959 resultados para Characteristic curves
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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O estudo das curvas características de um transístor permite conhecer um conjunto de parâmetros essenciais à sua utilização tanto no domínio da amplificação de sinais como em circuitos de comutação. Deste estudo é possível obter dados em condições que muitas vezes não constam na documentação fornecida pelos fabricantes. O trabalho que aqui se apresenta consiste no desenvolvimento de um sistema que permite de forma simples, eficiente e económica obter as curvas características de um transístor (bipolar de junção, efeito de campo de junção e efeito de campo de metal-óxido semicondutor), podendo ainda ser utilizado como instrumento pedagógico na introdução ao estudo dos dispositivos semicondutores ou no projecto de amplificadores transistorizados. O sistema é constituído por uma unidade de condicionamento de sinal, uma unidade de processamento de dados (hardware) e por um programa informático que permite o processamento gráfico dos dados obtidos, isto é, traçar as curvas características do transístor. O seu princípio de funcionamento consiste na utilização de um conversor Digital-Analógico (DAC) como fonte de tensão variável, alimentando a base (TBJ) ou a porta (JFET e MOSFET) do dispositivo a testar. Um segundo conversor fornece a variação da tensão VCE ou VDS necessária à obtenção de cada uma das curvas. O controlo do processo é garantido por uma unidade de processamento local, baseada num microcontrolador da família 8051, responsável pela leitura dos valores em corrente e em tensão recorrendo a conversores Analógico-Digital (ADC). Depois de processados, os dados são transmitidos através de uma ligação USB para um computador no qual um programa procede à representação gráfica, das curvas características de saída e à determinação de outros parâmetros característicos do dispositivo semicondutor em teste. A utilização de componentes convencionais e a simplicidade construtiva do projecto tornam este sistema económico, de fácil utilização e flexível, pois permite com pequenas alterações
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Mestrado em Gestão e Avaliação de Tecnologias em Saúde.
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OBJECTIVE:: To examine the accuracy of brain multimodal monitoring-consisting of intracranial pressure, brain tissue PO2, and cerebral microdialysis-in detecting cerebral hypoperfusion in patients with severe traumatic brain injury. DESIGN:: Prospective single-center study. PATIENTS:: Patients with severe traumatic brain injury. SETTING:: Medico-surgical ICU, university hospital. INTERVENTION:: Intracranial pressure, brain tissue PO2, and cerebral microdialysis monitoring (right frontal lobe, apparently normal tissue) combined with cerebral blood flow measurements using perfusion CT. MEASUREMENTS AND MAIN RESULTS:: Cerebral blood flow was measured using perfusion CT in tissue area around intracranial monitoring (regional cerebral blood flow) and in bilateral supra-ventricular brain areas (global cerebral blood flow) and was matched to cerebral physiologic variables. The accuracy of intracranial monitoring to predict cerebral hypoperfusion (defined as an oligemic regional cerebral blood flow < 35 mL/100 g/min) was examined using area under the receiver-operating characteristic curves. Thirty perfusion CT scans (median, 27 hr [interquartile range, 20-45] after traumatic brain injury) were performed on 27 patients (age, 39 yr [24-54 yr]; Glasgow Coma Scale, 7 [6-8]; 24/27 [89%] with diffuse injury). Regional cerebral blood flow correlated significantly with global cerebral blood flow (Pearson r = 0.70, p < 0.01). Compared with normal regional cerebral blood flow (n = 16), low regional cerebral blood flow (n = 14) measurements had a higher proportion of samples with intracranial pressure more than 20 mm Hg (13% vs 30%), brain tissue PO2 less than 20 mm Hg (9% vs 20%), cerebral microdialysis glucose less than 1 mmol/L (22% vs 57%), and lactate/pyruvate ratio more than 40 (4% vs 14%; all p < 0.05). Compared with intracranial pressure monitoring alone (area under the receiver-operating characteristic curve, 0.74 [95% CI, 0.61-0.87]), monitoring intracranial pressure + brain tissue PO2 (area under the receiver-operating characteristic curve, 0.84 [0.74-0.93]) or intracranial pressure + brain tissue PO2+ cerebral microdialysis (area under the receiver-operating characteristic curve, 0.88 [0.79-0.96]) was significantly more accurate in predicting low regional cerebral blood flow (both p < 0.05). CONCLUSION:: Brain multimodal monitoring-including intracranial pressure, brain tissue PO2, and cerebral microdialysis-is more accurate than intracranial pressure monitoring alone in detecting cerebral hypoperfusion at the bedside in patients with severe traumatic brain injury and predominantly diffuse injury.
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Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.
