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PloS One 2024The elderly is commonly susceptible to depression, the symptoms for which may overlap with natural aging or other illnesses, and therefore miss being captured by routine...
BACKGROUND
The elderly is commonly susceptible to depression, the symptoms for which may overlap with natural aging or other illnesses, and therefore miss being captured by routine screening questionnaires. Passive sensing data have been promoted as a tool for depressive symptoms detection though there is still limited evidence on its usage in the elderly. Therefore, this study aims to review current knowledge on the use of passive sensing data via smartphones and smartwatches in depressive symptom screening for the elderly.
METHOD
The search of literature was performed in PubMed, IEEE Xplore digital library, and PsycINFO. Literature investigating the use of passive sensing data to screen, monitor, and/or predict depressive symptoms in the elderly (aged 60 and above) via smartphones and/or wrist-worn wearables was included for initial screening. Studies in English from international journals published between January 2012 to September 2022 were included. The reviewed studies were further analyzed by a narrative analysis.
RESULTS
The majority of 21 included studies were conducted in Western countries with a few in Asia and Australia. Most studies adopted a cohort study design (n = 12), followed by cross-sectional design (n = 7) and a case-control design (n = 2). The most popular passive sensing data was related to sleep and physical activity using an actigraphy. Sleep characteristics, such as prolonged wakefulness after sleep onset, along with lower levels of physical activity, exhibited a significant association with depression. However, cohort studies expressed concerns regarding data quality stemming from incomplete follow-up and potential confounding effects.
CONCLUSION
Passive sensing data, such as sleep, and physical activity parameters should be promoted for depressive symptoms detection. However, the validity, reliability, feasibility, and privacy concerns still need further exploration.
Topics: Humans; Smartphone; Depression; Aged; Mass Screening; Wearable Electronic Devices; Sleep; Middle Aged; Exercise; Female
PubMed: 38935797
DOI: 10.1371/journal.pone.0304845 -
PloS One 2024Monitoring and improving the quality of sleep are crucial from a public health perspective. In this study, we propose a change-point detection method using diffusion...
Monitoring and improving the quality of sleep are crucial from a public health perspective. In this study, we propose a change-point detection method using diffusion maps for a more accurate detection of respiratory arrest points. Conventional change-point detection methods are limited when dealing with complex nonlinear data structures, and the proposed method overcomes these limitations. The proposed method embeds subsequence data in a low-dimensional space while considering the global and local structures of the data and uses the distance between the data as the score of the change point. Experiments using synthetic and real-world contact-free sensor data confirmed the superiority of the proposed method when dealing with noise, and it detected apnea events with greater accuracy than conventional methods. In addition to improving sleep monitoring, the proposed method can be applied in other fields, such as healthcare, manufacturing, and finance. This study will contribute to the development of advanced monitoring systems that adapt to diverse conditions while protecting privacy.
Topics: Humans; Sleep Apnea Syndromes; Polysomnography; Algorithms; Monitoring, Physiologic
PubMed: 38935677
DOI: 10.1371/journal.pone.0306139 -
JAMA Network Open Jun 2024Adjuvant endocrine therapy (AET) use among women with early-stage, hormone receptor-positive breast cancer reduces the risk of cancer recurrence, but its adverse... (Randomized Controlled Trial)
Randomized Controlled Trial
IMPORTANCE
Adjuvant endocrine therapy (AET) use among women with early-stage, hormone receptor-positive breast cancer reduces the risk of cancer recurrence, but its adverse symptoms contribute to lower adherence.
OBJECTIVE
To test whether remote monitoring of symptoms and treatment adherence with or without tailored text messages improves outcomes among women with breast cancer who are prescribed AET.
DESIGN, SETTING, AND PARTICIPANTS
This nonblinded, randomized clinical trial (RCT) following intention-to-treat principles included English-speaking women with early-stage breast cancer prescribed AET at a large cancer center with 14 clinics across 3 states from November 15, 2018, to June 11, 2021. All participants had a mobile device with a data plan and an email address and were asked to use an electronic pillbox to monitor AET adherence and to complete surveys at enrollment and 1 year.
INTERVENTIONS
Participants were randomized into 3 groups: (1) an app group, in which participants received instructions for and access to the study adherence and symptom monitoring app for 6 months; (2) an app plus feedback group, in which participants received additional weekly text messages about managing symptoms, adherence, and communication; or (3) an enhanced usual care (EUC) group. App-reported missed doses, increases in symptoms, and occurrence of severe symptoms triggered follow-ups from the oncology team.
MAIN OUTCOMES AND MEASURES
The primary outcome was 1-year, electronic pillbox-captured AET adherence. Secondary outcomes included symptom management abstracted from the medical record, as well as patient-reported health care utilization, symptom burden, quality of life, physician communication, and self-efficacy for managing symptoms.
