Jan Multmeier

Background: Pregnant women with ICD-10 ( International Statistical Classification of Diseases, Tenth Revision ) affective or stress-related disorders face an elevated risk of perinatal depression and anxiety, yet evidence on digital nonpharmacologic interventions for this population remains limited. Objective: This study evaluated the effectiveness of an 8-week digital mindfulness–based intervention (eMBI) compared with treatment as usual (TAU) among pregnant women with ICD-10 affective or stress-related disorders participating in a randomized controlled trial (RCT). Methods: This prespecified secondary analysis was conducted within a multicenter RCT in Baden-Württemberg, Germany. Pregnant women aged 18 years and older with elevated depressive symptoms (Edinburgh Postnatal Depression Scale [EPDS]>9) and ICD-10 –diagnosed affective or stress-related disorders were randomized 1:1 to eMBI or TAU. The intervention consisted of 8 weekly app-based mindfulness sessions (45 min each) delivered during gestational weeks 29‐36, with no direct therapist contact. The primary outcome was continuous depressive symptom severity measured with the EPDS at 4‐6 weeks post partum. Secondary outcomes included the EPDS at 6 months post partum, generalized anxiety (State-Trait Anxiety Inventory-State [STAI-S], State-Trait Anxiety Inventory-Trait [STAI-T]), and Pregnancy-Related Anxiety Questionnaire-Revised (PRAQ-R). Analyses followed the intention-to-treat (ITT) principle, using mixed models for repeated measures and multiple imputation. Results: Of the 5299 screened women, 147 met the inclusion criteria for this subgroup analysis (intervention group [IG] had n=73 women and control group had n=74 women). Groups were comparable at baseline. The IG showed significantly greater reductions in EPDS scores at gestational week 34 (Δ=–2.21, P =.01), week 36 (Δ=–3.25, P =.01), and 4‐6 weeks post partum (Δ=–4.81, P =.007). Treatment effects remained robust under conservative missing-data assumptions. At 4-6 weeks post partum, a higher proportion of participants in the IG achieved clinically meaningful improvement (31/73, 42.5% vs 21/74, 28.4%; adjusted odds ratio 1.56, 95% CI 1.19‐2.05; P =.001). Anxiety outcomes followed a similar pattern, whereas pregnancy-related anxiety did not differ between groups. Conclusions: In this prespecified subgroup of pregnant women with ICD-10 affective or stress-related disorders, the eMBI was associated with clinically meaningful reductions in depressive symptoms from late pregnancy to 4-6 weeks post partum. Effects at 6 months post partum were attenuated and less stable across missing-data assumptions. These findings support eMBIs as a scalable, nonpharmacological adjunct to perinatal mental health care for women with affective or stress-related disorders, while confirmation in adequately powered trials with strategies to reduce postpartum attrition is warranted.

Study Objectives: The efficacy and safety of chloral hydrate, used as approved for severe insomnia in the UK, were assessed in a single-arm, open-label, real-world, decentralized clinical trial using contemporary self-reported outcome measures. Methods: Participants (18– 75 years) had clinically significant impairment by severe insomnia (Insomnia Severity Index (ISI) score of 20– 28), and history of behavioral and pharmacological sleep therapy failure. Specialists confirmed the clinical diagnosis and prescribed chloral hydrate (500 mg/5 mL oral solution, 430 or 860 mg daily) for 2 weeks followed by a 4-week follow-up period. Endpoints included change in ISI score from confirmatory diagnosis to treatment end (primary); and sleep measures, health-related quality of life (HRQoL), anxiety, depression, and adverse events (AEs; secondaries). Results: Of the 96 participants (mean baseline ISI, 24.03 [SD, 2.06]), 85 completed the study. Improvements were observed with ISI at treatment end (week 2 mean change was − 10.79 [95% confidence interval, − 12.12, − 9.47]; n=93; week 6 mean change was − 8.04 (95% confidence interval, − 9.13, − 6.95; p < 0.0001; n=85), exceeding the 6-point change considered a minimal clinically important difference. Self-reported sleep measures including Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index, HRQoL, and anxiety shows significant improvements during treatment with some outcomes indicating continued benefit up to 4 weeks post-treatment. Most treatment-related AEs were mild in nature (83.9%, 256/305 events) including wind (73.9%), headache (58.7%), and stomach pain (31.5%). While no events met criteria for serious or severe intensity, seven participants (7.6%) withdrew owing to AEs. Conclusion: Short-term UK-approved chloral hydrate may provide a potential option for severe adult insomnia only when prior treatments have failed. Trial Registration: NCT06053840 (https://clinicaltrials.gov); ISRCTN10433315 (https://www.isrctn.com/). Plain Language Summary: Study Rationale Severe insomnia often persists despite behavioral and pharmacological interventions, leaving patients with limited options. Chloral hydrate, an older sedative still approved in the UK, has been less studied with modern outcome tools in routine clinical settings. This study evaluated its use in adults with severe insomnia that had been resistant to previous treatments. Study Impact The RESTORE study found that short-term chloral hydrate treatment was associated with improvements in insomnia severity and related quality-of-life measures, with some effects observed up to four weeks after treatment. Reported adverse events were generally mild, and no serious safety issues were identified during the study period. These findings indicate that chloral hydrate may warrant consideration for selected patients when other treatment options have not been successful whilst recognising the limitations of single arm designs in a real-world setting.

