Abdominal shotgun trauma: A case report

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Undergraduate nursing students' knowledge about palliative care and attitudes towards end-of-life care: a three-cohort, cross-sectional survey.

Background: Ensuring adequate knowledge about palliative care and positive attitudes towards death and dying are crucial educational aspects when preparing undergraduate nursing students to respond effectively to the complexities of care for people affected by a progressive, life-limiting illness. In undergraduate nursing education in Greece, the level of students' attained knowledge and developed attitudes towards palliative and end-of-life care remain unknown. Purpose: To investigate undergraduate nursing students' knowledge about palliative care and attitudes towards death and end-of-life care, and explore demographic and academic factors as potential moderators of student knowledge and attitudes. Methods: We conducted a descriptive, cross-sectional, questionnaire-based survey. We recruited 2nd, 3rd and 4th year undergraduate nursing students from the country's two University Faculties. Participants completed a demographic form, the Palliative Care Quiz for Nursing (PCQN), and the Frommelt Attitudes Towards Care of the Dying (FATCOD) questionnaire. Results: The final sample was 529 students (response rate = 87.6%). Mean total PCQN scores revealed low levels of knowledge. Knowledge about pain/symptom management and psychosocial/spiritual care was insufficient. Mean total FATCOD scores indicated positive, liberal and supportive attitudes towards end-of-life care, with 60% of respondents keen to care for a dying person and their family. We noted less positive attitudes mainly in relation to student comfort with the care of a dying person and his/her imminent death. Academic parameters (year of study) and student demographic characteristics (older age) were the most significant moderators of both knowledge and attitudes. Greater knowledge about palliative care was a relatively weak, yet significant, predictor of more liberal attitudes towards care of the dying. Conclusion: Our findings suggest that structured courses in palliative care can be a core part of undergraduate nursing education. Specific attention could be given to such areas patient-health professional communication, misconceptions and biases towards death and dying, and comfort in caring for the dying in order to prepare student nurses to psychologically deal with the sensitive and challenging process of death and dying

Anastomotic leak management after a low anterior resection leading to recurrent abdominal compartment syndrome: a case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Low anterior resection is usually the procedure of choice for rectal cancer, but a series of complications often accompany this procedure. This case report describes successful management of an intricate anastomotic leak after a low anterior resection.</p> <p>Case presentation</p> <p>A 66-year-old Caucasian man was admitted to our hospital and diagnosed with a low rectal adenocarcinoma. He underwent a low anterior resection but subsequently developed fecal peritonitis due to an anastomotic leak. He was operated on again but developed abdominal compartment syndrome, multi-organ failure and sepsis. He was aggressively treated in the intensive care unit and in the operating room. Overall, the patient underwent four laparotomies and stayed in the intensive care unit for 75 days. He was discharged after 3 months of hospitalization.</p> <p>Conclusion</p> <p>Abdominal compartment syndrome may present as a devastating complication of damage control laparotomy. Prompt recognition and goal-directed management are the cornerstones of treatment.</p

The eSMART study protocol : a randomised controlled trial to evaluate electronic symptom management using the advanced symptom management system (ASyMS) remote technology for patients with cancer

Introduction While some evidence exists that real-time remote symptom monitoring devices can decrease morbidity and prevent unplanned admissions in oncology patients, overall, these studies have significant methodological weaknesses. The electronic Symptom Management using the Advanced Symptom Management System (ASyMS) Remote Technology (eSMART) study is designed to specifically address these weaknesses with an appropriately powered, repeated-measures, parallel-group stratified randomised controlled trial of oncology patients. Methods and analysis A total of 1108 patients scheduled to commence first-line chemotherapy (CTX) for breast, colorectal or haematological cancer will be recruited from multiple sites across five European countries.Patients will be randomised (1:1) to the ASyMS intervention (intervention group) or to standard care currently available at each site (control group). Patients in the control and intervention groups will complete a demographic and clinical questionnaire, as well as a set of valid and reliable electronic patient-reported outcome measures at enrolment, after each of their CTX cycles (up to a maximum of six cycles) and at 3, 6, 9 and 12 months after completion of their sixth cycle of CTX. Outcomes that will be assessed include symptom burden (primary outcome), quality of life, supportive care needs, anxiety, self-care self-efficacy, work limitations and cost effectiveness and, from a health professional perspective, changes in clinical practice (secondary outcomes). Ethics and dissemination Ethical approval will be obtained prior to the implementation of all major study amendments. Applications will be submitted to all of the ethics committees that granted initial approval.eSMART received approval from the relevant ethics committees at all of the clinical sites across the five participating countries. In collaboration with the European Cancer Patient Coalition (ECPC), the trial results will be disseminated through publications in scientific journals, presentations at international conferences, and postings on the eSMART website and other relevant clinician and consumer websites; establishment of an eSMART website (www.esmartproject.eu) with publicly accessible general information; creation of an eSMART Twitter Handle, and production of a toolkit for implementing/utilising the ASyMS technology in a variety of clinical practices and other transferable health care contexts. Trial registration number NCT02356081

