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Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device
Get PDFThis study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration : ISRCTN – 12246987.Study co-funded by the European Union’s Horizon research and innovation programme and EFPIA via the innovative Medicine Initiative 2 (Mobilise-D Project)National Institute for Health Research (NIHR) Newcastle Biomedical Research CentreNIHR/Wellcome Trust Clinical Research Facility (CRF) infrastructure at Newcastle upon Tyne Hospitals NHS Foundation Trustthe Spanish Ministry of Science and Innovation through the “Centro de Excelencia Severo Ochoa 2019-2023” ProgramGeneralitat de Catalunya, CERCA ProgramNational Institute for Health Research (NIHR) through the Sheffield Biomedical Research CentreInnovative Medicines Initiative 2 Joint Undertaking (IMI2 JU) project IDEA-FAS
Allogeneic Hematopoietic Cell Transplantation in Advanced Systemic Mastocytosis: A retrospective analysis of the DRST and GREM registries
Get PDFWe identified 71 patients with AdvSM (aggressive SM [ASM], SM with an associated hematologic neoplasm [SM-AHN, e.g., acute myeloid leukemia, SM-AML], mast cell leukemia [MCL]) in two national registries (DRST/GREM) who received an allogeneic hematopoietic cell transplantation (alloHCT) performed in Germany from 1999–2021. Median overall survival (OS) of ASM/SM-AHN ( n = 30, 45%), SM-AML ( n = 28, 39%) and MCL ± AHN ( n = 13, 19%) was 9.0, 3.3 and 0.9 years ( P = 0.007). Improved median OS was associated with response of SM (17/41, 41%; HR 0.4 [0.2–0.9], P = 0.035) and/or of AHN (26/43, 60%, HR 0.3 [0.1–0.7], P = 0.004) prior to alloHCT. Adverse predictors for OS included absence of KIT D816V (10/61, 16%, HR 2.9 [1.2–6.5], P < 0.001) and a complex karyotype (9/60, 15%, HR 4.2 [1.8–10.0], P = 0.016). HLA-match, conditioning type or transplantation at centers reporting above-average alloHCTs (≥7) had no impact on OS. Taking into account competing events at years 1, 3 and 5, relapse-related mortality and non-relapse mortality rate were 15%/23%, 20%/30% and 23%/35%, respectively. Irrespective of subtype, subsequent treatment response was achieved in 13/30 (43%) patients and was highest on midostaurin/avapritinib (7/9, 78%). We conclude that outcome of alloHCT in AdvSM is more affected by disease phenotype and treatment response prior to transplant than by transplant characteristics
COVID-19 breakthrough infections in type 1 diabetes mellitus: a cross-sectional study by the COVID-19 Vaccination in Autoimmune Diseases (COVAD) Group
Get PDFTo investigate the frequency, profile, and severity of COVID-19 breakthrough infections (BI) in patients with type I diabetes mellitus (T1DM) compared to healthy controls (HC) after vaccination. The second COVID-19 Vaccination in Autoimmune Diseases (COVAD-2) survey is a multinational cross-sectional electronic survey which has collected data on patients suffering from various autoimmune diseases including T1DM. We performed a subgroup analysis on this cohort to investigate COVID-19 BI characteristics in patients with T1DM. Logistic regression with propensity score matching analysis was performed. A total of 9595 individuals were included in the analysis, with 100 patients having T1DM. Among the fully vaccinated cohort, 16 (16%) T1DM patients had one BI and 2 (2%) had two BIs. No morbidities or deaths were reported, except for one patient who required hospitalization with oxygen without admission to intensive care. The frequency, clinical features, and severity of BIs were not significantly different between T1DM patients and HCs after adjustment for confounding factors. Our study did not show any statistically significant differences in the frequency, symptoms, duration, or critical care requirements between T1DM and HCs after COVID-19 vaccination. Further research is needed to identify factors associated with inadequate vaccine response in patients with BIs, especially in patients with autoimmune diseases
Evaluation of a hybrid telehealth care pathway for patients with axial spondyloarthritis including self-sampling at home: results of a longitudinal proof-of-concept mixed-methods study (TeleSpactive)
