8 resultados para National Institutes of Health (U.S.). Clinical Center

em University of Queensland eSpace - Australia


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Background and Purpose - To assess the prevalence of premorbid undernutrition and its impact on outcomes 1 month after stroke. Methods - The study recruited from consecutive stroke admissions during a 10-month period. Premorbid nutritional status ( using the subjective global assessment [SGA]), premorbid functioning ( modified Rankin scale [MRS]), and stroke severity ( National Institutes of Health Stroke Scale [NIHSS] score) were assessed at admission. The associations between premorbid nutritional status, poor outcome ( defined as MRS greater than or equal to 3), and mortality were examined before and after adjustment for confounding variables, including age, gender, stroke risk factors, stroke severity, and admission serum albumin. Results - Thirty of 185 patients were assessed as having undernutrition at admission. Significant unadjusted associations were observed between undernutrition and poor outcome (odds ratio [OR], 3.4; 95% CI, 1.3 to 8.7; P = 0.01), and mortality (OR, 3.1, 95% CI, 1.3 to 7.7; P = 0.02) at 1 month. NIHSS, age, and premorbid MRS were also significantly associated with poor outcomes. After adjustment for these factors, the effect size of associations remained important but not significant ( poor outcome: OR, 2.4; 95% CI, 0.7 to 9.0, P = 0.18; mortality: OR, 3.2; 95% CI, 1.0 to 10.4, P = 0.05). Conclusions - Premorbid undernutrition, as assessed using the SGA, appears to be an independent predictor of poor stroke outcome. Stroke prevention strategies should target undernutrition in the population at risk for stroke to improve outcomes.

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Introduction. Potentially modifiable physiological variables may influence stroke prognosis but their independence from modifiable factors remains unclear. Methods. Admission physiological measures (blood pressure, heart rate, temperature and blood glucose) and other unmodifiable factors were recorded from patients presenting within 48 hours of stroke. These variables were compared with the outcomes of death and death or dependency at 30 days in multivariate statistical models. Results. In the 186 patients included in the study, age, atrial fibrillation and the National Institutes of Health Stroke Score were identified as unmodifiable factors independently associated with death and death or dependency. After adjusting for these factors, none of the physiological variables were independently associated with death, while only diastolic blood pressure (DBP) >= 90 mmHg was associated with death or dependency at 30 days (p = 0.02). Conclusions. Except for elevated DBP, we found no independent associations between admission physiology and outcome at 30 days in an unselected stroke cohort. Future studies should look for associations in subgroups, or by analysing serial changes in physiology during the early post-stroke period.

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Background: In mental health, policy-makers and planners are increasingly being asked to set priorities. This means that health economists, health services researchers and clinical investigators are being called upon to work together to define and measure costs. Typically, these researchers take available service utilisation data and convert them to costs, using a range of assumptions. There are inefficiencies, as individual groups of researchers frequently repeat essentially similar exercises in achieving this end. There are clearly areas where shared or common investment in the development of statistical software syntax, analytical frameworks and other resources could maximise the use of data. Aims of the Study: This paper reports on an Australian project in which we calculated unit costs for mental health admissions and community encounters. In reporting on these calculations, our purpose is to make the data and the resources associated with them publicly available to researchers interested in conducting economic analyses, and allow them to copy, distribute and modify them, providing that all copies and modifications are available under the same terms and conditions (i.e., in accordance with the 'Copyleft' principle), Within this context, the objectives of the paper are to: (i) introduce the 'Copyleft' principle; (ii) provide an overview of the methodology we employed to derive the unit costs; (iii) present the unit costs themselves; and (iv) examine the total and mean costs for a range of single and comorbid conditions, as an example of the kind of question that the unit cost data can be used to address. Method: We took relevant data from the Australian National Survey of Mental Health and Wellbeing (NSMHWB), and developed a set of unit costs for inpatient and community encounters. We then examined total and mean costs for a range of single and comorbid conditions. Results: We present the unit costs for mental health admissions and mental health community contacts. Our example, which explored the association between comorbidity and total and mean costs, suggested that comorbidly occurring conditions cost more than conditions which occur on their own. Discussion: Our unit costs, and the materials associated with them, have been published in a freely available form governed by a provision termed 'Copyleft'. They provide a valuable resource for researchers wanting to explore economic questions in mental health. Implications for Health Policies: Our unit costs provide an important resource to inform economic debate in mental health in Australia, particularly in the area of priority-setting. In the past, such debate has largely, been based on opinion. Our unit costs provide the underpinning to strengthen the evidence-base of this debate. Implications for Further Research: We would encourage other Australian researchers to make use of our unit costs in order to foster comparability across studies. We would also encourage Australian and international researchers to adopt the 'Copyleft' principle in equivalent circumstances. Furthermore, we suggest that the provision of 'Copyleft'-contingent funding to support the development of enabling resources for researchers should be considered in the planning of future large-scale collaborative survey work, both in Australia and overseas.