Background: Diagnostic delays in autism are common, with the time to diagnosis being up to 3 years from the onset of symptoms. Such delays have a proven detrimental effect on individuals and families going through the process. Digital health products, such as mobile apps, can help close this gap due to their scalability and ease of access. Further, mobile apps offer the opportunity to make the diagnostic process faster and more accurate by providing additional and timely information to clinicians undergoing autism assessments. Objective: The aim of this scoping review was to synthesize the available evidence about digital biomarker tools to aid clinicians, researchers in the autism field, and end users in making decisions as to their adoption within clinical and research settings. Methods: We conducted a structured literature search on databases and search engines to identify peer-reviewed studies and regulatory submissions that describe app characteristics, validation study details, and accuracy and validity metrics of commercial and research digital biomarker apps aimed at aiding the diagnosis of autism. Results: We identified 4 studies evaluating 4 products: 1 commercial and 3 research apps. The accuracy of the identified apps varied between 28% and 80.6%. Sensitivity and specificity also varied, ranging from 51.6% to 81.6% and 18.5% to 80.5%, respectively. Positive predictive value ranged from 20.3% to 76.6%, and negative predictive value fluctuated between 48.7% and 97.4%. Further, we found a lack of details around participants’ demographics and, where these were reported, important imbalances in sex and ethnicity in the studies evaluating such products. Finally, evaluation methods as well as accuracy and validity metrics of available tools were not clearly reported in some cases and varied greatly across studies. Different comparators were also used, with some studies validating their tools against the Diagnostic and Statistical Manual of Mental Disorders criteria and others through self-reported measures. Further, while in most cases, 2 classes were used for algorithm validation purposes, 1 of the studies reported a third category (indeterminate). These discrepancies substantially impact the comparability and generalizability of the results, thus highlighting the need for standardized validation processes and the reporting of findings. Conclusions: Despite their popularity, systematic evaluations and syntheses of the current state of the art of digital health products are lacking. Standardized and transparent evaluations of digital health tools in diverse populations are needed to assess their real-world usability and validity, as well as help researchers, clinicians, and end users safely adopt novel tools within clinical and research practices.

BACKGROUND Diagnostic delays in autism are common, with the time to diagnosis being up to 3 years from the onset of symptoms. Such delays have a proven detrimental effect on individuals and families going through the process. Digital health products, such as mobile apps, can help close this gap due to their scalability and ease of access. Further, mobile apps offer the opportunity to make the diagnostic process faster and more accurate by providing additional and timely information to clinicians undergoing autism assessments. OBJECTIVE The aim of this scoping review was to synthesize the available evidence about digital biomarker tools to aid clinicians, researchers in the autism field, and end users in making decisions as to their adoption within clinical and research settings. METHODS We conducted a structured literature search on databases and search engines to identify peer-reviewed studies and regulatory submissions that describe app characteristics, validation study details, and accuracy and validity metrics of commercial and research digital biomarker apps aimed at aiding the diagnosis of autism. RESULTS We identified 4 studies evaluating 4 products: 1 commercial and 3 research apps. The accuracy of the identified apps varied between 28% and 80.6%. Sensitivity and specificity also varied, ranging from 51.6% to 81.6% and 18.5% to 80.5%, respectively. Positive predictive value ranged from 20.3% to 76.6%, and negative predictive value fluctuated between 48.7% and 97.4%. Further, we found a lack of details around participants’ demographics and, where these were reported, important imbalances in sex and ethnicity in the studies evaluating such products. Finally, evaluation methods as well as accuracy and validity metrics of available tools were not clearly reported in some cases and varied greatly across studies. Different comparators were also used, with some studies validating their tools against the Diagnostic and Statistical Manual of Mental Disorders criteria and others through self-reported measures. Further, while in most cases, 2 classes were used for algorithm validation purposes, 1 of the studies reported a third category (indeterminate). These discrepancies substantially impact the comparability and generalizability of the results, thus highlighting the need for standardized validation processes and the reporting of findings. CONCLUSIONS Despite their popularity, systematic evaluations and syntheses of the current state of the art of digital health products are lacking. Standardized and transparent evaluations of digital health tools in diverse populations are needed to assess their real-world usability and validity, as well as help researchers, clinicians, and end users safely adopt novel tools within clinical and research practices.