Get PDFPatients with axial spondyloarthritis (axSpA) require close monitoring to achieve the goal of sustained disease remission. Telehealth can facilitate continuous care while relieving scarce healthcare resources. In a mixed-methods proof-of-concept study, we investigated a hybrid telehealth care axSpA pathway in patients with stable disease over 6 months. Patients used a medical app to document disease activity (BASDAI and PtGA bi-weekly, flare questionnaire weekly). To enable a remote ASDAS-CRP (TELE-ASDAS-CRP), patients used a capillary self-sampling device at home. Monitoring results were discussed and a decision was reached via shared decision-making whether a pre-planned 3-month on-site appointment (T3) was necessary. Ten patients completed the study, and eight patients also completed additional telephone interviews. Questionnaire adherence was high; BASDAI (82.3%), flares (74.8%) and all patients successfully completed the TELE-ASDAS-CRP for the T3 evaluation. At T3, 9/10 patients were in remission or low disease activity and all patients declined the offer of an optional T3 on-site appointment. Patient acceptance of all study components was high with a net promoter score (NPS) of +50% (mean NPS 8.8 ± 1.5) for self-sampling, +70% (mean NPS 9.0 ± 1.6) for the electronic questionnaires and +90% for the T3 teleconsultation (mean NPS 9.7 ± 0.6). In interviews, patients reported benefits such as a better overview of their condition, ease of use of telehealth tools, greater autonomy, and, most importantly, travel time savings. To our knowledge, this is the first study to investigate a hybrid approach to follow-up axSpA patients including self-sampling. The positive results observed in this scalable proof-of-concept study warrant a larger confirmatory study.Open Access funding enabled and organized by Projekt DEAL.Deutsche Forschungsgemeinschaft (DFG)Novartis Pharmahttp://dx.doi.org/10.13039/100008792Universitätsklinikum Würzburg (8913
Utilizing machine learning-based QSAR model to overcome standalone consensus docking limitation in beta-lactamase inhibitors screening: a proof-of-concept study
Get PDFIn virtual drug screening, consensus docking is a standard in-silico approach consisting of a combined result from optimized docking experiments, a minimum of two results combination. Therefore, consensus docking is subjected to a lower success rate than the best docking method due to its mathematical nature, an unavoidable limitation. This study aims to overcome this drawback via random forest, an ensemble machine learning model. First, in vitro beta-lactamase inhibitory screening was performed using an in-house chemical library. The in vitro results were later used as a validation. Consequently, we optimized docking protocols for AutoDock Vina and DOCK6 programs. With an appropriate scoring function, we found that DOCK6 could identify up to 70% of all active molecules, double the inappropriate. Further consensus analysis reduced the success rate to 50%. Simultaneously, a false positive rate was down to 16%, which was experimentally favorable for a drug search. Finally, we trained two quantitative structure-activity relationship (QSAR) models using logistic regression as a reference model and a random forest as a test model. After combining consensus docking results, random forest-based QSAR outperformed a logistic regression by restoring the success rate to 70% and maintaining a low false positive rate of around 21%. In conclusion, this study demonstrated the benefit of using a random forest (machine learning)-based QSAR model to overcome a standard consensus docking limitation in beta-lactamase inhibitor search as a proof-of-concept.Highlights An optimized DOCK6 scoring can maximize the success in identifying active molecules by up to 70%. Consensus docking can significantly reduce the false positive rate in determining experimental bioactive molecules compared to the best docking. Integrating a random forest-based QSAR model into a virtual screening workflow extends the limited success rate of consensus docking. An in-house screening reveals the first-time report of three bio beta-lactamase inhibitors.Graphical abstractOpen Access funding enabled and organized by Projekt DEAL.Friedrich-Alexander-Universität Erlangen-Nürnberg (1041
Associations of family socioeconomic indicators and physical activity of primary school-aged children: a systematic review
Get PDFBackground Family socioeconomic indicators (education, occupation, and household income) are key determinants influencing children’s physical activity (PA). This study aims to systematically review the current research about the association between family socioeconomic indicators and PA among primary school-aged children and to quantify the distribution of reported associations by childs’ and parents’ sex and according to analysis and assessment methods. Methods A systematic literature research in multiple scientific databases (MEDLINE via PubMed, Web of Science, ScienceDirect, SPORTDiscus and ERIC) was performed for literature published between 1st January 2010 and 31st March 2022. Only studies reporting statistical associations between an SES indicator of at least one parent (education, occupation, income, or an SES index) and different types and intensities of PA in primary school-aged children (6 to 12 years) were included in the analysis. The distributions of the reported associations were evaluated