Purpose: This research identifies nursing outcomes for patients with multiple traumas who present changes in physical mobility. Methods:This was a thorough literature review, following Whittemore and Knafl's method and the Preferred Reporting Items for Systematic Reviews and Meta-Analysest' guidelines (2005) and adopting the Oxford Center for Evidence-Based Classification

Objective: To assess the accuracy measurements for predisposing and precipitating Risk Factors for delirium in an adult Intensive Care Unit. Method: Cohort, prospective study with patients over 18 who had been hospitalized for over 24 hours and were able to communicate. The patients were assessed once a day until the onset of delirium or permanence in the Intensive Care Unit. Instruments were employed to track delirium, characterize the sample, and identify the risk factors. Descriptive statistics was employed for sample characterization and accuracy tests for risk factors. Results: The included patients amounted to 102, 31 of which presented delirium. The predisposing predictive risk factors were hypoalbuminemia, American Society of Anesthesiology over three, severity, altered tissue perfusion, dehydration, and being a male, whereas precipitating predictive factors were physical restraint, infection, pharmacological agent, polypharmacy, anemia, altered renal function, dehydration, invasive devices, altered tissue perfusion and altered quality and quantity of sleep. Conclusion: An accurate identification of predisposing and precipitating risk factors may contribute to planning preventive measures against delirium.

Objective: To generate a Classification Tree for the correct inference of the Nursing Diagnosis Fluid Volume Excess (00026) in chronic renal patients on hemodialysis. Method: Methodological, cross-sectional study with patients undergoing renal treatment. The data were collected through interviews and physical evaluation, using an instrument with socio-demographic variables, related factors, associated conditions and defining characteristics of the studied diagnosis. The classification trees were generated by the Chi-Square Automation Interaction Detection method, which was based on the Chi-square test. Results: A total of 127 patients participated, of which 79.5% (101) presented the diagnosis studied. The trees included the elements “Excessive sodium intake” and “Input exceeds output”, which were significant for the occurrence of the event, as the probability of occurrence of the diagnosis in the presence of these was 0.87 and 0.94, respectively. The prediction accuracy of the trees was 63% and 74%, respectively. Conclusion: The construction of the trees allowed to quantify the probability of the occurrence of Fluid Volume Excess (00026) in the studied population and the elements “Excessive sodium intake” and “Input exceeds output” were considered predictors of this diagnosis in the sample.

Objective: to analyze the content of the defining characteristics of the Disturbed Sleep Pattern Nursing Diagnosis (00198) in patients with Acute Coronary Syndrome. Method: content analysis performed by specialists who achieved a score equal to or greater than five, according to established criteria: clinical experience, teaching and/or research; participation in research groups; doctorate degree; master's degree; specialization and/or residency in cardiology and/or sleep and/or nursing classifications. Eight defining characteristics were evaluated for their relationship to population, relevance, clarity and accuracy. Descriptive statistics were performed to characterize the sample, binomial statistical test to establish if there is agreement between the experts and chi-square and Fisher's exact to establish associations between the evaluated items and the experts' variables. Results: 54 experts participated in the study. The defining characteristics validated by the experts were the following: dissatisfaction with sleep, feeling unrested, sleep deprivation, alteration in sleep pattern, unintentional awakening, difficulty initiating sleep and daytime sleepiness. There was a statistically significant association between evaluated items and the variables time of training, time of operation and punctuation. Conclusion: seven of the eight defining characteristics were considered valid after the application of binomial test. This study will contribute to the refinement of the Disturbed Sleep Pattern Nursing Diagnosis (000198) and may enable the improvement of the quality of care of patients hospitalized with Acute Coronary Syndrome regarding changes in sleep pattern. The content analysis stage will support the next stage of the validation process of the present diagnosis, the clinical validation.

Agradecimentos: Aos técnicos de enfermagem que participaram das oficinas, às lideranças que otimizaram a participação das equipes, e ao Departamento de Enfermagem /HC pelo apoio e divulgação.