Background: Increasing use of emergency departments (EDs) by patients with low urgency, combined with limited availability of medical staff, results in extended waiting times and delayed care. Technological approaches could possibly increase efficiency by providing urgency advice and symptom assessments. Objective: The purpose of this study is to evaluate the safety of urgency advice provided by a symptom assessment app, Ada, in an ED. Methods: The study was conducted at the interdisciplinary ED of Marburg University Hospital, with data collection performed between August 2019 and March 2020. This study had a single-center cross-sectional prospective observational design and included 378 patients. The app’s urgency recommendation was compared with an established triage concept (Manchester Triage System [MTS]), including patients from the lower 3 MTS categories only. For all patients who were undertriaged, an expert physician panel assessed the case to detect potential avoidable hazardous situations (AHSs). Results: Of 378 participants, 344 (91%) were triaged the same or more conservatively and 34 (8.9%) were undertriaged by the app. Of the 378 patients, 14 (3.7%) had received safe advice determined by the expert panel and 20 (5.3%) were considered to be potential AHS. Therefore, the assessment could be considered safe in 94.7% (358/378) of the patients when compared with the MTS assessment. From the 3 lowest MTS categories, 43.4% (164/378) of patients were not considered as emergency cases by the app, but could have been safely treated by a general practitioner or would not have required a physician consultation at all. Conclusions: The app provided urgency advice after patient self-triage that has a high rate of safety, a rate of undertriage, and a rate of triage with potential to be an AHS, equivalent to telephone triage by health care professionals while still being more conservative than direct ED triage. A large proportion of patients in the ED were not considered as emergency cases, which could possibly relieve ED burden if used at home. Further research should be conducted in the at-home setting to evaluate this hypothesis. Trial Registration: German Clinical Trial Registration DRKS00024909; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00024909

BACKGROUND Increasing use of emergency departments (EDs) by patients with low urgency, combined with limited availability of medical staff, results in extended waiting times and delayed care. Technological approaches could possibly increase efficiency by providing urgency advice and symptom assessments. OBJECTIVE The purpose of this study is to evaluate the safety of urgency advice provided by a symptom assessment app, Ada, in an ED. METHODS The study was conducted at the interdisciplinary ED of Marburg University Hospital, with data collection performed between August 2019 and March 2020. This study had a single-center cross-sectional prospective observational design and included 378 patients. The app’s urgency recommendation was compared with an established triage concept (Manchester Triage System [MTS]), including patients from the lower 3 MTS categories only. For all patients who were undertriaged, an expert physician panel assessed the case to detect potential avoidable hazardous situations (AHSs). RESULTS Of 378 participants, 344 (91%) were triaged the same or more conservatively and 34 (8.9%) were undertriaged by the app. Of the 378 patients, 14 (3.7%) had received safe advice determined by the expert panel and 20 (5.3%) were considered to be potential AHS. Therefore, the assessment could be considered safe in 94.7% (358/378) of the patients when compared with the MTS assessment. From the 3 lowest MTS categories, 43.4% (164/378) of patients were not considered as emergency cases by the app, but could have been safely treated by a general practitioner or would not have required a physician consultation at all. CONCLUSIONS The app provided urgency advice after patient self-triage that has a high rate of safety, a rate of undertriage, and a rate of triage with potential to be an AHS, equivalent to telephone triage by health care professionals while still being more conservative than direct ED triage. A large proportion of patients in the ED were not considered as emergency cases, which could possibly relieve ED burden if used at home. Further research should be conducted in the at-home setting to evaluate this hypothesis. CLINICALTRIAL German Clinical Trial Registration DRKS00024909; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00024909