across and differentiated by sub-group analysis of assessment methods (objectively measured vs. self-reported PA) and analysis methods (univariate vs. multivariate models). Results Overall, 93 studies reported in 77 publications were included in this review. Most of the studies were conducted in Europe and used self-reports (questionnaires) to assess PA. Most studies used only a single SES indicator (commonly maternal education), and only two studies calculated an SES index. The majority of the studies focused on moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and organized physical activity (OPA). Results showed predominantly positive associations between SES indicators and OPA. In contrast, results regarding different intensities of daily PA (TPA, LPA, MPA, MVPA, VPA, LTPA) were heterogeneous, with overwhelmingly no associations. Conclusion Overall, the results expand the knowledge about the association between family socioeconomic indicators and children’s PA and disprove the hypothesis of a clear positive association. However, large multicenter studies are lacking using a real SES index as a predictor and analyzing gender-specific multivariate models.Open Access funding enabled and organized by Projekt DEAL.Universität Leipzig (1039
An 8-week injury prevention exercise program combined with change-of-direction technique training limits movement patterns associated with anterior cruciate ligament injury risk
Get PDFKnee ligament sprains are common during change-of-direction (COD) maneuvers in multidirectional team sports. This study aimed to compare the effects of an 8-week injury prevention exercise program containing COD-specific exercises and a similar program containing linear sprint exercises on injury- and performance-related variables during a 135° COD task. We hypothesized that the COD-specific training would lead to (H1) stronger reductions in biomechanical variables associated with anterior cruciate ligament (ACL) injury risk during COD, i.e. knee abduction moment and angle, hip internal rotation angle and lateral trunk lean, and (H2) more effective improvements in COD performance according to the COD completion time, executed angle, ground contact time, and approach speed. Twenty-two sports science students (40% female) completed biomechanical assessments of COD movement strategies before and after participating in two supervised 25-min training sessions per week over 8 weeks. We observed significant ‘training x group’ interaction effects in support of H1: the COD-specific training but not the linear sprint training led to reduced peak knee abduction moments (interaction, p = 0.027), initial knee abduction (interaction, p < 0.001), and initial lateral trunk lean angles (interaction, p < 0.001) compared to baseline. Although the COD-specific training resulted in sharper executed angles (interaction, p < 0.001), the sprint-specific training group showed reduced COD completion (interaction, p = 0.037) and ground contact times (interaction, p < 0.001). In conclusion, a combination of generic and COD-specific injury prevention training resulted in COD technique adaptations that can help to avoid ACL injury-prone COD movements but may negatively affect COD speed
Analyse deutscher mobile Apps für das Management und Therapie chronisch entzündlicher Darmerkrankungen mit Hilfe der Mobile Application Rating Scale
Get PDFDOI: 10.2196/31102Hintergrund:
Das Feld der Telemedizin und mobile-health (mhealth) hat mittlerweile Einzug in viele Fachbereiche der Medizin gefunden. Unter anderem dient es auch zum Monitoring chronischer Krankheiten und in diesem Rahmen zur Kommunikation zwischen dem Patienten und dem behandelnden Team (Ärzte, Pflegepersonal). Bisher gibt es nur wenige Studien zu einzelnen Krankheitsbildern bei denen ein Krankheitsmonitoring mittels App oder Telemedizin untersucht wurde. In diesen konnten jedoch bereits einige Vorteile aufgezeigt werden. Unter anderem konnten bei Diabetes mellitus, Bluthochdruck, COPD, Herzinsuffizienz und systemischen Lupus Erythematodes nachgewiesen werden, dass durch die Anwendung der Telemedizin die Behandlungskosten gesenkt und das Patienten Outcome verbessert wird (1–5).
Im Rahmen der Sars COV-2 Pandemie rückte die mhealth und Telemedizin zunehmend in den Vordergrund um unnötige Krankenhausaufenthalte und Arztbesuche deutlich zu reduzieren. Zudem wurde in Deutschland durch das digitale Versorgungsgesetz, das im Dezember 2019 in Kraft trat, die Grundlage geschaffen, Apps an Patienten zu verschreiben und somit auch finanziell zu vergüten.
Ziel dieser Arbeit ist es aktuell verfügbare Apps die für das Management chronisch entzündlicher Darmerkrankungen nützlich sind zu identifizieren, eine standardisierte Bewertung mittels MARS durchzuführen und Empfehlungen für die Entwicklung zukünftiger Apps auszusprechen.
