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Sarcopenia as an outcome marker in children with solid organ malignancies
Get PDFBackground: Children with hepatoblastoma (HB) are at risk of sarcopenia due to immobility, chemotherapy, and malnutrition. We hypothesized that children with HB have a low preoperative total psoas muscle area (tPMA), reflecting sarcopenia, which negatively impacts outcome.
Procedure: Retrospective study of children (1-10 years) with hepatoblastoma treated at a large university children’s hospital from 2009 to 2018. tPMA was measured as the sum of the right and left psoas muscle area (PMA) at intervertebral disc levels L3- 4 and L4-5. z-Scores were calculated using age- and gender-specific reference values and were compared to anthropometric measurements, clinical variables, and outcomes. Sarcopenia was defined as a tPMA z-score below −2.
Results: Thirty-three children were included. Mean tPMA z-score was −2.18 ± 1.08, and 52% were sarcopenic. A poor correlation between tPMA and weight was seen (r = 0.35; confidence interval [CI] 0.01, 0.62; P = .045), and most children had weights within the normal range (mean z-score −0.55 ± 1.39). All children categorized as high risk with relapse (n = 5/12) were sarcopenic before surgery. Relapse was significantly higher in the high-risk sarcopenic group compared to the nonsarcopenic group (P = .008). The change in tPMA z-score 1-4 months after surgery did not improve in patients with relapse, but did improve in 75% of children without relapse.
Conclusions: The majority of children with HB were sarcopenic prior to surgery. Especially in children with high-risk hepatoblastoma, sarcopenia is an additional risk factor for relapse. Large multicenter studies are needed to confirm these preliminary results
Background: Sarcopenia describes a generalized loss of skeletal muscle mass, strength, or function. Determined by measuring the total psoas muscle area (tPMA) on cross-sectional imaging, sarcopenia is an independent marker for poor post- surgical outcomes in adults and children. Children with cancer are at high risk for sarcopenia due to immobility, chemotherapy, and cachexia. We hypothesize that sarcopenic children with neuroblastoma are at higher risk for poor post-operative outcomes.
Patients and Methods: Retrospective analysis of children with neuroblastoma ages 1–15 years who were treated at our hospital from 2008 to 2016 with follow-up through March 2021. Psoas muscle area (PMA) was measured from cross-sectional images, using computed tomography (CT) and magnetic resonance imaging (MRI) scans at lumbar disc levels L3-4 and L4-5. tPMA is the sum of the left and right PMA. Z- scores were calculated using age- and gender-specific reference values. Sarcopenia was defined as a tPMA z-score below −2. A correlation of tPMA z-scores and sarcopenia with clinical variables and outcome was performed.
Results: One hundred and sixty-four children with workup for neuroblastoma were identified, and 101 children fulfilled inclusion criteria for further analysis, with a mean age of 3.92 years (SD 2.71 years). Mean tPMA z-score at L4-5 was −2.37 (SD 1.02). Correlation of tPMA z-score at L4-5 with weight-for-age z-score was moderate (r = 0.54; 95% CI, 0.38, 0.66). No association between sarcopenia and short-term outcome was observed. Sarcopenia had a sensitivity of 0.82 (95% CI, 0.62–0.93) and a specificity of 0.48 (95% CI 0.36–0.61) in predicting 5-year survival. In a multiple regression analysis, pre-operative sarcopenia, pre-operative chemotherapy in the NB2004 high-risk group, unfavorable tumor histology, and age at diagnosis were associated with 5-year survival after surgery, with hazard ratios of 4.18 (95% CI 1.01– 17.26), 2.46 (95% CI 1.02–5.92), 2.39 (95% CI 1.03–5.54), and 1.01 (95% CI 1.00– 1.03), respectively.