Network Analysis of the Multidimensional Symptom Experience of Oncology

Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network. Document type: Articl

Adaptation and implementation of a multinational eHealth intervention for people with cancer : reflections from the field

Background: There has been an international shift in healthcare which has seen an increasing focus and development of technological and personalized at-home interventions which aim to improve health outcomes and patient-clinician communication. However, there is a notable lack of empirical evidence describing the preparatory steps of adapting and implementing technology of this kind across multiple countries and clinical settings. Objective: To describe the steps undertaken in the preparation of a multinational, multicentre randomized controlled trial to test a mobile phone-based remote symptom monitoring system, i.e. Advanced Symptom Management System Remote Technology (ASyMS), designed to enhance management of chemotherapy toxicities amongst people with cancer receiving adjuvant chemotherapy versus standard cancer centre care. Methods: Multiple steps were undertaken, including; a scoping review of empirical literature and clinical guidelines, translation and linguistic validation of study materials, development of standardised international care procedures and the integration and evaluation of the technology within each cancer centre. Results: ASyMS was successfully implemented and deployed in clinical practice across five European countries. The rigorous and simultaneous steps undertaken by the research team highlighted the strengths of the system in clinical practice, as well as the clinical and technical changes required to meet the diverse needs of its intended users within each country, prior to the commencement of the randomized controlled trial. Conclusions: Adapting and implementing this multinational, multicentre system required close attention to diverse considerations and unique challenges, primarily related to communication, clinical and technical issues. Success was dependent on collaborative and transparent communication amongst academics, technology industry, translation partners, patients, and clinicians as well as a simultaneous and rigorous methodological approach within the five relevant countries

Network analysis of the multidimensional symptom experience of oncology

Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network

Learning from Data to Predict Future Symptoms of Oncology Patients

Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient’s treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions. Document type: Articl

Congruence between latent class and k-modes analyses in the identification of oncology patients with distinct symptom experiences

CONTEXT: Risk profiling of oncology patients based on their symptom experience assists clinicians to provide more personalized symptom management interventions. Recent findings suggest that oncology patients with distinct symptom profiles can be identified using a variety of analytic methods. OBJECTIVES: The objective of this study was to evaluate the concordance between the number and types of subgroups of patients with distinct symptom profiles using latent class analysis and K-modes analysis. METHODS: Using data on the occurrence of 25 symptoms from the Memorial Symptom Assessment Scale, that 1329 patients completed prior to their next dose of chemotherapy (CTX), Cohen's kappa coefficient was used to evaluate for concordance between the two analytic methods. For both latent class analysis and K-modes, differences among the subgroups in demographic, clinical, and symptom characteristics, as well as quality of life outcomes were determined using parametric and nonparametric statistics. RESULTS: Using both analytic methods, four subgroups of patients with distinct symptom profiles were identified (i.e., all low, moderate physical and lower psychological, moderate physical and higher Psychological, and all high). The percent agreement between the two methods was 75.32%, which suggests a moderate level of agreement. In both analyses, patients in the all high group were significantly younger and had a higher comorbidity profile, worse Memorial Symptom Assessment Scale subscale scores, and poorer QOL outcomes. CONCLUSION: Both analytic methods can be used to identify subgroups of oncology patients with distinct symptom profiles. Additional research is needed to determine which analytic methods and which dimension of the symptom experience provide the most sensitive and specific risk profile