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## Gross Domestic Product (GDP) per capita and geographical distribution of ophthalmologists in Brazil

Fonte: Conselho Brasileiro de Oftalmologia
Publicador: Conselho Brasileiro de Oftalmologia

Tipo: Artigo de Revista Científica
Formato: text/html

Publicado em 01/12/2012
EN

Relevância na Pesquisa

36.1%

#Health manpower/statistics &#numerical data#Ophthalmologists#Human resources administration#Physician distribution/statistics &#numerical data#Gross domestic product#Census#Brazil

PURPOSE: To assess the number of ophthalmologists in Brazil, their regional distribution, ophthalmologist/habitant ratio, and the relation between ophthalmologist and State Gross Domestic Product (GDP) per capita to aid public health policies. METHODS: An ecologic study was conducted. Data were obtained from the "Census 2011 Brazilian Ophthalmology Council", from "Demographic Census of Brazilian Institute of Geography and Statistics (IBGE) 2010 and from "Brazilian Regional Accounts, 2005-2009"- Ministry of Planning, Budget and Management - IBGE. RESULTS: The number of ophthalmologists in Brazil is 15,719. Considering the performance in more than one municipality, the number of ophthalmologists in service is 17,992, that is, one ophthalmologist for 10,601; the ophthalmologist/site ratio vary among the States from a minimum of 1/51,437 (Amapá) to a maximum of 1/4,279 (Distrito Federal). There is a correlation among State GDP per capita and the number of ophthalmologists/habitant: the higher the GDP per capita, the larger is the number of ophthalmologists acting in the State (p<0.0001). CONCLUSION: According to this study, there is no lack of Ophthalmologists in the country, but a distribution imbalance which leads to professional shortage in particular places. A higher concentration of ophthalmologists/inhabitants was noticed in States which the economic growth is higher...

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## Evaluation of dengue fever reports during an epidemic, Colombia

Fonte: Faculdade de Saúde Pública da Universidade de São Paulo
Publicador: Faculdade de Saúde Pública da Universidade de São Paulo

Tipo: Artigo de Revista Científica
Formato: text/html

Publicado em 01/12/2014
EN

Relevância na Pesquisa

35.88%

#Dengue, epidemiology#Epidemics, statistics &#numerical data#Disease Notification#Sensitivity and Specificity#Epidemiological Surveillance

OBJECTIVE To assess the validity of dengue fever reports and how they relate to the definition of case and severity. METHODS Diagnostic test assessment was conducted using cross-sectional sampling from a universe of 13,873 patients treated during the fifth epidemiological period in health institutions from 11 Colombian departments in 2013. The test under analyses was the reporting to the National Public Health Surveillance System, and the reference standard was the review of histories identified by active institutional search. We reviewed all histories of patients diagnosed with dengue fever, as well as a random sample of patients with febrile syndromes. The specificity and sensitivity of reports were estimated for this purpose, considering the inverse of the probability of being selected for weighting. The concordance between reporting and the findings of the active institutional search was calculated using Kappa statistics. RESULTS We included 4,359 febrile patients, and 31.7% were classified as compatible with dengue fever (17 with severe dengue fever; 461 with dengue fever and warning signs; 904 with dengue fever and no warning signs). The global sensitivity of reports was 13.2% (95%CI 10.9;15.4) and specificity was 98.4% (95%CI 97.9;98.9). Sensitivity varied according to severity: 12.1% (95%CI 9.3;14.8) for patients presenting dengue fever with no warning signs; 14.5% (95%CI 10.6;18.4) for those presenting dengue fever with warning signs...

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## Every LWF and AMP chain graph originates from a set of causal models

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

35.91%

This paper aims at justifying LWF and AMP chain graphs by showing that they
do not represent arbitrary independence models. Specifically, we show that
every chain graph is inclusion optimal wrt the intersection of the independence
models represented by a set of directed and acyclic graphs under conditioning.
This implies that the independence model represented by the chain graph can be
accounted for by a set of causal models that are subject to selection bias,
which in turn can be accounted for by a system that switches between different
regimes or configurations.; Comment: Changes from v1 to v2: Major reorganization and correction of some
errors. Changes from v2 to v3: Negligible changes

