SEARCH · PubMed Health
Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Statistical models for variance components can be used to characterize the components of variance in potency estimates obtained from a bioassay. We outline these methods and discuss the implications for replication strategy. An example is provided.
OBJECTIVES: We examined the relationships among depressive symptoms, physician diagnosis of depression, and charges for care. STUDY DESIGN: We used a prospective observational design. POPULATION: Five hundred eight new adult patients were randomly assigned to senior residents in family practice and internal medicine. OUTCOMES MEASURED: Self-reports of health status assessment (Medical Outcomes Study Short Form-36) and depressive symptoms (Beck Depression Inventory) were determined at study entry and at 1-year follow-up. Physician diagnosis of depression was determined by chart audit; charges for care were monitored electronically. RESULTS: Symptoms of depression and the diagnosis of depression were associated with charges for care. Statistical models were developed to identify predictors for the occurrence and magnitude of medical charges. Neither depressive symptoms nor diagnosis of depression significantly predicted the occurrence of charges in the areas studied, but physician diagnosis of depression predicted the magnitude of primary care and total charges. CONCLUSIONS: A complex relationship exists among depressive symptoms, the diagnosis of depression, and charges for medical care. Understanding these relationships may help primary care physicians diagnose depression and deliver primary care to depressed patients more effectively while managing health care expenditures.
OBJECTIVE: To determine the value of using risk factors to decide which patients should undergo serum screening for type 2 diabetes. SEARCH STRATEGIES: The MEDLINE and EMBASE electronic databases were searched for original studies of screening for type 2 diabetes on the basis of risk factors. The reference lists of all reviews, letters, editorials, consensus statements, and guidelines for diabetes screening were searched for additional studies. The Cochrane database was also searched for relevant reviews. SELECTION CRITERIA: All original studies regarding selective serum screening for type 2 diabetes on the basis of risk factors were included. review. Three studies were cross-sectional in design; 3 employed survey data to develop computerized statistical models that used risk factors to identify cases of type 2 diabetes; and 1 used a similar method, but the resulting model was field tested in a separate population. No study describes a risk-factor-based method or instrument that helps substantially in the diagnosis of type 2 diabetes. CONCLUSIONS: Selective screening for type 2 diabetes on the basis of risk factors cannot be recommended. Serum screening can be offered to patients who present with typical symptoms of diabetes.
OBJECTIVE: To estimate the magnitude of misclassification rates with commonly used algorithms for the detection of hypertensives and to suggest a sequential approach to screening. DESIGN: A conventional statistical model was used with several different algorithms to determine the number and types of errors made in categorizing two different populations, a general population sample and a population with a high risk of hypertension. METHODS: The calculations were made for single-visit screens, similar to those used in epidemiologic studies, for three-visit screens commonly used in clinical practice and clinical trials for cutoff points of 85, 95 and 105 mmHg. A sequential probability ratio screen was proposed and the error rates estimated. RESULTS: Perhaps only one-third to two-thirds of people whose measured diastolic pressures exceed 95 mmHg actually have average pressures that high. The disparity between a single measured diastolic pressure and the mean of many pressure values also leads to errors in identifying individual subjects with mild hypertension. In a general population, single measurements of diastolic pressure exceed 95 mmHg in approximately equal numbers of normotensive, borderline and hypertensive subjects; moreover, one-third of those who are usually in the hypertensive range are not identified. All commonly used screening algorithms give too many false-positive and/or false-negative results. A sequential screening algorithm averaged 3.8 visits per subject and identified 95% of the hypertensives, with only 2.5% of those identified having usual diastolic pressures below 90 mmHg. CONCLUSIONS: Population-based surveys like the National Health and Nutrition Examination Survey (NHANES) may markedly overestimate the true prevalence of hypertension. This overestimate is greatest for mild hypertension and could significantly affect the cost/benefit analyses of public health policy. Alternative screening methods, such as the sequential algorithm proposed, may have significant benefits in providing a correct classification.
Ultrasound blood flow waveforms may be used in the diagnosis of arterial occlusive disease in human legs. We develop a statistical model to predict disease severity, conditional on the ultrasound data and some training data. It belongs to the class of models known as seemingly unrelated regressions, for which the Bayesian predictive density function cannot be evaluated analytically. Allowing for missing components of response vectors in the training data, we describe a first-order approximation to the predictive density, based on a Bayes estimate of the precision matrix. This approximation is then used to generate cross-validated predictions of disease severity in a set of 31 patients. We conclude with a discussion of the results.
