Cognitive Digital Biomarkers from Automated Transcription of Spoken Language.

BACKGROUND: Although patients with Alzheimer's disease and other cognitive-related neurodegenerative disorders may benefit from early detection, development of a reliable diagnostic test has remained elusive. The penetration of digital voice-recording technologies and multiple cognitive processes deployed when constructing spoken responses might offer an opportunity to predict cognitive status. OBJECTIVE: To determine whether cognitive status might be predicted from voice recordings of neuropsychological testing. DESIGN: Comparison of acoustic and (para)linguistic variables from low-quality automated transcriptions of neuropsychological testing (n = 200) versus variables from high-quality manual transcriptions (n = 127). We trained a logistic regression classifier to predict cognitive status, which was tested against actual diagnoses. SETTING: Observational cohort study. PARTICIPANTS: 146 participants in the Framingham Heart Study. MEASUREMENTS: Acoustic and either paralinguistic variables (e.g., speaking time) from automated transcriptions or linguistic variables (e.g., phrase complexity) from manual transcriptions. RESULTS: Models based on demographic features alone were not robust (area under the receiver-operator characteristic curve [AUROC] 0.60). Addition of clinical and standard acoustic features boosted the AUROC to 0.81. Additional inclusion of transcription-related features yielded an AUROC of 0.90. CONCLUSIONS: The use of voice-based digital biomarkers derived from automated processing methods, combined with standard patient screening, might constitute a scalable way to enable early detection of dementia.

Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.

The Better Understanding the Metamorphosis of Pregnancy (BUMP) study is a longitudinal feasibility study aimed to gain a deeper understanding of the pre-pregnancy and pregnancy symptom experience using digital tools. The present paper describes the protocol for the BUMP study. Over 1000 participants are being recruited through a patient provider-platform and through other channels in the United States (US). Participants in a preconception cohort (BUMP-C) are followed for 6 months, or until conception, while participants in a pregnancy cohort (BUMP) are followed into their fourth trimester. Participants are provided with a smart ring, a smartwatch (BUMP only), and a smart scale (BUMP only) alongside cohort-specific study apps. Participant centric engagement strategies are used that aim to co-design the digital approach with participants while providing knowledge and support. The BUMP study is intended to lay the foundational work for a larger study to determine whether participant co-designed digital tools can be used to detect, track and return multimodal symptoms during the perinatal window to inform individual level symptom trajectories.

Digital intervention increases influenza vaccination rates for people with diabetes in a decentralized randomized trial.

People with diabetes (PWD) have an increased risk of developing influenza-related complications, including pneumonia, abnormal glycemic events, and hospitalization. Annual influenza vaccination is recommended for PWD, but vaccination rates are suboptimal. The study aimed to increase influenza vaccination rate in people with self-reported diabetes. This study was a prospective, 1:1 randomized controlled trial of a 6-month Digital Diabetes Intervention in U.S. adults with diabetes. The intervention group received monthly messages through an online health platform. The control group received no intervention. Difference in self-reported vaccination rates was tested using multivariable logistic regression controlling for demographics and comorbidities. The study was registered at clinicaltrials.gov: NCT03870997. A total of 10,429 participants reported influenza vaccination status (5158 intervention, mean age (±SD) = 46.8 (11.1), 78.5% female; 5271 control, Mean age (±SD) = 46.7 (11.2), 79.4% female). After a 6-month intervention, 64.2% of the intervention arm reported influenza vaccination, vers us 61.1% in the control arm (diff = 3.1, RR = 1.05, 95% CI [1.02, 1.08], p = 0.0013, number needed to treat = 33 to obtain 1 additional vaccination). Completion of one or more intervention messages was associated with up to an 8% increase in vaccination rate (OR 1.27, 95% CI [1.17, 1.38], p < 0.0001). The intervention improved influenza vaccination rates in PWD, suggesting that leveraging new technology to deliver knowledge and information can improve influenza vaccination rates in high-risk populations to reduce public health burden of influenza. Rapid cycle innovation could maximize the effects of these digital interventions in the future with other populations and vaccines.

Transcontinental consults in surgical pathology via the Internet.

An efficient and inexpensive electronic system to submit surgical pathology cases in consultation via the Internet is presented. A transcontinental pilot study showed a high degree of concordance between the diagnosis provided by the consultant on the basis of the pathology images and that given after examining the corresponding microscopic slides.