Risk factors for oral mucositis in paediatric oncology patients receiving alkylant chemotherapy

BACKGROUND: We describe the risk indicators for oral mucositis (OM) in paediatric oncology patients hospitalised in the Institut Gustave Roussy (Villejuif-Paris) and treated with alkylant chemotherapy with autologous peripheral blood progenitor cells. METHODS: The sample was selected using PIGAS software. Three groups of subjects received different chemotherapy regimens: A. Melphalan, B. Busulfan and C. other alkylant protocols. The degree of mucositis was recorded by CTC version 2.0 (Common Toxicity Criteria). Descriptive statistics were performed. The association between mucositis and risk indicator variables was tested using a χ(2 )test. The association between case status and covariates was tested using unconditional logistic regression analysis. RESULTS: Of the 337 children enrolled, 241 showed mucositis (group 1) and 96 did not show mucositis (group 2) during alkylant chemotherapy. There was a higher prevalence of male patients in both groups. The three different chemotherapy regimen groups are correlated with the appearance of oral mucositis (χ(2 )= 22.42, p < 0.01). Weight loss was higher in group 1 (χ(2 )= 6.31, p = 0.01). The duration of aplasia was lower in the Busulfan protocol (7.5 days) than in the Melphalan group (9.3 days) or the other regimens (8.6 days). The use of Bufulfan(® )was directly associated with case status (presence of oral mucositis): odds ratio [OR] = 2.1 and confidence interval [95%CI] = 1.3–3.0. Also, occurrences of germinal tumours and secondary bacterial infections were directly linked with case status: [OR] = 1.4 and 1.8, confidence interval [95%CI] = 1.2 – 1.7 and 1.1 – 2.5, respectively. CONCLUSION: The presence of OM was associated with the three different chemotherapy regimens considered; in particularly patients treated with Busulfan had the highest prevalence

Quality of life and home enteral tube feeding: a French prospective study in patients with head and neck or oesophageal cancer

A prospective study was conducted to evaluate the impact of home enteral tube feeding on quality of life in 39 consecutive patients treated for head and neck or oesophageal cancer at the Centre François Baclesse in Caen, France. Patients were taken as their own controls. Quality of life was evaluated using the EORTC QLQ-C30 core questionnaire, and the EORTC H&N35 and OES24 specific questionnaires. The feeding technique tolerance was evaluated using a questionnaire specifically developed for this study. Two evaluations were made, the first a week after hospital discharge (n = 39) and the second 3 weeks later (n = 30). Overall, the global health status/quality of life scale score slightly improved; among symptoms, scale scores that significantly improved (P< 0.05) concerned constipation, coughing, social functioning and body image/sexuality. The physical feeding technique tolerance was acceptable while the technique was psychologically less tolerated with two-thirds of the patients longing to have the tube removed. Onethird of the patients was also uncomfortable about their body image. Home enteral tube feeding was responsible for not visiting family or close relations in 15% of patients, and not going out in public in 23%. We conclude that home enteral tube feeding is a physically well accepted technique although a substantial proportion of patients may experience psychosocial distress. © 2000 Cancer Research Campaig

Cisplatin-based adjuvant chemotherapy in patients with completely resected non-small-cell lung cancer

