14 research outputs found

    Fatal intoxication with naftidrofuryl

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    A 52-year-old man was found dead in his bed. He had financial and psychosocial problems like separation from his wife and children or unemployment due to alcoholism. Under treatment of disulfiram he was presently abstinent from alcohol. As he had suffered from epileptic seizures and dizziness, he received valproic acid and the vasodilator naftidrofuryl, respectively. Autopsy showed no morphologic cause of death. Chemical analysis of blood revealed concentrations for valproic acid and disulfiram in the therapeutic and above the therapeutic range but far below the lethal level, respectively. No ethanol was found. However, the very high concentration of 7500 μg/L naftidrofuryl in whole blood was considered as cause of death, and the most probable manner of death seemed to be suicide. To our knowledge, this is the first reported case of a fatal poisoning with naftidrofuryl

    Patient Experience in Virtual Visits Hinges on Technology and the Patient-Clinician Relationship: A Large Survey Study With Open-ended Questions

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    BackgroundPatient satisfaction with in-person medical visits includes patient-clinician engagement. However, communication, empathy, and other relationship-centered care measures in virtual visits have not been adequately investigated. ObjectiveThis study aims to comprehensively consider patient experience, including relationship-centered care measures, to assess patient satisfaction during virtual visits. MethodsWe conducted a large survey study with open-ended questions to comprehensively assess patients’ experiences with virtual visits in a diverse patient population. Adults with a virtual visit between June 21, 2017, and July 12, 2017, were invited to complete a survey of 21 Likert-scale items and textboxes for comments following their visit. Factor analysis of the survey items revealed three factors: experience with technology, patient-clinician engagement, and overall satisfaction. Multivariable logistic regression was used to test the associations among the three factors and patient demographics, clinician type, and prior relationship with the clinician. Using qualitative framework analysis, we identified recurrent themes in survey comments, quantitatively coded comments, and computed descriptive statistics of the coded comments. ResultsA total of 65.7% (426/648) of the patients completed the survey; 64.1% (273/426) of the respondents were women, and the average age was 46 (range 18-86) years. The sample was geographically diverse: 70.2% (299/426) from Ohio, 6.8% (29/426) from Florida, 4.2% (18/426) from Pennsylvania, and 18.7% (80/426) from other states. With regard to insurance coverage, 57.5% (245/426) were undetermined, 23.7% (101/426) had the hospital’s employee health insurance, and 18.7% (80/426) had other private insurance. Types of virtual visits and clinicians varied. Overall, 58.4% (249/426) of patients had an on-demand visit, whereas 41.5% (177/426) had a scheduled visit. A total of 41.8% (178/426) of patients had a virtual visit with a family physician, 20.9% (89/426) with an advanced practice provider, and the rest had a visit with a specialist. Most patients (393/423, 92.9%) agreed that their virtual visit clinician was interested in them as a person, and their virtual visit made it easy to get the care they needed (383/421, 90.9%). A total of 81.9% (344/420) of respondents agreed or strongly agreed that their virtual visit was as good as an in-person visit by a clinician. Having a prior relationship with their virtual visit clinician was associated with less comfort and ease with virtual technology among patients (odds ratio 0.58, 95% CI 0.35-0.98). In terms of technology, patients found the interface easy to use (392/423, 92.7%) and felt comfortable using it (401/423, 94.8%). Technical difficulties were associated with lower odds of overall satisfaction (odds ratio 0.46, 95% CI 0.28-0.76). ConclusionsPatient-clinician engagement in virtual visits was comparable with in-person visits. This study supports the value and acceptance of virtual visits. Evaluations of virtual visits should include assessments of technology and patient-clinician engagement, as both are likely to influence patient satisfaction

    Computerised cognitive assessment in patients with traumatic brain injury:an observational study of feasibility and sensitivity relative to established clinical scales

