EVOLUTION OF NURSING DIAGNOSES FOR CHILDREN WITH CONGENITAL HEART DISEASE

Objetivou-se descrever a evolução dos diagnósticos de enfermagem em crianças portadoras de cardiopatias congênitas. Estudo longitudinal desenvolvido nos meses de julho a novembro de 2004. A amostra foi composta por 45 crianças internadas em um hospital da rede pública do município de Fortaleza, acompanhadas durante quinze dias de internamento. No período efetivaram-se seis avaliações diagnósticas. Foram encontrados 21 diagnósticos de enfermagem. Entre os diagnósticos, seis evidenciaram maiores oscilações em suas trajetórias de ocorrência no tempo: Padrão respiratório ineficaz, Intolerância à atividade, Desobstrução ineficaz das vias aéreas, Hipertermia, Padrão de sono perturbado e Risco para intolerância à atividade. Foram construídos cinco modelos paramétricos no domínio do tempo, com vistas a predizer a ocorrência desses diagnósticos de enfermagem. Conclui-se que o conhecimento da evolução temporal das respostas do indivíduo pode direcionar os cuidados de enfermagem para as reais necessidades do cliente.


INTRODUCTION
Approximately 99% of infants with congenital heart disease manifest characteristics of heart defects within the first year of life.A diagnosis is established within the first week of life in 40% of patients and within one month in 50% (1) .The neonatal period can be critical for patients with congenital heart disease, due to the gravity of commonly present symptoms and to physiological changes from fetal to neonatal circulation.Congenital heart disease is suspected in the neonatal period when four main clinical signs are present: heart murmur, cyanosis, breathlessness and arrhythmia (2) .
Nursing care delivery to children with congenital heart disease must be established and accomplished as soon as a diagnosis of congenital heart defect is suspected.In order to develop the care plan, a careful information survey is fundamental, mainly directed at assessing the cardiac Impaired skin integrity (3)(4)(5) .Collaborative problems generally include potential complications: Pneumonia, Hypoxemia and Adverse effects of medication therapy (6) .Some studies of children with congenital heart disease assessed a specific aspect of care for this clientele, such as delayed growth and development for example (7) .Moreover, literature highlights statistically important associations, mainly between the following nursing diagnoses: Hyperthermia and Ineffective airway clearance, Imbalanced nutrition: less than body requirements and Delayed growth and development, Ineffective breathing pattern and Ineffective airway clearance, and between Ineffective breathing pattern and Hyperthermia (6) .
On the other hand, these are punctual studies that assessed the diagnostic profile at one single time during hospitalization.We have not found research that analyzed the evolution in nursing diagnoses and possible changes over time.
Detailed and thorough clinical data analysis is needed to understand the health-disease processes that are present in a given situation.And this analysis has been a constant task in nursing work (8) .However, as mentioned above, few studies have analyze nursing diagnoses in children with congenital heart disease, and one of the reasons for this lack is probably the need for a complex clinical analysis.Moreover, although nursing diagnoses have been used in different countries, nurses are not familiar with the diagnostic reasoning process (9) .

MATERIAL AND METHODS
The study design is observational and longitudinal.In observational studies, the researcher assumes a passive role in observing the phenomena that occurred with the study subjects (10) .As to the temporality of the data production process, we have decided on a longitudinal study, as we want to obtain data on a temporal follow-up scale, which depends on the study objectives.Initial trends and changes in the variables of interest are assessed over time (11)   .
The study was carried out at a public hospital in Fortaleza -Ceará, which is part of the SER VI -Regional Executive Secretary VI.This institution is a  (12) .We adopted the following parameters: a 95% reliability coefficient (z α = 1.96) and an 80% test power (z β = 0.84).The estimated proportion, represented by the occurrence proportion of the nursing diagnoses, found in an earlier study, corresponded to 70% (p = 0.7), considering the highest detected prevalence among the nursing diagnoses included in the diagnosis list (3,6) .We established a 40% frequency difference in nursing diagnoses between children with and without priority diagnoses (d = 0.4).For this purpose, we used the mean difference between the prevalence rates of the most frequent diagnoses (63.63%) and of other diagnoses that were found (26.98%) (3,6) .
Based on these parameters, we calculated a sample of 41 children with congenital heart disease.The following exclusion criteria were defined: situations that determined incomplete compliance with study inclusion criteria, a child's exit from the place of study because of discharge, transference or death within less than 15 days and follow-up by a person who was unable to provide all necessary data.
To elaborate the data collection instrument, we carried out a bibliographic survey to identify the signs and symptoms that constitute the defining  and inferring diagnoses and collaborative problems followed the steps recommended in specialized literature (14) : collection, interpretation / grouping of information and naming of categories.We used NANDA's Taxonomy II (13) for naming the diagnoses.
During Occam's razor, which determines the choice of the simplest model that answers the question (15)(16) .After for research involving human beings (17) .The persons responsible for the children gave their informed consent.1).Nursing actions should focus on human responses related to hemodynamic alterations that appear at an early stage and with high proportions, requiring greater attention by the nursing team.These diagnoses also suggest that the child's health state is more severe.

