The rapid digitalization of the healthcare domain in recent years highlighted the need for advanced predictive methods particularly based upon deep learning methods. Deep learning methods which are capable of dealing with time- series data have recently emerged in various fields such as natural language processing, machine translation, and the Intensive Care Unit (ICU). The recent applications of deep learning in ICU have increasingly received attention, and it has shown promising results for different clinical tasks; however, there is still a need for the benchmark models as far as a handful of public datasets are available in ICU. In this thesis, a novel benchmark model of four clinical tasks on a multi-center publicly available dataset is presented; we employed deep learning models to predict clinical studies. We believe this benchmark model can facilitate and accelerate the research in ICU by allowing other researchers to build on top of it. Moreover, we investigated the effectiveness of the proposed method to predict the risk of delirium in the varying observation and prediction windows, the variable ranking is provided to ease the implementation of a screening tool for helping caregivers at the bedside. Ultimately, an attention-based interpretable neural network is proposed to predict the outcome and rank the most influential variables in the model predictions’ outcome. Our experimental findings show the effectiveness of the proposed approaches in improving the application of deep learning models in daily ICU practice.

Objective: The diagnosis of delirium in intensive care unit patients is frequently missed. Key symptoms to identify delirium are motoric alterations, changes in activity level, and delirium-specific movements. This study aimed to explore features collected by a single wrist-worn accelerometer as indicators of delirium. Methods: The study included twenty-two patients in the intensive care unit. The data was collected with the GENEActiv accelerometer device and the activity level was calculated. Differences between the delirious and nondelirious patients were tested. Results: Differences in activity level and rest-activity patterns were noticed between the delirious and non-delirious patients. However, the differences were not found to be significant. Conclusion: Activity patterns revealed differences between delirious and non‐delirious patients. Further study is required to confirm the potential of actigraphy in the early detection of delirium in the intensive care unit. / Mål: Diagnosen delirium hos intensivvårdspatienter missas ofta. Nyckelsymptom för att identifiera delirium är motoriska förändringar, förändringar i aktivitetsnivå och deliriumspecifika rörelser. Denna studie syftade till att utforska funktioner som samlats in av en enskild handledsburen accelerometer som indikatorer på delirium. Metod: Studien omfattade tjugotvå patienter på intensivvårdsavdelningen. Data samlades in med GENEActiv accelerometerenheten och aktivitetsnivån beräknades. Skillnader mellan de delirious och icke-delirious patienterna testades. Resultat: Skillnader i aktivitetsnivå och viloaktivitetsmönster noterades mellan de deliriösa och icke-deliriösa patienterna. Skillnaderna visade sig dock inte vara signifikanta. Slutsats: Aktivitetsmönster avslöjade skillnader mellan deliriösa och ickedelirösa patienter. Ytterligare studier krävs för att bekräfta potentialen för aktigrafi vid tidig upptäckt av delirium på intensivvårdsavdelningen.