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## Error AMP Chain Graphs

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

36.05%

Any regular Gaussian probability distribution that can be represented by an
AMP chain graph (CG) can be expressed as a system of linear equations with
correlated errors whose structure depends on the CG. However, the CG represents
the errors implicitly, as no nodes in the CG correspond to the errors. We
propose in this paper to add some deterministic nodes to the CG in order to
represent the errors explicitly. We call the result an EAMP CG. We will show
that, as desired, every AMP CG is Markov equivalent to its corresponding EAMP
CG under marginalization of the error nodes. We will also show that every EAMP
CG under marginalization of the error nodes is Markov equivalent to some LWF CG
under marginalization of the error nodes, and that the latter is Markov
equivalent to some directed and acyclic graph (DAG) under marginalization of
the error nodes and conditioning on some selection nodes. This is important
because it implies that the independence model represented by an AMP CG can be
accounted for by some data generating process that is partially observed and
has selection bias. Finally, we will show that EAMP CGs are closed under
marginalization. This is a desirable feature because it guarantees parsimonious
models under marginalization.; Comment: In Proceedings of the 12th Scandinavian Conference on Artificial
Intelligence (SCAI 2013)...

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## Consistent Parameter Estimation for LASSO and Approximate Message Passing

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

26.17%

#Mathematics - Statistics Theory#Computer Science - Information Theory#Mathematics - Optimization and Control#Statistics - Machine Learning

We consider the problem of recovering a vector $\beta_o \in \mathbb{R}^p$
from $n$ random and noisy linear observations $y= X\beta_o + w$, where $X$ is
the measurement matrix and $w$ is noise. The LASSO estimate is given by the
solution to the optimization problem $\hat{\beta}_{\lambda} = \arg \min_{\beta}
\frac{1}{2} \|y-X\beta\|_2^2 + \lambda \| \beta \|_1$. Among the iterative
algorithms that have been proposed for solving this optimization problem,
approximate message passing (AMP) has attracted attention for its fast
convergence. Despite significant progress in the theoretical analysis of the
estimates of LASSO and AMP, little is known about their behavior as a function
of the regularization parameter $\lambda$, or the thereshold parameters
$\tau^t$. For instance the following basic questions have not yet been studied
in the literature: (i) How does the size of the active set
$\|\hat{\beta}^\lambda\|_0/p$ behave as a function of $\lambda$? (ii) How does
the mean square error $\|\hat{\beta}_{\lambda} - \beta_o\|_2^2/p$ behave as a
function of $\lambda$? (iii) How does $\|\beta^t - \beta_o \|_2^2/p$ behave as
a function of $\tau^1, \ldots, \tau^{t-1}$? Answering these questions will help
in addressing practical challenges regarding the optimal tuning of $\lambda$ or
$\tau^1...

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## Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

26.12%

The AMP Markov property is a recently proposed alternative Markov property
for chain graphs. In the case of continuous variables with a joint multivariate
Gaussian distribution, it is the AMP rather than the earlier introduced LWF
Markov property that is coherent with data-generation by natural
block-recursive regressions. In this paper, we show that maximum likelihood
estimates in Gaussian AMP chain graph models can be obtained by combining
generalized least squares and iterative proportional fitting to an iterative
algorithm. In an appendix, we give useful convergence results for iterative
partial maximization algorithms that apply in particular to the described
algorithm.; Comment: 15 pages, article will appear in Scandinavian Journal of Statistics

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## Marginal AMP Chain Graphs

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

36.05%

We present a new family of models that is based on graphs that may have
undirected, directed and bidirected edges. We name these new models marginal
AMP (MAMP) chain graphs because each of them is Markov equivalent to some AMP
chain graph under marginalization of some of its nodes. However, MAMP chain
graphs do not only subsume AMP chain graphs but also multivariate regression
chain graphs. We describe global and pairwise Markov properties for MAMP chain
graphs and prove their equivalence for compositional graphoids. We also
characterize when two MAMP chain graphs are Markov equivalent.
For Gaussian probability distributions, we also show that every MAMP chain
graph is Markov equivalent to some directed and acyclic graph with
deterministic nodes under marginalization and conditioning on some of its
nodes. This is important because it implies that the independence model
represented by a MAMP chain graph can be accounted for by some data generating
process that is partially observed and has selection bias. Finally, we modify
MAMP chain graphs so that they are closed under marginalization for Gaussian
probability distributions. This is a desirable feature because it guarantees
parsimonious models under marginalization.; Comment: Changes from v1 to v2: Discussion section got extended. Changes from
v2 to v3: New Sections 3 and 5. Changes from v3 to v4: Example 4 added to
discussion section. Changes from v4 to v5: None. Changes from v5 to v6: Some
minor and major errors have been corrected. The latter include the
definitions of descending route and pairwise separation base...

