only,” based on whether the trend of citations received per year was uptrending, neutral, or downtrending. Results Of the 101 evaluated classics, 53 qualified as foundational. Over half of these studies were published in Journal of Neurosurgery (13), New England Journal of Medicine (12), or Lancet (5). Grading systems, randomized trials, and prospective studies were most likely to achieve foundational status. Only 30% of functional and 17% of endovascular classics qualified as foundational (compared with 100% of spine classics), suggesting that these fields are rapidly changing or less mature subspecialties still developing a foundational literature base. Conclusion By assessing citation counts as a function of time, we are able to differentiate classic neurosurgical studies that are critical to modern-day practice from those that are primarily of historic interest. Given the exponential growth of literature in our field, analyses such as these will become increasingly important to both trainees and senior neurosurgeons who strive to educate themselves on the data that drive modern-day clinical decision making.

Background Hemodynamic response after successful extracorporeal cardiopulmonary resuscitation (eCPR) is very heterogeneous. Pulse pressure (PP) as an easy to access surrogate parameter and correlate for myocardial damage or recovery from it, might be a valuable tool to estimate the outcome of these patients. Purpose To investigate the predictive value of the surrogate parameter PP in eCPR patients. Methods We report retrospective data of a single-centre registry of eCPR patients, treated at our Interdisciplinary Medical Intensive Care Unit between 01/2017 and 01/2020. The association between PP of the first 10 days after eCPR and hospital survival was investigated. Moreover, patients were divided into three groups according to their PP (low (0–9 mmHg), mid (10–29 mmHg) and high (≥30 mmHg)) at each time point. Results 143 patients (age 63 years, 74.1% male, 40% OHCA, average low flow time 49 min) were analysed. Overall hospital survival rate was 28%. A low PP both early after eCPR (after 1, 3, 6 and 12 hours) and in the further course after day 1 to day 8 was associated with reduced hospital survival. At each time point (1 hour to day 5) the classification of patients into a low, mid and high PP group was able to categorize the patients for a low (5–20%), moderate (20–40%) and high (50–70%) survival rate. A multivariable analysis showed that the mean PP of the first 24 hours was an independent predictor for survival (p=0.008, figure 1). Conclusion In this analysis, PP occurred to be a valuable parameter to estimate survival and maybe support clinical decision making in the further course of patients after eCPR. Funding Acknowledgement Type of funding sources: None. Figure 1. Survival of eCPR patients by mean 24hPP

The COVID-19 pandemic has presented practitioners of applied behavior analysis (ABA) with new and uncharted challenges. Upholding ethical responsibilities while navigating an international public health crisis has opened areas of uncertainty that have no precedent. Although there is general guidance on how to respond ethically from the Behavior Analyst Certification Board (BACB) in their publication specific to the COVID-19 crisis (BACB, 2020, March 29, Ethics Guidance for ABA Providers During COVID-19 Pandemic, retrieved from https://www.bacb.com/ethics-guidance-for-aba-providers-during-covid-19-pandemic-2/), there remains a huge responsibility on the individual practitioner to make potentially life-changing decisions. In that regard, practitioners are urged to ensure that they rely on socially significant and valid decision-making processes. The goal of this article is to provide an exercise in accounting for stakeholder feedback and connecting with patients and families regarding their input on the acceptability of treatment during the COVID-19 pandemic. The exercise is in the form of a structured parent interview to help practitioners account for the setting variables and social validity of treatment during a crisis. It is our ethical responsibility to remember this critical dimension of our science and practice.