Introduction: Oral hygiene is a significant aspect of nursing care. Endocarditis, stroke, lung cancer, and hypertension have been associated with poor oral hygiene. Research exploring oral care practices for mechanically ventilated patients is well documented. In contrast, oral hygiene for the non-mechanically ventilated acute care population remains underestimated. The purpose of this study was to establish a baseline of the type, frequency, and consistency of oral hygiene being performed on non-mechanically ventilated ICU patients and explore how the oral care provided was documented. Methodology: A literature search was conducted and reported as a literature review. The databases CINAHL Plus with Full Text, MEDLINE, PsychINFO, Academic Search Premier, and Cochrane Database of Systematic Reviews were searched. Key terms used were "oral hygiene," "oral care," "oral intensity," "mouth rinse," "mouth care," chlorhexidine rinse and ICU, "intensive care unit," "critical care" and infection*, pneumonia*, NV, non-ventilat*, and nonventilat*. The articles' selection addressed type, frequency, consistency, and/or documentation of oral hygiene in ICU patients, particularly non-mechanically ventilated patients, if available. Inclusion criteria consisted of English language, and academic journal articles. No specified publication date was placed as a restriction. The results were limited to English language, academic journal articles, peer reviewed research articles, evidence-based articles or practices, and articles published within the last ten years (2006 to 2016). All articles on oral hygiene practices in the ICU or critical care population were included. Articles that did not relate to oral hygiene practices in acute care, ICU patients, or critically ill hospitalized patients were excluded. Articles focused solely on the mechanically ventilated or intubated population were also excluded. Results: The review yielded very few articles focusing solely on non-mechanically ventilated ICU patients. Nevertheless, resulting data showed four areas common to oral hygiene practices in non-mechanically ventilated patients in the ICU: type of documentation, type of products, frequency of care, and personnel providing care. Documentation was found to be lacking compared to personnel's self-reported frequency of oral care. Oral hygiene products were found to be consistent in non-mechanically ventilated patients, while there was no consistency of products used in the general acute care population. Oral hygiene was self-reported by staff members to have been performed an average of two to three times per day for non-mechanically ventilated patients. Oral hygiene self-reported frequency was found to be inconsistent among the general acute care population. Lastly, registered nurses (RNs) were the primary providers of oral hygiene to patients. Conclusions: Findings support the existing gap in the literature on oral hygiene practices in non-mechanically ventilated patients in the ICU. Despite evidence documenting the impact of oral hygiene on health, further research is guaranteed.

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By taking advantage of the increasing amount of available electronic health data, applications of machine learning in the intensive care unit have the potential to improve medical diagnostics and risk stratification. This thesis proposes an approach for early onset prediction of pneumothorax with such technique, using time series data extracted from a clinical database. The prevalence of pneumothorax among patients is identified through ICD-9 codes, and labels for the onset are obtained by relying on proxies closely related to the condition. Both simple algorithms and deep learning networks are used in a sliding window-based prediction framework, and the importance of each feature is measured with weighted Shapley values. The results proved the feasibility of this approach using Long Short-Term Memory models, although the number of false positives is noticeably high. Mechanical ventilation was the most contributing feature for the outcome. In future work, the focus should be on addressing the large class imbalance that prevails, along with considering more well-founded methods of target labeling.

In the intensive care unit, patients with crucial, life-threatening conditions are admitted and need constant monitoring. Here, the need for a quick and efficient decision support tool is the greatest. The use of machine learning has shown promising results in identifying patients at risk of different severe conditions in the intensive care unit and detection at an early stage is crucial in order to take preventive measures. This especially applies to conditions that can be hard to manage once developed, such as circulatory shock. In this master’s thesis, a machine learning modeling approach is suggested to detect and differentiate the onset of three types of circulatory shock – cardiogenic, hypovolemic and septic shock. Data was used from the open-source database MIMIC which represents thousands of patients from intensive care. The data was preprocessed and labels for the three shock types were created using ICD-9 codes combined with a proxy that is closely related to the condition – vasopressor. Different machine learning algorithms were then used for a static onset prediction as a base. The best performing models were also trained for a dynamic onset prediction in order to make predictions up to four hours ahead of onset. All models were evaluated using different evaluation metrics and at last, an interpretation method was used to enable a simpler interpretation of the results. The final results show that it is possible to detect and distinguish between the three types of shock, up to four hours ahead of onset. For future developments, further development and validation using more data should be the main focus before testing it in a clinical setting.