Conclusion: In this study, the majority of children had low tPMA z-scores and sarcopenia was a risk factor for decreased 5-year survival in children with neuroblastoma. Therefore, we suggest measuring the tPMA from pre-surgical cross- sectional imaging as a biomarker for additional risk stratification in children with neuroblastoma
Wiederholte Schädelhirntraumata im American Football und ihre Auswirkungen auf die Mikrostruktur des Gehirns
Get PDFDiese kumulative Dissertation basiert auf zwei Originalarbeiten, die beide im Sommer 2021 in wissenschaftlichen Fachzeitschriften veröffentlicht wurden (“ Exposure to Repetitive Head Impacts Is Associated With Corpus Callosum Microstructure and Plasma Total Tau in Former Professional American Football Players” im Journal of Magnetic Resonance Imaging (Erstautorenschaft) und “Age at First Exposure to Tackle Football is Associated with Cortical Thickness in Former Professional American Football Players” im Journal Cerebral Cortex (Mitautorenschaft)). Beide Publikationen untersuchen die langfristigen Auswirkungen repetitiver, klinisch- und subklinisch verlaufender Kopferschütterungen (englisch: repetitive head impacts [RHI]) auf die Hirnstruktur anhand einer Kohorte ehemaliger American Football Spieler der National Football League (NFL). Die Daten entstammen der amerikanischen Studie „Diagnosing and Evaluating Traumatic Encephalopathy using Clinical Tests“ (DETECT). Grundlage der Bildgebung waren T1-gewichtete und diffusionsgewichtete Bilder der Magnetresonanztomographie (MRT).
In Arbeit 1 werden die langfristigen Auswirkungen der Exposition gegenüber wiederholten Schädelhirntraumata auf die weiße Substanz - hier das Corpus Callosum (CC) - untersucht. Des Weiteren wird der Zusammenhang zwischen mikrostrukturellen Veränderungen des CC und dem im Blutplasma gemessenen Protein Tau untersucht.
Arbeit 2 setzt das Alter der Probanden bei Aufnahme der Kontaktsportart (englisch: age at first exposure [AFE]) in Relation zur grauen Substanz anhand der kortikalen Dicke in verschiedenen Hirnarealen im höheren Lebensalter.
Beide Publikationen explorieren zudem die Assoziation von Mikrostruktur und kognitiver Funktion.This cumulative dissertation is based on two original papers, both published in scientific journals in the summer of 2021 (" Exposure to Repetitive Head Impacts Is Associated With Corpus Callosum Microstructure and Plasma Total Tau in Former Professional American Football Players" in the Journal of Magnetic Resonance Imaging (first authorship) and "Age at First Exposure to Tackle Football is Associated with Cortical Thickness in Former Professional American Football Players" in the Journal Cerebral Cortex (co-authorship)). Both publications examine the long-term effects of repetitive, clinical, and subclinical head impacts (RHI) on brain structure in a cohort of former American football players from the National Football League (NFL). The data originate from the american study "Diagnosing and Evaluating Traumatic Encephalopathy using Clinical Tests" (DETECT). Imaging was based on T1-weighted and diffusion-weighted images of magnetic resonance imaging (MRI).
Paper 1 investigates the long-term effects of exposure to repetitive head impacts (RHI) on white matter - in this case, the corpus callosum (CC). Furthermore, the relationship between microstructural changes of the CC and the protein tau measured in blood plasma is investigated.
Paper 2 relates the age at first exposure (AFE) of subjects to gray matter cortical thickness in different brain areas at advanced ages.
Both publications also explore the association of microstructure and cognitive function
Resolving the Hubble tension with Early Dark Energy
Get PDFVerschiedene Messungen der Hubble-Konstante, einem Maß für die Ausdehnungsgeschwindigkeit des Universums, ergeben abweichendeWerte. Kann diese Diskrepanz – bekannt als “Hubble-Tension” – nicht durch systematische Fehler in den Messungen erklärt werden, so könnte sie ein Hinweis auf neue physikalische Effekte jenseits des Standard-ΛCDM-Modells sein. Ein vielversprechendes Modell zur Behebung dieser Diskrepanz ist frühe dunkle Energie (Early Dark Energy,
EDE), eine Form von dunkler Energie, die im frühen Universum auftreten soll. In der Literatur besteht jedoch kein Konsens darüber, ob das EDE-Modell sowohl die Hubble-Tension lösen als auch die gute Übereinstimmung mit den Daten des kosmischen Mikrowellenhintergrunds und der großräumigen Struktur des Universums erhalten kann.