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OBJECTIVE: To develop a simple prognostic model to predict outcome at 1 month after acute basilar artery occlusion (BAO) with readily available predictors. METHODS: The Basilar Artery International Cooperation Study (BASICS) is a prospective, observational, international registry of consecutive patients who presented with an acute symptomatic and radiologically confirmed BAO. We considered predictors available at hospital admission in multivariable logistic regression models to predict poor outcome (modified Rankin Scale [mRS] score 4-5 or death) at 1 month. We used receiver operator characteristic curves to assess the discriminatory performance of the models. RESULTS: Of the 619 patients, 429 (69%) had a poor outcome at 1 month: 74 (12%) had a mRS score of 4, 115 (19%) had a mRS score of 5, and 240 (39%) had died. The main predictors of poor outcome were older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIH Stroke Scale (NIHSS) score, and longer time to treatment. A prognostic model that combined demographic data and stroke risk factors had an area under the receiver operating characteristic curve (AUC) of 0.64. This performance improved by including findings from the neurologic examination (AUC 0.79) and CT imaging (AUC 0.80). A risk chart showed predictions of poor outcome at 1 month varying from 25 to 96%. CONCLUSION: Poor outcome after BAO can be reliably predicted by a simple model that includes older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIHSS score, and longer time to treatment.
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Background: Ventilator-associated pneumonia (VAP) is the most common hospital-acquired, life-threatening infection. Poor outcome and health-care costs of nosocomial pneumonia remain a global burden. Currently, physicians rely on their experience to discriminate patients with good and poor outcome. However, standardized prognostic measures might guide medical decisions in the future. Pancreatic stone protein (PSP)/regenerating protein (reg) is associated with inflammation, infection, and other disease-related stimuli. The prognostic value of PSP/reg among critically ill patients is unknown. The aim of this pilot study was to evaluate PSP/reg in VAP.Methods: One hundred one patients with clinically diagnosed VAP were assessed. PSP/reg was retrospectively analyzed using deep-frozen serum samples from VAP onset up to day 7. The main end point was death within 28 days after VAP onset.Results: Serum PSP/reg was associated with the sequential organ failure assessment score from VAP onset (Spearman rank correlation coefficient 0.49 P < .001) up to day 7. PSP/reg levels at VAP onset were elevated in nonsurvivors (n = 20) as compared with survivors (117.0 ng/mL [36.1-295.3] vs 36.3 ng/mL [21.0-124.0] P = .011). The areas under the receiver operating characteristic curves of PSP/reg to predict mortality/survival were 0.69 at VAP onset and 0.76 at day 7. Two PSP/reg cutoffs potentially allow for identification of individuals with a particularly good and poor outcome. Whereas PSP/reg levels below 24 ng/mL at YAP onset were associated with a good chance of survival, levels above 177 ng/mL at day 7 were present in patients with a very poor outcome.Conclusions: Serum PSP/reg is a biomarker related to organ failure and outcome in patients with VAP.
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OBJECTIVES: The aim of this study was to evaluate new electrocardiographic (ECG) criteria for discriminating between incomplete right bundle branch block (RBBB) and the Brugada types 2 and 3 ECG patterns. BACKGROUND: Brugada syndrome can manifest as either type 2 or type 3 pattern. The latter should be distinguished from incomplete RBBB, present in 3% of the population. METHODS: Thirty-eight patients with either type 2 or type 3 Brugada pattern that were referred for an antiarrhythmic drug challenge (AAD) were included. Before AAD, 2 angles were measured from ECG leads V(1) and/or V(2) showing incomplete RBBB: 1) α, the angle between a vertical line and the downslope of the r'-wave, and 2) β, the angle between the upslope of the S-wave and the downslope of the r'-wave. Baseline angle values, alone or combined with QRS duration, were compared between patients with negative and positive results on AAD. Receiver-operating characteristic curves were constructed to identify optimal discriminative cutoff values. RESULTS: The mean β angle was significantly smaller in the 14 patients with negative results on AAD compared to the 24 patients with positive results on AAD (36 ± 20° vs. 62 ± 20°, p < 0.01). Its optimal cutoff value was 58°, which yielded a positive predictive value of 73% and a negative predictive value of 87% for conversion to type 1 pattern on AAD; α was slightly less sensitive and specific compared with β. When the angles were combined with QRS duration, it tended to improve discrimination. CONCLUSIONS: In patients with suspected Brugada syndrome, simple ECG criteria can enable discrimination between incomplete RBBB and types 2 and 3 Brugada patterns.