Background The amount of available textual health data such as scientific and biomedical literature is constantly growing and becoming more and more challenging for health professionals to properly summarize those data and practice evidence-based clinical decision making. Moreover, the exploration of unstructured health text data is challenging for professionals without computer science knowledge due to limited time, resources, and skills. Current tools to explore text data lack ease of use, require high computational efforts, and incorporate domain knowledge and focus on topics of interest with difficulty. Objective We developed a methodology able to explore and target topics of interest via an interactive user interface for health professionals with limited computer science knowledge. We aim to reach near state-of-the-art performance while reducing memory consumption, increasing scalability, and minimizing user interaction effort to improve the clinical decision-making process. The performance was evaluated on diabetes-related abstracts from PubMed. Methods The methodology consists of 4 parts: (1) a novel interpretable hierarchical clustering of documents where each node is defined by headwords (words that best represent the documents in the node), (2) an efficient classification system to target topics, (3) minimized user interaction effort through active learning, and (4) a visual user interface. We evaluated our approach on 50,911 diabetes-related abstracts providing a hierarchical Medical Subject Headings (MeSH) structure, a unique identifier for a topic. Hierarchical clustering performance was compared against the implementation in the machine learning library scikit-learn. On a subset of 2000 randomly chosen diabetes abstracts, our active learning strategy was compared against 3 other strategies: random selection of training instances, uncertainty sampling that chooses instances about which the model is most uncertain, and an expected gradient length strategy based on convolutional neural networks (CNNs). Results For the hierarchical clustering performance, we achieved an F1 score of 0.73 compared to 0.76 achieved by scikit-learn. Concerning active learning performance, after 200 chosen training samples based on these strategies, the weighted F1 score of all MeSH codes resulted in a satisfying 0.62 F1 score using our approach, 0.61 using the uncertainty strategy, 0.63 using the CNN, and 0.45 using the random strategy. Moreover, our methodology showed a constant low memory use with increased number of documents. Conclusions We proposed an easy-to-use tool for health professionals with limited computer science knowledge who combine their domain knowledge with topic exploration and target specific topics of interest while improving transparency. Furthermore, our approach is memory efficient and highly parallelizable, making it interesting for large Big Data sets. This approach can be used by health professionals to gain deep insights into biomedical literature to ultimately improve the evidence-based clinical decision making process.

Background Sepsis is a life-threatening condition that can rapidly lead to organ damage and death. Existing risk scores predict outcomes for patients who have already become acutely ill. Objective We aimed to develop a model for identifying patients at risk of getting sepsis within 2 years in order to support the reduction of sepsis morbidity and mortality. Methods Machine learning was applied to 2,683,049 electronic health records (EHRs) with over 64 million encounters across five states to develop models for predicting a patient’s risk of getting sepsis within 2 years. Features were selected to be easily obtainable from a patient’s chart in real time during ambulatory encounters. Results The models showed consistent prediction scores, with the highest area under the receiver operating characteristic curve of 0.82 and a positive likelihood ratio of 2.9 achieved with gradient boosting on all features combined. Predictive features included age, sex, ethnicity, average ambulatory heart rate, standard deviation of BMI, and the number of prior medical conditions and procedures. The findings identified both known and potential new risk factors for long-term sepsis. Model variations also illustrated trade-offs between incrementally higher accuracy, implementability, and interpretability. Conclusions Accurate implementable models were developed to predict the 2-year risk of sepsis, using EHR data that is easy to obtain from ambulatory encounters. These results help advance the understanding of sepsis and provide a foundation for future trials of risk-informed preventive care.