BACKGROUND

Assessment of goal-directed closed-loop management in intensive care medicine

Given an aging population, shortage of nursing staff and a continuously increasing workload, automation in the medical sector is an important aspect of future intensive care. Although automation and machine learning are current research topics, progress is still very limited in comparison to other application areas. Probably one of the most serious problems is data shortage in a heterogeneous landscape of medical devices with limited interfaces and various protocols. In addition, the recording of data or, even more so, the evaluation of automation is limited by a complex legal framework. Given these complications and the sensitive legal nature of medical records, only very limited data is accessible for further analysis and development of automated systems. For this reason, within the context of this thesis various solutions for data acquisition and automation were developed and evaluated concomitant to two clinical studies utilizing a large animal model in a realistic intensive care setting at the University Hospital Tübingen. Foremost, to overcome the problems of data availability and interconnection of medical devices, a software framework for data collection and remote control using a client-server architecture was developed and significant amounts of research data could be collected in a central database. Furthermore, a closed-loop controller based on fuzzy logic was developed and used for management of end-tital CO2, glucose, and other parameters to stabilize the animal subjects during therapy and reduce caregivers’ workload. In addition to the fuzzy controller, closed-loop management for temperature and anticoagulation could be established by developing hardware interfaces for a forced-air warming unit and a point-of-care analysis device, respectively. Besides further reduction of caregivers’ workload, such systems can provide additional patient safety and allow management in settings where human supervision may not be present at all times. One general and encountered problem for closed-loop control in a medical setting is limited availability of measurements, especially if manual blood withdrawals are required. As an initial step to address this problem, measured parameters from other devices as potential surrogates were evaluated in a comparison between different regression approaches. The required training data, a matched set of blood gas and monitoring parameters, was obtained by utilizing a developed algorithm for automated detection of withdrawal events. Yet, besides any specific implementations and analysis, many general aspects regarding the physical implementation of such a system and interaction with caregivers could be evaluated in the experimental setting and might guide further development of clinical automation.Angesichts der alternden Bevölkerung, des Mangels an Pflegekräften und der ständig steigenden Arbeitsbelastung ist Automatisierung ein wichtiger Aspekt zukünftiger Intensivmedizin. Obwohl Automatisierung und maschinelles Lernen aktuelle Forschungsthemen sind, ist der Fortschritt im Vergleich zu anderen Anwendungsbereichen jedoch noch sehr begrenzt. Eines der größten Probleme ist wohl die Datenknappheit in einer heterogenen Medizinproduktelandschaft mit begrenzten Schnittstellen und zahlreichen unterschiedlichen Protokollen. Darüber hinaus sind die Datenerfassung und erst recht die Erprobung einer Automatisierung durch ein komplexes rechtliches Rahmenwerk eingeschränkt. Aufgrund dieser Komplikationen und der sensiblen Rechtslage für Patientendaten sind diese nur sehr begrenzt für weitere Analysen und die Entwicklung automatisierter Systeme zugänglich. Im Rahmen dieser Dissertation wurden daher verschiedene Lösungen zur Datenerfassung und Automatisierung begleitend zu zwei klinischen Studien des Universitätsklinikums Tübingen am Großtiermodell in einer realitätsnahen Intensivstation entwickelt und evaluiert. Um die Probleme der Datenverfügbarkeit und Vernetzung medizinischer Geräte zu lösen, wurde vorrangig ein Software-Framework für die Datenerfassung und Steuerung mittels einer Client-Server-Architektur entwickelt und umfangreiche Forschungsdaten in einer zentralen Datenbank gesammelt. Darüber hinaus wurde ein auf Fuzzy-Logik basierender Regler entwickelt, welcher zur Stabilisierung des endtitalen CO2, Glukose und anderen Parametern verwendet wurde und damit die Arbeitsbelastung der Pflegekräfte reduzieren konnte. Zusätzlich zum Fuzzy-Regler konnten durch die Entwicklung von Hardware-Schnittstellen für Geräte zum Temperaturmanagement mittels luftbasierter Wärmedecken und zur Messung der Blutgerinnung geschlossene Regelkreise aufgebaut werden. Neben einer weiteren Arbeitserleichterung für die Pflegekräfte können solche Systeme zusätzliche Sicherheit für den Patienten bieten und die Anwendung in nicht ständig überwachten Bereichen ermöglichen. Ein allgemeines und auch beobachtetes Problem für Regelkreise im medizinischen Bereich ist die begrenzte Verfügbarkeit von Messwerten, insbesondere bei manuellen Blutentnahmen. Als erster Schritt zur Lösung dieses Problems wurden Messparameter anderer Geräte als potentielle Ersatzparameter mit verschiedenen Regressionsansätzen analysiert und verglichen. Die dazu erforderlichen Trainingsdaten, Paare von Blutgas- und weiteren Vitaldaten, wurden mit Hilfe eines entwickelten Algorithmus zur automatisierten Erkennung von Blutentnahmen erzeugt. Abgesehen von diesen konkreten Anwendungen und Analysen konnten in der experimentellen Evaluation auch viele generelle Aspekte der realen Implementierung eines solchen Systems und die Interaktion mit Ärzten und Pflegekräften untersucht werden und damit der Entwicklung weiterer klinischen Automatisierung dienen