RESULTS
Among 304 female participants randomized (app group, 98; app plus feedback group, 102; EUC group, 104), the mean (SD) age was 58.6 (10.8) years (median, 60 years; range, 31-83 years), and 60 (19.7%) had an educational level of high school diploma or less. The study completion rate was 87.5% (266 participants). There were no statistically significant differences by treatment group in AET adherence (primary outcome): 76.6% for EUC, 73.4% for the app group (difference vs EUC, -3.3%; 95% CI, -11.4% to 4.9%; P = .43), and 70.9% for the app plus feedback group (difference vs EUC, -5.7%; 95% CI, -13.8% to 2.4%; P = .17). At the 1-year follow-up, app plus feedback participants had fewer total health care encounters (adjusted difference, -1.23; 95% CI, -2.03 to -0.43; P = .003), including high-cost encounters (adjusted difference, -0.40; 95% CI, -0.67 to -0.14; P = .003), and office visits (adjusted difference, -0.82; 95% CI, -1.54 to -0.09; P = .03) over the previous 6 months compared with EUC participants.
CONCLUSIONS AND RELEVANCE
This RCT found that a remote monitoring app with alerts to the patient's care team and tailored text messages to patients did not improve AET adherence among women with early-stage breast cancer; however, it reduced overall and high-cost health care encounters and office visits without affecting quality of life.
TRIAL REGISTRATION
ClinicalTrials.gov Identifier: NCT03592771.
Topics: Humans; Female; Breast Neoplasms; Middle Aged; Medication Adherence; Antineoplastic Agents, Hormonal; Mobile Applications; Aged; Text Messaging; Adult; Chemotherapy, Adjuvant
PubMed: 38935379
DOI: 10.1001/jamanetworkopen.2024.17873 -
MSystems Jun 2024Airway microbiota are known to contribute to lung diseases, such as cystic fibrosis (CF), but their contributions to pathogenesis are still unclear. To improve our...
Airway microbiota are known to contribute to lung diseases, such as cystic fibrosis (CF), but their contributions to pathogenesis are still unclear. To improve our understanding of host-microbe interactions, we have developed an integrated analytical and bioinformatic mass spectrometry (MS)-based metaproteomics workflow to analyze clinical bronchoalveolar lavage (BAL) samples from people with airway disease. Proteins from BAL cellular pellets were processed and pooled together in groups categorized by disease status (CF vs. non-CF) and bacterial diversity, based on previously performed small subunit rRNA sequencing data. Proteins from each pooled sample group were digested and subjected to liquid chromatography tandem mass spectrometry (MS/MS). MS/MS spectra were matched to human and bacterial peptide sequences leveraging a bioinformatic workflow using a metagenomics-guided protein sequence database and rigorous evaluation. Label-free quantification revealed differentially abundant human peptides from proteins with known roles in CF, like neutrophil elastase and collagenase, and proteins with lesser-known roles in CF, including apolipoproteins. Differentially abundant bacterial peptides were identified from known CF pathogens (e.g., ), as well as other taxa with potentially novel roles in CF. We used this host-microbe peptide panel for targeted parallel-reaction monitoring validation, demonstrating for the first time an MS-based assay effective for quantifying host-microbe protein dynamics within BAL cells from individual CF patients. Our integrated bioinformatic and analytical workflow combining discovery, verification, and validation should prove useful for diverse studies to characterize microbial contributors in airway diseases. Furthermore, we describe a promising preliminary panel of differentially abundant microbe and host peptide sequences for further study as potential markers of host-microbe relationships in CF disease pathogenesis.IMPORTANCEIdentifying microbial pathogenic contributors and dysregulated human responses in airway disease, such as CF, is critical to understanding disease progression and developing more effective treatments. To this end, characterizing the proteins expressed from bacterial microbes and human host cells during disease progression can provide valuable new insights. We describe here a new method to confidently detect and monitor abundance changes of both microbe and host proteins from challenging BAL samples commonly collected from CF patients. Our method uses both state-of-the art mass spectrometry-based instrumentation to detect proteins present in these samples and customized bioinformatic software tools to analyze the data and characterize detected proteins and their association with CF. We demonstrate the use of this method to characterize microbe and host proteins from individual BAL samples, paving the way for a new approach to understand molecular contributors to CF and other diseases of the airway.
