81 resultados para Diferencial diagnoses

em Queensland University of Technology - ePrints Archive


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Background Diagnosing attention-deficit/hyperactivity disorder (ADHD) in adults is difficult when the diagnostician cannot establish an onset prior to the DSM-IV criterion of age 7 or if the number of symptoms recalled does not achieve the DSM-IV threshold for diagnosis. Because neuropsychological deficits are associated with ADHD, we addressed the validity of the DSM-IV age at onset and symptom threshold criteria by using neuropsychological test scores as external validators. Methods We compared four groups of adults: 1) full ADHD subjects met all DSM-IV criteria for childhood-onset ADHD; 2) late-onset ADHD subjects met all criteria except the age at onset criterion; 3) subthreshold ADHD subjects did not meet full symptom criteria; and 4) non-ADHD subjects did not meet any of the above criteria. Results Late-onset and full ADHD subjects had similar patterns of neuropsychological dysfunction. By comparison, subthreshold ADHD subjects showed few neuropsychological differences with non-ADHD subjects. Conclusions Our results showing similar neuropsychological underpinning in subjects with late-onset ADHD suggest that the DSM-IV age at onset criterion may be too stringent. Our data also suggest that ADHD subjects who failed to ever meet the DSM-IV threshold for diagnosis have a milder form of the disorder.

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Abstract Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

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A cross-sectional study was performed to investigate the prevalence and predictors of suicidal ideation and past suicide attempt in an Australian sample of human imumunodeficiency virus (HIV)-positive and HIV-negative homosexual and bisexual men. Sixty-five HIV-negative and 164 HIV-positive men participated. A suicidal ideation score was derived from using five items selected from the Beck Depression Inventory and the General Health Questionnaire (28-item version). Lifetime and current prevalence rates of psychiatric disorder were evaluated with the Diagnostic Interview Schedule Version-III-R. The HIV-positive (Centers for Disease Control and Prevention [CDC] Stage IV) men (n=85) had significantly higher total suicidal ideation scores than the asymptomatic HIV-positive men (CDC Stage II/III) (n=79) and the HIV-negative men. High rates of past suicide attempt were detected in the HIV-negative (29%) and HIV-positive men (21%). Factors associated with suicidal ideation included being HIV-positive, the presence of current psychiatric disorder, higher neuroticism scores, external locus of control, and current unemployment. In the HIV-positive group analyzed separately, higher suicidal ideation was discriminated by the adjustment to HIV diagnosis (greater hopelessness and lower fighting spirit), disease factors (greater number of current acquired immunodeficiency syndrome [AIDS]-related conditions), and background variables (neuroticism). Significant predictors of a past attempted suicide were a positive lifetime history of psychiatric disorder (particularly depression diagnoses), a lifetime history of injection drug use, and a family history of suicide attempts. The findings indicate increased levels of suicidal ideation in symptomatic HIV-positive men and highlight the role that multiple psychosocial factors associated with suicidal ideation and attempted suicide play in this population.

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This study investigated the psychological impact of HIV infection through assessment of posttraumatic stress disorder in response to HIV infection. Sixty-one HIV-positive homosexual/bisexual men were assessed for posttraumatic stress disorder in response to HIV infection (PTSD-HIV) using a modified PTSD module of the DIS-III-R. Thirty percent met criteria for a syndrome of posttraumatic stress disorder in response to HIV diagnosis (PTSD-HIV). In over one-third of the PTSD cases, the disorder had an onset greater than 6 months after initial HIV infection diagnosis. PTSD-HIV was associated with other psychiatric diagnoses, particularly the development of first episodes of major depression after HIV infection diagnosis. PTSD-HIV was significantly associated with a pre-HIV history of PTSD from other causes, and other pre-HIV psychiatric disorders and neuroticism scores, indicating a similarity with findings in studies of PTSD from other causes. The findings from this preliminary study suggest that a PTSD response to HIV diagnosis has clinical validity and requires further investigation in this population and other medically ill groups. The results support the inclusion of the diagnosis of life-threatening illness as a traumatic incident that may lead to a posttraumatic stress disorder, which is consistent with the DSM-IV criteria.