Some nursing diagnoses
The importance of nurses verifying vital signs should also be emphasized, as Hyperthermia displays high proportions after six days of hospitalization.
function and detecting characteristic signs and symptoms of complications of the congenital heart disease.Literature has indicated various nursing diagnoses found in children with congenital heart disease who are hospitalized in clinical and postsurgical recovery units: Imbalanced nutrition: less than body requirements, Risk for infection, Ineffective airway clearance, Impaired gas exchange, Hyperthermia, Risk for imbalanced body temperature, Acute Pain, Delayed growth and development, Sleep pattern disturbance, Risk for constipation and characteristics and factors related to the nursing diagnoses that may be present in children with congenital heart disease.Next, we grouped data according to the eight domains presented by NANDA's Taxonomy II (13) , involving physical / physiological human responses.These were: Nutrition, Elimination, Activity / Rest, Perception / Cognition, Coping / Stress Tolerance, Safety / Protection, Comfort and Growth / Development.The remaining domains were excluded because they are hard to observe in the age range of the study population.In order to validate its contents and appearance, the instrument was presented to four faculty who do research on nursing diagnoses in patients with heart diseases, two of whom directly work with children with congenital heart disease.These faculty members' suggestions were incorporated into the instrument, which was then applied to five children with congenital heart disease.However, as no inadequacies were found in the test, the instrument was considered appropriate.Data collection occurred from July to November 2004.Initially, the researcher presented herself to the child's responsible, explained about the study purpose and requested authorization to include the child.Data were collected after confidentiality of information and identity had been guaranteed and after participants signed the free and informed consent term.Once the child's participation had been allowed, the researcher applied the data collection instrument by means of an interview, aimed at answering items related to information about the mother.After the interview, the researcher carried out a careful clinical nursing exam, based on the data collection instrument, and consulted the results of biochemical and radiological exams, as well as prescriptions and evolutions by all health team members.The 45 children in the sample were accompanied during 15 hospitalization days, counted from the admission date.In this period, six diagnostic evaluations were accomplished at 48-hour intervals, totaling 270 observations.The process of elaboration diagnostic inference, we individually assessed clinical histories.Diagnoses that all researchers agreed upon were accepted.In case of disagreement, clinical histories were reevaluated until a consensus was obtained.Particularly diagnoses related to activity tolerance presented peculiar characteristics in the study sample.This capacity was assessed by identifying abnormal heart frequency, breathing frequency and arterial pressure responses to the child's normal activities, specifically during breastfeeding or bottle feeding.Risk for intolerance was considered by the presence of circulatory and/or respiratory problems that are characteristic of the basic congenital disease.In all identified diagnoses, we considered direct observation of signs and symptoms and health team members' recordings in the patient files.Information provided by relatives and companions was always confirmed by these two manners in order to consider the human response as present.Data were organized in electronic worksheets and stored in a *.xls file.The time series analysis and graphs were developed by means of Excel 2003 © software.Absolute and percentage frequencies and confidence intervals (95%) were considered for descriptive analysis.We constructed three dispersion graphs with the temporal distribution of the nursing diagnoses.Due to the fact that many diagnoses evidenced a constant occurrence pattern, we considered the analysis of a trend model for all to be unnecessary.The six diagnoses with the greatest variability were selected to define a trend regression model.The definition of the highest variability was based on the analysis of the dispersion graphs constructed for all diagnoses and of the estimated variance of their proportions.As children with congenital heart disease remain hospitalized at the pediatric unit for a relatively short time, seasonal and cyclical factors were not taken into account for defining the regression models.Data for the six selected diagnoses were plotted isolatedly for a more precise analysis, with a view to obtaining a trend regression equation that would better adjust to the data for the sake of forecasting.We developed five parametrical models in the time domain of equations for each selected diagnosis, with the respective determination coefficients (R 2 ): linear, second order polynomial, logarithmic, power and exponential.The choice of the most adequate model considered the smallest dispersion of data in relation to the trendline (residues), the highest determination coefficient and defining the model, graphs were plotted with the original data, the trendline, the equation and the selected R 2 for each diagnosis.The objective of the time series analysis was to produce equations that could forecast the proportion of hospitalized children that would develop the diagnosis over a certain period of time.Diagnoses identified in more than 80% of the children during the first assessment were defined as having an early start.Evolutions and involutions of the diagnoses were based on the increase and decrease in the proportions of the diagnoses in each of the six assessments.The project was submitted to the Board of Directors of the institution to obtain authorization for data collection, and approved by the Ethics Committee, in compliance with Resolution 196/96 by the National Health Council/Brazilian Ministry of Health were constant across the six assessments: Risk for infection, Delayed growth and development, Risk for disproportionate growth, Risk for delayed development and risk for deficient fluid volume.Other nursing diagnoses increasingly appeared, specifically: Impaired gas exchange, Ineffective tissue perfusion, Activity intolerance, Ineffective airway clearance and Risk for aspiration.On the other hand, some diagnoses gradually decreased: Ineffective breathing pattern, Hyperthermia, Impaired skin integrity, Sleep pattern disturbance and Risk for activity intolerance.Some human responses were actually and potentially identified in the children with congenital heart disease: Delayed growth and development, Risk for disproportionate growth, and Risk for delayed development, Activity intolerance and risk for activity intolerance, Impaired skin integrity and Risk for impaired skin integrity.The nursing diagnoses of Diarrhea and Risk for injury only appeared in one single assessment.It should be highlighted that all participants presented Activity intolerance or Risk for activity intolerance.This is due to the different hemodynamic and respiratory alterations that may be or are produced when minimal activities like sucking at the mother's breast are accomplished.Older infants can also present characteristics like increased respiratory discomfort and alterations in heart frequencies while crying, evacuating and playing.In most cases, the occurrence levels of nursing diagnoses presented slight changes, tending towards stabilization.Diagnoses above the 75 th percentile appeared in the early hospitalization phase and tended to stabilize already during this period.Three of these evidenced greater variations: Ineffective breathing pattern, Activity intolerance and Ineffective airway clearance.Diagnoses between the 50 th and 75 th percentile presented lower proportions and generally appeared after and as a consequence of the first diagnoses or collaborative problems.In general, diagnoses between the 25 th and 50 th percentile occurred at a later stage, as complications or possible complications of other diagnoses or collaborative problems, and presented great changes in occurrence levels.Evolution of nursing diagnoses... Silva VM, Araujo TL, Lopes MVO.Rev Latino-am Enfermagem 2006 julho-agosto; 14(4):561-8 www.eerp.usp.br/rlaeNext, we selected those nursing diagnoses with the greatest variations in occurrence levels to construct mathematical models that would allow us to predict what proportion of children with congenital heart disease would develop these diagnoses during a time interval.For the other nursing diagnoses with a more stable picture, other parameters can be used, such as confidence intervals.These provide proportion intervals for the occurrence of these phenomena.

