Understanding Barriers and Facilitators to Signing Up for a Mobile-Responsive Registry to Recruit Healthy Volunteers and Members of Underrepresented Communities for Alzheimer's Disease Prevention Studies

BACKGROUND

Alzheimer's disease (AD) disproportionately affects Black/African American and Hispanic/Latino adults, yet they are underrepresented in AD studies. Recruitment challenges for these populations limit generalizability of findings.

OBJECTIVES

This study explores barriers and facilitators to signing up for an AD participant recruitment registry website intended to optimize recruitment of these adults. The registry is geared toward recruitment on smartphones and tablets (mobile devices), as research suggests that mobile-first approaches may be more successful within these populations.

DESIGN

In 2020, we conducted four focus groups (n = 39) and an online survey (n = 1010) with Black/African American and Hispanic/Latino adults. The survey also included Whites as a comparison group.

SETTING

Focus groups were in-person at research facilities in New Orleans, Louisiana, and Los Angeles, California. The online survey was distributed by a survey panel company to participants nationwide.

PARTICIPANTS

Black/African American (n = 360), Hispanic/Latino (n = 359), or White (n = 330) individuals, 45-75 years old, who self-reported not having mild cognitive impairment (MCI), dementia, or AD.

MEASUREMENTS

Barriers and facilitators explored in the focus groups and survey were related to health and AD (e.g., AD-related concerns and past participation/willingness to participate in health or AD studies); current use of mobile devices (e.g., comfort using devices and receptivity to the AD recruitment registry); and participant characteristics and beliefs (e.g., demographics, health literacy level, and trust in government and the scientific community).

RESULTS

The focus groups and survey revealed similar findings. Participants commonly use mobile devices to go online and perform health-related activities. They were aware of AD, expressed concerns with developing it, and were willing to participate in AD-related studies (motivated by personal connection to AD, altruism, and compensation). When presented with the AD recruitment registry, most provided positive feedback (e.g., easy to use and informative) and shared an interest in joining. Barriers to joining the registry with a mobile device included complex or multistep enrollment processes, beliefs that studies are primarily for those with a specific disease, and confusion about how studies can prevent AD among those low-risk for AD. The focus groups also revealed that Black/African American participants expressed more hesitation than Hispanic/Latinos in joining the registry due to greater distrust in the government and scientific community.

CONCLUSIONS

Recruiting more Black/African American and Hispanic/Latino participants into AD studies is vitally important. This mixed methods study suggests that adults in these underrepresented groups are motivated to prevent AD and willing to sign up for an AD participant recruitment registry using mobile devices. Most barriers to joining a registry can be addressed through slight modifications to the registry's design and functionality and by adding content. These findings can help enhance the appeal of joining AD recruitment registries to ultimately enroll more diverse, representative groups of participants and increase the generalizability of AD study findings.

Automated left ventricular dimension assessment using artificial intelligence

Background and purpose

Artificial intelligence (AI) has the potential to greatly improve efficiency and reproducibility of quantification in echocardiography, but to gain widespread use it must both meet expert standards of excellence and have a transparent methodology. We developed an online platform to enable multiple collaborators to annotate medical images for training and validating neural networks.

Methods

Using our online collaborative platform 9 expert echocardiographers labelled 2056 images that comprised the training dataset. They labelled the four points from where the standard parasternal long axis (PLAX) measurements (interventricular septum, posterior wall, left ventricular dimension) would be made. Using these labelled images we trained a 2d convolutional neural network to replicate these labels. Separately, we curated an external validation dataset of the systolic and diastolic frames of 100 PLAX acquisitions. Each of these images were labelled twice by 13 different experts, and the average of the 26 measurements was taken as the consensus standard.

We then compared the individual experts and the AI measurements on the external validation dataset to the consensus standard, and calculated the precision standard deviation (SD) of the signed differences from the consensus standard.