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    Background: Online technology could potentially revolutionise how patients are cognitively assessed and monitored. However, it remains unclear whether assessments conducted remotely can match established pen-and-paper neuropsychological tests in terms of sensitivity and specificity. Methods: This observational study aimed to optimise an online cognitive assessment for use in traumatic brain injury (TBI) clinics. The tertiary referral clinic in which this tool has been clinically implemented typically sees patients a minimum of 6 months post-injury in the chronic phase. Between March and August 2019, we conducted a cross-group, cross-device and factor analyses at the St. Mary's Hospital TBI clinic and major trauma wards at Imperial College NHS trust and St. George's Hospital in London (UK), to identify a battery of tasks that assess aspects of cognition affected by TBI. Between September 2019 and February 2020, we evaluated the online battery against standard face-to-face neuropsychological tests at the Imperial College London research centre. Canonical Correlation Analysis (CCA) determined the shared variance between the online battery and standard neuropsychological tests. Finally, between October 2020 and December 2021, the tests were integrated into a framework that automatically generates a results report where patients’ performance is compared to a large normative dataset. We piloted this as a practical tool to be used under supervised and unsupervised conditions at the St. Mary's Hospital TBI clinic in London (UK). Findings: The online assessment discriminated processing-speed, visual-attention, working-memory, and executive-function deficits in TBI. CCA identified two significant modes indicating shared variance with standard neuropsychological tests (r = 0.86, p &lt; 0.001 and r = 0.81, p = 0.02). Sensitivity to cognitive deficits after TBI was evident in the TBI clinic setting under supervised and unsupervised conditions (F (15,555) = 3.99; p &lt; 0.001). Interpretation: Online cognitive assessment of TBI patients is feasible, sensitive, and efficient. When combined with normative sociodemographic models and autogenerated reports, it has the potential to transform cognitive assessment in the healthcare setting. Funding: This work was funded by a National Institute for Health Research (NIHR) Invention for Innovation (i4i) grant awarded to DJS and AH ( II-LB-0715-20006).</p

    Computerised cognitive assessment in patients with traumatic brain injury: an observational study of feasibility and sensitivity relative to established clinical scalesResearch in context

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    Summary: Background: Online technology could potentially revolutionise how patients are cognitively assessed and monitored. However, it remains unclear whether assessments conducted remotely can match established pen-and-paper neuropsychological tests in terms of sensitivity and specificity. Methods: This observational study aimed to optimise an online cognitive assessment for use in traumatic brain injury (TBI) clinics. The tertiary referral clinic in which this tool has been clinically implemented typically sees patients a minimum of 6 months post-injury in the chronic phase. Between March and August 2019, we conducted a cross-group, cross-device and factor analyses at the St. Mary’s Hospital TBI clinic and major trauma wards at Imperial College NHS trust and St. George’s Hospital in London (UK), to identify a battery of tasks that assess aspects of cognition affected by TBI. Between September 2019 and February 2020, we evaluated the online battery against standard face-to-face neuropsychological tests at the Imperial College London research centre. Canonical Correlation Analysis (CCA) determined the shared variance between the online battery and standard neuropsychological tests. Finally, between October 2020 and December 2021, the tests were integrated into a framework that automatically generates a results report where patients’ performance is compared to a large normative dataset. We piloted this as a practical tool to be used under supervised and unsupervised conditions at the St. Mary’s Hospital TBI clinic in London (UK). Findings: The online assessment discriminated processing-speed, visual-attention, working-memory, and executive-function deficits in TBI. CCA identified two significant modes indicating shared variance with standard neuropsychological tests (r = 0.86, p < 0.001 and r = 0.81, p = 0.02). Sensitivity to cognitive deficits after TBI was evident in the TBI clinic setting under supervised and unsupervised conditions (F (15,555) = 3.99; p < 0.001). Interpretation: Online cognitive assessment of TBI patients is feasible, sensitive, and efficient. When combined with normative sociodemographic models and autogenerated reports, it has the potential to transform cognitive assessment in the healthcare setting. Funding: This work was funded by a National Institute for Health Research (NIHR) Invention for Innovation (i4i) grant awarded to DJS and AH (II-LB-0715-20006)
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