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ECG criteria for left ventricular hypertrophy (LVH) have been almost exclusively elaborated and calibrated in white populations. Because several interethnic differences in ECG characteristics have been found, the applicability of these criteria to African individuals remains to be demonstrated. We therefore investigated the performance of classic ECG criteria for LVH detection in an African population. Digitized 12-lead ECG tracings were obtained from 334 African individuals randomly selected from the general population of the Republic of Seychelles (Indian Ocean). Left ventricular mass was calculated with M-mode echocardiography and indexed to body height. LVH was defined by taking the 95th percentile of body height-indexed LVM values in a reference subgroup. In the entire study sample, 16 men and 15 women (prevalence 9.3%) were finally declared to have LVH, of whom 9 were of the reference subgroup. Sensitivity, specificity, accuracy, and positive and negative predictive values for LVH were calculated for 9 classic ECG criteria, and receiver operating characteristic curves were computed. We also generated a new composite time-voltage criterion with stepwise multiple linear regression: weighted time-voltage criterion=(0.2366R(aVL)+0.0551R(V5)+0.0785S(V3)+ 0.2993T(V1))xQRS duration. The Sokolow-Lyon criterion reached the highest sensitivity (61%) and the R(aVL) voltage criterion reached the highest specificity (97%) when evaluated at their traditional partition value. However, at a fixed specificity of 95%, the sensitivity of these 10 criteria ranged from 16% to 32%. Best accuracy was obtained with the R(aVL) voltage criterion and the new composite time-voltage criterion (89% for both). Positive and negative predictive values varied considerably depending on the concomitant presence of 3 clinical risk factors for LVH (hypertension, age >/=50 years, overweight). Median positive and negative predictive values of the 10 ECG criteria were 15% and 95%, respectively, for subjects with none or 1 of these risk factors compared with 63% and 76% for subjects with all of them. In conclusion, the performance of classic ECG criteria for LVH detection was largely disparate and appeared to be lower in this population of East African origin than in white subjects. A newly generated composite time-voltage criterion might provide improved performance. The predictive value of ECG criteria for LVH was considerably enhanced with the integration of information on concomitant clinical risk factors for LVH.
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The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.
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OBJECTIVES: Therapeutic hypothermia and pharmacological sedation may influence outcome prediction after cardiac arrest. The use of a multimodal approach, including clinical examination, electroencephalography, somatosensory-evoked potentials, and serum neuron-specific enolase, is recommended; however, no study examined the comparative performance of these predictors or addressed their optimal combination. DESIGN: Prospective cohort study. SETTING: Adult ICU of an academic hospital. PATIENTS: One hundred thirty-four consecutive adults treated with therapeutic hypothermia after cardiac arrest. MEASUREMENTS AND MAIN RESULTS: Variables related to the cardiac arrest (cardiac rhythm, time to return of spontaneous circulation), clinical examination (brainstem reflexes and myoclonus), electroencephalography reactivity during therapeutic hypothermia, somatosensory-evoked potentials, and serum neuron-specific enolase. Models to predict clinical outcome at 3 months (assessed using the Cerebral Performance Categories: 5 = death; 3-5 = poor recovery) were evaluated using ordinal logistic regressions and receiving operator characteristic curves. Seventy-two patients (54%) had a poor outcome (of whom, 62 died), and 62 had a good outcome. Multivariable ordinal logistic regression identified absence of electroencephalography reactivity (p < 0.001), incomplete recovery of brainstem reflexes in normothermia (p = 0.013), and neuron-specific enolase higher than 33 μg/L (p = 0.029), but not somatosensory-evoked potentials, as independent predictors of poor outcome. The combination of clinical examination, electroencephalography reactivity, and neuron-specific enolase yielded the best predictive performance (receiving operator characteristic areas: 0.89 for mortality and 0.88 for poor outcome), with 100% positive predictive value. Addition of somatosensory-evoked potentials to this model did not improve prognostic accuracy. CONCLUSIONS: Combination of clinical examination, electroencephalography reactivity, and serum neuron-specific enolase offers the best outcome predictive performance for prognostication of early postanoxic coma, whereas somatosensory-evoked potentials do not add any complementary information. Although prognostication of poor outcome seems excellent, future studies are needed to further improve prediction of good prognosis, which still remains inaccurate.
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The soil structure transformation from ferralic to nitic horizons was studied in a toposequence on quaternary red clayey sediments and diabase in Piracicaba (SP), Brazil. Morphological and micromorphological studies, image analysis, soil water characteristic curves and monitoring of (total) soil water potential head were used. The presence of polyconcave vughs, clayskins and planar voids shows that the vertical and lateral transition and structural transformation from ferralic to nitic horizons is given by the coalescence of the microaggregates, probably due to tensions created in a drier period in the past. Changes to a more humid climate with a defined dry season and alternate drying and wetting cycles resulted in the fissuration of the previously coalesced material, forming polyhedral aggregates and microaggregates. Simultaneously, clay illuviation filled the voids and together with the compacting action of the biological activity of these soils contributed to the coalescence of microaggregates.
