Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

Can Artificail Entities Assert?

There is an existing debate regarding the view that technological instruments, devices, or machines can assert ‎or testify. A standard view in epistemology is that only humans can testify. However, the notion of quasi-‎testimony acknowledges that technological devices can assert or testify under some conditions, without ‎denying that humans and machines are not the same. Indeed, there are four relevant differences between ‎humans and instruments. First, unlike humans, machine assertion is not imaginative or playful. Second, ‎machine assertion is prescripted and context restricted. As such, computers currently cannot easily switch ‎contexts or make meaningful relevant assertions in contexts for which they were not programmed. Third, ‎while both humans and computers make errors, they do so in different ways. Computers are very sensitive to ‎small errors in input, which may cause them to make big errors in output. Moreover, automatic error control ‎is based on finding irregularities in data without trying to establish whether they make sense. Fourth, ‎testimony is produced by a human with moral worth, while quasi-testimony is not. Ultimately, the notion of ‎quasi-testimony can serve as a bridge between different philosophical fields that deal with instruments and ‎testimony as sources of knowledge, allowing them to converse and agree on a shared description of reality, ‎while maintaining their distinct conceptions and ontological commitments about knowledge, humans, and ‎nonhumans.

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 324)

This bibliography lists 200 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during May, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Role of N-methyl-D-aspartate receptors in action-based predictive coding deficits in schizophrenia

Published in final edited form as:Biol Psychiatry. 2017 March 15; 81(6): 514–524. doi:10.1016/j.biopsych.2016.06.019.BACKGROUND: Recent theoretical models of schizophrenia posit that dysfunction of the neural mechanisms subserving predictive coding contributes to symptoms and cognitive deficits, and this dysfunction is further posited to result from N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction. Previously, by examining auditory cortical responses to self-generated speech sounds, we demonstrated that predictive coding during vocalization is disrupted in schizophrenia. To test the hypothesized contribution of NMDAR hypofunction to this disruption, we examined the effects of the NMDAR antagonist, ketamine, on predictive coding during vocalization in healthy volunteers and compared them with the effects of schizophrenia. METHODS: In two separate studies, the N1 component of the event-related potential elicited by speech sounds during vocalization (talk) and passive playback (listen) were compared to assess the degree of N1 suppression during vocalization, a putative measure of auditory predictive coding. In the crossover study, 31 healthy volunteers completed two randomly ordered test days, a saline day and a ketamine day. Event-related potentials during the talk/listen task were obtained before infusion and during infusion on both days, and N1 amplitudes were compared across days. In the case-control study, N1 amplitudes from 34 schizophrenia patients and 33 healthy control volunteers were compared. RESULTS: N1 suppression to self-produced vocalizations was significantly and similarly diminished by ketamine (Cohen’s d = 1.14) and schizophrenia (Cohen’s d = .85). CONCLUSIONS: Disruption of NMDARs causes dysfunction in predictive coding during vocalization in a manner similar to the dysfunction observed in schizophrenia patients, consistent with the theorized contribution of NMDAR hypofunction to predictive coding deficits in schizophrenia.This work was supported by AstraZeneca for an investigator-initiated study (DHM) and the National Institute of Mental Health Grant Nos. R01 MH-58262 (to JMF) and T32 MH089920 (to NSK). JHK was supported by the Yale Center for Clinical Investigation Grant No. UL1RR024139 and the US National Institute on Alcohol Abuse and Alcoholism Grant No. P50AA012879. (AstraZeneca for an investigator-initiated study (DHM); R01 MH-58262 - National Institute of Mental Health; T32 MH089920 - National Institute of Mental Health; UL1RR024139 - Yale Center for Clinical Investigation; P50AA012879 - US National Institute on Alcohol Abuse and Alcoholism)Accepted manuscrip

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

Transient neurological symptoms in the older population:report of a prospective cohort study--the Medical Research Council Cognitive Function and Ageing Study (CFAS)

Transient ischaemic attack (TIA) is a recognised risk factor for stroke in the older population requiring timely assessment and treatment by a specialist. The need for such TIA services is driven by the epidemiology of transient neurological symptoms, which may not be caused by TIA. We report prevalence and incidence of transient neurological symptoms in a large UK cohort study of older people

Thoughts about disordered thinking: measuring and quantifying the laws of order and disorder

Peer ReviewedPostprint (author's final draft