BackgroundClinical pathways (CPs) can improve patient outcomes but can be complex to implement. Technologies, such as clinical decision support (CDS) tools, can facilitate their use, but require end-user testing in clinical settings.ObjectiveThis study applied the Technology Acceptance Model to evaluate the individual, organizational, and technological contexts impacting application of a portal to facilitate a CP for anxiety and depression (the ADAPT Portal) in a metropolitan cancer service. The ADAPT Portal triggers patient screening on patient reported outcomes, alerts staff to high scores, recommends evidence-based management, and triggers review and rescreening at set intervals.MethodsQuantitative and qualitative data on portal activity, data accuracy, and health service staff perspectives were collected. Quantitative data were analyzed descriptively, and thematic analysis was applied to qualitative data.ResultsOverall, 15 (100% of those invited) health service staff agreed to be interviewed. During the pilot, 73 users (36 health service staff members and 37 patients) were registered on the ADAPT Portal. Of the 37 patients registered, 16 (43%) completed screening at least once, with seven screening positive and triaged appropriately. In total, 34 support requests were lodged, resulting in 17 portal enhancements (technical issues). Health service staff considered the ADAPT Portal easy to use and useful; however, some deemed it unnecessary or burdensome (individual issues), particularly in a busy cancer service (organizational issues).ConclusionsUser testing of a CDS to facilitate screening and assessment of anxiety and depression in cancer patients highlighted some technological issues in implementing the ADAPT CDS, resulting in 17 enhancements. Our results highlight the importance of obtaining health service staff feedback when piloting specialized CDS tools and addressing contextual factors when implementing them.

We describe the extent to which comprehensive genomic profiling (CGP) results were used by oncologists to guide targeted therapy selection in a cohort of solid tumor patients tested as part of standard care at Roswell Park Comprehensive Cancer Center June 2016–June 2017, with adequate follow up through September 2018 (n = 620). Overall, 28.4% of CGP tests advised physicians about targeted therapy use supported by companion diagnostic or practice guideline evidence. Post-test targeted therapy uptake was highest for patients in active treatment at the time of order (86% versus 76% of treatment naïve patients), but also took longer to initiate (median 50 days versus 7 days for treatment naïve patients), with few patients (2.6%) receiving targeted agents prior to testing. 100% of patients with resistance variants did not receive targeted agents. Treatment naïve patients received immunotherapy as the most common alternative. When targeted therapy given off-label or in a trial was the best CGP option, (7%) of patients received it. Our data illustrate the appropriate and heterogeneous use of CGP by oncologists as a longitudinal treatment decision tool based on patient history and treatment needs, and that some patients may benefit from testing prior to initiation of other standard treatments.

Background Improving clinical reasoning skills—the thought processes used by clinicians to formulate appropriate questions and diagnoses—is essential for reducing missed diagnostic opportunities. The electronic Clinical Reasoning Educational Simulation Tool (eCREST) was developed to improve the clinical reasoning of future physicians. A feasibility trial demonstrated acceptability and potential impacts; however, the processes by which students gathered data were unknown. Objective This study aims to identify the data gathering patterns of final year medical students while using eCREST and how eCREST influences the patterns. Methods A mixed methods design was used. A trial of eCREST across 3 UK medical schools (N=148) measured the potential effects of eCREST on data gathering. A qualitative think-aloud and semistructured interview study with 16 medical students from one medical school identified 3 data gathering strategies: Thorough, Focused, and Succinct. Some had no strategy. Reanalysis of the trial data identified the prevalence of data gathering patterns and compared patterns between the intervention and control groups. Patterns were identified based on 2 variables that were measured in a patient case 1 month after the intervention: the proportion of Essential information students identified and the proportion of irrelevant information gathered (Relevant). Those who scored in the top 3 quartiles for Essential but in the lowest quartile for Relevant displayed a Thorough pattern. Those who scored in the top 3 quartiles for Relevant but in the lowest quartile for Essential displayed a Succinct pattern. Those who scored in the top 3 quartiles on both variables displayed a Focused pattern. Those whose scores were in the lowest quartile on both variables displayed a Nonspecific pattern. Results The trial results indicated that students in the intervention group were more thorough than those in the control groups when gathering data. The qualitative data identified data gathering strategies and the mechanisms by which eCREST influenced data gathering. Students reported that eCREST promoted thoroughness by prompting them to continuously reflect and allowing them to practice managing uncertainty. However, some found eCREST to be less useful, and they randomly gathered information. Reanalysis of the trial data revealed that the intervention group was significantly more likely to display a Thorough data gathering pattern than controls (21/78, 27% vs 6/70, 9%) and less likely to display a Succinct pattern (13/78, 17% vs 20/70, 29%; χ23=9.9; P=.02). Other patterns were similar across groups. Conclusions Qualitative data suggested that students applied a range of data gathering strategies while using eCREST and that eCREST encouraged thoroughness by continuously prompting the students to reflect and manage their uncertainty. Trial data suggested that eCREST led students to demonstrate more Thorough data gathering patterns. Virtual patients that encourage thoroughness could help future physicians avoid missed diagnostic opportunities and enhance the delivery of clinical reasoning teaching.

