Exploratory Study of Associations and Agreement between Prognostic Patient-Registered Factors, Physiotherapists' Intuitive Synthesis, and Patient-Reported Factors in Whiplash-Associated Disorders.

BACKGROUND: A large proportion of people who sustain a whiplash injury will have persistent pain, disability, and participation problems. Several prognostic factors for functional recovery have been reported in the literature but these factors are often evaluated based on differing implementations in clinical practice. Additionally, physiotherapists also rely on their clinical intuition to estimate the functional prognosis of their patients, but this is seldom measured in experimental research. Furthermore, no study to date has explored the associations between clinical intuition, clinically estimated factors, and objectively measured factors for functional recovery of patients with Whiplash-Associated Disorders (WAD). AIM: The aim of this exploratory study is to evaluate associations between prognostic factors for functional recovery, based on routinely collected data in a specialized primary care physiotherapy practice in a consecutive sample of patients (n = 523) with WAD. METHODS: Three sources of prognostic factors were selected: (1) physiotherapists' synthesis of clinical intuition in terms of high-risk, inconclusive risk, or low-risk for functional recovery, (2) patient-registered factors from history taking, and (3) patient-reported prognostic factors derived from questionnaires. Prognostic factors were selected based on the literature, recommendations in Dutch clinical practice guidelines, and consensus between experts. Spearman's rank correlation coefficients were calculated to explore the associations between sources of prognostic factors, using a cutoff ≥0.25 for acceptable association. RESULTS: Associations between physiotherapists' intuitive synthesis and patient-registered variables were substantial (rs = 0.86), between patient-registered variables and patient-reported variables fair (ranging from 0.30 to 0.41) to substantial (ranging from 0.69 to 0.73), and between physiotherapists intuitive synthesis and patient-reported variables fair (ranging from 0.30 to 0.37). CONCLUSION: When estimating prognosis for functional recovery using clinical reasoning, physiotherapists should integrate patients' registered experience of their course of recovery, as well as the timeline after an accident, with their own synthesis of clinical intuition regarding prognostic factors in patients with WAD.

Testing Clinical Intuitions About Barriers to Improvement in Cognitive-Behavioral Therapy for Panic Disorder.

Although clinical intuitions influence psychotherapeutic practice and are a rich source of novel hypotheses for research, many remain to be empirically tested. This study evaluates whether clinicians' beliefs about barriers to progress in cognitive-behavioral therapy (CBT) for panic disorder are supported by data. Data from a randomized-controlled trial comparing CBT to panic-focused psychodynamic psychotherapy (PFPP) for adults with primary panic disorder (N = 161) were used to evaluate 15 factors endorsed by clinicians as impediments to CBT in a recent survey. Panic severity was assessed before, during (at Weeks 1, 5, and 9), and at termination of treatment (Week 12) using the Panic Disorder Severity Scale. Hierarchical linear modeling revealed that none of the perceived barriers were predictive of poor outcome. Contrary to clinicians' intuitions, dissociation during panic attacks was associated with greater symptomatic improvement in both treatment arms (ß = -0.69, p < .05), above the effect of established predictors. Moderation analyses revealed that when patients had PTSD diagnosed with the Anxiety Disorders Interview Schedule (ß = 1.71, p < .05) or less severe panic disorder (ß = 0.45, p = .04), they changed more rapidly in CBT than in PFPP. Overall, clinician agreement was inversely related to the strength of a predictor (r = -.24, p = .39). Although clinical intuitions can be useful as clinical and empirical signals, such beliefs should be critically examined before informing practice. Dialogue between academics and clinicians might be enhanced through research that incorporates input from front-line practitioners.

Machine-learning Prognostic Models from the 2014-16 Ebola Outbreak: Data-harmonization Challenges, Validation Strategies, and mHealth Applications.

BACKGROUND: Ebola virus disease (EVD) plagues low-resource and difficult-to-access settings. Machine learning prognostic models and mHealth tools could improve the understanding and use of evidence-based care guidelines in such settings. However, data incompleteness and lack of interoperability limit model generalizability. This study harmonizes diverse datasets from the 2014-16 EVD epidemic and generates several prognostic models incorporated into the novel Ebola Care Guidelines app that provides informed access to recommended evidence-based guidelines. METHODS: Multivariate logistic regression was applied to investigate survival outcomes in 470 patients admitted to five Ebola treatment units in Liberia and Sierra Leone at various timepoints during 2014-16. We generated a parsimonious model (viral load, age, temperature, bleeding, jaundice, dyspnea, dysphagia, and time-to-presentation) and several fallback models for when these variables are unavailable. All were externally validated against two independent datasets and compared to further models including expert observational wellness assessments. Models were incorporated into an app highlighting the signs/symptoms with the largest contribution to prognosis. FINDINGS: The parsimonious model approached the predictive power of observational assessments by experienced clinicians (Area-Under-the-Curve, AUC = 0.70-0.79, accuracy = 0.64-0.74) and maintained its performance across subcohorts with different healthcare seeking behaviors. Age and viral load contributed > 5-fold the weighting of other features and including them in a minimal model had a similar AUC, albeit at the cost of specificity. INTERPRETATION: Clinically guided prognostic models can recapitulate clinical expertise and be useful when such expertise is unavailable. Incorporating these models into mHealth tools may facilitate their interpretation and provide informed access to comprehensive clinical guidelines. FUNDING: Howard Hughes Medical Institute, US National Institutes of Health, Bill & Melinda Gates Foundation, International Medical Corps, UK Department for International Development, and GOAL Global.

