800 resultados para PREDICTING FALLS
Resumo:
INTRODUCTION: Population aging in Brazil has increased the prevalence of neurodegenerative diseases (Parkinson's and Alzheimer's disease) and affective disorders (anxiety, depression), all common in old age. A retrospective study was carried out with the purpose of ascertaining if there is an association between falls and psychoactive medication use among older residents of a community in Brazil. METHODS: All residents aged 65+ (n=161) of one neighborhood of Campo Belo, Brazil (population of 48,000) were evaluated regarding the use of psychoactive drugs and the occurrence of falls in the 12 months preceding the study. Vision and hearing screenings were also performed. RESULTS: From the study population, 9.3% were taking prolonged half-life benzodiazepines, 4.4% anticonvulsants (mostly barbiturates), 2.5% antidepressants (all cyclics) and 8.1% alpha-methyldopa. No subject reported use of hypnotics, neuroleptics or drugs to treat Alzheimer's or Parkinson's diseases (except biperiden). As a whole, drugs that increase the risk of falls were used by 1/5 of this population. In the 12-month period preceding the study, 27 residents (16.8%) experienced falls and, of those, 4 (14.8%) had fracture(s). There was an independent association between psychoactive drug use and falls when variables such as age, gender, vision and hearing were controlled (p=0.02). CONCLUSIONS: Although the population of this neighborhood must be considered young (only 4% are 65 years old or more), there are already problems related to the use of psychoactive drugs among people. Prescribed anxiolytics, anticonvulsants, antidepressants and antihypertensives are not appropriate for this age group and their use is associated with falls.
Resumo:
OBJECTIVE: To determine the best cut-offs of body mass index for identifying alterations of blood lipids and glucose in adolescents. METHODS: A probabilistic sample including 577 adolescent students aged 12-19 years in 2003 (210 males and 367 females) from state public schools in the city of Niterói, Southeastern Brazil, was studied. The Receiver Operating Characteristic curve was used to identify the best age-adjusted BMI cut-off for predicting high levels of serum total cholesterol (>150mg/dL), LDL-C (>100mg/dL), serum triglycerides (>100mg/dL), plasma glucose (>100mg/dL) and low levels of HDL-C (< 45mg/dL). Four references were used to calculate sensitivity and specificity of BMI cut-offs: one Brazilian, one international and two American. RESULTS: The most prevalent metabolic alterations (>50%) were: high total cholesterol and low HDL-C. BMI predicted high levels of triglycerides in males, high LDL-C in females, and high total cholesterol and the occurrence of three or more metabolic alterations in both males and females (areas under the curve range: 0.59 to 0.67), with low sensitivity (57%-66%) and low specificity (58%-66%). The best BMI cut-offs for this sample (20.3 kg/m² to 21.0 kg/m²) were lower than those proposed in the references studied. CONCLUSIONS: Although BMI values lower than the International cut-offs were better predictor of some metabolic abnormalities in Brazilian adolescents, overall BMI is not a good predictor of these abnormalities in this population.
Resumo:
Aim - To identify clinical and/or genetic predictors of response to several therapies in Crohn’s disease (CD) patients. Methods - We included 242 patients with CD (133 females) aged (mean ± standard deviation) 39 ± 12 years and a disease duration of 12 ± 8 years. The single-nucleotide polymorphisms (SNPs) studied were ABCB1 C3435T and G2677T/A, IL23R G1142A, C2370A, and G9T, CASP9 C93T, Fas G670A and LgC844T, and ATG16L1 A898G. Genotyping was performed with real-time PCR with Taqman probes. Results - Older patients responded better to 5-aminosalicylic acid (5-ASA) and to azathioprine (OR 1.07, p = 0.003 and OR 1.03, p = 0.01, respectively) while younger ones responded better to biologicals (OR 0.95, p = 0.06). Previous surgery negatively influenced response to 5-ASA compounds (OR 0.25, p = 0.05), but favoured response to azathioprine (OR 2.1, p = 0.04). In respect to genetic predictors, we observed that heterozygotes for ATGL16L1 SNP had a significantly higher chance of responding to corticosteroids (OR 2.51, p = 0.04), while homozygotes for Casp9 C93T SNP had a lower chance of responding both to corticosteroids and to azathioprine (OR 0.23, p = 0.03 and OR 0.08, p = 0.02,). TT carriers of ABCB1 C3435T SNP had a higher chance of responding to azathioprine (OR 2.38, p = 0.01), while carriers of ABCB1 G2677T/A SNP, as well as responding better to azathioprine (OR 1.89, p = 0.07), had a lower chance of responding to biologicals (OR 0.31, p = 0.07), which became significant after adjusting for gender (OR 0.75, p = 0.005). Conclusions - In the present study, we were able to identify a number of clinical and genetic predictors of response to several therapies which may become of potential utility in clinical practice. These are preliminary results that need to be replicated in future pharmacogenomic studies.