In dieser Dissertation beginnen wir mit einem kurzen Überblick über die nötigen Konzepte des Standard-ΛCDM-Modells, der Hubble-Tension, EDE und Statistik. Wir untersuchen den Ursprung gegensätzlicher Schlussfolgerungen zu EDE in der Literatur mithilfe einer Rasteranalyse und finden Hinweise darauf, dass technische Effekte in der Markov-Chain-Monte-Carlo-Analyse, sogenannte Volumeneffekte, eine große Rolle spielen und den Dissens in der Literatur erklären können. UmKonfidenzintervalle zu konstruieren, die unabhängig von Volumeneffekten sind, verwenden wir die Profile-Likelihood-Methode, eine Methode aus der frequentistischen Statistik, die selten für Analysen in der Kosmologie genutzt wird. Mithilfe des Profile-Likelihoods finden wir,
dass das EDE-Modell in der Lage ist, die Hubble-Konstante zu erhöhen, um die Hubble-Tension unter eine Signifikanz von 1,7σ zu reduzieren, während gleichzeitig eine gute Übereinstimmung mit allen in dieser Dissertation betrachteten Datensätzen gewährleistet wird. Obwohl EDE damit vielversprechende Eigenschaften in Bezug auf die Auflösung der Hubble-Tension zeigt, führt es auch zu einer erhöhten Amplitude der Dichteschwankungen im späten Universum, S8, was bereits
vorhandene Diskrepanzen bei Messungen von S8 verschlechtert. Wir untersuchen eine natürliche Erweiterung des EDE-Modells, die die Summe der Neutrinomassen als freien Parameter enthält, und bewerten, ob höhere Neutrinomassen die EDE-induzierte Erhöhung von S8 kompensieren können. Unsere Ergebnisse zeigen, dass dieses Szenario jedoch durch Messdaten der großräumigen Struktur des Universums stark eingeschränkt ist. Wir schlussfolgern, dass das EDE-Modell
ein möglicher Kandidat zur Auflösung der Hubble-Tension ist, während die gleichzeitige Behebung der S8-Diskrepanz anderer Erklärung bedarf.With the increasing precision of cosmological measurements, a number of discrepancies have emerged among which the Hubble tension, a mismatch between different measurements of the current expansion rate of the Universe, is the most significant. If not caused by systematics in the measurements, this tension could be a hint of new physics beyond the standard ΛCDM model. One of the most promising proposed solutions to this tension is Early Dark Energy (EDE), which
introduces a dark-energy-like component in the early Universe that decays very quickly around recombination. However, there is no consensus in the literature whether the tension-resolving EDE model can provide an adequate fit to cosmological data of the cosmic microwave background and large-scale structure (LSS) of the Universe. Further, it has been suggested that prior volume effects influence the constraints of the EDE model from Markov Chain Monte Carlo (MCMC) analyses, which originate in the specific parametrization of the model, and lead to a strong dependence of the constraints on the prior.
In this thesis, we begin by giving a brief overview about the necessary concepts of the standard ΛCDM model, the Hubble tension, EDE, and statistics. In order to understand the origin of different conclusions about EDE in the literature, we deconstruct the current constraints using a grid analysis and find evidence that prior volume effects affect the constraints of the EDE model from an MCMC analysis, suggesting that these effects are the reason behind the disagreement in the literature. Motivated by this, we use a profile-likelihood analysis to construct confidence intervals for the parameters of the EDE model. The profile likelihood, which is rarely used for cosmological parameter inference, is a standard tool in frequentist statistics to construct confidence intervals, which are independent of a prior and hence serve as a powerful tool to assess the influence of prior volume effects. With the profile likelihood, we find that the EDE model is able to raise the Hubble constant in order to reduce the Hubble tension below a significance of 1.7σ, while presenting a good fit to all data sets considered in this thesis. Although EDE shows promising properties with regards to resolving the Hubble tension, it is well known that introducing EDE comes at the cost of an increased clustering amplitude, which worsens the already existing tension in measurements of the clustering amplitude. We explore one well-motivated extension of the EDE model, which includes the sum of neutrino masses as a free parameter, and
assess whether higher neutrino masses can compensate the EDE-induced clustering enhancement. We find that this scenario is disfavored since higher neutrino masses within the EDE model are tightly constrained by LSS data
Designing better policies: three applications of behavioral economics to health and development policies
Get PDFTherapieprädiktion und Verlaufsevaluation bei stationären depressiven Patienten mit Hilfe des Beck-Depression-Inventar II (BDI-II)
Get PDFIn dieser Doktorarbeit wurde die Effektivität des etablierten Depressionsfragebogens BDI-II zum frühzeitigen Erkennen von therapierefraktären Patienten untersucht. Es zeigte sich, dass es möglich ist, bei Patienten bereits im frühen Behandlungsverlauf eine unzureichende Verbesserung der depressiven Symptomatik mit dem BDI-II fest zu stellen, wodurch im weiteren Verlauf auf eine Nonresponse geschlossen werden kann.