PubMed: 38934598
DOI: 10.1128/msystems.00929-23 -
Fundamental Research May 2024The aerosol transmission of coronavirus disease in 2019, along with the spread of other respiratory diseases, caused significant loss of life and property; it impressed... (Review)
Review
The aerosol transmission of coronavirus disease in 2019, along with the spread of other respiratory diseases, caused significant loss of life and property; it impressed upon us the importance of real-time bioaerosol detection. The complexity, diversity, and large spatiotemporal variability of bioaerosols and their external/internal mixing with abiotic components pose challenges for effective online bioaerosol monitoring. Traditional methods focus on directly capturing bioaerosols before subsequent time-consuming laboratory analysis such as culture-based methods, preventing the high-resolution time-based characteristics necessary for an online approach. Through a comprehensive literature assessment, this review highlights and discusses the most commonly used real-time bioaerosol monitoring techniques and the associated commercially available monitors. Methods applied in online bioaerosol monitoring, including adenosine triphosphate bioluminescence, laser/light-induced fluorescence spectroscopy, Raman spectroscopy, and bioaerosol mass spectrometry are summarized. The working principles, characteristics, sensitivities, and efficiencies of these real-time detection methods are compared to understand their responses to known particle types and to contrast their differences. Approaches developed to analyze the substantial data sets obtained by these instruments and to overcome the limitations of current real-time bioaerosol monitoring technologies are also introduced. Finally, an outlook is proposed for future instrumentation indicating a need for highly revolutionized bioaerosol detection technologies.
PubMed: 38933213
DOI: 10.1016/j.fmre.2023.05.012 -
RSC Advances Jun 2024Taurine is now widely used as a new biomarker for cardiovascular and neurodegenerative diseases. This study discusses the importance of accurately determining taurine...
Taurine is now widely used as a new biomarker for cardiovascular and neurodegenerative diseases. This study discusses the importance of accurately determining taurine biomarker levels in various tissues and fluids for the early diagnosis of important pathologies and diseases. Current methods for taurine analysis face challenges such as low sensitivity, lack of selectivity, and complex procedures. Therefore, an efficient analytical method/technique is urgently needed by clinicians. A new paper-based photochemical method using triangular silver nanoparticles (TA-AgNPs) as optical nanoprobes was developed to detect taurine in human blood plasma and urine samples. This method involves a chemical reaction between taurine and TA-AgNPs, leading to a color change at pH 4.8, which is detected using a paper-based colorimetry (PCD) assay. The reaction is further confirmed by UV-visible spectrophotometry as the interaction between taurine and TA-AgNPs causes a significant change in the absorption spectrum, enabling the rapid and reliable measurement of this important biomarker with a detection limit of less than 0.2 μM to 20 mM. The method has been successfully applied to bioanalyzing taurine in human body fluids. Additionally, it requires optimized single-drop paper/parafilm-based colorimetric devices (OD-PCDs) for and on-demand taurine analysis. This study represents the first use of TA-AgNPs for the specific and sensitive detection of taurine in real samples. The sensor design allows for the direct quantification of biomarkers in biological samples without the need for derivatization procedures or sample preparation. The simplicity and portability of OD-PCDs make them promising for tracking and monitoring. This method is expected to contribute to improving environmental health and occupational safety and represents a significant advancement in colorimetric analysis for the sensitive and selective detection of taurine, potentially providing a platform for the identification of taurine and other biomarkers.
PubMed: 38932979
DOI: 10.1039/d4ra03575e -
Pharmaceutics Jun 2024Fluvoxamine is used in children and adolescents ('youths') for treating obsessive compulsive disorder (OCD) but also off-label for depressive and anxiety disorders. This...
INTRODUCTION
Fluvoxamine is used in children and adolescents ('youths') for treating obsessive compulsive disorder (OCD) but also off-label for depressive and anxiety disorders. This study aimed to investigate the relationship between fluvoxamine dose and serum concentrations, independent correlates of fluvoxamine concentrations, and a preliminary therapeutic reference range (TRR) for youths with OCD and treatment response.
METHODS
Multicenter naturalistic data of a therapeutic drug monitoring service, as well as prospective data of the 'TDM Vigil study' (EudraCT 2013-004881-33), were analyzed. Patient and treatment characteristics were assessed by standardized measures, including Clinical Global Impressions-Severity (CGI-S) and -Change (CGI-I), with CGI-I of much or very much improved defining treatment response and adverse drug reactions using the Udvalg for Kliniske Undersogelser (UKU) Side Effect Rating Scale. Multivariable regression analysis was used to evaluate the influence of sex, age, body weight, body mass index (BMI), and fluvoxamine dose on fluvoxamine serum concentrations.
RESULTS
The study included 70 youths (age = 6.7-19.6 years, OCD = 78%, mean fluvoxamine dose = 140.4 (range = 25-300) mg/d). A weak positive correlation between daily dose and steady-state trough serum concentrations was found (r = 0.34, = 0.004), with dose variation explaining 16.2% of serum concentration variability. Multivariable correlates explaining 25.3% of the variance of fluvoxamine concentrations included higher fluvoxamine dose and lower BMI. Considering responders with OCD, the estimated TRR for youths was 55-371 ng/mL, exceeding the TRR for adults with depression of 60-230 ng/mL.