Background Risk scores can be useful in clinical risk stratification and accurate allocations of medical resources, helping health providers improve patient care. Point-based scores are more understandable and explainable than other complex models and are now widely used in clinical decision making. However, the development of the risk scoring model is nontrivial and has not yet been systematically presented, with few studies investigating methods of clinical score generation using electronic health records. Objective This study aims to propose AutoScore, a machine learning–based automatic clinical score generator consisting of 6 modules for developing interpretable point-based scores. Future users can employ the AutoScore framework to create clinical scores effortlessly in various clinical applications. Methods We proposed the AutoScore framework comprising 6 modules that included variable ranking, variable transformation, score derivation, model selection, score fine-tuning, and model evaluation. To demonstrate the performance of AutoScore, we used data from the Beth Israel Deaconess Medical Center to build a scoring model for mortality prediction and then compared the data with other baseline models using the receiver operating characteristic analysis. A software package in R 3.5.3 (R Foundation) was also developed to demonstrate the implementation of AutoScore. Results Implemented on the data set with 44,918 individual admission episodes of intensive care, the AutoScore-created scoring models performed comparably well as other standard methods (ie, logistic regression, stepwise regression, least absolute shrinkage and selection operator, and random forest) in terms of predictive accuracy and model calibration but required fewer predictors and presented high interpretability and accessibility. The nine-variable, AutoScore-created, point-based scoring model achieved an area under the curve (AUC) of 0.780 (95% CI 0.764-0.798), whereas the model of logistic regression with 24 variables had an AUC of 0.778 (95% CI 0.760-0.795). Moreover, the AutoScore framework also drives the clinical research continuum and automation with its integration of all necessary modules. Conclusions We developed an easy-to-use, machine learning–based automatic clinical score generator, AutoScore; systematically presented its structure; and demonstrated its superiority (predictive performance and interpretability) over other conventional methods using a benchmark database. AutoScore will emerge as a potential scoring tool in various medical applications.

Background Serum biomarkers may inform and improve care in traumatic brain injury (TBI). We aimed to correlate serum biomarkers with clinical severity, care path and imaging abnormalities in TBI, and explore their incremental value over clinical characteristics in predicting computed tomographic (CT) abnormalities. Methods We analyzed six serum biomarkers (S100B, NSE, GFAP, UCH-L1, NFL and t-tau) obtained

Background The range of decisions and considerations that women with advanced breast cancer (ABC) face can be overwhelming and difficult to manage. Research shows that most patients prefer a shared decision-making (SDM) approach as it provides them with the opportunity to be actively involved in their treatment decisions. The current engagement of these patients in their clinical decisions is suboptimal. Moreover, implementing SDM into routine clinical care can be challenging as patients may not always feel adequately prepared or may not expect to be involved in the decision-making process. Objective Avalere Health developed the Preparation for Shared Decision-Making (PFSDM) tool to help patients with ABC feel prepared to communicate with their clinicians and engage in decision making aligned with their preferences. The goal of this study was to validate the tool for its acceptability and usability among this patient population. Methods We interviewed a diverse group of women with ABC (N=30). Interviews were audiorecorded, transcribed, and double coded by using NVivo. We assessed 8 themes to understand the acceptability and usability of the tool. Results Interviewees expressed that the tool was acceptable for preparing patients for decision making and would be useful for helping patients know what to expect in their care journey. Interviewees also provided useful comments to improve the tool. Conclusions This validation study confirms the acceptability and usability of the PFSDM tool for women with ABC. Future research should assess the feasibility of the tool’s implementation in the clinical workflow and its impact on patient outcomes.