Methoden:
Um die verfügbaren Apps zu identifizieren, wurde der Google Playstore und der Apple Appstore nach verfügbaren CED assoziierten Apps durchsucht. Hierfür wurden folgende Suchbegriffe verwendet: „Morbus Crohn“, “Colitis ulcerosa”, “CED”, “Chronisch entzündliche Darmerkankungen”, “IBD”, “Crohn’s disease”, “ulcerative colitis”, “UC”, “inflammatory bowel disease”, “Crohn” und “colitis”. Die Suche wurde halbautomatisch mit der Software „Webcrawler“ durchgeführt. Im Anschluss erfolgte eine manuelle Selektion der vorausgewählten Apps durch 2 der 6 App-Rater, dafür wurden die jeweiligen Appstore Beschreibungen gelesen. Dabei mussten die Apps nicht spezifisch für chronisch entzündliche Darmerkrankungen sein, sondern lediglich mit dem Thema Gesundheit assoziiert sein. Folgende Punkte wurden als Einschlusskriterien ausgewählt: (1) deutsche Sprache, (2) Verfügbarkeit in beiden Appstores, (3) Patienten oder Ärzte als Zielgruppe, (4) CED spezifische oder für CED relevante Apps, oder zumindest Gesundheit assoziierte Apps. Ausschlusskriterien waren (1) Kongressapps, (2) Journalapps, (3) Apps die nur im Rahmen von Studien verwendet wurden, (4) inaktive Apps und (5) Apps die nur in einem der beiden Appstores verfügbar waren. Anschließend erfolgte die Bewertung der Apps durch insgesamt 6 Ärzte wobei jeweils 4 Apps von allen 6 Ratern bewertet wurden, die anderen 10 Apps wurden nach dem Zufallsprinzip zugeordnet und jeweils von einem Android und einem iOS Nutzer anhand der mobile app rating scale (MARS), die durch Stoyanov entwickelt wurde, bewertet (6). Zuvor schauten sich, wie durch die Entwickler von MARS empfohlen, alle der bewertenden Ärzte das Trainingsvideo an. Die bewerteten Apps wurden jeweils mindestens 10 Minuten durch die bewertenden Ärzte getestet. Anschließend erfolgte die statistische Analyse und Auswertung der Ergebnisse mittels der Open Source Software R Foundation (Version 3.5.3; R Foundation) und Einordnung der Ergebnisse.
Zudem wurden die Apps auf Zusatzfunktionen wie Tagebuchfunktion, Medikamenten-Erinnerung und Toilettenfinder gescreent, welche in der Tabelle 1 des Orginalartikels aufgeführt wurden. In dieser Tabelle wurden zudem die Zielgruppe, Krankheitsspezifität, Entwickler, technische Aspekte, Studienverfügbarkeit, Zulassung als Medizinprodukt, Datenschutzbestimmung der App aufgeführt. Diese Zusatzfunktionen bzw. Informationen wurden durch manuelles Screening erlangt, indem die jeweiligen Apps getestet und nach diesen Funktionen durchsucht wurden, Zudem wurden die Homepages der Betreiber und Informationen in den Appstores gelesen.
Ergebnisse und Beobachtungen
Bei der initialen automatisierten Suche mittels Webcrawler erhielten wir 1764 Treffer. Nach manueller Anwendung der Ein- und Ausschlusskriterien konnten 14 Apps identifiziert werden. Dabei wurden 1386 Apps entfernt, bei denen kein Bezug zu CED oder zu dem Thema Gesundheit bestand 317 Apps wurden aussortiert, da sie nicht in deutscher Sprache verfügbar waren, 5 Kongress-Apps und 6 Apps die nur im Rahmen von Studien angewendet werden konnten wurden ebenfalls ausgeschlossen. 7 weitere Apps wurden ausgeschlossen, da sie nur in Verbindung mit einem zusätzlichen Device verwendbar waren. In den meisten Fällen handelte es sich dabei um einen häuslich anwendbaren Calprotectin Test, der zum Detektieren der Calprotectin Höhe im Stuhl verwendet wird. Von den übriggebliebenen Apps wurden weitere 20 Apps ausgeschlossen die nur in einem der beiden Appstores verfügbar waren, sowie 4 Journalapps, 3 Duplikate und eine inaktive App.