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## State Evolution for General Approximate Message Passing Algorithms, with Applications to Spatial Coupling

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

26%

We consider a class of approximated message passing (AMP) algorithms and
characterize their high-dimensional behavior in terms of a suitable state
evolution recursion. Our proof applies to Gaussian matrices with independent
but not necessarily identically distributed entries. It covers --in
particular-- the analysis of generalized AMP, introduced by Rangan, and of AMP
reconstruction in compressed sensing with spatially coupled sensing matrices.
The proof technique builds on the one of [BM11], while simplifying and
generalizing several steps.; Comment: 29 pages, 1 figure, minor updates in citations

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## Phase Transitions in Sparse PCA

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 01/03/2015

Relevância na Pesquisa

26.05%

#Computer Science - Information Theory#Condensed Matter - Statistical Mechanics#Statistics - Machine Learning

We study optimal estimation for sparse principal component analysis when the
number of non-zero elements is small but on the same order as the dimension of
the data. We employ approximate message passing (AMP) algorithm and its state
evolution to analyze what is the information theoretically minimal mean-squared
error and the one achieved by AMP in the limit of large sizes. For a special
case of rank one and large enough density of non-zeros Deshpande and Montanari
[1] proved that AMP is asymptotically optimal. We show that both for low
density and for large rank the problem undergoes a series of phase transitions
suggesting existence of a region of parameters where estimation is information
theoretically possible, but AMP (and presumably every other polynomial
algorithm) fails. The analysis of the large rank limit is particularly
instructive.; Comment: 6 pages, 3 figures

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## Parameterless Optimal Approximate Message Passing

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 31/10/2013

Relevância na Pesquisa

26.04%

#Computer Science - Information Theory#Mathematics - Statistics Theory#Statistics - Machine Learning

Iterative thresholding algorithms are well-suited for high-dimensional
problems in sparse recovery and compressive sensing. The performance of this
class of algorithms depends heavily on the tuning of certain threshold
parameters. In particular, both the final reconstruction error and the
convergence rate of the algorithm crucially rely on how the threshold parameter
is set at each step of the algorithm. In this paper, we propose a
parameter-free approximate message passing (AMP) algorithm that sets the
threshold parameter at each iteration in a fully automatic way without either
having an information about the signal to be reconstructed or needing any
tuning from the user. We show that the proposed method attains both the minimum
reconstruction error and the highest convergence rate. Our method is based on
applying the Stein unbiased risk estimate (SURE) along with a modified gradient
descent to find the optimal threshold in each iteration. Motivated by the
connections between AMP and LASSO, it could be employed to find the solution of
the LASSO for the optimal regularization parameter. To the best of our
knowledge, this is the first work concerning parameter tuning that obtains the
fastest convergence rate with theoretical guarantees.

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## Characterizing Markov equivalence classes for AMP chain graph models

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 03/07/2006

Relevância na Pesquisa

36.32%

Chain graphs (CG) ($=$ adicyclic graphs) use undirected and directed edges to
represent both structural and associative dependences. Like acyclic directed
graphs (ADGs), the CG associated with a statistical Markov model may not be
unique, so CGs fall into Markov equivalence classes, which may be
superexponentially large, leading to unidentifiability and computational
inefficiency in model search and selection. It is shown here that, under the
Andersson--Madigan--Perlman (AMP) interpretation of a CG, each
Markov-equivalence class can be uniquely represented by a single distinguished
CG, the AMP essential graph, that is itself simultaneously Markov equivalent to
all CGs in the AMP Markov equivalence class. A complete characterization of AMP
essential graphs is obtained. Like the essential graph previously introduced
for ADGs, the AMP essential graph will play a fundamental role for inference
and model search and selection for AMP CG models.; Comment: Published at http://dx.doi.org/10.1214/009053606000000173 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org)

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## The Noise-Sensitivity Phase Transition in Compressed Sensing

