With one in five adults in the United States owning a smartwatch or fitness tracker, these devices are poised to impact all aspects of medicine by offering a more objective approach to replace self-reported data. Oncology has proved to be a prototypical example, and wearables offer immediate benefits to patients and oncologists with the ability to track symptoms and health metrics in real time. We aimed to review the recent literature on consumer-grade wearables and its current applications in cancer from the perspective of both the patient and the provider. The relevant studies suggested that these devices offer benefits, such as improved medication adherence and accuracy of symptom tracking over self-reported data, as well as insights that increase patient empowerment. Physical activity is consistently correlated with stronger patient outcomes, and a patient’s real-time metrics were found to be capable of tracking medication side effects and toxicity. Studies have made associations between wearable data and telomere shortening, cardiovascular disease, alcohol consumption, sleep apnea, and other conditions. The objective data obtained by the wearable presents a more complete picture of an individual’s health than the snapshot of a 15-minute office visit and a single set of vital signs. Real-time metrics can be translated into a digital phenotype that identifies risk factors specific to each patient, and shared risk factors across one’s social network may uncover common environmental exposures detrimental to one’s health. Wearable data and its upcoming integration with social media will be the foundation for the next generation of personalized medicine.
Schizophrenia affects 1% of the world population and is associated with a reduction in life expectancy of 20 years. The increasing prevalence of both consumer technology and clinical-grade wearable technology offers new metrics to guide clinical decision-making remotely and in real time. Herein, recent literature is reviewed to determine the potential utility of wearables in schizophrenia, including their utility in diagnosis, first-episode psychosis, and relapse prevention and their acceptability to patients. Several studies have further confirmed the validity of various devices in their ability to track sleep—an especially useful metric in schizophrenia, as sleep disturbances may be predictive of disease onset or the acute worsening of psychotic symptoms. Through machine learning, wearable-obtained heart rate and motor activity were used to differentiate between controls and patients with schizophrenia. Wearables can capture the autonomic dysregulation that has been detected when patients are actively experiencing paranoia, hallucinations, or delusions. Multiple platforms are currently being researched, such as Health Outcomes Through Positive Engagement and Self-Empowerment, Mobile Therapeutic Attention for Treatment-Resistant Schizophrenia, and Sleepsight, that may ultimately link patient data to clinicians. The future is bright for wearables in schizophrenia, as the recent literature exemplifies their potential to offer real-time insights to guide diagnosis and management.
Social media has redesigned the landscape of human interaction, and data obtained through these platforms are promising for schizophrenia diagnosis and management. Recent research shows mounting evidence that machine learning analysis of social media content is capable of not only differentiating schizophrenia patients from healthy controls, but also predicting conversion to psychosis and symptom exacerbations. Novel platforms such as Horyzons show promise for improving social functioning and providing timely access to therapeutic resources. Social media is also a considerable means to assess and lessen the stigma surrounding schizophrenia. Herein, the relevant literature pertaining to social media and its clinical applications in schizophrenia over the past five years are summarized, followed by a discussion centered on user feedback to highlight future directions. Social media provides valuable contributions to a multifaceted digital phenotype that may improve schizophrenia care in the near future.
Purpose: To report a case of cellulitis-causing late-onset Group B streptococcus (GBS) GBS in a neonate with a previously negative antenatal tested mother. This report aims to discuss the various transmission modes potentially causing this case of cellulitis, such as contaminated breast milk. Case Description: A preterm neonate, born via cesarean section (C-section) at 29 weeks gestation to a G1P0 mother with a negative GBS rectovaginal antenatal swab test, subsequently developed late-onset cellulitis in the lower extremity due to GBS 19 days later. Methods: This is a retrospective case report followed by clinical observation, blood cultures, imaging, and antibiotic interventions. Results: A neonate with left lower extremity cellulitis was found to be GBS positive from a previously negative antenatal GBS-negative mother. Discussion: As GBS is a common pathogen of neonatal sepsis and less commonly cellulitis, testing rectovaginal fluids once may not be enough to prevent neonates and preterm infants from protecting against transmission. As there have been rare cases of GBS-contaminated breast milk, culturing and testing of breast milk should also be considered, especially in preterm infants.
Purpose: To report a case of a post-term neonate with an isolated cystic hygroma upon birth. Methods: This is a retrospective case report followed by clinical observation, genetic testing, and surgical intervention. Results: A post-term neonate was found with an isolated left parapharyngeal cystic hygroma with no incidence of concurrent genetic syndromes upon karyotyping and underwent surgical removal. Discussion: Cystic hygromas are very commonly associated with genetic syndromes or maternal risk factors. If none exist, specific subtypes of cystic hygromas can also be inherited in an autosomal recessive fashion, a possibility that may need to be explored comprehensively
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