BACKGROUND: For a decade, despite results from many studies, telemedicine systems have suffered from a lack of recommendations for chronic heart failure (CHF) care because of variable study results. Another limitation is the hospital-based architecture of most telemedicine systems. Some systems use an algorithm based on daily weight, transcutaneous oxygen measurement, and heart rate to detect and treat acute heart failure (AHF) in patients with CHF as early on as possible.
OBJECTIVE: The aim of this study is to determine the efficacy of a telemonitoring system in detecting clinical destabilization in real-life settings (out-of-hospital management) without generating too many false positive alerts.
METHODS: All patients self-monitoring at home using the system after a congestive AHF event treated at a cardiology clinic in France between March 2020 and March 2021 with at least 75% compliance on daily measurements were included retrospectively. New-onset AHF was defined by the presence of at least 1 of the following criteria: transcutaneous oxygen saturation loss, defined as a transcutaneous oxygen measurement under 90%; rise of cardiac frequency above 110 beats per minute; weight gain of at least 2 kg; and symptoms of congestive AHF, described over the phone. An AHF alert was generated when the criteria reached our definition of new-onset acute congestive heart failure (HF).
RESULTS: A total of 111 consecutive patients (n=70 men) with a median age of 76.60 (IQR 69.5-83.4) years receiving the telemonitoring system were included. Thirty-nine patients (35.1%) reached the HF warning level, and 28 patients (25%) had confirmed HF destabilization during follow-up. No patient had AHF without being detected by the telemonitoring system. Among incorrect AHF alerts (n=11), 5 patients (45%) had taken inaccurate measurements, 3 patients (27%) had supraventricular arrhythmia, 1 patient (9%) had a pulmonary bacterial infection, and 1 patient (9%) contracted COVID-19. A weight gain of at least 2 kg within 4 days was significantly associated with a correct AHF alert (P=.004), and a heart rate of more than 110 beats per minute was more significantly associated with an incorrect AHF alert (P=.007).
CONCLUSIONS: This single-center study highlighted the efficacy of the telemedicine system in detecting and quickly treating cardiac instability complicating the course of CHF by detecting new-onset AHF as well as supraventricular arrhythmia, thus helping cardiologists provide better follow-up to ambulatory patients.

OBJECTIVE: Faecal immunochemical tests (FIT) are highly sensitive for colorectal cancer (CRC) detection. Little evidence exists regarding repeat FIT. The repeat FIT (RFIT) study aimed to determine whether second and third FIT provide reassurance and improve CRC or significant bowel disease (SBD) identification.
METHODS: This was a prospective observational study. Patients recruited from urgent referrals returned three FIT and underwent colonoscopy. Chi-square tests compared categorical data. Diagnostic accuracy variables (sensitivity/specificity/positive predictive value [PPV]/negative predictive value [NPV]) were calculated for one, two and three FIT (95% CI). Three negative FIT (<10 μg Hb/g of faeces [μg/g]) groups (one, two, three) were compared with positive groups (one or more FIT ≥10 μg/g). CRC and SBD detection rates were compared by strategy.
RESULTS: A total of 460 patients (mean age: 66.8 years, 233 males and 227 females, 23 CRC, 80 SBD) were included in the study. For one, two and three negative FIT, CRC sensitivity remained static (95.7%); specificity (44.6%, 40.7% and 38.4%) and NPV decreased (99.5%, 99.4% and 99.4%). For SBD, sensitivity increased (78.8%, 83.8% and 86.3%), specificity decreased (47.4%, 43.7% and 41.6%) and NPV increased (91.4%, 92.7% and 93.5%). In one, two and three positive FIT groups, CRC detection was 8.3%,16.1% and 20.9%. CRC mean FIT was 150 μg/g, <6 μg/g for benign pathology.
CONCLUSIONS: One or more negative FIT increases the sensitivity for CRC/SBD. Repeating FIT provides greater differentiation of patients with and without CRC/SBD compared to single FIT but is associated with decreased specificity and PPV. Multiple negative FIT may offer reassurance; however, application of repeating FIT may be restricted given the associated increase in investigations S1.