Conducting research in practice settings is the primary mechanism for establishing a strong foundation of evidence for clinical decision making. In behavior analysis, this type of research frequently originates from university-based systems that have established institutional review boards. Independent human service agencies that want to contribute applied research to the literature base that is clinically meaningful and conducted in an ethical fashion must establish a research review committee (RRC). The purpose of this article is to provide information and guidance for establishing and maintaining the activity of an RRC in a human service setting.

OBJECTIVES: Physical therapists (PTs) may practice in direct access or act as primary care practitioners, which necessitate patients’ screening and management for red, orange and yellow flags. The objective of the project was to assess the American PT’s ability to manage red, orange and yellow flags in patients with low back pain (LBP), and to compare this ability among PTs with different qualifications. METHODS: The project was an electronic cross-sectional survey. The investigators contacted 2,861 PTs. Participants made clinical decisions for three vignettes: LBP with red flag for ectopic pregnancy, with orange flag for depression and with yellow flag for fear avoidance behaviour (FAB). The investigators used logistic regression to compare management of warning flags among PTs with distinct qualifications: orthopaedic clinical specialists (PTOs), fellows of the AAOMPT (PTFs), PTOs and PTFs (PTFOs), and PTs without clinical specialization (PTMSs). RESULTS: A total of 410 PTs completed all sections of the survey (142 PTOs, 110 PTFOs, 74 PTFs and 84 PTMSs). Two hundred and seventeen PTs (53%) managed the patient with LBP and symptoms of ectopic pregnancy correctly, 115 PTs (28.5%) of them managed the patient with LBP and symptoms of depression correctly, and 177 (43.2%) managed the patient with LBP and FAB correctly. DISCUSSION: In general, PTs with specialization performed significantly better than PTMSs in all three clinical vignettes. PTs ability to manage patients with warning flags was relatively low. Based on our results, further education on patients with LBP and warning flags is needed. The survey had the potential for non-response and self-selection bias. LEVEL OF EVIDENCE: 3b.

We tested the feasibility of setting individualized glycemic goals and factors influencing targets set in a clinical trial in elderly patients with type 2 diabetes. A 24-week, randomized, double-blind, placebo-controlled study was conducted in 45 outpatient centers in seven European countries. 278 drug-naïve or inadequately controlled (mean HbA1c 7.9%) patients with type 2 diabetes aged ≥70 years with HbA1c levels ≥7.0% and ≤10.0% were enrolled. Investigator-defined individualized HbA1c targets and the impact of baseline characteristics on individualized treatment targets was evaluated. The average individualized HbA1c target was set at 7.0%. HbA1c at baseline predicted a target setting such that higher the HbA1c, more aggressive was the target (P

OBJECTIVES: Clinical mentoring is important for novice clinicians as they are developing advanced critical-thinking skills. Research exploring innovative mentoring strategies to reduce barriers and enhance learning is needed. The purpose of this study was to examine the effects of providing online clinical mentoring to small international groups of novice clinicians treating patients with spinal dysfunction in the outpatient setting. METHODS: Eleven novice and four expert clinicians were allocated into small international groups. Four one-hour group video-conference mentoring sessions were held in which each novice clinician presented a case study. Data were collected from pre- and post-participation surveys and post-participation focus groups. Data were evaluated with a mixed-methods phenomenological analysis. RESULTS: Four themes emerged from the novice qualitative data: improved confidence, enhanced critical thinking, appreciation of the structured design and accessibility to peers and mentors. The quantitative data revealed significant improvement in three confidence measures, improvement of 1.48 points on self-selected clinical goals, and 82.0% reported improved clinical decision-making. Two themes emerged from the expert data: value of the model to fill a need within the profession and viability of the model to stand alone or as part of an educational program. All participants rated their experience on average at 8.76/10 and expressed interest in future mentoring programs. DISCUSSION: Online small group international clinical mentoring appears to be an effective strategy to provide clinical mentoring to promote confidence and critical-thinking skills. This research could provide a viable model to increase accessibility to clinical mentors and fill a need within the profession.