In dieser prospektiven klinischen Studie wurden 134 Patienten über einen Zeitraum von 4 Wochen beobachtet. 94 % der mit dem BDI-II ermittelten Non-Improver NI2(20), können auch später keine Response erreichen. Der negative prädiktive Wert liegt im oberen Bereich des in der Literatur beschriebenen Intervalls. Der BDI-II erkennt genauso gut Early Improvement und vor allem das Ausbleiben des Early Improvements mit der folgenden Non-Response, wie dies z.B. mit dem Fremdbeurteilungsfragebogen Hamilton in anderen Studien gezeigt werden konnte. Die vorliegende Dissertation konnte somit also zeigen, dass nicht nur mit einem Fremdbeurteilungstool die Prädiktion durch Early Improvement nachweisbar ist, sondern auch mit dem Selbstbeurteilungsfragebogen BDI-II. Das ist für die Praxis eine enorme Zeitersparnis und eine wichtige Erkenntnis in der Forschung zur Behandlung von Depressionen
Mental health and psychosocial relations in the context of the COVID-19 pandemic: investigation of maternal, paternal, young children, and student populations
Get PDFEvaluationsmethoden für mobile Anwendungen in der gesundheitlichen Versorgung
Get PDFMobile Anwendungen spielen in der gesundheitlichen Versorgung zunehmend eine größere Rolle und haben das Potential, die Versorgung zu verbessern bei gleichzeitig möglicher Kosteneinsprung. In der Literatur ist die Abkürzung mHealth für den englischsprachigen Begriff mobile health gebräuchlich. mHealth-Anwendungen sind eine Unterkategorie von electronic health (eHealth)-Anwendungen. eHealth bezeichnet Anwendungen, bei denen Informations- und Kommunikationstechnologien (IKT) zur Behandlung und Betreuung von Patientinnen und Patienten genutzt werden. mHealth-Anwendungen verwenden dabei mobile IKTs. Der Begriff mHealth-Anwendungen beinhaltet sowohl die ausschließlich für den Endnutzer-Markt konzipierten Anwendungen als auch Applikationen für den Einsatz im professionellen Bereich.
Für die zunehmende Verbreitung von mHealth-Anwendungen sind mehrere Faktoren verantwortlich. Zum einen haben Rechenleistung und Kapazität mobiler Endgeräte in den vergangenen Jahren stark zugenommen. Zusätzlich steht durch den kontinuierlichen Netzausbau in vielen Gebieten eine stabile breitbandige Mobilfunkverbindung zur Verfügung.
Nachdem mHealth-Anwendungen anfänglich fast ausschließlich von Patienten selbst bezahlt werden mussten, entstehen nun erste Finanzierungsmöglichkeiten durch die öffentlichen Kostenträger. Durch das 2019 eingeführte Digitale-Versorgung-Gesetz (DVG) haben gesetzlich Krankenversicherte in Deutschland einen verbrieften Anspruch auf digitale Gesundheitsanwendungen (DiGAs).
Ziel der Dissertation ist es, eine kritische Übersicht über die Bewertungsmethoden für mHealth-Anwendungen zu geben und Empfehlungen für weitere Entwicklungen zu geben.
In einem Herausgeberwerk mit dem Titel „mHealth-Anwendungen für chronisch Kranke“ wurden Beiträge über verschiedene Anwendungsgebiete für mHealth-Anwendungen zusammengestellt, um die Breite der Anwendungsbereiche aufzuzeigen. Beispiele sind die Versorgung und Prävention von chronischen Rückenschmerzen, KI-gestütztes Wundmanagement und die Versorgung von Patienten mit Herzinsuffizienz. Und es wurde ein Systematic Review zu mHealth-Anwendungen für chronische Schmerzpatienten durchgeführt. Die Ergebnisse legen nahe, dass insbesondere bei der Schmerzlinderung eine Behandlung über mHealth-Anwendungen langfristig hilfreich sein kann.