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OBJECTIVE: This study aimed to assess the impact of individual comorbid conditions as well as the weight assignment, predictive properties and discriminating power of the Charlson Comorbidity Index (CCI) on outcome in patients with acute coronary syndrome (ACS). METHODS: A prospective multicentre observational study (AMIS Plus Registry) from 69 Swiss hospitals with 29 620 ACS patients enrolled from 2002 to 2012. The main outcome measures were in-hospital and 1-year follow-up mortality. RESULTS: Of the patients, 27% were female (age 72.1 ± 12.6 years) and 73% were male (64.2 ± 12.9 years). 46.8% had comorbidities and they were less likely to receive guideline-recommended drug therapy and reperfusion. Heart failure (adjusted OR 1.88; 95% CI 1.57 to 2.25), metastatic tumours (OR 2.25; 95% CI 1.60 to 3.19), renal diseases (OR 1.84; 95% CI 1.60 to 2.11) and diabetes (OR 1.35; 95% CI 1.19 to 1.54) were strong predictors of in-hospital mortality. In this population, CCI weighted the history of prior myocardial infarction higher (1 instead of -0.4, 95% CI -1.2 to 0.3 points) but heart failure (1 instead of 3.7, 95% CI 2.6 to 4.7) and renal disease (2 instead of 3.5, 95% CI 2.7 to 4.4) lower than the benchmark, where all comorbidities, age and gender were used as predictors. However, the model with CCI and age has an identical discrimination to this benchmark (areas under the receiver operating characteristic curves were both 0.76). CONCLUSIONS: Comorbidities greatly influenced clinical presentation, therapies received and the outcome of patients admitted with ACS. Heart failure, diabetes, renal disease or metastatic tumours had a major impact on mortality. CCI seems to be an appropriate prognostic indicator for in-hospital and 1-year outcomes in ACS patients. ClinicalTrials.gov Identifier: NCT01305785.
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OBJECTIVE: To better assess the diagnosis of an infection in patients presenting at an emergency department with peripheral blood leukocytosis (>10 x 10(9) cells/l) on laboratory testing. METHODS: We prospectively evaluated serum procalcitonin concentration (PCT), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). Patients were divided into two groups according to their final diagnosis: patients with infection and those without infection. PCT, CRP, and ESR were compared between these groups. Sensitivity, specificity, positive predictive values, negative predictive values, receiver operating characteristic curves, and areas under the curves were calculated for each biological measurement. RESULTS: Out of 173 patients, 99 (57%) had a final diagnosis of systemic infection. If a cutoff point of 0.5 ng/ml is considered, procalcitonin concentration had a sensitivity of 0.57, a specificity of 0.85, a negative predictive value of 0.59, and a positive predictive value of 0.84 for the diagnosis of a systemic infection. Adding CRP or ESR to PCT gave no more information (p=0.84). CONCLUSIONS: Only about half of the patients attending the emergency department with leukocytosis were suffering from an infection. Determination of the procalcitonin level may be useful for these patients, particularly in the case of a value higher than 0.5 ng/ml.
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Treatment options for patients with high-risk acute myeloid leukemia (AML) include high-dose chemotherapy regimens in combination with allogeneic hematopoietic stem cell transplantation, which takes advantage of the donor T-cell-mediated graft-versus-leukemia effect. Together with beneficial responses observed in assays targeted at leukemia-associated antigens (LAA), this encouraged research on cancer vaccines and adoptive cellular therapies in AML. The receptor for hyaluronic acid-mediated motility (RHAMM, CD168) was identified as one of the most promising LAA in AML. Thus far, little is known about in situ expression in leukemic bone marrow blasts or the prognostic role of RHAMM and its interaction partners in AML. We immunohistochemically analyzed the expression and prognostic significance of RHAMM on trephine bone marrow biopsies from 71 AML cases that had been evaluated for cytogenetics and presence of FLT3-internal tandem duplications and NPM1 mutations. Fifty-five patients (77%) were treated with curative intent, while 16 (23%) received the most appropriate supportive care. Twenty of 71 (28%) AML cases were considered RHAMM+. Receiver operating characteristic curves showed significant discriminatory power considering overall survival (OS) in AML patients treated curatively for RHAMM (p = 0.015). Multivariable analysis revealed that expression of RHAMM in >5% of leukemic blasts identifies a subgroup of curatively treated cases with adverse OS independent of failures to achieve complete remission. RHAMM not only represents a promising LAA with specific T-cell responses in AML but, if assessed in situ on blasts, also a probable prognostic factor.