DISCUSSION
These preliminary data contribute to the definition of a TRR in youth with OCD treated with fluvoxamine and identify higher BMI as a moderator of lower fluvoxamine concentrations.
PubMed: 38931893
DOI: 10.3390/pharmaceutics16060772 -
Sensors (Basel, Switzerland) Jun 2024The monitoring of body temperature is a recent addition to the plethora of parameters provided by wellness and fitness wearable devices. Current wearable temperature...
The monitoring of body temperature is a recent addition to the plethora of parameters provided by wellness and fitness wearable devices. Current wearable temperature measurements are made at the skin surface, a measurement that is impacted by the ambient environment of the individual. The use of near-infrared spectroscopy provides the potential for a measurement below the epidermal layer of skin, thereby having the potential advantage of being more reflective of physiological conditions. The feasibility of noninvasive temperature measurements is demonstrated by using an in vitro model designed to mimic the near-infrared spectra of skin. A miniaturizable solid-state laser-diode-based near-infrared spectrometer was used to collect diffuse reflectance spectra for a set of seven tissue phantoms composed of different amounts of water, gelatin, and Intralipid. Temperatures were varied between 20-24 °C while collecting these spectra. Two types of partial least squares (PLS) calibration models were developed to evaluate the analytical utility of this approach. In both cases, the collected spectra were used without pre-processing and the number of latent variables was the only optimized parameter. The first approach involved splitting the whole dataset into separate calibration and prediction subsets for which a single optimized PLS model was developed. For this first case, the coefficient of determination (R) is 0.95 and the standard error of prediction (SEP) is 0.22 °C for temperature predictions. The second strategy used a leave-one-phantom-out methodology that resulted in seven PLS models, each predicting the temperatures for all spectra in the held-out phantom. For this set of phantom-specific predicted temperatures, R and SEP values range from 0.67-0.99 and 0.19-0.65 °C, respectively. The stability and reproducibility of the sample-to-spectrometer interface are identified as major sources of spectral variance within and between phantoms. Overall, results from this in vitro study justify the development of future in vivo measurement technologies for applications as wearables for continuous, real-time monitoring of body temperature for both healthy and ill individuals.
Topics: Phantoms, Imaging; Spectroscopy, Near-Infrared; Humans; Least-Squares Analysis; Calibration; Skin; Gelatin; Temperature; Water; Wearable Electronic Devices; Emulsions; Soybean Oil; Phospholipids
PubMed: 38931768
DOI: 10.3390/s24123985 -
Sensors (Basel, Switzerland) Jun 2024Telehealth and remote patient monitoring (RPM), in particular, have been through a massive surge of adoption since 2020. This initiative has proven potential for the... (Review)
Review
Telehealth and remote patient monitoring (RPM), in particular, have been through a massive surge of adoption since 2020. This initiative has proven potential for the patient and the healthcare provider in areas such as reductions in the cost of care. While home-use medical devices or wearables have been shown to be beneficial, a literature review illustrates challenges with the data generated, driven by limited device usability. This could lead to inaccurate data when an exam is completed without clinical supervision, with the consequence that incorrect data lead to improper treatment. Upon further analysis of the existing literature, the RPM Usability Impact model is introduced. The goal is to guide researchers and device manufacturers to increase the usability of wearable and home-use medical devices in the future. The importance of this model is highlighted when the user-centered design process is integrated, which is needed to develop these types of devices to provide the proper user experience.
Topics: Humans; Telemedicine; Monitoring, Physiologic; Wearable Electronic Devices
PubMed: 38931760
DOI: 10.3390/s24123977 -
Sensors (Basel, Switzerland) Jun 2024Skiing technique and performance improvements are crucial for athletes and enthusiasts alike. This study presents SnowMotion, a digital human motion training assistance...
Skiing technique and performance improvements are crucial for athletes and enthusiasts alike. This study presents SnowMotion, a digital human motion training assistance platform that addresses the key challenges of reliability, real-time analysis, usability, and cost in current motion monitoring techniques for skiing. SnowMotion utilizes wearable sensors fixed at five key positions on the skier's body to achieve high-precision kinematic data monitoring. The monitored data are processed and analyzed in real time through the SnowMotion app, generating a panoramic digital human image and reproducing the skiing motion. Validation tests demonstrated high motion capture accuracy (cc > 0.95) and reliability compared to the Vicon system, with a mean error of 5.033 and a root-mean-square error of less than 12.50 for typical skiing movements. SnowMotion provides new ideas for technical advancement and training innovation in alpine skiing, enabling coaches and athletes to analyze movement details, identify deficiencies, and develop targeted training plans. The system is expected to contribute to popularization, training, and competition in alpine skiing, injecting new vitality into this challenging sport.
Topics: Skiing; Humans; Wearable Electronic Devices; Biomechanical Phenomena; Movement; Mobile Applications
PubMed: 38931758
DOI: 10.3390/s24123975