Background Collaborative reasoning occurs in clinical practice but is rarely developed during education. The computerized virtual patient (VP) cases allow for a stepwise exploration of cases and thus stimulate active learning. Peer settings during VP sessions are believed to have benefits in terms of reasoning but have received scant attention in the literature. Objective The objective of this study was to thoroughly investigate interactions during medical students’ clinical reasoning in two-party VP settings. Methods An in-depth exploration of students’ interactions in dyad settings of VP sessions was performed. For this purpose, two prerecorded VP sessions lasting 1 hour each were observed, transcribed in full, and analyzed. The transcriptions were analyzed using thematic analysis, and short clips from the videos were selected for subsequent analysis in relation to clinical reasoning and clinical aspects. Results Four categories of interactions were identified: (1) task-related dialogue, in which students negotiated a shared understanding of the task and strategies for information gathering; (2) case-related insights and perspectives were gained, and the students consolidated and applied preexisting biomedical knowledge into a clinical setting; (3) clinical reasoning interactions were made explicit. In these, hypotheses were followed up and clinical examples were used. The researchers observed interactions not only between students and the VP but also (4) interactions with other resources, such as textbooks. The interactions are discussed in relation to theories of clinical reasoning and peer learning. Conclusions The dyad VP setting is conducive to activities that promote analytic clinical reasoning. In this setting, components such as peer interaction, access to different resources, and reduced time constraints provided a productive situation in which the students pursued different lines of reasoning.

Introduction: The objective of this guideline is to outline the role of magnetic resonance imaging (MRI) in clinical decision making and outcome prediction in patients with traumatic spinal cord injury (SCI). Methods: A systematic review of the literature was conducted to address key questions related to the use of MRI in patients with traumatic SCI. This review focused on longitudinal studies that controlled for baseline neurologic status. A multidisciplinary Guideline Development Group (GDG) used this information, their clinical expertise, and patient input to develop recommendations on the use of MRI for SCI patients. Based on GRADE (Grading of Recommendation, Assessment, Development and Evaluation), a strong recommendation is worded as “we recommend,” whereas a weaker recommendation is indicated by “we suggest.” Results: Based on the limited available evidence and the clinical expertise of the GDG, our recommendations were: (1) “We suggest that MRI be performed in adult patients with acute SCI prior to surgical intervention, when feasible, to facilitate improved clinical decision-making” (quality of evidence, very low) and (2) “We suggest that MRI should be performed in adult patients in the acute period following SCI, before or after surgical intervention, to improve prediction of neurologic outcome” (quality of evidence, low). Conclusions: These guidelines should be implemented into clinical practice to improve outcomes and prognostication for patients with SCI.

Introduction: MicroRNA (miR)371a-3p was suggested to be a sensitive and specific new serum biomarker of germ cell tumours (GCTs); however, its clinical usefulness remains unproven. Patients, Methods: In 312 consecutive cases with various testicular diseases, serum levels of miR371a-3p were measured. Measurement results became available only after completion of treatment. Five patients with testicular seminoma were selected for review because of unanticipated clinical courses. Results: In each two patients, elevated miR levels heralded undetected primary testicular GCT and metastases despite inconclusive radiological findings. In one case, a normal miR371a-3p level correctly pointed to the absence of metastases contrary to clinical assessment. In all cases, knowledge about the miR371a-3p levels would have altered the clinical management. Conclusions: These cases highlight the exceptional usefulness of the new GCT biomarker. In contrast to classical markers, miR371a-3p can identify primary testicular GCT. The marker can aid in clinical decision making in cases with ambiguous clinical findings.