Sick leave among the children in 24 day nurseries in Copenhagen was registered during a period of one year. The physical, environmental and hygienic conditions of the institutions were assessed by means of interviews and inspection, supplemented by information from the local authorities. Sick leave constitutes 7.5% of the days during which the institutions were open and the average number of sick days per child varied from 14.6 to 24.4. Comparisons with similar investigations are inclusive on account of variations in the methods of registration and age distributions. It was characteristic of the institutions investigated that these included a number of old institutions in flats, many in streets with considerable traffic and where the conditions of ventilation and space do not conform with present-day standards. In some of the institutions, the hygiene is unsatisfactory, particularly where ventilation, outdoor activities and hand-washing are concerned. A statistically significant connection was found between amount of traffic at the institution, the hygiene and playroom area per child, on one hand, and absence due to sickness, on the other, as assessed by a statistical model for sick leave for child in a given institution. In order to prevent sickness, it is concluded that efforts to improve hygiene and space are desirable and, similarly, further research concerning the effects of atmospheric pollution is relevant.
OBJECTIVES: In schizophrenia research, little attention yet has been directed on methods for analyzing data from studies with repeated measurements over time. Motivation for this research stems from a project within the German Research Network on Schizophrenia, in which an algorithm is developed to guide prodrome-based early intervention strategies in stable first episode patients. METHODS: We present two different approaches for the analysis of correlated response data, the Generalized Estimating Equations (GEE) method and the Artificial Neural Network (ANN) approach. We illustrate the methods using the data of the A.N.I. study, which is one of the largest German multicenter treatment studies in regard to the long-term treatment of schizophrenia conducted between 1983 and 1989. RESULTS: The results of statistical model selection prior to GEE analysis and various data presentation methods for ANNs are presented. The primary goal of our evaluation is to investigate if the defined prodromes are valid predictors for relapse. Additionally, it is shown that both methods are applicable on a realistic data set. CONCLUSIONS: It is concluded that both methods are suitable for predictor analysis especially since all variable time points of the patients are included instead of only selected, so that it can be assumed that results are not biased. With the GEE method a test of association for each predictor can be performed whereas with ANNs a general proposition can be made for prodromes depending on the type of data presentation. Using the A.N.I. data the prodrome 'trouble sleeping' seems to be the most informative predictor. Finally, the important differences of the two methods are discussed.
The Boston brace has been shown to efficiently prevent scoliosis curve progression. However, it rarely achieves complete 3-D correction; its adjustment being often empirical and its biomechanical modes of action still remaining poorly understood. This study investigates the in-brace spinal shape (correction) in relationship with the patient's out-of-brace deformation, and the adjustment parameters of the brace, namely the strap tensions and the equivalent forces calculated at the patient-brace interface. Many of the observed relationships illustrate the fact that the in-brace spinal shape is strongly related to the characteristics of the patient's out-of-brace deformation. The pattern of pressure distribution as described by the equivalent forces computed in the thoracic, lumbar, pelvic and sternal regions has important effect on the in-brace Cobb angles, lumbar lordosis, frontal and sagittal imbalances and the apical axial rotations. The complex role of the strap tension on the correction has not been explained and needs further investigation. This project has the potential to give insight into the biomechanical effects of brace treatment by providing a statistical model leading to more rational and personalized brace adjustments.
We propose a wavelet multi-resolution analysis to localize specific features in both lateral and frontal radiographs. This analysis allows an elegant spectral investigation that leads simultaneously to image de-noising and edge extraction. It is combined with an a priori knowledge of the spine's morphology and a 3D spline curve characterization of its global shape. Actual work deals with identifying the contours of the vertebral bodies and the localization of vertebrae's endplates. However, this information could also lead to the selection of a 3D statistical model of the spine suited for the studied deformation. Working with retro-projections of the model, we aim at creating edge models for each vertebra that will be used to geometrically match the wavelet's edges. The manual feature identification could then be replaced in the reconstruction of the 3D representation of the spine.