Keine der finalen 14 Apps war krankheitsspezifisch für Morbus Crohn oder Colitis ulcerosa, 3 der 14 Apps bezogen sich auf chronisch entzündliche Darmerkrankungen im Allgemeinen. Alle 14 analysierten Apps waren für die Nutzung durch Patientin entwickelt, keine der Apps hatte Ärzte als Zielgruppe. Einige der Apps wiesen nützliche Zusatzfunktionen wie
3
Medikamenteneinnahme Erinnerungen, Toilettenfinder, Tagebuchfunktion auf. Diese sind zudem im Artikel in Tabelle 1 aufgeführt. Die App Deutsches Gesundheitsportal zitierte bei ihren Inhalten als einzige App direkt Studien. Die meisten der Apps wurden von pharmazeutischen Unternehmen oder Subunternehmen entwickelt. Keine der identifizierten Apps verwendete Krankheit spezifische Scores.
Die MARS Ratings der finalen Apps ergaben mediane Werte von 2,38/5 bis 4,11/5. Es zeigten sich dabei keine signifikanten Unterschiede zwischen Android und iPhone Bewertungen.
Praktische Schlussfolgerungen
Aktuell finden sich nur eine sehr geringe Anzahl an Apps, die CED-relevante Funktionen haben. Es ließen sich insgesamt drei CED-spezifische Apps mittels der oben aufgeführten Suchbegriffe identifizieren. Nur eine der Apps zitierte unmittelbar Studien um die aufgeführten Inhalte zu belegen. Die Subkategorie Informationen wurde mittels MARS Analyse sehr niedrig bewertet, wobei der Punkt Informationen über die Krankheit und mögliche Therapien oft die Hauptinteressen der Patienten sind. Bei keiner der untersuchten Apps wurden krankheitsspezifische klinische Aktivitätsscores wie der Harvey-Bradshaw Index für Morbus Crohn oder der partial Mayo Score für Colitis ulcerosa erhoben.
Für die Entwicklung zukünftiger Apps sollten sowohl Patienten als auch Wissenschaftler und Ärzte in die Entwicklung mit einbezogen werden. Des Weiteren sollten die jeweiligen Apps ausführliche Informationen zu den spezifischen Krankheitsbildern und möglichen Therapieoptionen beinhalten, dabei sollten die verwendeten Informationen mit Studien belegt werden, zudem sollten krankheitsspezifische Scores in die Apps implementiert werden. Die Entwickler der App sollten klar identifizierbar sein, des weiteren sollte ein einfacher und sicherer Datentransfer zwischen Patienten und behandelndem Team möglich sein.Background and aims
The field of telemedicine and so-called mobile health (mhealth) has now found its way into many areas of medicine. Among others it is used for monitoring chronic diseases and for communication with the treating team. So far, there are only few studies on individual diseases in which disease monitoring by means of apps or telemedicine has been investigated, but these have already shown some advantages. Among other things, it has been shown that telemedicine can reduce treatment costs and improve patient outcomes in diabetes, hypertension, COPD, heart failure and systemic lupus erythematosus.
In the context of the Sars COV-2 pandemic, mhealth and telemedicine increasingly came to the fore in order to significantly reduce unnecessary hospital stays and doctor visits. Furthermore, in Germany, the Digital Care Act, which came into force in December 2019, created the basis to prescribe apps to patients.
The aim of this work is to identify currently available apps that are useful for the management of inflammatory bowel disease (IBD), to perform a standardized evaluation using MARS, and to make recommendations for the development of future apps.
Design and methods
A To identify available apps, the Google Playstore and Apple Appstore were searched for available CED associated apps. For this, the following search terms were used: "Crohn's disease," "ulcerative colitis," "CED," "inflammatory bowel disease," "IBD," "Crohn's disease," "ulcerative colitis," "UC," "inflammatory bowel disease," "Crohn's," and "colitis." The search was performed semi-automatically using "Webcrawler" software. This was followed by a manual selection of the preselected apps by 2 of the 6 app raters, for which the respective appstore descriptions were read. The apps did not have to be specific for inflammatory bowel disease, but health related. The following items were selected as inclusion criteria: (1) German language, (2) availability in both appstores, (3) patients or physicians as target group, (4) apps specific or relevant for CED, or at least health associated apps. Exclusion criteria were (1) congressional apps, (2) journal apps, (3) apps used only in the context of studies, (4) inactive apps, and (5) apps available only in one of the two app stores. Subsequently, the apps were rated by a total of 6 physicians, with 4 apps rated by all 6 raters, and the other 10 apps were randomly assigned and rated by one Android and one iOS user using the mobile app rating scale (MARS) developed by Stoyanov. Beforehand, as recommended by the developers of MARS, all of the rating physicians watched the training video. The rated apps were each tested at least 10 minutes in advance by the rating physicians. Subsequently, statistical analysis and evaluation of the results was performed using the open source software R Foundation (version 3.5.3; R Foundation) and classification of the results.