BACKGROUND: Mental health problems and suicide ideation are common in adolescents. Early detection of these issues could prevent the escalation of mental health-related symptoms in the long term. Moreover, characterizing different profiles of prevalent symptoms in conjunction with emotional regulation strategies could guide the design of specific interventions. The use of web-based screening (WBS) tools has been regarded as a suitable strategy to timely detect symptomatology while improving the appeal, cost, timeliness, and reach of detection in young populations. However, the evidence regarding the accuracy of these approaches is not fully conclusive.
OBJECTIVE: The study aims (1) to examine the capability of a WBS to identify adolescents with psychiatric symptoms and suicidality and (2) to characterize the mental health profiles of a large sample of adolescents using WBS.
METHODS: A total of 1599 Latin American Spanish-speaking adolescents (mean age 15.56, SD 1.34 years), consisting of 47.3% (n=753) female, 98.5% Chilean (n=1570), and 1.5% Venezuelan (n=24) participants, responded to a mental health WBS. A randomized subsample of participants also responded to the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID). McNemar χ2 and receiver-operating characteristic curves tested the detection accuracy of WBS contrasted with the MINI-KID. Latent profile analyses explored the symptomatic and emotional regulation profiles of participants.
RESULTS: Both measures showed an adequate level of agreement (area under the curve per symptom domain ranging from 0.70 to 0.89); however, WBS yielded a higher prevalence than MINI-KID for all psychiatric symptoms, except suicide ideation and depression. Latent profile analyses yielded 4 profiles-one of them presented elevated psychopathological symptoms, constituting 11% of the sample (n=175). Rumination (odds ratio [OR] 130.15, 95% CI 51.75-439.89; P<.001), entrapment (OR 96.35, 95% CI 29.21-317.79; P<.001), and defeat (OR 156.79, 95% CI 50.45-487.23; P<.001) contributed significantly to the prediction of latent profile memberships, while cognitive reappraisal did not contribute to the prediction of any latent profile memberships, and expressive suppression was only associated to profile-2 membership.
CONCLUSIONS: WBS is acceptable for the timely detection of adolescents at risk of mental health conditions. Findings from the symptomatic and emotional regulation profiles highlight the need for comprehensive assessments and differential interventions.

BACKGROUND: Cognitive impairment and dementia are frequently under-recognized. Health system strategies anchored in primary care are essential to address gaps in timely, comprehensive diagnosis. The goal of this paper is to describe the adaptation of a tablet-based brain health assessment (TabCAT-BHA) intervention and the study protocol to test its effectiveness in improving the detection of cognitive impairment, including dementia.
METHODS: This mixed-methods, pragmatic, cluster randomized, hybrid effectiveness-implementation trial is being conducted in two 18-month waves with 26 Kaiser Permanente Southern California primary care clinics, with 13 serving as intervention clinics and 13 as usual care clinics. Patients 65 years and older with memory concerns (n ~ 180,000) receiving care at the 26 clinics will be included in the analyses. Primary care clinics are provided the following practice supports as part of the TabCAT-BHA intervention: brief education and training on neurocognitive disorders and study workflows; digital tools to assess cognitive function and support clinician decision making and documentation; and registered nurse support during the work-up and post-diagnosis periods for primary care providers, patients, and families. The intervention was adapted based on engagement with multiple levels of clinical and operational leaders in the healthcare system. Effectiveness outcomes include rates of cognitive impairment diagnosis in primary care and rates of completed standardized cognitive assessments and specialist referrals with incident diagnoses. Implementation outcomes include acceptability-appropriateness-feasibility, adoption, and fidelity.
RESULTS: We identified seven themes organized by system-, provider-, and patient-level domains that were used to adapt the TabCAT-BHA intervention. Accordingly, changes were made to the provider education, diagnostic work-up, and post-diagnostic support. Results will be reported in fall of 2027.
CONCLUSIONS: Our engagement with multiple primary and specialty care clinical and operational leaders to adapt the TabCAT-BHA intervention to these primary care clinics has informed the protocol to evaluate the intervention\'s effectiveness for improving the detection of cognitive impairment, including dementia, in an integrated healthcare system.
BACKGROUND: Clinicaltrials.gov: NCT06090578 (registered 10/24/23).