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The effective management of bridge stock involves making decisions as to when to repair, remedy, or do nothing, taking into account the financial and service life implications. Such decisions require a reliable diagnosis as to the cause of distress and an understanding of the likely future degradation. Such diagnoses are based on a combination of visual inspections, laboratory tests on samples and expert opinions. In addition, the choice of appropriate laboratory tests requires an understanding of the degradation mechanisms involved. Under these circumstances, the use of expert systems or evaluation tools developed from “realtime” case studies provides a promising solution in the absence of expert knowledge. This paper addresses the issues in bridge infrastructure management in Queensland, Australia. Bridges affected by alkali silica reaction and chloride induced corrosion have been investigated and the results presented using a mind mapping tool. The analysis highights that several levels of rules are required to assess the mechanism causing distress. The systematic development of a rule based approach is presented. An example of this application to a case study bridge has been used to demonstrate that preliminary results are satisfactory.

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Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

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Schizophrenia is associated with significant brain abnormalities, including changes in brain metabolites as measured by proton magnetic resonance spectroscopy (MRS). What remains unclear is the extent to which these changes are a consequence of the emergence of psychotic disorders or the result of treatment with antipsychotic medication. We assessed 34 patients with first episode psychosis (15 antipsychotic naïve) and 19 age- and gender-matched controls using short-echo MRS in the medial temporal lobe bilaterally. Overall, there were no differences in any metabolite, regardless of treatment status. However, when the analysis was limited to patients with a diagnosis of schizophrenia, schizophreniform or schizoaffective disorder, significant elevations of creatine/phosphocreatine (Cr/PCr) and myo-inositol (mI) were found in the treated group. These data indicate a relative absence of temporal lobe metabolic abnormalities in first episode psychosis, but suggest that some treatment-related changes in mI might be apparent in patients with schizophrenia-spectrum diagnoses. Seemingly illness-related Cr/PCr elevations were also specific to the diagnosis of schizophrenia-spectrum disorder and seem worthy of future study.

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Objective: The objectives of this article are to explore the extent to which the International Statistical Classification of Diseases and Related Health Problems (ICD) has been used in child abuse research, to describe how the ICD system has been applied and to assess factors affecting the reliability of ICD coded data in child abuse research.----- Methods: PubMed, CINAHL, PsychInfo and Google Scholar were searched for peer reviewed articles written since 1989 that used ICD as the classification system to identify cases and research child abuse using health databases. Snowballing strategies were also employed by searching the bibliographies of retrieved references to identify relevant associated articles. The papers identified through the search were independently screened by two authors for inclusion, resulting in 47 studies selected for the review. Due to heterogeneity of studies metaanalysis was not performed.----- Results: This paper highlights both utility and limitations of ICD coded data. ICD codes have been widely used to conduct research into child maltreatment in health data systems. The codes appear to be used primarily to determine child maltreatment patterns within identified diagnoses or to identify child maltreatment cases for research.----- Conclusions: A significant impediment to the use of ICD codes in child maltreatment research is the under-ascertainment of child maltreatment by using coded data alone. This is most clearly identified and, to some degree, quantified, in research where data linkage is used. Practice Implications: The importance of improved child maltreatment identification will assist in identifying risk factors and creating programs that can prevent and treat child maltreatment and assist in meeting reporting obligations under the CRC.