BACKGROUND: Shared decision making (SDM) involves the formation of a collaborative partnership between the patient and clinician combining both of their expertise in order to benefit decision making. In order for clinicians to be able to carry out this skilled task, they require practice. Virtual reality, in the form of a virtual patient, could offer a potential method of facilitating this. OBJECTIVE: The objective of this study was to create a virtual patient that simulated a primary care consultation, affording the opportunity to practice SDM. A second aim was to involve patients in the design of a virtual patient simulation and report the process of the design. METHODS: We employed a multistep design process drawing on patient and expert involvement. RESULTS: A virtual patient, following a narrative style, was built, which allows a user to practice and receive feedback; both clinical and communication skills are required for the simulation. The patient group provided multiple insights, which the academic team had overlooked. They pertained mostly to issues concerning the patient experience. CONCLUSIONS: It is possible to design a virtual patient that allows a learner to practice their ability to conduct SDM. Patient input into the design of virtual patient simulations can be a worthwhile activity.

BackgroundSmartphones and other mobile devices are having and will continue to have an impact on health care delivery in acute settings in Australia and overseas. Nurses, unlike physicians, have been slow to adopt these technologies and the reasons for this may relate to the status of both these professions within the hospital setting. ObjectiveTo explore nurses’ perspectives on iPhone use within an acute care unit. We examined their experiences and views on how this device may improve communication and decision-making processes at the point of care. MethodsTwo focus group discussions, using a semistructured interview, were conducted over the trial period. The discussions focused on the nurses’ experiences regarding ease of use, features, and capabilities of the device. The focus groups were recorded, transcribed, and analyzed using semistructured interview questions as a guide. ResultsThe positive findings indicated that the iPhones were accessible and portable at point of care with patients, enhanced communication in the workplace, particularly among the nurses, and that this technology would evolve and be embraced by all nurses in the future. The negatives were the small screen size when undertaking bedside education for the patient and the invasive nature of the device. Another issue was the perception of being viewed as unprofessional when using the device in real time with the patients and their family. ConclusionsThe use of iPhones by nurses in acute care settings has the potential to enhance patient care, especially through more effective communication among nurses, and other health care professionals. To ensure that the benefits of this technology is woven into the everyday practice of the nurse, it is important that leaders in these organizations develop the agenda or policy to ensure that this occurs.

WOS: 000371745700019, PubMed ID: 26325175, Successful vaccination policies for protection from invasive pneumococcal diseases (IPD) dependent on determination of the exact serotype distribution in each country. We aimed to identify serotypes of pneumococcal strains causing IPD in children in Turkey and emphasize the change in the serotypes before and after vaccination with 7-valent pneumococcal conjugate vaccine (PCV-7) was included and PCV-13 was newly changed in Turkish National Immunization Program. Streptococcus pneumoniae strains were isolated at 22 different hospitals of Turkey, which provide healthcare services to approximately 65% of the Turkish population. Of the 335 diagnosed cases with S. pneumoniae over the whole period of 2008-2014, the most common vaccine serotypes were 19F (15.8%), 6B (5.9%), 14 (5.9%), and 3 (5.9%). During the first 5y of age, which is the target population for vaccination, the potential serotype coverage ranged from 57.5 % to 36.8%, from 65.0% to 44.7%, and from 77.4% to 60.5% for PCV-7, PCV-10, and PCV-13 in 2008-2014, respectively. The ratio of non-vaccine serotypes was 27.2% in 2008-2010 whereas was 37.6% in 2011-2014 (p=0.045). S. penumoniae serotypes was less non-susceptible to penicillin as compared to our previous results (33.7vs 16.5 %, p=0.001). The reduction of those serotype coverage in years may be attributed to increasing vaccinated children in Turkey and the increasing non-vaccine serotype may be explained by serotype replacement. Our ongoing IPD surveillance is a significant source of information for the decision-making processes on pneumococcal vaccination., PfizerPfizer, This study was supported by Pfizer.

