Navegando por Palavras-chave "Data Accuracy"

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    Diagnósticos de enfermagem de alta acurácia em pessoas com insuficiência cardíaca
    (Universidade Federal de São Paulo (UNIFESP), 2020-08-27) Souza, Larissa Maiara Da Silva Alves [UNIFESP]; Barros, Alba Lucia Bottura Leite De [UNIFESP]; Universidade Federal de São Paulo
    Introduction: Heart failure (HF) is a complex clinical syndrome secondary to cardiac structural and functional abnormalities. The existence of comorbidities such as hypertension, diabetes, physical inactivity and dyslipidemia and non-adherence to drug and non-drug treatment, as well as a lack of knowledge of the exacerbation symptoms of the disease are associated with hospitalizations. It is estimated that around 2 million new cases appear worldwide each year. In 2018, there were 200,814 hospital admissions registered in the Unified Health System (UHS) associated with HF, with 9,156 admissions registered in the state of São Paulo. Today, approximately 5.1 million Americans have HF. It is believed that this number tends to increase 46% by 2030, reaching eight million individuals diagnosed with HF. In this scenario, the performance of nursing can be circumstantial. When identifying the nursing diagnoses (ND) associating them to clinical signs and symptoms, the nurse unifies the individual's needs so that the elaborated interventions are aimed at solving these identified NDs. These diagnoses, when elaborated in an accurate way, make possible a more assertive care, with higher rates of resolution, reduction of complications and improvement of health status. The Nursing Diagnosis Accuracy Scale version-2 (NDAS-2) assesses the degree to which the statement of the ND is confirmed through a set of clinical information of the patient being used to measure the degree of accuracy of the listed NDs. Objectives: to identify highly accurate NDs present on admission and discharge of patients hospitalized for HF; identify the prevalence of NDs on admission and discharge from patients hospitalized for HF; test the reliability of the NDAS-2 within the between evaluators regarding the degree of accuracy of the diagnoses; Method: prospective cohort of diagnostic accuracy conducted in the Emergency Room of a large reference hospital in cardiology in a Brazilian metropolis, from August 2018 to July 2019, 155 patients hospitalized for HF participated in the research. Socio-demographic, clinical and drug treatment data were collected from an instrument developed by the researchers and previously tested. Subsequently, two researchers applied EADE-2 to NDs registered on admission and discharge of hospitalized HF patients. The variables were presented by means of descriptive statistics (absolute and relative frequencies) and by mean ± standard deviation. Fisher's exact test was used and associations with a descriptive level≤0.05 were considered significant. To assess the agreement between the evaluators, the Kappa coefficient was used, which varies from 0 to 1, and the closer to one, the greater the agreement. Results: The average age of hospitalized patients was 62.6 years, the majority being male (61.3%), white (54.19%) and incomplete elementary school (49.03%). The predominant hemodynamic profile was B (73.5%), the most frequent etiologies were cardiomyopathies (19.4%) and chagas disease (16.1%), with 25.16% not having a classification. Acute coronary syndrome was the most frequent pathology, observed in 43 patients (27.7%), the most prevalent comorbidities were hypertension (74.19%), diabetes (40.64%) and dyslipidemia (40.64%). Among the 18 NDs identified, four were prevalent both at admission and at discharge: Risk for Infection, Risk for Fall, Risk for decreased cardiac output and Fluid volume excess. These DEs had a good agreement between evaluators, with the Fluid volume excess being the one with the highest correlation at admission (0.7) and at discharge (0.9). Considering all NDs 85% were classified as highly accurate on admission and about 66% on hospital discharge. The NDs that stood out in this high accuracy classification were: Risk for Infection and Risk for decreased cardiac output on admission; and at discharge, he kept the Risk for infection together with the Risk for fall. Conclusion: The results of the study possibled to identify highly accurate nursing diagnoses. In addition, ND Risk for infection was the most prevalent and highly accurate, although it is not directly related to pathology such as the Risk for decreased cardiac output and the Fluid volume excess that are NDs related to the pathophysiological conditions of HF, demonstrating that there is the need to prioritize those NDs of greater clinical relevance in critical situations such as admission and discharge. Considering that nurses, through signs and symptoms, physical examination, laboratory and image exams, can identify other NDs, and thus make decisions in view of the current and real conditions of patients, the identification of highly accurate NDs will help them during systematic care, enabling appropriate nursing planning and care.