Case Report A Case Study of Intractable Vomiting with Final Diagnosis of Neuromyelitis Optica

This case study presents a patient living in a suburban/rural community who received appropriate referral to secondary and tertiary care for nausea and vomiting, accompanied by waxing and waning neurological symptoms, yet proved difficult to diagnose. This patient is presented to draw attention to a rare neurological disorder which should be included in the differential diagnosis of nausea and vomiting with some key neurological complaints, even in the absence of physical findings

Decision or No Decision: How Do Patient–Physician Interactions End and What Matters?

BACKGROUND: A clearly stated clinical decision can induce a cognitive closure in patients and is an important investment in the end of patient–physician communications. Little is known about how often explicit decisions are made in primary care visits. OBJECTIVE: To use an innovative videotape analysis approach to assess physicians’ propensity to state decisions explicitly, and to examine the factors influencing decision patterns. DESIGN: We coded topics discussed in 395 videotapes of primary care visits, noting the number of instances and the length of discussions on each topic, and how discussions ended. A regression analysis tested the relationship between explicit decisions and visit factors such as the nature of topics under discussion, instances of discussion, the amount of time the patient spoke, and competing demands from other topics. RESULTS: About 77% of topics ended with explicit decisions. Patients spoke for an average of 58 seconds total per topic. Patients spoke more during topics that ended with an explicit decision, (67 seconds), compared with 36 seconds otherwise. The number of instances of a topic was associated with higher odds of having an explicit decision (OR = 1.73, p < 0.01). Increases in the number of topics discussed in visits (OR = 0.95, p < .05), and topics on lifestyle and habits (OR = 0.60, p < .01) were associated with lower odds of explicit decisions. CONCLUSIONS: Although discussions often ended with explicit decisions, there were variations related to the content and dynamics of interactions. We recommend strengthening patients’ voice and developing clinical tools, e.g., an “exit prescription,” to improving decision making

Surface Phenotype and Functionality of WNV Specific T Cells Differ with Age and Disease Severity

West Nile virus (WNV) infection can result in severe neuroinvasive disease, particularly in persons with advanced age. As rodent models demonstrate that T cells play an important role in limiting WNV infection, and strong T cell responses to WNV have been observed in humans, we postulated that inadequate antiviral T cell immunity was involved in neurologic sequelae and the more severe outcomes associated with age. We previously reported the discovery of six HLA-A*0201 restricted WNV peptide epitopes, with the dominant T cell targets in naturally infected individuals being SVG9 (Env) and SLF9 (NS4b). Here, memory phenotype and polyfunctional CD8+ T cell responses to these dominant epitopes were assessed in 40 WNV seropositive patients displaying diverse clinical symptoms. The patients' PBMC were stained with HLA-I multimers loaded with the SVG9 and SLF9 epitopes and analyzed by multicolor flow cytometry. WNV-specific CD8+ T cells were found in peripheral blood several months post infection. The number of WNV-specific T cells in older individuals was the same, if not greater, than in younger members of the cohort. WNV-specific T cells were predominantly monofunctional for CD107a, MIP-1β, TNFα, IL-2, or IFNγ. When CD8+ T cell responses were stratified by disease severity, an increased number of terminally differentiated, memory phenotype (CD45RA+ CD27− CCR7− CD57+) T cells were detected in patients suffering from viral neuroinvasion. In conclusion, T cells of a terminally differentiated/cytolytic profile are associated with neuroinvasion and, regardless of age, monofunctional T cells persist following infection. These data provide the first indication that particular CD8+ T cell phenotypes are associated with disease outcome following WNV infection

An Efficient Method of Identifying Major Depression and Panic Disorder In Primary Care

The research literature is replete with evidence of and concerns about the prevalence and undertreatment of mental disorders in primary care. Although screening, on its own, may not directly affect clinical outcomes, it is still the most efficient and effective way to identify psychologically distressed patients for either research purposes or to provide patients with or refer patients to appropriate care. The current study sought to establish the utility of the MHI-5 for the detection of patients suffering from major depression or panic disorder, two of the most common psychiatric conditions seen in primary care settings. This study was conducted in a family medicine clinic and 246 adult outpatients participated. Patients completed the Mental Health Index-5 (MHI-5) as the screening measure and the PRIME-MD Patient Health Questionnaire (PHQ) as the diagnostic instrument. ROC analyses indicated that a cut-off score of 23 on the MHI-5 yielded a sensitivity of 91% and a specificity of 58% for predicting provisional diagnoses of major depression or panic disorder from the PHQ. Using a single item to screen for a PHQ diagnosis of major depression yielded a sensitivity of 88% and a specificity of 62% and a second question had a sensitivity of 100% and specificity of 63% for PHQ diagnosis of panic disorder. These results indicate that it is possible to use a small number of items to efficiently and effectively screen for mental disorders affecting a significant portion of primary care patients

Critical assessment of automated flow cytometry data analysis techniques

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.