Introduktion: Akut konfusion är ett tillstånd som karakteriseras av akut kognitiv svikt och drabbar upp till 80% av kritiskt sjuka patienter på intensivvårdsavdelningar.  Tillståndet skapar ett lidande hos patienten och ger även negativa konsekvenser för anhöriga, vården och samhället. Behandlingen består i första hand av omvårdnadsåtgärder vilket ställer höga krav på sjuksköterskans kompetens.  Syfte: Syftet med studien var att beskriva vuxna patienters upplevelser av akut konfusion på intensivvårdsavdelning.  Metod: Allmän litteraturstudie med kvalitativ ansats. Tretton kvalitativa artiklar söktes i databaserna PubMed, CINAHL samt i metaanalysers referenslistor. Kvalitetsgranskningen utfördes med kvalitetsgranskningsmall från SBU. Resultatanalysen genomfördes med Forsberg & Wengströms analysmodell.  Resultat: I resultatet identifierades fem teman: upplevelser av sjuksköterskans och närståendes förhållningssätt och bemötande, upplevelser av perceptionsstörningar, upplevelser av att vara vilsen i tid och rum, upplevelser av skiftande sinnesstämning samt upplevelser av agitation och paranoia.  Slutsats: Patienternas upplevelser av akut konfusion beskrevs som ett lidande. De framkom att patienterna nyttjade olika copingstrategier för att hantera tillståndet. Genom att ha kunskap om detta kan sjuksköterskan vara ett stöd i att lindra patientens lidande. Patienters upplevelser behöver studeras ytterligare så sjukvårdspersonal kan utbildas vidare i ämnet och på så sätt erbjuda en god vård för denna patientgrupp. / Introduction: Acute confusion is a condition characterized by an acute cognitive failure and affects up to 80% of the severely ill patients in intensive care units. The condition contributes to suffering for the patient and also generates negative consequences for relatives, healthcare and society. The treatment is primarily nursing measures which makes high demands on nurses competence.  Aim: The aim of the study was to describe the adult patient's experience of acute confusion in the intensive care unit.  Method: A general literature study with a qualitative approach. Thirteen qualitative studies were found in the databases PubMed, CINAHL and through metaanalyzes references. The quality review was done implementing the quality review template from SBU. The result analysis was carried out using Forsberg and Wengströms analysis model.  Results: The result identified five themes: experiences of the nurse and relatives approach and reception, experiences of perception disorders, experiences of being disoriented in time and space, experiences of mood swings, and also experiences of agitation and paranoia.  Conclusion: Patients' experiences of acute confusion was described as a suffering. Patients used different coping strategies to manage their condition. With knowledge about the condition the nurse can be a support in easing the patients suffering. Patients' experiences need to be studied further so healthcare professionals can be educated about the subject and offer good care för this patient group.

Yes / Aim and Objectives: To explore fathers' views and experiences of providing Kangaroo Care (KC) to their baby cared for in a Neonatal Intensive Care Unit (NICU). Kangaroo Care has been known to improve the health outcome for preterm, low birth weight and medically vulnerable term infants and achieve the optimal perinatal health wellbeing for parents and infants. Historically, mothers are considered as the dominant KC providers, whereas fathers are spectators and have been overlooked. Little is known about the fathers' perspectives in providing KC in NICUs. Methods: Individual semi-structured interviews were conducted with 10 fathers who delivered KC to their baby when in the NICU. Data were analysed using Braun and Clarke's six-phase thematical framework. The Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist was followed to report this qualitative study. Findings: Fathers in this study identified they were passing a silent language of love and connecting with their baby by the act of KC in a challenging environment. Three themes emerged: ‘Positive psychological connection’, ‘Embracing father-infant Kangaroo Care’ and ‘Challenges to father-infant Kangaroo Care’. Conclusion: The findings of this study show KC enhances the bonding and attachment between fathers and infants. The conceptualisation of the paternal role in caregiving to a newborn is evolving as a contemporary practice. Further research is warranted to confirm or refute the study findings. Policies and facilities should be modified to include father–infant KC within the fields of neonatal care. Relevance to Clinical Practice: It is important for nurses and other health professionals to support and enable fathers to give KC. Father–infant KC is recommended in neonatal care settings. / Open access publishing facilitated by University of South Australia, as part of the Wiley - University of South Australia agreement via the Council of Australian University Librarians.