Während erste Bewertungssysteme speziell für mHealth-Anwendungen entwickelt wurden, werden vorwiegend die Bewertungssysteme für eletronic Health (eHealth)-Anwendungen bei der Bewertung von mHealth-Anwendungen verwendet. Diese müssen jedoch angepasst werden. In vielen nationalen und internationalen Fachgesellschaften der Medizininformatik gibt es Arbeitsgruppen für Evaluationen und Health Technology Assessment (HTA). Zusätzlich zu den oben genannten Bewertungssystemen für eHealth gibt es für mHealth-Anwendungen auch etablierte akademische Bewertungssysteme. Ein anerkanntes und validiertes wissenschaftliches Bewertungssystem ist die Mobile App Rating Scale (MARS). Die deutschsprachige Version der MARS, die G-MARS wurde verwendet, um die in Deutschland verfügbaren Apps für COVID-19 zu bewerten. Alle Anwendungen erhielten durchweg hohe Bewertungsscores (mit der niedrigsten Bewertung in der Kategorie „Engagement“). Die von Experten kritisierten Datenschutzprobleme einer App hatten keinen Einfluss auf die Bewertung.
Eine erste Scoping Review zu den in der publizierten Literatur über mHealth-Anwendungen verwendeten Bewertungsmethoden zeigt, dass häufig singuläre Messungen zu krankheitsbezogenen, klinischen Parametern und im Hinblick auf die Nutzerperspektive durchgeführt werden. Ökonomische Bewertungen sind selten, Interoperabilität wurde in keiner Studie betrachtet. Bei einem systematischen Review zu den verwendeten Bewertungsmethoden für mHealth-Anwendungen für KHK wurden 38 Studien analysiert. Am häufigsten wurden Kriterien wie Usability, Motivation und Benutzererfahrung anhand von standardisierten Fragebögen und Nutzungsprotokollen evaluiert. Klinische Resultate wurden durch Labordiagnostik und standardisierte Fragebögen zur Lebensqualität bewertet. Weiterhin erfolgten ökonomische Bewertungen im Rahmen von Kosten-Wirksamkeits-Analysen.
Eine im ländlichen Kamerun durchgeführte Machbarkeitsstudie einer mHealth-Anwendung für Diabetes-Patienten zeigte das große Potential zur Verbesserung des Zugangs zu medizinischer Versorgung. Allerdings zeigte sich auch die Wichtigkeit der Auswahl der richtigen Zielvariablen, da viele Studienteilnehmer nicht das mHealth-System, sondern nur die Verfügbarkeit der Blutzuckermessgeräte bewerteten.
Ein Online-Panel mit anschließender Experten-Diskussion zu Bewertungsmethoden mit Beispielen aus verschiedenen Bereichen der medizinischen Informatik zeigte, dass alle derzeit verwendeten Bewertungsmethoden nur Einzelaspekte berücksichtigen und wichtige Faktoren vernachlässigen. Die Wahl des richtigen Studiendesigns wurde diskutiert. Durch eine mehrstufige Experten-Befragung mittels einer Delphi-Survey wurde eine Liste von essenziellen Bewertungsindikatoren für mHealth-Anwendungen erstellt. Die Liste umfasst 81 Indikatoren, gruppiert in die drei Kategorien des Qualitätsmodells von Donabedian (Struktur, Proess und Ergebnis). Die Strukturqualität hatte die meisten Elemente, während die Ergebnisqualität die wenigsten aufweist. Auch die Anzahl der Elemente bei der Prozessqualität ist beachtlich.
Im letzten Teil des Dissertationsprojekts wurde das Bewertungssystem für die Erstattungsfähigkeit im Rahmen des DVG für DiGAs analysiert. Das für die Entscheidung zur Erstattung von DiGAs entwickelte Fast-Track-Verfahren hat Schwächen. Ethische und soziale Aspekte fehlen. Eine generelle Einschränkung der DiGAs ist, dass nur Medizinprodukte der Risikoklassen I und II darunterfallen. mHealth-Anwendungen, die ausschließlich zu Prävention dienen, sind kein Medizinprodukt und sind deswegen auch nicht als DiGA erstattungsfähig.