BACKGROUND: The present case-control investigation was undertaken with the aim of thoroughly assessing the risk profile of young coronary patients and to correlate it with their endothelium-dependent vasodilation and with the presence of atherosclerotic lesions. METHODS: Forty-eight subjects (age < 41 years) diagnosed with myocardial infarction were screened. They were matched 1:1, for age and sex, with controls. We evaluated the serum total, HDL-, and LDL-cholesterol, triacylglycerols, fibrinogen, homocysteine, folic acid, vitamin B12, vitamin E, antioxidant capacity, and uric acid levels, and we also analyzed the patients for the presence of Helicobacter pylori and of methylenetetrahydrofolate reductase and cystathionine beta-synthase genetic mutations. Post-ischemic vasodilation of the brachial artery was evaluated and the intima-media thickness of the carotid arteries was measured at echo-Doppler. RESULTS: A statistical modeling selection between block variables revealed that smoking, the apoepsilon genotype, dyslipidemia, fibrinogen, vitamin E concentrations, and intima-media thickness were important predictors of cardiovascular disease, with an accuracy of 91.7%. CONCLUSIONS: On the basis of these results, we believe that acute coronary events in young subjects should be followed by a screening of their siblings, as they might be at higher risk for cardiovascular disease.
An important component of arbovirus surveillance is monitoring the vector for presence of the pathogen. Intervention and preventive programs need early detection of arboviral activity in mosquito populations. In this report, we examine the factors affecting the probability of detection of mosquito infections. Since arbovirus infection rates in mosquito populations are very low, observations of zero-infected mosquito samples are common. Using statistical models, we describe methods to estimate the probability of detection and upper bounds of confidence intervals of mosquito infection rates as measures of confidence for observations of zero infection. Our results show that detection of low levels of mosquito infections requires large samples (greater than 1,600 individuals) for a high probability (0.8) of detection. Due to focal transmission of arboviruses, grouping samples over different sampling sites and times is often inappropriate for detection of mosquito infection. We emphasize sample size as a key determinant in detection of mosquito infections and recommend intensified entomologic surveys at sentinel sites to detect arboviral activity.
INTRODUCTION: Midair collisions cause loss of life and property and undermine general aviation; they also represent failures of the see-and-avoid concept in air traffic control. This study identifies limitations of the see-and-avoid concept. METHODS: Analysis of National Transportation Safety Board data on 159 U.S. civil aviation midair collisions and limitations of the see-and-avoid concept. RESULTS: On average, there were 15.6 midair collisions annually from 1991 through 2000. At least one aircraft was maneuvering in 88% of collisions, and both in 70%. There were 77% that involved arrival to, departure from, or flight over an airport, with 61% in the traffic pattern. Head-tail collisions were more frequent in the traffic pattern than out (28.3%, 2.8%, p < 0.05). Other horizontal convergence angles were equally frequent in or out of the pattern: head-on (8.3%, 11.0%), obtuse (11.0%, 8.3%), and acute (13.8%, 16.6%). DISCUSSION: Because the relative bearing to each aircraft on an unaccelerated collision course is constant, pilots sometimes cannot see converging aircraft when climbing, descending, or level. Even if a converging aircraft is unobstructed, it appears small, motionless, camouflaged, and inconspicuous until imminent impact. A statistical model reveals that the probabilities of seeing and avoiding a converging 40-ft aircraft, for an optimal observer or theoretical pilot scanning 2/3 or 1/3 of the time, respectively, are less than 0.91, 0.60, 0.30 at 200 kn; 0.49, 0.32, 0.16 at 300 kn; 0.28, 0.18, 0.09 at 400 kn; and 0.15, 0.10, 0.05 at 500 kn. The see-and-avoid concept has striking physical and behavioral limitations.
This study describes a source apportionment methodology for nitrogen river transport. A statistical model has been developed to determine the contribution of each source (punctual and diffuse) of nitrogen to river-mouth transport. A non-linear regression equation was developed, relating measured nitrogen transport rates in streams to spatially referenced nitrogen sources and basin characteristics. The model considers applied fertilizer, atmospheric deposition and point discharges as sources, and winter rainfall, average air temperature, topographic wetness index and dry season flow as basin characteristics. The model was calibrated in an area of 8913 km2 in East Anglia (UK). In the studied area, the average contribution of agriculture to the nitrogen load is estimated around 71%. Point sources and atmospheric deposition respectively account for 24% and 5% of the exported nitrogen. The model allowed the estimation of the contribution of each source to nitrogen emissions and the nitrogen retention in soils and waters as influenced by basin factors.