BACKGROUND Early efforts to control the COVID-19 pandemic have been focused on Non-Pharmaceutical Interventions (NPIs) in the absence of effective treatments or sufficient vaccine supply. While retrospective analyses and modeling studies confirmed that severe restrictions of social contacts, i.e., lockdowns, are most effective in reducing transmission of SARS-CoV-2, they incur large economic costs and mental health risks. Earlier detection of cases has also been proposed as an effective method of control, but studies have so far only considered enhanced laboratory testing. Digital applications have been developed which aim to identify possible cases of COVID-19 based on reported symptoms and risk factors. OBJECTIVE The aim of this study is to explore the effects of digital screening applications for COVID-19 on the transmission of SARS-CoV-2. METHODS Using an established epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model for infectious disease transmission, we simulate the transmission of SARS-CoV-2 in Germany, the UK, and the USA for 366 days after the virus was introduced in the population. We study 4 scenarios: 1) no interventions (base case), 2) symptom-based self-isolation after consulting healthcare providers, 3) self-isolation using digital screening applications, and 4) severe social contact limitations (lockdown). We included sensitivity analyses for different ratios of infectiousness of pre-symptomatic cases compared to symptomatic cases, and different rates of adoption of digital screening tools. RESULTS Without any intervention, 74% of the German population would be infected with SARS-CoV-2 within the simulation period (UK: 76%, USA: 77%). Self-isolation of symptomatic cases would already slow the spread of the virus significantly and lead to only 18% of the German population being infected (UK: 17%, USA: 17%). Using a digital application could further reduce the infected population to 10% (UK: 9%, USA: 9%), compared to 3% under lockdown conditions. While the effectiveness of digital screening applications varies with the adoption rate, even a low adoption rate could significantly reduce transmission. In the case that pre-symptomatic cases are less infectious than symptomatic cases, the overall proportion of infected individuals in the population decreases, and the effectiveness of different interventions converges. CONCLUSIONS Digital symptom-based screening tools can substantially impact the transmission of SARS-CoV-2 and might be a viable element in strategies to control COVID-19 through NPIs.

BACKGROUND Early efforts to control the COVID-19 pandemic have been focused on Non-Pharmaceutical Interventions (NPIs) in the absence of effective treatments or sufficient vaccine supply. While retrospective analyses and modeling studies confirmed that severe restrictions of social contacts, i.e., lockdowns, are most effective in reducing transmission of SARS-CoV-2, they incur large economic costs and mental health risks. Earlier detection of cases has also been proposed as an effective method of control, but studies have so far only considered enhanced laboratory testing. Digital applications have been developed which aim to identify possible cases of COVID-19 based on reported symptoms and risk factors. OBJECTIVE The aim of this study is to explore the effects of digital screening applications for COVID-19 on the transmission of SARS-CoV-2. METHODS Using an established epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model for infectious disease transmission, we simulate the transmission of SARS-CoV-2 in Germany, the UK, and the USA for 366 days after the virus was introduced in the population. We study 4 scenarios: 1) no interventions (base case), 2) symptom-based self-isolation after consulting healthcare providers, 3) self-isolation using digital screening applications, and 4) severe social contact limitations (lockdown). We included sensitivity analyses for different ratios of infectiousness of pre-symptomatic cases compared to symptomatic cases, and different rates of adoption of digital screening tools. RESULTS Without any intervention, 74% of the German population would be infected with SARS-CoV-2 within the simulation period (UK: 76%, USA: 77%). Self-isolation of symptomatic cases would already slow the spread of the virus significantly and lead to only 18% of the German population being infected (UK: 17%, USA: 17%). Using a digital application could further reduce the infected population to 10% (UK: 9%, USA: 9%), compared to 3% under lockdown conditions. While the effectiveness of digital screening applications varies with the adoption rate, even a low adoption rate could significantly reduce transmission. In the case that pre-symptomatic cases are less infectious than symptomatic cases, the overall proportion of infected individuals in the population decreases, and the effectiveness of different interventions converges. CONCLUSIONS Digital symptom-based screening tools can substantially impact the transmission of SARS-CoV-2 and might be a viable element in strategies to control COVID-19 through NPIs.

Background: Crowding can negatively affect patient and staff experience, and consequently the performance of health care facilities. Crowding can potentially be eased through streamlining and the reduction of duplication in patient history-taking through the use of a digital symptom-taking app. Objective: We simulated the introduction of a digital symptom-taking app on patient flow. We hypothesized that waiting times and crowding in an urgent care center (UCC) could be reduced, and that this would be more efficient than simply adding more staff. Methods: A discrete-event approach was used to simulate patient flow in a UCC during a 4-hour time frame. The baseline scenario was a small UCC with 2 triage nurses, 2 doctors, 1 treatment/examination nurse, and 1 discharge administrator in service. We simulated 33 scenarios with different staff numbers or different potential time savings through the app. We explored average queue length, waiting time, idle time, and staff utilization for each scenario. Results: Discrete-event simulation showed that even a few minutes saved through patient app-based self-history recording during triage could result in significantly increased efficiency. A modest estimated time saving per patient of 2.5 minutes decreased the average patient wait time for triage by 26.17%, whereas a time saving of 5 minutes led to a 54.88% reduction in patient wait times. Alternatively, adding an additional triage nurse was less efficient, as the additional staff were only required at the busiest times. Conclusions: Small time savings in the history-taking process have potential to result in substantial reductions in total patient waiting time for triage nurses, with likely effects of reduced patient anxiety, staff anxiety, and improved patient care. Patient self-history recording could be carried out at home or in the waiting room via a check-in kiosk or a portable tablet computer. This formative simulation study has potential to impact service provision and approaches to digitalization at scale.