Analysing sequencing data in Hadoop: The road to interactivity via SQL

Analysis of high volumes of data has always been performed with distributed computing on computer clusters. But due to rapidly increasing data amounts in, for example, DNA sequencing, new approaches to data analysis are needed. Warehouse-scale computing environments with up to tens of thousands of networked nodes may be necessary to solve future Big Data problems related to sequencing data analysis. And to utilize such systems effectively, specialized software is needed. Hadoop is a collection of software built specifically for Big Data processing, with a core consisting of the Hadoop MapReduce scalable distributed computing platform and the Hadoop Distributed File System, HDFS. This work explains the principles underlying Hadoop MapReduce and HDFS as well as certain prominent higher-level interfaces to them: Pig, Hive, and HBase. An overview of the current state of Hadoop usage in bioinformatics is then provided alongside brief introductions to the Hadoop-BAM and SeqPig projects of the author and his colleagues. Data analysis tasks are often performed interactively, exploring the data sets at hand in order to familiarize oneself with them in preparation for well targeted long-running computations. Hadoop MapReduce is optimized for throughput instead of latency, making it a poor fit for interactive use. This Thesis presents two high-level alternatives designed especially with interactive data analysis in mind: Shark and Impala, both of which are Hive-compatible SQL-based systems. Aside from the computational framework used, the format in which the data sets are stored can greatly affect analytical performance. Thus new file formats are being developed to better cope with the needs of modern and future Big Data sets. This work analyses the current state of the art storage formats used in the worlds of bioinformatics and Hadoop. Finally, this Thesis presents the results of experiments performed by the author with the goal of understanding how well the landscape of available frameworks and storage formats can tackle interactive sequencing data analysis tasks

The role of electricity storage in low carbon energy systems : techno-economic drivers and transistional barriers

UK Government policy sets out ambitious aims to decarbonise the energy system. This requires fundamental changes to the existing energy infrastructure and electricity from low carbon sources is expected to play a major role in this transition. Electricity storage is widely believed to be able to support the integration of low carbon technologies. So far, the installation of wind power in the UK has not led to any significant deployment of additional storage capacity. Investors still regard electricity storage as too expensive. As more low carbon technologies are deployed, the need for storage may increase. How do these developments affect the role for electricity storage in future UK energy systems? This thesis addresses this question by combining technical, economic and social approaches. A techno-economic model has been developed to examine the commercial opportunities for electricity storage in future scenarios. A socio-technical perspective of technological transition complements this approach. Stakeholders have informed the analysis on the uptake of storage through a workshop and interviews. The results point towards a significant increase in the gross value of electricity storage, even at modest efficiencies, especially within highly renewables based scenarios. However, the concept of storing electricity is poorly aligned with existing institutions and regulatory structures. Despite the potential increase in value, electricity storage may fail to be adopted in the best societal interest. Path dependency may lead to the deployment of established alternative solutions, or favour storage technologies with unnecessarily high performance. This thesis concludes that if electricity storage is to play an effective role as part of a low carbon transition, long term developments would need to be considered as part of a strategic policy framework. These may need to address commercial as well as institutional barriers to deployment