In der publizierten Literatur werden nur selten bis keine holistischen Bewertungen durchgeführt, sondern oft nur singuläre Aspekte bewertet. Dadurch ist die Vergleichbarkeit verschiedener Anwendungen untereinander sehr schwierig. Die größte Herausforderung ist die Balance zwischen der Bewertung von neuen Anwendungen, die durch schnelle technische Fortschritte immer öfter zur Verfügung stehen und der Detailtiefe der Bewertung. Wird eine Bewertung mit sehr hoher Qualität durchgeführt, kann die Anwendung bereits vor Ende der Evaluation veraltet sein. Die Betrachtung von ethischen Aspekten spielt eine wichtige Rolle, wird aber bei aktuellen Verfahren öfter vernachlässigt. Aktuell werden im Rahmen von Bewertungen zu wenig Daten zu den wirtschaftlichen Gesamtkosten von mHealth-Anwendungen erhoben. Es ist daher bei der zukünftigen Weiterentwicklung von Bewertungssystemen für mHealth-Anwendungen darauf zu achten, dass neben krankheitsgerechter klinischer Outcome-Bewertungen auch die sozioökonomische Komponente in Form eines Kostenvergleichs der Intervention mit dem Versorgungsstandard erfasst wird. Diese Informationen sollten in die Kosten-Nutzen-Bewertung eingebaut werden.
Weitere Herausforderungen sind die Eingruppierung von Apps innerhalb der europäischen Medical Device Regulation. Zur Bewertung von Aspekten der künstlichen Intelligenz als Teil einer App gibt es noch kaum Veröffentlichungen, vor allem bezogen auf die Risikoabschätzung solcher Komponenten. Da die Entwicklungen in diesem Bereich aber sehr schnell voranschreiten, besteht hier einiger Nachholbedarf.Mobile applications are playing an increasingly important role in health care and have the potential to improve care while potentially reducing costs. In the literature, the abbreviation mHealth is commonly used for the term mobile health. mHealth applications are a subcategory of electronic health (eHealth) applications. eHealth refers to applications in which information and communication technologies (ICTs) are used to treat and care for patients. mHealth applications use mobile ICTs. The term mHealth includes applications designed exclusively for the end-user market and applications for use in the professional sector.
Several factors are responsible for the increasing spread of mHealth applications. Mobile devices' computing power and capacity have increased significantly in recent years. In addition, a stable broadband mobile connection is available in many areas due to the continuous expansion of the network.
While mHealth applications initially had to be paid for almost exclusively by patients, the first financing opportunities are now emerging from public payers. As a result of the Digital Health Care Act (DVG), introduced in 2019, people with statutory health insurance in Germany have a securitized entitlement to digital health applications (DiGAs).
The dissertation aims to provide a critical overview of the evaluation methods for mHealth applications and to make recommendations for further developments.
In an edited series entitled "mHealth applications for the chronically ill," contributions on various areas of application for mHealth applications were compiled to show the breadth of application areas. Examples include chronic back pain care and prevention, AI-assisted wound management, and heart failure patient care. And a systematic review was conducted on mHealth applications for chronic pain patients. The results suggest that treatment via mHealth applications can be helpful in the long term, particularly for pain relief.
While initial evaluation systems were developed specifically for mHealth applications, the evaluation systems for eHealth applications are predominantly used in the evaluation of mHealth applications. However, these need to be adapted. Many national and international medical informatics societies have working groups for evaluations and Health Technology Assessment (HTA). In addition to the evaluation systems for eHealth mentioned above, there are also established academic evaluation systems for mHealth applications. The Mobile App Rating Scale (MARS) is a recognized and validated academic rating system. The German version of the MARS, the G-MARS, was used to rate the apps available in Germany for COVID-19. All apps received consistently high scores (with the lowest in the "engagement" category). The privacy issues of one app, criticized by experts, did not influence the rating.
An initial scoping review of the evaluation methods used in the published literature on mHealth applications shows that singular measurements on disease-related, clinical parameters and concerning the user perspective are frequently performed. Economic evaluations are rare, and interoperability has not been considered in any study. In a systematic review on the evaluation methods used for mHealth applications for coronary heart disease, 38 studies were analyzed. Criteria such as usability, motivation, and user experience were most commonly evaluated using standardized questionnaires and usage protocols. Clinical outcomes were evaluated by laboratory diagnostics and standardized quality of life questionnaires. Furthermore, economic evaluations were conducted in the context of cost-effectiveness analyses.
