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BACKGROUND: No standardized, evidence-based surveillance practices exist to guide and optimize recurrence detection in patients with cutaneous melanoma. OBJECTIVE: To determine the most high-yield positive review of systems for signaling recurrence in patients with cutaneous melanoma. METHODS: This retrospective cohort study assessed patients with a history of cutaneous melanoma and compared demographic and clinical characteristics, including a comprehensive review of systems, amongst those who developed recurrence and those who did not. RESULTS: A high-yield positive review of systems associated with cutaneous melanoma recurrence can be remembered using the mnemonic 'ATLAS': Appetite change, Tiredness, Lymph node enlargement, Abdominal pain, and Shortness of breath LIMITATIONS: Retrospective design, limited sample size, and variability in follow up time between recurrent and non-recurrent cohorts. CONCLUSION: Any treating physician using this model may have a greater opportunity to detect recurrent cutaneous melanoma and improve outcomes while limiting cost and morbidity.

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Objective: To examine the effect of digital physical therapy (PT) delivered by mobile application (app) on reducing pain and improving function for people with a variety of musculoskeletal conditions. Design: An observational, longitudinal, retrospective study using survey data collected pre- and postdigital PT to estimate multilevel models with random intercepts for patient episodes. Setting: Privately insured employees participating in app-based PT as an employer health care benefit. Participants: The study sample included 814 participants (N=814) 18 years or older who completed their digital PT program with reported final clinical outcomes between February 2019 (program launch) through December 2020. Mean age of the sample at baseline was 40.9±11.89 years, 47.5% were female, 21% sought care for lower back pain, 16% for shoulders, 15% for knees, and 13% for neck. Interventions: Digital PT consisted of a synchronous video evaluation with a physical therapist followed by a course of PT delivered through a mobile app. Main Outcome Measures: Pain was measured by the visual analog scale from 0 "no pain" to 10 "worst pain imaginable" and physical function by the Patient-Specific Functional Scale on a scale from 0 "completely unable to perform" to 10 "able to perform normally." Results: After controlling for significant demographics, comorbid conditions, adverse symptoms, chronicity, and severity, the results from multilevel random intercept models showed decreased pain (-2.69 points; 95% CI, -2.86 to -2.53; P<.001) and increased physical function (+2.67 points; 95% CI, 2.45-2.89; P<.001) after treatment. Conclusions: Digital PT was associated with clinically meaningful improvements in pain and function among a diverse set of participants. These early data are an encouraging indicator of the clinical benefit of digital PT.

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Treating a patient with traumatic brain injury requires an interdisciplinary approach because of the pervasive, profound and protean manifestations of this condition. In this review, key aspects of the medical history and review of systems will be described in order to highlight how the role of any provider must evolve to become a better patient advocate. Although this review is written from the vantage point of a vision care provider, it is hoped that patients, caregivers and providers will recognize the need for a team approach.

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BACKGROUND: The provision of psychometrically valid patient reported outcomes (PROs) improves patient outcomes and reflects their quality of life. Consequently, ad hoc clinician-generated questionnaires of the past are being replaced by more rigorous instruments. This change, while beneficial, risks the loss/orphaning of decades-long information on difficult to capture/chronically ill populations. The goal of this study was to assess to the quality of data retrieved from these legacy questionnaires. METHODS: Participants included 8563 patients who generated a total of 12,626 hospital admissions over the 2004-2014 study period. Items used to screen for issues related to function, mood, symptoms, and social support among patients with chronic disease were identified in our medical center's patient information questionnaire. Cluster and exploratory factor analyses (EFA) followed by multidimensional item response theory (MIRT) analyses were used to select items that defined factors. Scores were derived with summation and MIRT approaches; inter-factor relationships and relationships of factor scores to assigned diagnostic codes were assessed. Rasch analyses assessed the constructs' measurement properties. RESULTS: Literature review and clinician interviews yielded four hypothesized constructs: psychological distress/wellbeing, symptom burden, social support, and physical function. Rasch analyses showed that, while all had good measurement properties, only one, function, separated individuals well. In exploratory factor analyses (EFA), 11 factors representing depression, respiratory symptoms, musculoskeletal pain, family support, mobility, activities of daily living, alcohol consumption, weight loss, fatigue, neurological disorders, and fear at home were identified. Based on the agreement between EFA and cluster analyses as well as Cronbach's alpha, six domains were retained for analyses. Correlations were strong between activities of daily living and mobility (.84), and moderate between pain and mobility (.37) and psychological distress (.59) Known-group validity was supported from the relationships between factor scores and the relevant diagnostic code assignments (.12 to .20). CONCLUSIONS AND DISCUSSION: Items from ad hoc clinician-generated patient information questionnaires can be aggregated into valid factors that assess supportive care domains among chronically ill patients. However, the binary response options offered by many screening items limit their information content and consequently, as highlighted by Rasch analyses, their ability to meaningfully discriminate trait levels in these populations.

