American Society for Reproductive Medicine

ImportanceConsumer wearable technologies have wide applications, including some that have US Food and Drug Administration clearance for health-related notifications. While wearable technologies may have premarket testing, validation, and safety evaluation as part of a regulatory authorization process, information on their postmarket use remains limited. The Stanford Center for Digital Health organized 2 pan-stakeholder think tank meetings to develop an organizing concept for empirical research on the postmarket evaluation of consumer-facing wearables.ObservationsThe postmarket evaluation of consumer wearables involves broad consideration of an individual consumer’s journey from acquisition, intended and unintended use of the wearable, and access to health care resources on receipt of a notification. For individuals who do access the health care system, a wearable’s downstream effects can be studied through appropriate clinical evaluation, delivery of guideline-directed treatments, shared decision-making in areas of clinical equipoise, and analysis of clinical end points and patient harms. Effective postmarket research draws from denominators appropriate to the clinical question, with clearly defined parameters for success and failure. Generalizability related to data completeness and reliability should also be considered. As patients increasingly integrate wearables into their health monitoring, cross-platform data sharing with a focus on privacy and data quality can drive patient-centered innovation and identify opportunities to bridge gaps in medical care.RelevanceThe think tank identified priorities in postmarket research, comprising the journey from consumer to patient and accounting for patient, clinician, health care delivery system, and societal impacts of consumer wearables. Overall, this approach serves not only to organize the study of consumer wearables but also to act as a guidepost for using real-world data in postmarket research.

Abstract This article examines the first occupation of Boston (1768-1770) through the writings of Boston’s night watch. The arrival of a competing police power unsettled regular systems of policing and governance and transformed the customary duties of Boston’s night watch, remaking familiar spaces like the streets themselves.

Atrial fibrillation (AF) is increasingly diagnosed early, close to its first occurrence due to: (i) increased public awareness with self-screening; (ii) health care initiatives including population screening and opportunistic case finding; and (iii) increased use and surveillance of implantable cardiac devices. At its onset, AF is often low burden, and cardiovascular co-morbidities may be absent or at an early stage. Thus, the management of recent-onset AF has become an issue of growing importance. Professional guidelines have traditionally focused on anticoagulant thromboprophylaxis, generally recommending a cautious approach to rhythm control, and priority has been given to rate control to alleviate symptoms. In recent guidelines, the importance of managing lifestyle and co-morbidities has increased. The AF-SCREEN collaboration proposes that a vigorous approach to active management of recent-onset AF may be warranted. This includes addressing co-morbidities and promoting healthy lifestyles to prevent the emergence or progression of AF and associated cardiovascular disease, as well as the initiation of active rhythm control ± anticoagulation to prevent AF-related morbidity and mortality, including stroke and heart failure (HF). Intuitively, intervention early after AF onset would be beneficial since lifestyle and co-morbidity management, plus rhythm control and anticoagulation, are important contributors to improved outcomes in patients with established AF, but robust evidence is lacking for recent-onset AF. There is a delicate balance between achieving favourable outcomes such as preventing strokes, HF and AF progression vs the complications and potential adverse effects of interventions. Given the serious long-term consequences, innovative approaches are necessary to determine the value and risks of initiating active therapy very early in the course of AF. More data are needed to guide the best management of recent-onset AF, bearing AF burden in mind. Long-term studies using large national databases linked to electronic medical records and rhythm monitoring devices offer excellent opportunities. Shorter-term studies focusing on reducing AF burden to slow AF progression and studies focusing on outcomes such as HF could be used in both randomized clinical trials and observational cohort studies.

In contemporary society, socially active women are increasingly planning their fertility for later in life. The fertility outcomes for advanced-age patients, even with egg donation, are often suboptimal due to endometrial aging. Recurrent implantation failure (RIF) is one of the core problems for assisted reproductive technology (ART), especially for advanced-age patients. High-quality, euploid embryos and synchronization between the embryonic stage and the uterine endometrial lining are crucial for positive outcomes. The study aims to improve ART outcomes with personalized embryo transfer (pET) according to endometrial receptivity analysis (ERA) in advanced-age patients with challenging reproductive histories, and RIF by utilizing, donor oocytes andpreimplantation genetic testing for aneuploidy (PGT-A) for embryo testing. A randomized, controlled observational follow-up study was conducted from2020 to 2023. After obtaining informed consent, 320 patients with RIF were selected. Patients were allocated into the study group and control group 1 based on consistent application of randomization principles, while control group 2 was selected separately. The study group included patients undergoing PGT-A and ERA, aged 35-45 years, with a mean age of 40.5±3.7 years. Control group 1 comprised patients undergoing PGT-A, aged 35-45 years, with a mean age of 40±4.2 years. Control group 2 consisted of patients undergoing PGT-A and ERA, aged less than 35 years, with a mean age of 31.6±2.2 years. Results suggestthat ERA may improve implantation and pregnancy outcomes in advanced-age patients, particularly those withRIFs. The pregnancy rate was significantly higher in the study group (77.9%), compared to control group 1 (57.6%) (p=0.0007), and no significant difference compared to control group 2(77.3%) (p=0.94). The implantation rate was higher in the study group (54.1%) than in control group 1 (39.4%) (p=0.0009), and there wasno significant difference between the study group and control group 2(50%, p=0.87). The live birth rate was also higher in the study group (71.3%), compared to control group 1 (39.4%) (p<0.0001). There were no significant differences between the study group and control group 2 (65.9%, p=0.50). pETguided by ERAsignificantly improves pregnancy, implantation, and live birth rates in advanced-age patients with challenging reproductive histories. pET providesART outcomes with no significant difference between advanced-age patients and younger patients with pET guided by ERA.

An app‐based clinical trial enrolment process can contribute to duplicated records, carrying data management implications. Our objective was to identify duplicated records in real time in the Apple Heart Study (AHS). We leveraged personal identifiable information (PII) to develop a dissimilarity score (DS) using the Damerau–Levenshtein distance. For computational efficiency, we focused on four types of records at the highest risk of duplication. We used the receiver operating curve (ROC) and resampling methods to derive and validate a decision rule to classify duplicated records. We identified 16,398 (4%) duplicated participants, resulting in 419,297 unique participants out of a total of 438,435 possible. Our decision rule yielded a high positive predictive value (96%) with negligible impact on the trial's original findings. Our findings provide principled solutions for future digital trials. When establishing deduplication procedures for digital trials, we recommend collecting device identifiers in addition to participant identifiers; collecting and ensuring secure access to PII; conducting a pilot study to identify reasons for duplicated records; establishing an initial deduplication algorithm that can be refined; creating a data quality plan that informs refinement; and embedding the initial deduplication algorithm in the enrolment platform to ensure unique enrolment and linkage to previous records.