Figure 1 -Figure 2 -Figure 3 -
Figure 1 -Temporal analysis of Ineffective breathing pattern (IBP) and Activity Intolerance (AI) diagnoses with trendline.Fortaleza, 2004 increasing and then stabilizing, indicating a possible influence of Impaired gas Exchange on Activity intolerance.The adjustment of the second order polynomial model for Sleep pattern disturbance and Hyperthermia still revealed great dispersion between data and the trendline.Besides time, approximately 30% of other variables determine the proportion of children who will manifest these diagnoses.The latter two diagnoses presented a variation with a clearly curvilinear trend, that is, their proportions first increased and soon afterwards decreased, forming a curved trendline, which justified the choice of a more complex equation.Diagnoses that were not included in this part of our analysis either presented a constant proportion or a linear pattern with very slight variation.Another point that must be considered in more specific studies is the determination of factors that contribute to the establishment of diagnoses like Hyperthermia and Sleep pattern disturbance.When considering only the time variable, the adjustment of the models proposed here for these diagnoses remains modest.CONCLUSIONS Six nursing diagnoses revealed greater variation over time: Ineffective breathing pattern, Activity intolerance, Ineffective airway clearance, Hyperthermia, Sleep pattern disturbance and Risk for activity intolerance.Five parametric models were constructed in the time domain, with a view to predicting the occurrence of the nursing diagnoses.The most adequate mathematical models followed the structure of linear and second order polynomial equations.The adjustment of these equations for Disturbed sleep pattern and Hyperthermia still revealed great dispersion between data and the trendline.This indicates that, besides time, other variables determine the proportion of children who will manifest these diagnoses.Although we have considered 75% of the mean hospitalization time for children with congenital heart disease, the data analyzed by the time series must be weighed in terms of forecasting the behavior of nursing diagnoses for children who remain hospitalized for a longer period.We believe that knowledge about the temporal evolution of children's responses contributes to nursing interventions guided by diagnostic decisions, which facilitates the choice of more adequate actions and allows for better prognoses.

Table 1 -
Nursing diagnoses identified in children with congenital heart disease.Fortaleza, 2004 between six and nine.Patients with acyanotic diseases corresponded to 53.3% of the total, with confidence intervals ranging from 37.9% to 68.3%; the frequency of cyanotic diseases was 46.7%, with intervals from 31.7% to 62.1%.

Table 2 -
Equations to calculate trends in the