UNASSIGNED: Acute kidney injury (AKI) is a marker of clinical deterioration and renal toxicity. While there are many studies offering prediction models for the early detection of AKI, those predicting AKI occurrence using distributed research network (DRN)-based time series data are rare.
UNASSIGNED: In this study, we aimed to detect the early occurrence of AKI by applying an interpretable long short-term memory (LSTM)-based model to hospital electronic health record (EHR)-based time series data in patients who took nephrotoxic drugs using a DRN.
UNASSIGNED: We conducted a multi-institutional retrospective cohort study of data from 6 hospitals using a DRN. For each institution, a patient-based data set was constructed using 5 drugs for AKI, and an interpretable multivariable LSTM (IMV-LSTM) model was used for training. This study used propensity score matching to mitigate differences in demographics and clinical characteristics. Additionally, the temporal attention values of the AKI prediction model\'s contribution variables were demonstrated for each institution and drug, with differences in highly important feature distributions between the case and control data confirmed using 1-way ANOVA.
UNASSIGNED: This study analyzed 8643 and 31,012 patients with and without AKI, respectively, across 6 hospitals. When analyzing the distribution of AKI onset, vancomycin showed an earlier onset (median 12, IQR 5-25 days), and acyclovir was the slowest compared to the other drugs (median 23, IQR 10-41 days). Our temporal deep learning model for AKI prediction performed well for most drugs. Acyclovir had the highest average area under the receiver operating characteristic curve score per drug (0.94), followed by acetaminophen (0.93), vancomycin (0.92), naproxen (0.90), and celecoxib (0.89). Based on the temporal attention values of the variables in the AKI prediction model, verified lymphocytes and calcvancomycin ium had the highest attention, whereas lymphocytes, albumin, and hemoglobin tended to decrease over time, and urine pH and prothrombin time tended to increase.
UNASSIGNED: Early surveillance of AKI outbreaks can be achieved by applying an IMV-LSTM based on time series data through an EHR-based DRN. This approach can help identify risk factors and enable early detection of adverse drug reactions when prescribing drugs that cause renal toxicity before AKI occurs.

Workplace mental health challenges have emerged as a significant concern post-pandemic. Despite this, the pervasive stigma surrounding mental illness leads to the concealment of symptoms and reluctance to seek professional help among employees. This study aims to explore the perception of different stakeholders towards the \'Detection and disclosure\' of workplace mental health challenges in the Indian context. Fifteen semi-structured interviews were conducted with human resource professionals, counselors, and employees who had previously experienced mental health challenge(s). Thematic analysis was done to identify recurring themes and sub-themes. Three critical pathways were identified: minimizing the inhibitory factors, including lack of awareness, denial, low self-efficacy, stigma, and underestimating organizational capability; maximizing the encouraging factors, including psychological safety, perceived social support, and communicating success stories; and implementing supportive organizational practices, including generating awareness and literacy, build the organizational capability, strengthen the role of managers, leadership advocacy, policies, and processes. By fostering a culture of support and prioritizing employee well-being, organizations in India can create healthier and more resilient work environments, benefiting both individuals and the larger society.