A feasibility study conducted in rural Cameroon for a mHealth application for diabetes patients showed the great potential to improve access to care. However, it also revealed the importance of selecting the right outcome variable, as many study participants did not rate the mHealth system but only the availability of blood glucose meters.
An online panel followed by an expert discussion on evaluation methods with examples from different areas of medical informatics showed that all currently used evaluation methods only consider single aspects and neglect important factors. The choice of the proper study design was discussed. A multi-stage expert survey using a Delphi survey created a list of essential evaluation indicators for mHealth applications. The list includes 81 indicators grouped into the three categories of Donabedian's quality model (structure, process, and outcome). Structure quality had the most elements, while outcome quality had the fewest. The number of factors in process quality is also considerable.
The final part of the dissertation project analyzed the evaluation system for reimbursement eligibility under the DVG for DiGAs. The fast-track process developed for the decision to reimburse DiGAs has weaknesses. Ethical and social aspects are missing. A general limitation of DiGA is that only risk classes I and II medical devices are covered. mHealth applications solely for preventive purposes are not medical devices and therefore not reimbursable as DiGA.
In the published literature, holistic evaluations are rarely performed, but only singular aspects are often evaluated, making it very difficult to compare different applications. The main challenge is to balance the assessment of new applications, which are increasingly available due to rapid technical advances, with the level of detail of the assessment. If an evaluation is performed with very high quality, the application may be obsolete before the end of the evaluation. The consideration of ethical aspects plays an important role but is more often neglected in current procedures. Currently, too little data is collected on the total economic costs of mHealth applications as part of evaluations. Therefore, in the future de-velopment of evaluation systems for mHealth applications, care should be taken to ensure that, in addition to disease-specific clinical outcome evaluations, the socioeconomic component is also recorded in the form of cost comparison of the intervention with the standard of care. This information should be built into the cost-benefit assessment.
Other challenges include the categorization of apps within the European Medical Device Regulation. There are still hardly any publications on the evaluation of artificial intelligence aspects as part of an app, especially related to the risk assessment of such components. However, as developments in this area progress rapidly, these aspects must be included in evaluations
Experimental volcanic lightning under early Earth conditions: Implications for prebiotic synthesis and the origin of life
Get PDFThe emergence of life is one of the most enigmatic and substantial questions in human existence. Although science has advanced progressively unraveling many potential reaction mechanisms and discovering many puzzle pieces to explain the emergence of life, it is still not fully understood nor reproducible under laboratory conditions. The emergence of life remains a mystery.
The search for the emergence of life includes the search for a geologically plausible environmental setting. A plausible environmental setting must provide all necessary prerequisites like a source of energy to initiate chemical reactions, a sufficient concentration of the abiotic building blocks for life, liquid water, temperature conditions enhancing chemical reactions but not destroying organic molecules, and disequilibrium conditions. The search for plausible environmental settings for the emergence of life is a challenging task as Earth's system has changed significantly since its origin. The atmosphere has changed significantly from an an-oxic state to its current oxic conditions. Oxygen is a waste product of today’s metabolism, so free oxygen was almost nonexistent before the emergence of life. The ocean composition and oxidation state have also changed significantly since the Earth’s origin. Unfortunately, no geological rock record survived from the time most plausible for the emergence of life and the exact geological conditions of early Earth are not known today.
Many plausible environmental settings have been proposed in the research concerning the emergence of life. Here, the focus is on active volcanic settings. Volcanoes were active on early Earth and represented a highly diverse environment. Surrounded by the early Earth’s ocean, volcanic eruptions were the leading source of volatiles in the primary atmosphere. In addition to the heat emitted by magma, volcanic lightning also accompanies these explosive erruptions; both of which are important energy sources for prebiotic reactions. Recent explosive volcanism is accompanied by volcanic lightning: electrical discharges in and/or from the eruption column. The electrical activity within a volcanic plume can be characterized into three categories, whereby the boundaries overlap. Close to the vent, smaller discharges, vent-discharges, and near-vent lightning are observable. Further up in the plume, a large and impressive plume lightning takes place. Various charging and discharging mechanisms contribute in different amounts to each of those three discharge categories. This thesis focuses on near-vent lightning, which is dominantly generated by triboelectrification. Triboelectrification describes the process of frictional, non-disruptive interaction between the expelled ash particles. A grain size-dependent charging is observed during this process: smaller particles tend to charge negatively, whereas larger particles obtain a positive charge due to their frictional interaction with the smaller particles. The separation of the charged particles results in discharges. As discharges are regarded as one potential prebiotic synthesis mechanism for creating the first organics, the aim of this thesis is to determine the impact of environmental conditions as the atmospheric composition on the discharge behavior in experimentally generated volcanic lightning.