The role of gut feelings in diagnostic reasoning is recognized by most GPs throughout Europe, and probably throughout the world. Studies on this topic have emerged from different countries but there is the risk that authors will use different terms for similar concepts. The European Expert Group on Cognitive and Interactive Processes in Diagnosis and Management in General Practice, COGITA for short, was founded in 2008 to conduct cross-border research in the area of non-analytical diagnostic reasoning. Academic GPs, PhD students, psychologists, linguists and students meet once a year to share their experiences, exchange results and initiate new studies on the topic. A milestone in their research is this publication of a short glossary of diagnostic reasoning terms relating to the gut feelings research topic. It was constructed by the COGITA group members following a literature review, which aimed to define salient terms used in their publications. They described the terms, cross-reviewed the wording and reached consensus within the group. Two sections were created: (1) a diagnostic reasoning section that describes concepts such as analytical and non-analytical reasoning, clinical mind lines, and intuition, and (2) a research methods section describing concepts such as linguistic validity and saturation. The glossary, including relevant literature, has been published on the website http://www.gutfeelingsingeneralpractice.eu. In the future, the glossary will be modified if necessary and completed by members of the COGITA group. KEY MESSAGE A glossary of diagnostic reasoning terms relating to gut feelings research was constructed by the COGITA group to define salient terms, used in their publications. It is a prerequisite to conduct further cross-border research into gut feelings in family medicine. The development of the glossary is ongoing.

Background: The goal of teleconsultation is to omit geographical and functional distance between two or more geographically separated health care providers. The purpose of present study is to review and analyze physician-physician teleconsultations. Method: The PubMed electronic database was searched. The primary search was done on January 2015 and was updated on December 2015. A fetch and tag plan was designed by the researchers using an online Zotero library. Results: 174 full-text articles of 1702 records met inclusion criteria. Teleconsultation for pediatric patients accounts for 14.36 percent of accepted articles. Surgery and general medicine were the most prevalent medical fields in the adults and pediatrics, respectively. Most teleconsultations were inland experiences (no=135), and the USA, Italy and Australia were the three top countries in this group. Non-specialists health care providers/centers were the dominant group who requested teleconsultation (no=130). Real time, store and forward, and hybrid technologies were used in 50, 31, and 16.7 percent of articles, respectively. The teleconsultation were reported to result in change in treatment plan, referral or evacuation rate, change in diagnosis, educational effects, and rapid decision making. Use of structured or semi-structured template had been noticed only in a very few articles. Conclusion: The present study focused on the recent ten years of published articles on physician-physician teleconsultations. Our findings showed that although there are positive impacts of teleconsultation as improving patient management, still have gaps that need to be repaired.

Despite a significant expansion in the use of cardiac MRI (CMR), there is inadequate evaluation of its incremental impact on clinical decision-making over and above other well-established modalities. We sought to determine the incremental utility of CMR in routine practice.629 consecutive CMR studies referred by 44 clinicians from 9 institutions were evaluated. Pre-defined algorithms were used to determine the incremental influence on diagnostic thinking, influence on clinical management and thus the overall clinical utility. Studies were also subdivided and evaluated according to the indication for CMR.CMR provided incremental information to the clinician in 85% of cases, with incremental influence on diagnostic thinking in 85% of cases and incremental impact on management in 42% of cases. The overall incremental utility of CMR exceeded 90% in 7 out of the 13 indications, whereas in settings such as the evaluation of unexplained ventricular arrhythmia or mild left ventricular systolic dysfunction, this was50%.CMR was frequently able to inform and influence decision-making in routine clinical practice, even with analyses that accepted only incremental clinical information and excluded a redundant duplication of imaging. Significant variations in yield were noted according to the indication for CMR. These data support a wider integration of CMR services into cardiac imaging departments.These data are the first to objectively evaluate the incremental value of a UK CMR service in clinical decision-making. Such data are essential when seeking justification for a CMR service.