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Peripheral corneal opacities are a common clinical finding. In this case report we describe the routine presentation of a young adult male patient with unilateral opacities in the peripheral cornea resembling a corneal arcus. These opacities were confined to the level of the anterior corneal stroma. The patient also exhibited bilateral signs of mild keratoconus and reported a history of vernal keratoconjunctivitis as a child. A diagnosis of unilateral pseudogerontoxon was made. Pseudogerontoxon is an opacity of the peripheral cornea resembling corneal arcus that typically occurs in patients with a history of allergic eye disease. The clinical features and differential diagnoses of this relatively uncommon cause of peripheral corneal opacity are discussed.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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Background: Early pregnancy loss has been linked to enduring psychological morbidity. Aims: This study aimed to investigate the utility of the Kessler 10 (K10) questionnaire as a brief screening instrument to identify women at risk for the development of psychiatric diagnoses three months post-miscarriage. Method: Participants were 117 consecutive women presenting at a public hospital emergency department and receiving a diagnosis of miscarriage. Main outcome measures: K10 screen for psychological distress and the Structured Clinical Interview for DSM Disorders to determine psychiatric diagnoses. Results: A majority of women (81.2%) experienced elevated levels of distress initially, 24.8% in the very high range. They were not at increased risk of psychiatric diagnoses at three months compared with the general population; however, they were significantly more likely to report subsyndromal symptoms at this time compared with the general population. The baseline K10 score was the only significant predictor of distress at follow-up (r = 0.45, P < 0.001). The receiver operating characteristic curve shows that a cut-off of 14 on the K10 has suitable sensitivity (97%) and specificity (82%) for predicting ongoing psychological distress in women who miscarry. Conclusions: The K10 is effective in identifying women at risk for ensuring psychological symptoms following miscarriage.

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Background: Untreated Chlamydia trachomatis infections in women can result in disease sequelae such as salpingitis and pelvic inflammatory disease (PID), ultimately culminating in tubal occlusion and infertility. Whilst nucleic acid amplification tests can effectively diagnose uncomplicated lower genital tract (LGT) infections, they are not suitable for diagnosing upper genital tract (UGT) pathological sequelae. As a consequence, this study aimed to identify serological markers that can, with a high degree of sensitivity and specificity, discriminate between LGT infections and UGT pathology. Methods: Plasma was collected from 73 women with a history of LGT infection, UGT pathology due to C. trachomatis or no serological evidence of C. trachomatis infection. Western blotting was used to analyse antibody reactivity against extracted chlamydial proteins. Sensitivity and specificity of differential markers were also calculated. Results: Four antigens (CT157, CT423, CT727 and CT396) were identified and found to be capable of discriminating between the infection and disease sequelae state. Sensitivity and specificity calculations showed that our assay for diagnosing LGT infection had a sensitivity and specificity of 75% and 76% respectively, whilst the assay for identifying UGT pathology demonstrated 80% sensitivity and 86% specificity. Conclusions: The use of these assays could potentially facilitate earlier diagnoses in women suffering UGT pathology due to C. trachomatis.

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Background Concern about skin cancer is a common reason for people from predominantly fair-skinned populations to present to primary care doctors. Objectives To examine the frequency and body-site distribution of malignant, pre-malignant and benign pigmented skin lesions excised in primary care. Methods This prospective study conducted in Queensland, Australia, included 154 primary care doctors. For all excised or biopsied lesions, doctors recorded the patient's age and sex, body site, level of patient pressure to excise, and the clinical diagnosis. Histological confirmation was obtained through pathology laboratories. Results Of 9650 skin lesions, 57·7% were excised in males and 75·0% excised in patients ≥50years. The most common diagnoses were basal cell carcinoma (BCC) (35·1%) and squamous cell carcinoma (SCC) (19·7%). Compared with the whole body, the highest densities for SCC, BCC and actinic keratoses were observed on chronically sun-exposed areas of the body including the face in males and females, the scalp and ears in males, and the hands in females. The density of BCC was also high on intermittently or rarely exposed body sites. Females, younger patients and patients with melanocytic naevi were significantly more likely to exert moderate/high levels of pressure on the doctor to excise. Conclusions More than half the excised lesions were skin cancer, which mostly occurred on the more chronically sun-exposed areas of the body. Information on the type and body-site distribution of skin lesions can aid in the diagnosis and planned management of skin cancer and other skin lesions commonly presented in primary care.