Resumo:
Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”
Resumo:
INTRODUCTION: Predicting outcome in comatose survivors of cardiac arrest is based on data validated by guidelines that were established before the era of therapeutic hypothermia. We sought to evaluate the predictive value of clinical, electrophysiological and imaging data on patients submitted to therapeutic hypothermia. MATERIALS AND METHODS: A retrospective analysis of consecutive patients receiving therapeutic hypothermia during years 2010 and 2011 was made. Neurological examination, somatosensory evoked potentials, auditory evoked potentials, electroencephalography and brain magnetic resonance imaging were obtained during the first 72 hours. Glasgow Outcome Scale at 6 months, dichotomized into bad outcome (grades 1 and 2) and good outcome (grades 3, 4 and 5), was defined as the primary outcome. RESULTS: A total of 26 patients were studied. Absent pupillary light reflex, absent corneal and oculocephalic reflexes, absent N20 responses on evoked potentials and myoclonic status epilepticus showed no false-positives in predicting bad outcome. A malignant electroencephalographic pattern was also associated with a bad outcome (p = 0.05), with no false-positives. Two patients with a good outcome showed motor responses no better than extension (false-positive rate of 25%, p = 0.008) within 72 hours, both of them requiring prolonged sedation. Imaging findings of brain ischemia did not correlate with outcome. DISCUSSION: Absent pupillary, corneal and oculocephalic reflexes, absent N20 responses and a malignant electroencephalographic pattern all remain accurate predictors of poor outcome in cardiac arrest patients submitted to therapeutic hypothermia. CONCLUSION: Prolonged sedation beyond the hypothermia period may confound prediction strength of motor responses.
Resumo:
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
Resumo:
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
Resumo:
Climate change is emerging as one of the major threats to natural communities of the world’s ecosystems; and biodiversity hotspots, such as Madeira Island, might face a challenging future in the conservation of endangered land snails’ species. With this thesis, progresses have been made in order to properly understand the impact of climate on these vulnerable taxa; and species distribution models coupled with GIS and climate change scenarios have become crucial to understand the relations between species distribution and environmental conditions, identifying threats and determining biodiversity vulnerability. With the use of MaxEnt, important changes in the species suitable areas were obtained. Laurel forest species, highly dependent on precipitation and relative humidity, may face major losses on their future suitable areas, leading to the possible extinction of several endangered species, such as Leiostyla heterodon. Despite the complexity of the biological systems, the intrinsic uncertainty of species distribution models and the lack of information about land snails’ functional traits, this analysis contributed to a pioneer study on the impacts of climate change on endemic species of Madeira Island. The future inclusion of predictions of the effect of climate change on species distribution as part of IUCN assessments could contribute to species prioritizing, promoting specific management actions and maximizing conservation investment.
Resumo:
This study deals with investigating the groundwater quality for irrigation purpose, the vulnerability of the aquifer system to pollution and also the aquifer potential for sustainable water resources development in Kobo Valley development project. The groundwater quality is evaluated up on predicting the best possible distribution of hydrogeochemicals using geostatistical method and comparing them with the water quality guidelines given for the purpose of irrigation. The hydro geochemical parameters considered are SAR, EC, TDS, Cl-, Na+, Ca++, SO4 2- and HCO3 -. The spatial variability map reveals that these parameters falls under safe, moderate and severe or increasing problems. In order to present it clearly, the aggregated Water Quality Index (WQI) map is constructed using Weighted Arithmetic Mean method. It is found that Kobo-Gerbi sub basin is suffered from bad water quality for the irrigation purpose. Waja Golesha sub-basin has moderate and Hormat Golena is the better sub basin in terms of water quality. The groundwater vulnerability assessment of the study area is made using the GOD rating system. It is found that the whole area is experiencing moderate to high risk of vulnerability and it is a good warning for proper management of the resource. The high risks of vulnerability are noticed in Hormat Golena and Waja Golesha sub basins. The aquifer potential of the study area is obtained using weighted overlay analysis and 73.3% of the total area is a good site for future water well development. The rest 26.7% of the area is not considered as a good site for spotting groundwater wells. Most of this area fall under Kobo-Gerbi sub basin.
Resumo:
This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.
Resumo:
Introduction Dengue is prevalent in many tropical and sub-tropical regions. The clinical diagnosis of dengue is still complex, and not much data are available. This work aimed at assessing the diagnostic accuracy of the tourniquet test in patients with suspected dengue infection and its positivity in different classifications of this disease as reported to the Information System for Notifiable Disease in Belo Horizonte, State of Minas Gerais, Brazil between 2001 and 2006. Methods Cross-section analysis of the diagnostic accuracy of the tourniquet test for dengue, using IgM-anti-DENV ELISA as a gold standard. Results We selected 9,836 suspected cases, of which 41.1% were confirmed to be dengue. Classic dengue was present in 95.8%, dengue with complications in 2.5% and dengue hemorrhagic fever in 1.7%. The tourniquet test was positive in 16.9% of classic dengue cases, 61.7% of dengue cases with complications and 82.9% of cases of dengue hemorrhagic fever. The sensitivity and specificity of the tourniquet test were 19.1% and 86.4%, respectively. Conclusions A positive tourniquet test can be a valuable tool to support diagnosis of dengue where laboratory tests are not available. However, the absence of a positive test should not be read as the absence of infection. In addition, the tourniquet test was demonstrated to be an indicator of dengue severity.
Resumo:
Dissertação de Mestrado apresentada ao ISPA - Instituto Universitário
Resumo:
Research literature and regulators are unconditional in pointing the disclosure of operating cash flow through direct method a section of unique information. Besides the intuitive facet, it is also consistent in forecasting future operating cash flows and a cohesive piece to financial statement puzzle. Bearing this in mind, I produce an analysis on the usefulness and predictive ability on the disclosure of gross cash receipts and payments over the disclosure of reconciliation between net income and accruals for two markets with special features, Portugal and Spain. Results validate the usefulness of direct method format in predicting future operating cash flow. Key
Resumo:
This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.