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 07/04/2010

Relevância na Pesquisa

26%

Consider the noisy underdetermined system of linear equations: y=Ax0 + z0,
with n x N measurement matrix A, n < N, and Gaussian white noise z0 ~
N(0,\sigma^2 I). Both y and A are known, both x0 and z0 are unknown, and we
seek an approximation to x0. When x0 has few nonzeros, useful approximations
are obtained by l1-penalized l2 minimization, in which the reconstruction \hxl
solves min || y - Ax||^2/2 + \lambda ||x||_1.
Evaluate performance by mean-squared error (MSE = E ||\hxl - x0||_2^2/N).
Consider matrices A with iid Gaussian entries and a large-system limit in which
n,N\to\infty with n/N \to \delta and k/n \to \rho. Call the ratio MSE/\sigma^2
the noise sensitivity. We develop formal expressions for the MSE of \hxl, and
evaluate its worst-case formal noise sensitivity over all types of k-sparse
signals. The phase space 0 < \delta, \rho < 1 is partitioned by curve \rho =
\rhoMSE(\delta) into two regions. Formal noise sensitivity is bounded
throughout the region \rho < \rhoMSE(\delta) and is unbounded throughout the
region \rho > \rhoMSE(\delta). The phase boundary \rho = \rhoMSE(\delta) is
identical to the previously-known phase transition curve for equivalence of l1
- l0 minimization in the k-sparse noiseless case. Hence a single phase boundary
describes the fundamental phase transitions both for the noiseless and noisy
cases. Extensive computational experiments validate the predictions of this
formalism...

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## Learning AMP Chain Graphs under Faithfulness

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 24/04/2012

Relevância na Pesquisa

36.17%

#Statistics - Machine Learning#Computer Science - Artificial Intelligence#Mathematics - Statistics Theory

This paper deals with chain graphs under the alternative
Andersson-Madigan-Perlman (AMP) interpretation. In particular, we present a
constraint based algorithm for learning an AMP chain graph a given probability
distribution is faithful to. We also show that the extension of Meek's
conjecture to AMP chain graphs does not hold, which compromises the development
of efficient and correct score+search learning algorithms under assumptions
weaker than faithfulness.

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## Learning AMP Chain Graphs and some Marginal Models Thereof under Faithfulness: Extended Version

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

36.08%

#Statistics - Machine Learning#Computer Science - Artificial Intelligence#Computer Science - Learning

This paper deals with chain graphs under the Andersson-Madigan-Perlman (AMP)
interpretation. In particular, we present a constraint based algorithm for
learning an AMP chain graph a given probability distribution is faithful to.
Moreover, we show that the extension of Meek's conjecture to AMP chain graphs
does not hold, which compromises the development of efficient and correct
score+search learning algorithms under assumptions weaker than faithfulness.
We also introduce a new family of graphical models that consists of
undirected and bidirected edges. We name this new family maximal
covariance-concentration graphs (MCCGs) because it includes both covariance and
concentration graphs as subfamilies. However, every MCCG can be seen as the
result of marginalizing out some nodes in an AMP CG. We describe global, local
and pairwise Markov properties for MCCGs and prove their equivalence. We
characterize when two MCCGs are Markov equivalent, and show that every Markov
equivalence class of MCCGs has a distinguished member. We present a constraint
based algorithm for learning a MCCG a given probability distribution is
faithful to.
Finally, we present a graphical criterion for reading dependencies from a
MCCG of a probability distribution that satisfies the graphoid properties...

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## Factorization, Inference and Parameter Learning in Discrete AMP Chain Graphs

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

36.05%

We address some computational issues that may hinder the use of AMP chain
graphs in practice. Specifically, we show how a discrete probability
distribution that satisfies all the independencies represented by an AMP chain
graph factorizes according to it. We show how this factorization makes it
possible to perform inference and parameter learning efficiently, by adapting
existing algorithms for Markov and Bayesian networks. Finally, we turn our
attention to another issue that may hinder the use of AMP CGs, namely the lack
of an intuitive interpretation of their edges. We provide one such
interpretation.

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## From Denoising to Compressed Sensing

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

26.17%

#Computer Science - Information Theory#Mathematics - Statistics Theory#Statistics - Machine Learning

A denoising algorithm seeks to remove perturbations or errors from a signal.
The last three decades have seen extensive research devoted to this arena, and
as a result, today's denoisers are highly optimized algorithms that effectively
remove large amounts of additive white Gaussian noise. A compressive sensing
(CS) reconstruction algorithm seeks to recover a structured signal acquired
using a small number of randomized measurements. Typical CS reconstruction
algorithms can be cast as iteratively estimating a signal from a perturbed
observation. This paper answers a natural question: How can one effectively
employ a generic denoiser in a CS reconstruction algorithm? In response, in
this paper, we develop a denoising-based approximate message passing (D-AMP)
algorithm that is capable of high-performance reconstruction. We demonstrate
that, for an appropriate choice of denoiser, D-AMP offers state-of-the-art CS
recovery performance for natural images. We explain the exceptional performance
of D-AMP by analyzing some of its theoretical features. A critical insight in
our approach is the use of an appropriate Onsager correction term in the D-AMP
iterations, which coerces the signal perturbation at each iteration to be very
close to the white Gaussian noise that denoisers are typically designed to
remove.