Clinical assessment before hepatectomy identifies high-risk patients.

BACKGROUND: Liver resection is associated with significant morbidity, and assessment of risk is an important part of preoperative consultations. Objective methods exist to assess operative risk, including cardiopulmonary exercise testing (CPX). Subjective assessment is also made in clinic, and patients perceived to be high-risk are referred for CPX at our institution. This article addresses clinicians' ability to identify patients with a higher risk of surgical complications after hepatectomy, using selection for CPX as a surrogate marker for increased operative risk. MATERIALS AND METHODS: Prospectively collected data on patients undergoing hepatectomy between February 2008 and November 2013 were retrieved and the cohort divided according to CPX referral. Complications were classified using the Clavien-Dindo system. RESULTS: CPX testing was carried out before 101 of 405 liver resections during the study period. The median age was 72 and 64 in CPX and non-CPX groups, respectively (P < 0.001). The resection size was similar between the groups. No difference was noted for grade III complications between CPX and non-CPX tested-groups; however, 19 (18.8%) and 28 (9.2%) patients suffered grade IV-V complications, respectively (P = 0.009). There was no difference in long-term survival between groups (P = 0.63). CONCLUSIONS: This study attempts to assess clinicians' ability to identify patients at greater risk of complications after hepatectomy. The confirmation that patients identified in this way are at greater risk of grade IV-V complications demonstrates the value of preoperative counseling. High-risk patients do not have worse long-term outcomes suggesting survival is determined by other factors, particularly disease recurrence.

An examination of clinical intuition in risk assessment among acute coronary syndromes patients: observations from a prospective multi-center international observational registry.

BACKGROUND: As there are limited data evaluating "clinical intuition" in risk prediction among acute coronary syndromes (ACS) patients. We evaluated the relationship between perceived and "scored" risk in ACS patients, and their association with care and outcome. METHODS AND RESULTS: Within a prospective multi-center international ACS study from 58 hospitals in Australia, China, India and Russia enrolling patients between May 2009 and February 2011, at least 2 physicians involved in each patient's care estimated the patient's untreated risk, and the change in risk with invasive management. The association between clinical factors and physician perceived risk was assessed with multilevel mixed-effects regression models. Risk underestimation was defined as when physician-predicted risk was lower than GRACE score calculated risk and was used to compare clinical care and 6 month mortality. In total, 1542 patients and 4230 patient-specific physicians' estimates were obtained. By 6 months 48/1542 (3.1%) of patients had died compared with an estimated rate of 2.5% with full treatment. Advanced age, hypotension, tachycardia and ST changes on ECG were associated with increased perceived risk, while female gender was associated with lower perceived risk. Clinician risk underestimation was associated with less guideline therapy and higher 6-month mortality (not underestimated: 10/967 (1.0%) vs. one physician underestimated: 25/429 (5.8%) vs. all physician's underestimated: 13/146 (8.9%), any underestimation vs. no underestimation adjusted OR: 6.0 [95% CI: 2.3-15.5, p<0.001]). CONCLUSIONS: Clinical risk prediction using established risk characteristics is not consistently observed in clinical practice. Studies evaluating the implementation and outcomes associated with objective risk prediction are warranted.

Intuition, insight, and the right hemisphere: Emergence of higher sociocognitive functions.

Intuition is the ability to understand immediately without conscious reasoning and is sometimes explained as a 'gut feeling' about the rightness or wrongness of a person, place, situation, temporal episode or object. In contrast, insight is the capacity to gain accurate and a deep understanding of a problem and it is often associated with movement beyond existing paradigms. Examples include Darwin, Einstein and Freud's theories of natural selection, relativity, or the unconscious; respectively. Many cultures name these concepts and acknowledge their value, and insight is recognized as particularly characteristic of eminent achievements in the arts, sciences and politics. Considerable data suggests that these two concepts are more related than distinct, and that a more distributed intuitive network may feed into a predominately right hemispheric insight-based functional neuronal architecture. The preparation and incubation stages of insight may rely on the incorporation of domain-specific automatized expertise schema associated with intuition. In this manuscript the neural networks associated with intuition and insight are reviewed. Case studies of anomalous subjects with ability-achievement discrepancies are summarized. This theoretical review proposes the prospect that atypical localization of cognitive modules may enhance intuitive and insightful functions and thereby explain individual achievement beyond that expected by conventionally measured intelligence tests. A model and theory of intuition and insight's neuroanatomical basis is proposed which could be used as a starting point for future research and better understanding of the nature of these two distinctly human and highly complex poorly understood abilities.