Results

For diastolic septum thickness, the AI had a precision SD of 1.8 mm (ICC 0.81; 95% CI 0.73 to 0.97), compared with 2.0 mm for the individual experts (ICC 0.64; 95% CI 0.57 to 0.72). For diastolic posterior wall thickness, the AI had a precision SD 1.4 mm (ICC 0.54; 95% CI 0.38 to 0.66), and the individual experts 2.2 mm (ICC 0.37; 95% CI 0.29 to 0.46).

The AI's precision SD for left ventricular internal dimension was 3.5 mm (ICC 0.93, 95% CI 0.90 to 0.94), and for individual experts was 4.4mm (ICC 0.82, 95% CI 0.78 to 0.95). Both the experts and AI performed better in diastole than systole (precision SD AI 2.5mm vs 4.3mm, p<0.0001; experts 3.3mm vs 5.3mm, p<0.0001).

Conclusions

AI trained by a group of echocardiography experts was able to perform PLAX measurements which matched the reference standard more closely than any individual expert's own measurements.

This open, collaborative approach may be a model for the development of AI that is explainable to, and trusted by clinicians.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIHR Imperil BRC ITMATDr Howard was additionally funded by Wellcome. Online collaborative platformResults of AI and experts

Fully automated global longitudinal strain assessment using artificial intelligence developed and validated by a UK-wide echocardiography expert collaborative

Background

Left ventricular longitudinal strain has been reported to deliver reproducibility, sensitivity and prognostic value over and above ejection fraction. However, it currently relies on uninspectable proprietary algorithms and suffers from a lack of widespread clinical use. Uptake may be improved by increasing user trust through greater transparency.

Purpose

We therefore developed a machine-learning based method, trained, and validated with accredited experts from our AI Echocardiography Collaborative. We make the dataset, code, and trained network freely available under an open-source license.

Methods

AI enables strain to be calculated without relying on speckle tracking by directly locating key points and borders across frames. Strain can then be calculated as the fractional shortening of the left ventricular perimeter. We first curated a dataset of 7523 images, including 2587 apical four chamber, each labelled by a single expert from our collaboration of 17 hospitals, using our online platform (Figure 1). Using both this dataset and a semi-supervised approach, we trained a 3d convolutional neural network to identify the annulus, apex, and the endocardial border throughout the cardiac cycle.

Separately, we constructed an external validation dataset of 100 apical 4 chamber video-loops. The systolic and diastolic frame were identified, and each image was separately labelled by 11 experts. From these labels we then derived the expert consensus strain for each of the 100 video loops. These experts also ordered all 100 echocardiograms by their visual grading of left ventricular longitudinal function. Finally, a single expert calculated strain using two different proprietary commercial packages (A and B).

Results

Consensus strain measurements (obtained by averaging individual assessments by the 11 experts) across the 100 cases ranged from −4% to −27%, with strong correlations with the individual experts and machine methods (Figure 2). Using each cases' consensus across experts as the gold standard, median error from consensus was 3.1% for individual experts, 3.4% for Propriety A, 2.6% for Proprietary B, 2.6% for our AI.

Using the visual grading of longitudinal strain as the reference, the 11 individual experts and 4 machine methods each showed significant correlation: coefficients ranged from 0.55 to 0.69 for experts, and for Proprietary A was 0.68, Proprietary B 0.69, and our AI 0.69.

Conclusions

Our open-source, vendor-independent AI-based strain measure automatically produces values that agree with expert consensus, as strongly as the individual experts do. It also agrees with the subjective visual ranking by longitudinal function. Our open-source AI strain performs at least as well as closed-source speckle-based approaches, and may enable increased clinical and research use of longitudinal strain.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIHR Imperial BRC ITMAT.Dr Howard was additionally funded by Wellcome. Figure 1. Collaborative online platformFigure 2. Correlations between strain methods

The role of backbone conformational heat capacity in protein stability: temperature dependent dynamics of the B1 domain of Streptococcal protein G