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This paper reports on the evaluation of the implementation of the National Recommendations for the Clinical Management of Alcohol-Related Problems in Indigenous Primary Care Settings undertaken in 2001 through 74 standardized workshops, which sought to determine: ( 1) whether this approach to implementation influenced the likelihood that the National Recommendations would be used; ( 2) whether it influenced participants' willingness to engage with Indigenous patients regarding alcohol-related issues; and ( 3) whether the implementation as a whole influenced both practice and clinicians' willingness to engage. Evaluation included pre-/post-workshop and follow-up questionnaires and a focus group. The findings presented indicate that distribution of clinical resources alone is not sufficient to ensure use and that, particularly for medical practitioners, appropriate introduction not only increases use but also positively influences willingness to engage with alcohol-related problems as part of primary clinical care. Further, the enthusiasm for guideline production should be tempered by the need to develop effective implementation strategies.

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We conducted a national survey of Australian hospitals to assess their use of telehealth. Information was sought from the 814 hospitals with 10 or more beds, excluding the small number that provided only day surgery and seven for which we could not identify a contact person. A total of 564 replies were received (a 69% response rate). Nationally, nearly half (49%) reported that they were engaged in some telehealth activity. However, there was a significant difference across jurisdictions. Hospitals in the public sector were significantly more likely to report the use of telehealth than those in the private sector (62% vs 14%). Hospital remoteness was measured according to the Accessibility/Remoteness Index of Australia (ARIA). The highest levels of use were reported by hospitals in 'very remote' and 'remote' areas (90% and 88%, respectively), with moderate levels of use in 'moderately accessible' and 'accessible' areas (67% and 52%, respectively) and the lowest level of use in 'highly accessible' areas (35%). This trend was significant.

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Aims The study estimated serious adverse event (SAE) rates among entrants to pharmacotherapies for opioid dependence, during treatment and after leaving treatment. Design A longitudinal study based on data from 12 trials included in the Australian National Evaluation of Pharmacotherapies for Opioid Dependence (NEPOD). Participants and settings A total of 1.244 heroin users and methadone patients treated in hospital, community and GP settings. Intervention Six trials included detoxification; all included treatment with methadone, buprenorphine, levo-alpha-acetyl-methadol (LAAM) or naltrexone. Findings During 394 person-years of observation, 79 SAEs of 28 types were recorded. Naltrexone participants experienced 39 overdoses per 100 person-years after leaving treatment (44% occurred within 2 weeks after stopping naltrexone). This was eight times the rate recorded among participants who left agonist treatment. Rates of all other SAEs were similar during treatment versus out of treatment, for both naltrexone-treated and agonist-treated participants. Five deaths occurred, all among participants who had left treatment, at a rate of six per 100 person-years. Total SAE rates during naltrexone and agonist treatments were similar (20, 14 per 100 person-years, respectively). Total SAE and death rates observed among participants who had left treatment were three and 19 times the corresponding rates during treatment. Conclusions Individuals who leave pharmacotherapies for opioid dependence experience higher overdose and death rates compared with those in treatment. This may be due partly to a participant self-selection effect rather than entirely to pharmacotherapy being protective. Clinicians should alert naltrexone treatment patients in particular about heroin overdose risks. Duty of care may extend beyond cessation of dosing.

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Background The aims of this study were threefold. First, to ascertain whether personality disorder (PD) was a significant predictor of disability (as measured in a variety of ways) over and above that contributed by Axis I mental disorders and physical conditions. Second, whether the number of PD diagnoses given to an individual resulted in increasing severity of disability, and third, whether PD was a significant predictor of health and mental health consultations with GPs, psychiatrists, and psychologists, respectively, over the last 12 months. Method Data were obtained from the National Survey of Mental Health and Wellbeing, conducted between May and August 1997. A stratified random sample of households was generated, from which all those aged 18 and over were considered potential interviewees. There were 10 641 respondents to the survey, and this represented a response rate of 78%. Each interviewee was asked questions indexing specific ICD-10 PD criteria. Results Five measures of disability were examined. It was found that PD was a significant predictor of disability once Axis I and physical conditions were taken into account for four of the five disability measures. For three of the dichotomously-scored disability measures, odds ratios ranged from 1.88 to 6.32 for PD, whilst for the dimensionally-scored Mental Summary Subscale of the SF-12, a beta weight of -0.17 was recorded for PD. As regards number of PDs having a quasi-linear relationship to disability, there was some indication of this on the SF-12 Mental Summary Subscale and the two role functioning measures, and less so on the other two measures. As regards mental consultations, PD was a predictor of visits to GPs, psychiatrists and psychologists, over and above Axis I disorders and physical conditions. Conclusion The study reports findings from a nationwide survey conducted within Australia and as such the data are less influenced by the selection and setting bias inherent in other germane studies. However, it does support previous findings that PD is a significant predictor of disability and mental health consultations independent of Axis I disorders and physical conditions.