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The number of children with special health care needs surviving infancy and attending school has been increasing. Due to their health status, these children may be at risk of low social-emotional and learning competencies (e.g., Lightfoot, Mukherjee, & Sloper, 2000; Zehnder, Landolt, Prchal, & Vollrath, 2006). Early social problems have been linked to low levels of academic achievement (Ladd, 2005), inappropriate behaviours at school (Shiu, 2001) and strained teacher-child relationships (Blumberg, Carle, O‘Connor, Moore, & Lippmann, 2008). Early learning difficulties have been associated with mental health problems (Maughan, Rowe, Loeber, & Stouthamer-Loeber, 2003), increased behaviour issues (Arnold, 1997), delinquency (Loeber & Dishion, 1983) and later academic failure (Epstein, 2008). Considering the importance of these areas, the limited research on special health care needs in social-emotional and learning domains is a factor driving this research. The purpose of the current research is to investigate social-emotional and learning competence in the early years for Australian children who have special health care needs. The data which informed this thesis was from Growing up in Australia: The Longitudinal Study of Australian Children. This is a national, longitudinal study being conducted by the Commonwealth Department of Families, Housing, Community Services and Indigenous Affairs. The study has a national representative sample, with data collection occurring biennially, in 2004 (Wave 1), 2006 (Wave 2) and 2008 (Wave 3). Growing up in Australia uses a cross-sequential research design involving two cohorts, an Infant Cohort (0-1 at recruitment) and a Kindergarten Cohort (4-5 at recruitment). This study uses the Kindergarten Cohort, for which there were 4,983 children at recruitment. Three studies were conducted to address the objectives of this thesis. Study 1 used Wave 1 data to identify and describe Australian children with special health care needs. Children who identified as having special health care needs through the special health care needs screener were selected. From this, descriptive analyses were run. The results indicate that boys, children with low birth weight and children from families with low levels of maternal education are likely to be in the population of children with special health care needs. Further, these children are likely to be using prescription medications, have poor general health and are likely to have specific condition diagnoses. Study 2 used Wave 1 data to examine differences between children with special health care needs and their peers in social-emotional competence and learning competence prior to school. Children identified by the special health care needs screener were chosen for the case group (n = 650). A matched case control group of peers (n = 650), matched on sex, cultural and linguistic diversity, family socioeconomic position and age, were the comparison group. Social-emotional competence was measured through Social/Emotional Domain scores taken from the Growing up in Australia Outcome Index, with learning competence measured through Learning Domain scores. Results suggest statistically significant differences in scores between the two groups. Children with special health care needs have lower levels of social-emotional and learning competence prior to school compared to their peers. Study 3 used Wave 1 and Wave 2 data to examine the relationship between special health care needs at Wave 1 and social-emotional competence and learning competence at Wave 2, as children started school. The sample for this study consisted of children in the Kindergarten Cohort who had teacher data at Wave 2. Results from multiple regression models indicate that special health care needs prior to school (Wave 1) significantly predicts social-emotional competence and learning competence in the early years of school (Wave 2). These results indicate that having special health care needs prior to school is a risk factor for the social-emotional and learning domains in the early years of school. The results from these studies give valuable insight into Australian children with special health care needs and their social-emotional and learning competence in the early years. The Australia population of children with special health care needs were primarily male children, from families with low maternal education, were likely to be of poor health and taking prescription medications. It was found that children with special health care needs were likely to have lower social-emotional competence and learning competence prior to school compared to their peers. Results indicate that special health care needs prior to school were predictive of lower social-emotional and learning competencies in the early years of school. More research is required into this unique population and their competencies over time. However, the current research provides valuable insight into an under researched 'at risk' population.