INTRODUCTION: In recent years, many syndromic surveillance systems have been deployed around the United States for the early detection of biologic terrorism-related and naturally occurring outbreaks. These systems and the associated aberration detection methods need to be evaluated. OBJECTIVE: This study evaluated several detection methods of the Early Aberration Reporting System (EARS) under serially correlated syndromic data and to demonstrated the need for calibrating these methods. METHODS: In an initial evaluation of the Syndromic Tracking and Reporting System in Hillsborough County, Florida, serially correlated syndromic data were simulated using statistical models in conjunction with real syndromic data. The detection methods were tested against two patterns of simulated outbreaks. They were compared using a conditional average run length and a receiver operating characteristic curve under defined patterns of detection. RESULTS: Increasing serial correlation inflates the false alarm rate and elevates sensitivity. Among the detection methods in EARS, C2 and P-chart have the best overall receiver operating characteristic curve within the context of the simulations. C2 is least affected by the serial correlation, the outbreak type, and the defined patterns of detection signal. CONCLUSION: Evaluation of the detection methods needs to be adaptable to the constantly changing nature of syndromic surveillance. Deployment of EARS and other methods requires adjusting the false alarm rate and sensitivity in accordance with the syndromic data, the operating resources, and the objectives of the local system. For timely detection, C2 is superior to other methods, including C3, under the simulation conditions. P-chart is the most sensitive when the serial correlation is negligible.
Ontogenetic growth can be described by mathematical equations constructed on the goodness of fit. Recently, the biological mechanism underlying mathematical growth equations has been explored using basic cellular properties. Here, we derive a general statistical model for understanding the genetic regulation of ontogenetic growth by integrating those biologically-proven meaningful growth equations into a quantitative trait locus (QTL) mapping framework. We can characterize the dynamic patterns of effects of QTL governing growth curves and estimate the global effect of the underlying QTL throughout the entire course of growth. The model provides the basis for deciphering genetic relationships for growth rates and the timing of life history events for any kind of organisms.
Measurement of transpiration is essential to assess plant water use efficiency. Applying Grainer method, this paper measured the sap flow of Choerospondias axillaries in an agro-forestrial system, aimed to evaluate the effects of intercropping and pruning on the diurnal variation of transpiration, and to relate the transpiration rate with climatic factors. The results showed that the diurnal variation of Choerospondias arillaries transpiration rate appeared in parabola, low in the morning and evening, and high at noon. The transpiration rate was closely related to leaf stomatal conductivity and soil water potential, especially the water potential in 100 cm soil depth (R = 0.737). The transpiration rate of Choerospondias axillaries was increased by about 40% approximately 160% in agro-forestrial system through the changes in regional environment and in the deep soil water use by tree. Correlation analysis and multi-factor successive regression analysis indicated that the transpiration was controlled by ray radiation intensity, air temperature and ground temperature, followed by the difference between saturated and actual vapor pressure and the wind speed. A statistical model for calculating the sap flow rate by micrometeorological factors was also provided.
Several new advances facilitate current understanding of the progression of Parkinson's disease. The application of statistical modeling techniques has helped to estimate rates of clinical decline in the context of symptomatic interventions. These approaches may allow a new means for testing neuroprotection effects even when patients are on dopaminergic treatment. Further, the development of new rating scales, specifically the Movement Disorder Society-initiated revision of the Unified Parkinson's Disease Rating Scale has capitalized on a greater clinical appreciation of non-motor elements of Parkinson's disease. Finally, adaptations of new technologies that are computer-based and enable data transmission from at-home environments allow researchers to capture disease impairment and disability with potentially greater precision and much more frequently than permissible in a hospital clinic or practice setting.
The objective of the present research was to evaluate the potential of NIR diffuse reflectance spectroscopy as a way for nondestructive measurement of loquat soluble solid content of three varieties harvested from two orchards. According to the analysis, it was shown that the correlation coefficient of curves was relatively high in the two regions of 1400-1500 nm and 1900- 2000 nm. Statistical models were developed using partial least square regression (PLSR), stepwise multiple linear regression (SMLR) and principal component regression (PCR) methods in the full spectral region from 800 to 2500 nm and in the combined region of 1400-1500 nm and 1900-2000 nm. The results of PLSR model in the full spectral region were better than those of other models. The modeling results based on derivative spectra were not as good as those based on original spectra. Finally, a model was established based on the original spectra with 17 points smoothing for all the three varieties in the full spectral region by PLSR method. The correlation coefficients of calibration and validation were 0.96 and 0.95, respectively. The results indicate that it is feasible to use NIR spectroscopy technique for quantitative analysis of loquat soluble solid content.