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OBJECTIVES: In Kampo medicine, a traditional medicine pattern(TM1) refers to the complete clinical presentation of the patient at a given moment in time. Candidate herbal formulas are chosen for a chief complaint, and an appropriate formula is determined on the basis of the pattern(TM1) diagnosis. In this study, we demonstrated the importance of accompanying symptoms in diagnosing traditional medicine patterns(TM1). DESIGN: Single centre observational study. SETTING: We analysed data from 524 new patients with a hypersensitivity to cold sensation as their primary diagnosis (mean age 51.6 ± 17.8 years; female ratio 82.1%) who visited the Keio University Hospital Kampo Clinic between 2008 and 2013. MAIN OUTCOME MEASURES: Accompanying symptoms were recorded on the browser-based e-questionnaire system, which contained 128 items. The Japan Society for Oriental Medicine's board certified Kampo specialists diagnosed the traditional medicine patterns(TM1). RESULTS: When participants were classified according to the origin of their cold sensation, there were no differences in their traditional medicine patterns. In contrast, when patients were classified based on the number of accompanying symptoms, a significant difference in the patterns was identified. An increasing number of accompanying symptoms was associated with more frequent qi stagnation and blood stasis pattern(TM1). Patients with a qi stagnation pattern had higher rates of depression and insomnia. In contrast, patients with a blood stasis pattern(TM1), had higher rates of acne, body stiffness, and menstrual abnormality. CONCLUSIONS: Qi stagnation and blood stasis patterns(TM1) are related to a number of different accompanying symptoms in the patients with hypersensitivity to cold sensation.

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We have developed and operated a browser-based questionnaire system for Kampo medicine based on conventional questionnaires and review of systems to reveal implicit Kampo wisdom both in patients' questionnaire data and in some Kampo specialists' examination data. However, the questionnaire data were found to be inaccurate because too many questions were included and cumbersome input steps were required. The purpose of the present study was to solve these problems and to develop a new patient-centered questionnaire system with fewer questions and an easier input method. After analyzing inquiry database from collaborating institutes and hospitals, we deleted, combined, and added questions. We changed the evaluation method of symptoms from a visual analogue scale to a simple staged evaluation, and introduced another method to evaluate the main symptoms in each time of visit using a visual analogue scale. At the same time, a tool for predicting Kampo pattern diagnoses based on the questionnaire data was implemented. We have already started collecting more accurate and reliable data using the new questionnaire system. It is expected to support routine practices and facilitate more precise clinical research on Kampo medicine.