BACKGROUND: Vocal biomarkers, derived from acoustic analysis of vocal characteristics, offer noninvasive avenues for medical screening, diagnostics, and monitoring. Previous research demonstrated the feasibility of predicting type 2 diabetes mellitus through acoustic analysis of smartphone-recorded speech. Building upon this work, this study explores the impact of audio data compression on acoustic vocal biomarker development, which is critical for broader applicability in health care.
OBJECTIVE: The objective of this research is to analyze how common audio compression algorithms (MP3, M4A, and WMA) applied by 3 different conversion tools at 2 bitrates affect features crucial for vocal biomarker detection.
METHODS: The impact of audio data compression on acoustic vocal biomarker development was investigated using uncompressed voice samples converted into MP3, M4A, and WMA formats at 2 bitrates (320 and 128 kbps) with MediaHuman (MH) Audio Converter, WonderShare (WS) UniConverter, and Fast Forward Moving Picture Experts Group (FFmpeg). The data set comprised recordings from 505 participants, totaling 17,298 audio files, collected using a smartphone. Participants recorded a fixed English sentence up to 6 times daily for up to 14 days. Feature extraction, including pitch, jitter, intensity, and Mel-frequency cepstral coefficients (MFCCs), was conducted using Python and Parselmouth. The Wilcoxon signed rank test and the Bonferroni correction for multiple comparisons were used for statistical analysis.
RESULTS: In this study, 36,970 audio files were initially recorded from 505 participants, with 17,298 recordings meeting the fixed sentence criteria after screening. Differences between the audio conversion software, MH, WS, and FFmpeg, were notable, impacting compression outcomes such as constant or variable bitrates. Analysis encompassed diverse data compression formats and a wide array of voice features and MFCCs. Wilcoxon signed rank tests yielded P values, with those below the Bonferroni-corrected significance level indicating significant alterations due to compression. The results indicated feature-specific impacts of compression across formats and bitrates. MH-converted files exhibited greater resilience compared to WS-converted files. Bitrate also influenced feature stability, with 38 cases affected uniquely by a single bitrate. Notably, voice features showed greater stability than MFCCs across conversion methods.
CONCLUSIONS: Compression effects were found to be feature specific, with MH and FFmpeg showing greater resilience. Some features were consistently affected, emphasizing the importance of understanding feature resilience for diagnostic applications. Considering the implementation of vocal biomarkers in health care, finding features that remain consistent through compression for data storage or transmission purposes is valuable. Focused on specific features and formats, future research could broaden the scope to include diverse features, real-time compression algorithms, and various recording methods. This study enhances our understanding of audio compression\'s influence on voice features and MFCCs, providing insights for developing applications across fields. The research underscores the significance of feature stability in working with compressed audio data, laying a foundation for informed voice data use in evolving technological landscapes.

BACKGROUND: The use of artificial intelligence (AI) can revolutionize health care, but this raises risk concerns. It is therefore crucial to understand how clinicians trust and accept AI technology. Gastroenterology, by its nature of being an image-based and intervention-heavy specialty, is an area where AI-assisted diagnosis and management can be applied extensively.
OBJECTIVE: This study aimed to study how gastroenterologists or gastrointestinal surgeons accept and trust the use of AI in computer-aided detection (CADe), computer-aided characterization (CADx), and computer-aided intervention (CADi) of colorectal polyps in colonoscopy.
METHODS: We conducted a web-based questionnaire from November 2022 to January 2023, involving 5 countries or areas in the Asia-Pacific region. The questionnaire included variables such as background and demography of users; intention to use AI, perceived risk; acceptance; and trust in AI-assisted detection, characterization, and intervention. We presented participants with 3 AI scenarios related to colonoscopy and the management of colorectal polyps. These scenarios reflect existing AI applications in colonoscopy, namely the detection of polyps (CADe), characterization of polyps (CADx), and AI-assisted polypectomy (CADi).
RESULTS: In total, 165 gastroenterologists and gastrointestinal surgeons responded to a web-based survey using the structured questionnaire designed by experts in medical communications. Participants had a mean age of 44 (SD 9.65) years, were mostly male (n=116, 70.3%), and mostly worked in publicly funded hospitals (n=110, 66.67%). Participants reported relatively high exposure to AI, with 111 (67.27%) reporting having used AI for clinical diagnosis or treatment of digestive diseases. Gastroenterologists are highly interested to use AI in diagnosis but show different levels of reservations in risk prediction and acceptance of AI. Most participants (n=112, 72.72%) also expressed interest to use AI in their future practice. CADe was accepted by 83.03% (n=137) of respondents, CADx was accepted by 78.79% (n=130), and CADi was accepted by 72.12% (n=119). CADe and CADx were trusted by 85.45% (n=141) of respondents and CADi was trusted by 72.12% (n=119). There were no application-specific differences in risk perceptions, but more experienced clinicians gave lesser risk ratings.
CONCLUSIONS: Gastroenterologists reported overall high acceptance and trust levels of using AI-assisted colonoscopy in the management of colorectal polyps. However, this level of trust depends on the application scenario. Moreover, the relationship among risk perception, acceptance, and trust in using AI in gastroenterology practice is not straightforward.