In addition, the apps were screened for additional functions such as diary function, medication reminder, toilet finder which were listed in Table 1. of the article. In this table, the target group, disease specificity, developer, technical aspects, study availability, approval as a medical device, privacy policy of the app were also listed. These additional functions or information were obtained through manual screening by testing the respective apps and searching for these functions, as well as reading the homepages of the operators and information in the app stores.
Observations and results
In the initial automated search using a web crawler, we received 1764 hits. After manual application of the inclusion and exclusion criteria, 14 apps were identified. Thereby, 1386 apps were removed that were not related to IBD or health, 317 apps were removed because they were not available in German, 5 congress apps and 6 apps that could only be used in the context of studies were also excluded. 7 additional apps were excluded because they could only be used in conjunction with an additional device. In most cases, the app was a calprotectin test to detect calprotectin levels in the stool. Of the remaining apps, a further 20 apps were excluded that were only available in one of the two app stores, as well as 4 journal apps, 3 duplicates and one inactive app.
None of the final 14 apps were disease-specific for Crohn's disease or ulcerative colitis, and 3 of the 14 apps were related to inflammatory bowel disease in general. All 14 apps analyzed were developed for patient use; none of the apps targeted physicians. Many of the apps had useful additional functions such as medication reminders, toilet finder, diary function which are listed in the article in Table 1. The app Deutsches Gesundheitsportal was the only one that directly cited studies in its content. Most of the apps were developed by pharmaceutical companies or subcontractors. None of the identified apps used disease-specific scores.
The MARS ratings of the final apps resulted in median scores of 2.38/5 to 4.11/5, with no significant differences between Android and iPhone ratings.
In addition, the apps were screened for additional functions such as diary function, medication reminder, toilet finder which were listed in Table 1. of the article. In this table, the target group, disease specificity, developer, technical aspects, study availability, approval as a medical device, privacy policy of the app were also listed. These additional functions or information were obtained through manual screening by testing the respective apps and searching for these functions, as well as reading the homepages of the operators and information in the app stores.
Conclusions
Currently, only a very small number of apps can be found that have IBD-relevant functions; a total of three IBD-specific apps could be identified using the search terms listed above. Only one of the apps directly cited studies to support the listed content. The subcategory information was rated very low using MARS analysis, with the item information about the disease and possible therapies often being the main interests of patients. None of the apps studied collected disease-specific activity scores such as the Harvey-Bradshaw Index for Crohn's disease or the partial Mayo Score for ulcerative colitis.
For the development of future apps, patients, scientists as well as physicians should be involved in the development. Furthermore, the respective apps should contain detailed information on the respective clinical pictures and possible therapy options, the information used should be supported by studies, and disease-specific scores should be implemented in the apps. The developers of the app should be clearly identifiable, and simple and secure data transfer between the patient and the treating team should be possible
Sacral neuromodulation for constipation and fecal incontinence in children and adolescents – study protocol of a prospective, randomized trial on the application of invasive vs. non-invasive technique
