Validity of recall absent schoolchildren to free eye health projects

Purpose: To analyze the results of recall absent schoolchildren to eye health projects. Methods: Cross-sectional study. Visual screening was performed in schoolchildren attending 1st to 4th grades at public schools, from 7 to 10 years-old, to select and forward to complete ophthalmic evaluation. The projects were performed during weekends, at a public school, in the same municipality. Free transportation, food and eyeglasses were offered. A second opportunity of examination was offered to the students who were absent from the first call, with the same facilities. Results: 51,509 schoolchildren had their vision tested, 14,651 (28.4%) were referred for ophthalmic examination. Of these, 8,683 (59.3%) attended the first call, 2,228 (37.3%) attended the recall and 25.5% of parents did not take their children to ophthalmic examination. The need for eyeglasses for children who attended the examination was 23.8% and 32.0% in the first opportunity and recall, respectively. The recall increased the coverage in 15.2% (59.3% to 74.5%). Conclusion: An expressive number of parents (25.5%) did not bring their children to be examined, even at a second opportunity of exam. The facilities offered: access, free examination, transportation and glasses. Children who were absent in the first opportunity and appeared at recall had a greater need for eyeglasses. Recall increased the coverage in 15.2% (59.3% to 74.5%) and it is not recommended when financial resources are limited.

A study of pent-up demand in ophthalmology: Divinolandia Hospital/Unicamp

Objective: To assess the waiting time for eye care identifying the number of patients with each complaint; to investigate how the waiting time may worsen the patient's condition; to check the screening of urgent cases for effectiveness; and to devise means of increasing the medical-surgical care capacity. Methods: A retrospective descriptive survey was conducted using data obtained on 12 occasions during collaborative team visits to provide eyecare services. These initiatives were designed to decrease the waiting time and to treat urgent cases that occurred on each occasion; eyecare services were provided every Saturday, in the period from June to August 2006, in 16 cities of the region covered by Conderg (Consortium for the Development of the Sao Joao da Boa Vista Administrative Region). Results: Referrals used 1,743 (87.1%) of the 2,000 places available. The most frequent diagnoses were refractive errors, with 683 cases, corresponding to 39.1% of the total, followed by cataracts, with 296 cases, corresponding to 20.9%. Of the 238 surgeries indicated, 54.6% were phakectomies. Thirty-five (2.0%) cases were considered urgent. Conclusion: The most common diagnoses made during the team visits to manage the excess demand for eyecare were refractive errors and cataracts, which, together, accounted for the majority of the cases. The Divinolandia Hospital has the necessary human and material resources to meet the demand left unattended by the local SUS network. Immediate referral of urgent cases by the primary units' screeners proved effective.

A study of pent-up demand in ophthalmology: Divinolândia Hospital/Unicamp

OBJECTIVE: To assess the waiting time for eye care identifying the number of patients with each complaint; to investigate how the waiting time may worsen the patient's condition; to check the screening of urgent cases for effectiveness; and to devise means of increasing the medical-surgical care capacity. METHODS: A retrospective descriptive survey was conducted using data obtained on 12 occasions during collaborative team visits to provide eyecare services. These initiatives were designed to decrease the waiting time and to treat urgent cases that occurred on each occasion; eyecare services were provided every Saturday, in the period from June to August 2006, in 16 cities of the region covered by Conderg (Consortium for the Development of the São João da Boa Vista Administrative Region). RESULTS: Referrals used 1,743 (87.1%) of the 2,000 places available. The most frequent diagnoses were refractive errors, with 683 cases, corresponding to 39.1% of the total, followed by cataracts, with 296 cases, corresponding to 20.9%. Of the 238 surgeries indicated, 54.6% were phakectomies. Thirty-five (2.0%) cases were considered urgent. CONCLUSION: The most common diagnoses made during the team visits to manage the excess demand for eyecare were refractive errors and cataracts, which, together, accounted for the majority of the cases. The Divinolândia Hospital has the necessary human and material resources to meet the demand left unattended by the local SUS network. Immediate referral of urgent cases by the primary units' screeners proved effective.

Prediction with measurement errors in finite populations

We address the problem of selecting the best linear unbiased predictor (BLUP) of the latent value (e.g., serum glucose fasting level) of sample subjects with heteroskedastic measurement errors. Using a simple example, we compare the usual mixed model BLUP to a similar predictor based on a mixed model framed in a finite population (FPMM) setup with two sources of variability, the first of which corresponds to simple random sampling and the second, to heteroskedastic measurement errors. Under this last approach, we show that when measurement errors are subject-specific, the BLUP shrinkage constants are based on a pooled measurement error variance as opposed to the individual ones generally considered for the usual mixed model BLUP. In contrast, when the heteroskedastic measurement errors are measurement condition-specific, the FPMM BLUP involves different shrinkage constants. We also show that in this setup, when measurement errors are subject-specific, the usual mixed model predictor is biased but has a smaller mean squared error than the FPMM BLUP which points to some difficulties in the interpretation of such predictors. (C) 2011 Elsevier By. All rights reserved.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Homology and errors

A recent review of the homology concept in cladistics is critiqued in light of the historical literature. Homology as a notion relevant to the recognition of clades remains equivalent to synapomorphy. Some symplesiomorphies are homologies inasmuch as they represent synapomorphies of more inclusive taxa; others are complementary character states that do not imply any shared evolutionary history among the taxa that exhibit the state. Undirected character-state change (as characters optimized on an unrooted tree) is a necessary but not sufficient test of homology, because the addition of a root may alter parsimonious reconstructions. Primary and secondary homology are defended as realistic representations of discovery procedures in comparative biology, recognizable even in Direct Optimization. The epistemological relationship between homology as evidence and common ancestry as explanation is again emphasized. An alternative definition of homology is proposed. (c) The Willi Hennig Society 2012.

A log-Birnbaum-Saunders regression model with asymmetric errors

This paper introduces a skewed log-Birnbaum-Saunders regression model based on the skewed sinh-normal distribution proposed by Leiva et al. [A skewed sinh-normal distribution and its properties and application to air pollution, Comm. Statist. Theory Methods 39 (2010), pp. 426-443]. Some influence methods, such as the local influence and generalized leverage, are presented. Additionally, we derived the normal curvatures of local influence under some perturbation schemes. An empirical application to a real data set is presented in order to illustrate the usefulness of the proposed model.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.