An experimental setup to recreate different atmospheric compositions relevant to early Earth and extra-terrestrial bodies was built, as the atmospheric composition and pressure changed during the evolution of the Earth. This setup makes it possible to explore the influencing parameters of volcanic lightning and test if volcanic lightning might have been equally efficient under those conditions as it had been in current volcanic eruptions (Chapter 2). The experimental setup needs a gas-tight and secure supply of various gases. For this thesis, the impact of CO2 and CO as components of the enveloping atmosphere was tested on volcanic lightning, and equally vigorous generation of near-vent discharges compared to experiments conducted in an atmosphere containing current air was observed. To test the impact of the transporting gas phase, two transporting gas phases (argon and nitrogen) were used in the experiments. The change in transporting gas phase significantly changes the magnitude and number of detected near-vent discharges. Those results imply that the exsolved gas phase in the volcanic plume significantly impacts near-vent discharges. The recovered ash was analyzed for organic compounds by GC/MS, but no newly formed organic compounds were detected in the samples.
Also, the overall magma composition of volcanic eruptions has changed over time. Therefore, the ability of two different volcanic materials, a phonolitic pumice and a recent tholeiitic basalt, to create discharges was compared against an analog material made of synthetic soda-lime glass beads (Chapter 3). The experimental generation of discharges allowed us to apply similar eruption conditions (10 MPa). The results demonstrate that all three materials can produce discharges during an eruption. To further evaluate the parameters governing the intensity and number of discharges, experiments to investigate the influence of grain size distribution on the bimodally distributed grain size compositions were performed. Each material's coarse and fine grain size fraction was mixed and used in the decompression experiments. The results demonstrated that for the synthetic soda-lime glass beads and the tholeiitic basalt, the abundance of a very fine grain size fraction (< 10 µm) was necessary to produce discharges. The more porous phonolitic pumice needed a broader grain size distribution to generate detectable discharges. Nonetheless, the abundance of fines was crucial to generate discharges for the pumice. The analysis of the high-speed recordings of the decompressed jets suggested that the coupling of the particles to the transporting gas-phase is the main governing factor controlling the generation of charge and discharge between particles.
Additionally, as clay minerals in mud are a widely used material in the prebiotic context, experiments investigating discharges in mud eruptions as a potential ignition mechanism were performed (Chapter 4). Modern mud volcanism represents a source of methane emission, a highly reactive reducing gas. Today, very explosive, destructive mud eruptions are often accompanied by spectacular flames that can sustain for centuries. As the previous experiments suggest discharges between particles as a potential energy source for reactions in reducing gas phases, it was tested if potential discharges might occur, which could potentially ignite the methane-gas emitted in those eruptions. The mud samples analyzed in this study originate from the Davis-Schrimpf location (California, USA). Careful sample preparation caused only slight changes in the grain size distribution of the sampled mud. For safety reasons, the transporting gas phase was not methane but argon. The dried samples showed intense discharges during decompression. To test the influence of grain size distribution and humidity, a fraction of the dry samples was mixed with coarser sand grains, and another fraction was exposed to controlled humid conditions. Increasing the humidity and coarse grain size fraction decreases the number and magnitude of discharges. The results demonstrate that dry natural mud samples can cause discharges, representing a potential ignition mechanism in natural mud eruptions.
The experimentally obtained results emphasize the probability of volcanic lightning as a potential prebiotic synthesis mechanism on early Earth as in the experiments with an enveloping atmosphere containing CO2, N2 and CO discharges were successfully detected. The environmental conditions so far tested in the experiments permit near-vent discharges, which can react with the transporting gas phase of the plume, in the experimental case, the jet. The results obtained so far strongly encourage further investigation of active volcanic settings as a potential environment for the emergence of life