The contributions of backbone NH group dynamics to the conformational heat capacity of the B1 domain of Streptococcal protein G have been estimated from the temperature dependence of 15N NMR-derived order parameters. Longitudinal (R1) and transverse (R2) relaxation rates, transverse cross-relaxation rates (eta(xy)), and steady state [1H]-15N nuclear Overhauser effects were measured at temperatures of 0, 10, 20, 30, 40, and 50 degrees C for 89-100% of the backbone secondary amide nitrogen nuclei in the B1 domain. The ratio R2/eta(xy) was used to identify nuclei for which conformational exchange makes a significant contribution to R2. Relaxation data were fit to the extended model-free dynamics formalism, incorporating an axially symmetric molecular rotational diffusion tensor. The temperature dependence of the order parameter (S2) was used to calculate the contribution of each NH group to conformational heat capacity (Cp) and a characteristic temperature (T*), representing the density of conformational energy states accessible to each NH group. The heat capacities of the secondary structure regions of the B1 domain are significantly higher than those of comparable regions of other proteins, whereas the heat capacities of less structured regions are similar to those in other proteins. The higher local heat capacities are estimated to contribute up to approximately 0.8 kJ/mol K to the total heat capacity of the B1 domain, without which the denaturation temperature would be approximately 9 degrees C lower (78 degrees C rather than 87 degrees C). Thus, variation of backbone conformational heat capacity of native proteins may be a novel mechanism that contributes to high temperature stabilization of proteins.

Zinc diffusion through lipid bilayers

Zinc diffusion across liposome bilayers was measured for a set of phosphatidylcholines. These lipids were sonicated to form small unilamellar vesicles in the presence of the metallochromic indicator antipyrylazo III. This chelator sequentially forms two complexes with zinc ion. The rate constant for the first complex formation is shown to increase linearly with zinc concentration. The slope of this line, a [Zn2+]-independent, second-order rate constant, varies with changes in phosphatidylcholine properties. The rate constant is little affected by changes in fluidity as estimated from the reduced temperature [Tr = (Texperimental-Tc)/Tc]. In contrast, the rate constant is directly dependent on lipid oxidation as measured by either a thiobarbituric acid test or a spectrophotometric determination of conjugate dienes. We estimate that zinc diffusion stimulated by lipid oxidation can approach rates observed in hepatocyte zinc transport.

Therapy for paraneoplastic neurologic syndromes in six patients with protein A column immunoadsorption

BACKGROUND

Paraneoplastic neurologic syndromes, although rare, cause significant morbidity and mortality. They are thought to be immunologically mediated, but to date those involving the central nervous system (CNS) have not been particularly responsive to immunologic therapy. The use of the novel immunomodulator, protein A immunoadsorption, was explored to address this question.

METHODS

Six patients with neurologic paraneoplastic syndromes were treated with this technique, using the "off line" method. Two hundred fifty ml of plasma was perfused through a column containing protein A covalently attached to a silica matrix. The plasma was then returned to the patient.

RESULTS

Five of the patients responded to the therapy, with complete and durable responses in three patients with opsoclonus-myoclonus, objective, though transient, improvement in one patient with paraneoplastic brainstem encephalitis associated with a Merkel cell tumor, and stabilization and partial improvement in one patient with paraneoplastic limbic encephalitis. The patient without response developed a cutaneous vasculitis after the second treatment, and therapy was discontinued.

CONCLUSIONS

This therapy appears beneficial for a number of paraneoplastic syndromes, most dramatically in the opsoclonus/myoclonus syndrome.

Campylobacter laridis causing bacteremia in an immunosuppressed patient

An unusual species, Campylobacter laridis , belonging to the group of nalidixic acid resistant thermophilic Campylobacter species, was isolated from the blood of a 71-year-old man with multiple myeloma, hyperviscosity syndrome, and renal failure. The organism was first recognized in the laboratory by gram-stain reaction and resistance to nalidixic acid. The organism differs from C. jejuni and C. coli by its resistance to nalidixic acid, whereas anaerobic growth in the presence of trimethylamine N-oxide hydrochloride differentiates this organism from other Campylobacter species. Biochemical characterization and DNA homology studies confirmed the identity of this species as being C. laridis . To our knowledge, this is the first recorded case of bacteremia due to C. laridis in humans.