Get PDFBackground A therapeutic effect of sacral neuromodulation (SNM) on fecal incontinence (FI) and quality of life has been proven in adults. SNM is, however, rarely used in pediatric cases. The aim of the study is to investigate effects of SNM in pediatric constipation in a prospective parallel-group trial. Methods A monocentric, randomized, unblinded, parallel-group trial is conducted. SNM is conducted in the invasive variant and in an innovative, external approach with adhesive electrodes (enteral neuromodulation, ENM). We include patients with constipation according to the ROME IV criteria and refractory to conventional options. Patients with functional constipation and Hirschsprung’s disease are able to participate. Participants are allocated in a 1:1 ratio to either SNM or ENM group. Clinical data and quality of life is evaluated in regular check-ups. Neuromodulation is applied continuously for 3 months (end point of the study) with follow-up-points at 6 and 12 months. Findings are analyzed statistically considering a 5% significance level ( p ≤ 0.05). Outcome variables are defined as change in (1) episodes of abdominal pain, (2) episodes of FI, (3) defecation frequency, (4) stool consistency. Improvement of proprioception, influence on urinary incontinence, quality of life and safety of treatment are assessed as secondary outcome variables. We expect a relevant improvement in both study groups. Discussion This is the first trial, evaluating effects of neuromodulation for constipation in children and adolescents and comparing effects of the invasive and non-invasive application (SNM vs. ENM). Trial registration The study is registered with clinicaltrials.gov, Identifier NCT04713085 (date of registration 01/14/2021).Open Access funding enabled and organized by Projekt DEAL.Deutsche Gesellschaft für KoloproktologieUniversitätsklinikum Erlangen (8546
Histomolecular classification of urothelial carcinoma of the urinary bladder
No full textZusammenfassung Hintergrund Muskelinvasive Urothelkarzinome (MIUC) der Harnblase repräsentieren ca. 25 % aller Urothelkarzinome (UC) und weisen eine 5‑Jahres-Überlebensrate von ca. 50 % auf. Bisher haben Erkenntnisse aus der molekularen Klassifikation der MIUCs noch keinen Einfluss auf die klinische Praxis genommen. Ziel Ziel der Arbeit ist die Vorhersage molekularer Konsensus-Subtypen in MIUCs mittels Künstlicher Intelligenz (KI) anhand histologischer Hämatoxylin-Eosin(HE)-Schnitte. Material und Methoden Durchgeführt wurde ein pathologisches Review und die Annotation von Tumorarealen in der Bladder-Cancer(BLCA)-Kohorte ( N = 412) des „The Cancer Genome Atlas“ (TCGA) und der BLCA-Kohorte ( N = 181) des Dr. Senckenbergischen Instituts für Pathologie (SIP). Anhand der annotierten Histomorphologie zur Vorhersage molekularer Subtypen wurde ein KI-Modell trainiert. Ergebnisse In einer 5fachen Kreuzvalidierung mit TCGA-Fällen ( N = 274), internem TCGA-Testset ( N = 18) und externem SIP-Testset ( N = 27) erreichten wir durchschnittliche Werte der „area under the receiver operating characteristic curve“ (AUROC) von jeweils 0,73, 0,8 und 0,75 zur Klassifikation der verwendeten molekularen Subtypen „luminal“, „basal/squamous“ und „stroma-rich“ . Durch Training auf Korrelationen zu einzelnen molekularen Subtypen statt auf eine Subtypzuordnung pro Fall konnte die KI-Vorhersage von Subtypen signifikant verbessert werden. Diskussion Nachfolgestudien mit RNA-Extraktion aus verschiedenen Bereichen KI-vorhergesagter molekularer Heterogenität könnten molekulare Klassifikationen und damit die darauf trainierten KI-Modelle verbessern.Background Of all urothelial carcinomas (UCs), 25% are muscle invasive and associated with a 5-year overall survival rate of 50%. Findings regarding the molecular classification of muscle-invasive urothelial carcinomas (MIUCs) have not yet found their way into clinical practice. Objectives Prediction of molecular consensus subtypes in MIUCs with artificial intelligence (AI) based on histologic hematoxylin-eosin (HE) sections. Methods Pathologic review and annotation of The Cancer Genome Atlas (TCGA) Bladder Cancer (BLCA) Cohort ( N = 412) and the Dr. Senckenberg Institute of Pathology (SIP) BLCA Cohort ( N = 181). An AI model for the prediction of molecular subtypes based on annotated histomorphology was trained. Results For a five-fold cross-validation with TCGA cases ( N = 274), an internal TCGA test set ( N = 18) and an external SIP test set ( N = 27), we reached mean area under the receiver operating characteristic curve (AUROC) scores of 0.73, 0.8 and 0.75 for the classification of the used molecular subtypes “luminal” , “basal/squamous” and “stroma-rich” . By training on correlations to individual molecular subtypes, rather than training on one subtype assignment per case, the AI prediction of subtypes could be significantly improved. Discussion Follow-up studies with RNA extraction from various areas of AI-predicted molecular heterogeneity may improve molecular classifications and thereby AI algorithms trained on these classifications.Open Access funding enabled and organized by Projekt DEAL.Johann Wolfgang Goethe-Universität, Frankfurt am Main (1022