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OBJECTIVE: Early and accurate diagnosis of patients with psychogenic nonepileptic seizures (PNES) leads to appropriate treatment and improves long-term seizure prognosis. However, this is complicated by the need to record seizures to make a definitive diagnosis. Suspicion for PNES can be raised through knowledge that patients with PNES have increased somatic sensitivity and report more positive complaints on review-of-systems questionnaires (RoSQs) than patients with epileptic seizures. If the responses on the RoSQ can differentiate PNES from other seizure types, then these forms could be an early screening tool. METHODS: Our dataset included all patients admitted from January 2006 to June 2016 for video-electroencephalography at UCLA. RoSQs prior to May 2015 were acquired through retrospective chart review (n=405), whereas RoSQs from subsequent patients were acquired prospectively (n=190). Controlling for sex and number of comorbidities, we used binomial regression to compare the total number of symptoms and the frequency of specific symptoms between five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of RoSQs to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and the number of medical comorbidities. RESULTS: On average, patients with PNES or mixed PNES and ES reported more than twice as many symptoms than patients with isolated ES or PSLE (p<0.001). The prospective accuracy to differentiate PNES from ES was not significantly higher than naïve assumption that all patients had ES (76% vs 70%, p>0.1). DISCUSSION: This analysis of RoSQs confirms that patients with PNES with and without comorbid ES report more symptoms on a population level than patients with epilepsy or PSLE. While these differences help describe the population of patients with PNES, the consistency of RoSQ responses was neither accurate nor specific enough to be used solely as an early screening tool for PNES. Our results suggest that the RoSQ may help differentiate PNES from ES only when, based on other information, the pre-test probability of PNES is at least 50%.

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We investigated the utility of a very brief review of system (ROS) questionnaire in differentiating psychogenic nonepileptic seizures (PNES) from epilepsy. In this retrospective study, we investigated all patients with PNES admitted to Jefferson Comprehensive Epilepsy Center from October 2013 through April 2015. Patients with a confirmed diagnosis of PNES or epilepsy based on video-EEG monitoring were included. These were matched with respect to age and sex. All patients had a brief ROS questionnaire in their electronic charts. The questionnaire included 10 general yes/no questions about the presence or absence of any abnormality in body systems. Thirty patients with PNES and 30 patients with epilepsy were investigated. The mean of ROS responses for the presence of any abnormality (±standard deviation) for the PNES group was 2.43 (±1.33) and for the epilepsy group was 1.50 (±0.94) (p=0.01). Cut-off point of three positive ROS was able to differentiate these two conditions from each another (p=0.01; OR: 6, 95% confidence interval: 1.48-24.29). Presence of multiple complaints in the ROS questionnaire argues in favor of PNES compared with epilepsy. This brief and easy to apply ROS questionnaire may be used as a valuable ancillary tool to differentiate PNES from epilepsy during the initial screening visit. This may help prevent the delay in making the diagnosis.

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Patients with refractory epilepsy undergo video-electroencephalography for seizure characterization, among whom approximately 10-30% will be discharged with the diagnosis of psychogenic nonepileptic seizures (PNESs). Clinical PNES predictors have been described but in general are not sensitive or specific. We evaluated whether multiple complaints in a routine review-of-system (ROS) questionnaire could serve as a sensitive and specific marker of PNESs. We performed a retrospective analysis of a standardized ROS questionnaire completed by patients with definite PNESs and epileptic seizures (ESs) diagnosed in our adult epilepsy monitoring unit. A multivariate analysis of covariance (MANCOVA) was used to determine whether groups with PNES and ES differed with respect to the percentage of complaints in the ROS questionnaire. Tenfold cross-validation was used to evaluate the predictive error of a logistic regression classifier for PNES status based on the percentage of positive complaints in the ROS questionnaire. A total of 44 patients were included for analysis. Patients with PNESs had a significantly higher number of complaints in the ROS questionnaire compared to patients with epilepsy. A threshold of 17% positive complaints achieved a 78% specificity and 85% sensitivity for discriminating between PNESs and ESs. We conclude that the routine ROS questionnaire may be a sensitive and specific predictive tool for discriminating between PNESs and ESs.

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Owing to lack of standardization for eliciting patient symptoms, the limited time available during clinical encounters, and the often-competing priorities of patients and providers, providers may not appreciate the full spectrum of the patient's symptom experience. Using electronically collected patient-reported outcomes to capture the review of system outside of the clinic visit may not only improve the efficiency, completeness, and accuracy of data collection for the review of system, but also provide the opportunity to operationalize incorporating the patient's voice into the electronic health record. While the necessary technology is already available, multiple stakeholders, including electronic health record vendors, clinicians, researchers, and professional societies, need to align their interests before this can become a widespread reality.

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