OBJECTIVE: Few studies have evaluated the adenoma detection rate (ADR) of colonoscopy with texture and color enhancement imaging (TXI), a novel image-enhancing technology. This study compares the detection of colorectal polyps using TXI to that using white light imaging (WLI).
METHODS: This single-center retrospective study used propensity-matched scoring based on the patients\' baseline characteristics (age, sex, indication, bowel preparation, endoscopist, colonoscope type, and withdrawal time) to compare the results of patients who underwent chromoendoscopy using WLI or TXI at the Toyoshima Endoscopy Clinic. The differences in polyp detection rates and the mean number of detected polyps per colonoscopy were determined between the TXI and WLI groups.
RESULTS: After propensity score matching, 1970 patients were enrolled into each imaging modality group. The mean patient age was 57.2 ± 12.5 years, and 44.5% of the cohort were men. The ADR was higher in the TXI group than in the WLI group (55.0% vs 49.4%, odds ratio: 1.25). High-risk ADR were more common in the TXI group than in the WLI group (17.6% vs 12.8%; OR: 1.45). The mean number of adenomas per colonoscopy (APC) was higher in the TXI group than in the WLI group (1.187 vs 0.943, OR: 1.12). APC with a flat morphology (1.093 vs 0.848, OR: 1.14) and APC of <6 mm (0.992 vs 0.757, OR: 1.16) were higher in the TXI group than in the WLI group.
CONCLUSIONS: Compared to WLI, TXI improved the ADR in patients who underwent chromoendoscopy based on actual clinical data.

BACKGROUND: Testing for SARS-CoV-2 is essential to provide early COVID-19 treatment for people at high risk of severe illness and to limit the spread of infection in society. Proper upper respiratory specimen collection is the most critical step in the diagnosis of the SARS-CoV-2 virus in public settings, and throat swabs were the preferred specimens used for mass testing in many countries during the COVID-19 pandemic. However, there is still a discussion about whether throat swabs have a high enough sensitivity for SARS-CoV-2 diagnostic testing, as previous studies have reported a large variability in the sensitivity from 52% to 100%. Many previous studies exploring the diagnostic accuracy of throat swabs lack a detailed description of the sampling technique, which makes it difficult to compare the different diagnostic accuracy results. Some studies perform a throat swab by only collecting specimens from the posterior oropharyngeal wall, while others also include a swab of the palatine tonsils for SARS-CoV-2 testing. However, studies suggest that the palatine tonsils could have a tissue tropism for SARS-CoV-2 that may improve the SARS-CoV-2 detection during sampling. This may explain the variation of sensitivity reported, but no clinical studies have yet explored the differences in sensitivity and patient discomfort whether the palatine tonsils are included during the throat swab or not.
OBJECTIVE: The objective of this study is to examine the sensitivity and patient discomfort of a throat swab including the palatine tonsils compared to only swabbing the posterior oropharyngeal wall in molecular testing for SARS-CoV-2.
METHODS: We will conduct a randomized controlled study to compare the molecular detection rate of SARS-CoV-2 by a throat swab performed from the posterior oropharyngeal wall and the palatine tonsils (intervention group) or the posterior oropharyngeal wall only (control group). Participants will be randomized in a 1:1 ratio. All participants fill out a baseline questionnaire upon enrollment in the trial, examining their reason for being tested, symptoms, and previous tonsillectomy. A follow-up questionnaire will be sent to participants to explore the development of symptoms after testing.
RESULTS: A total of 2315 participants were enrolled in this study between November 10, 2022, and December 22, 2022. The results from the follow-up questionnaire are expected to be completed at the beginning of 2024.
CONCLUSIONS: This randomized clinical trial will provide us with information about whether throat swabs including specimens from the palatine tonsils will improve the diagnostic sensitivity for SARS-CoV-2 molecular detection. These results can, therefore, be used to improve future testing recommendations and provide additional information about tissue tropism for SARS-CoV-2.
BACKGROUND: ClinicalTrials.gov NCT05611203; https://clinicaltrials.gov/study/NCT05611203.
UNASSIGNED: DERR1-10.2196/47446.