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## Sparse Estimation with the Swept Approximated Message-Passing Algorithm

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 17/06/2014

Relevância na Pesquisa

26.23%

#Computer Science - Information Theory#Condensed Matter - Disordered Systems and Neural Networks#Physics - Data Analysis, Statistics and Probability#Statistics - Machine Learning

Approximate Message Passing (AMP) has been shown to be a superior method for
inference problems, such as the recovery of signals from sets of noisy,
lower-dimensionality measurements, both in terms of reconstruction accuracy and
in computational efficiency. However, AMP suffers from serious convergence
issues in contexts that do not exactly match its assumptions. We propose a new
approach to stabilizing AMP in these contexts by applying AMP updates to
individual coefficients rather than in parallel. Our results show that this
change to the AMP iteration can provide theoretically expected, but hitherto
unobtainable, performance for problems on which the standard AMP iteration
diverges. Additionally, we find that the computational costs of this swept
coefficient update scheme is not unduly burdensome, allowing it to be applied
efficiently to signals of large dimensionality.; Comment: 11 pages, 3 figures, implementation available at
https://github.com/eric-tramel/SwAMP-Demo

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## Approximate Message Passing with Restricted Boltzmann Machine Priors

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

26.12%

#Computer Science - Information Theory#Condensed Matter - Disordered Systems and Neural Networks#Physics - Data Analysis, Statistics and Probability#Statistics - Machine Learning

Approximate Message Passing (AMP) has been shown to be an excellent
statistical approach to signal inference and compressed sensing problem. The
AMP framework provides modularity in the choice of signal prior; here we
propose a hierarchical form of the Gauss-Bernouilli prior which utilizes a
Restricted Boltzmann Machine (RBM) trained on the signal support to push
reconstruction performance beyond that of simple iid priors for signals whose
support can be well represented by a trained binary RBM. We present and analyze
two methods of RBM factorization and demonstrate how these affect signal
reconstruction performance within our proposed algorithm. Finally, using the
MNIST handwritten digit dataset, we show experimentally that using an RBM
allows AMP to approach oracle-support performance.

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## Avaliação oftalmológica de um grupo de motoristas profissionais de Campinas, São Paulo; Retrospective evaluation of 100 ophtamologic files of professional drivers in Campinas

Fonte: Universidade de São Paulo. Faculdade de Medicina
Publicador: Universidade de São Paulo. Faculdade de Medicina

Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion;
Formato: application/pdf

Publicado em 18/12/2012
POR

Relevância na Pesquisa

35.88%

#Acuidade visual#Condução de veículos/estatística & dados numéricos#Transtornos da visão/diagnóstico#Registros médicos.#Visual acuity#Automobile driving/statistics & numeral data#Vision disorders/diagnosis#Medical redords.

Vision is the main skill for the driving act and a good visual accuity is mandatory to be a professional driver. Objective: to evaluate the visual conditions in a group of 100 professional drivers of Campinas, SP. Methods: This retrospective study rewied records of 100 active professional drivers whose ophthalmologic examination was performed at Fundação Dr. João Penido Burnier de Campinas, a public and private ophthalmologic clinic, from 2006 to 2011. Results: Driver’s mean age was 52.8 years and all were males. They came to ophthalmologic evaluation because of periodic evaluation (36.8%) and impaired visual accuity (33.6%). Systemic comorbidities were presented by 44%, with predominance of diabetes and systemic arterial hypertension. The visual accuity was 100% in 47% and equal or higher than 0.66 in 69.4%, being each eye avaluated separately. The visual accuity was less than 0.5 in one eye in 22.1%. The most prevalent ophthalmologic disease was cristalin opacification (44.2%), with cataract surgery indication in 16.8%. Glaucoma was identified in 3.1%, pterigium in 5.2%, pinguecula in 6.3% and increased intraocular pression in 8.6%. Fundoscopy was considered normal in 53.6% and the main pathologies were suspect optic nerve escavation (10.5%)...

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## Evaluation of dengue fever reports during an epidemic, Colombia

Fonte: Faculdade de Saúde Pública da Universidade de São Paulo
Publicador: Faculdade de Saúde Pública da Universidade de São Paulo

Tipo: Artigo de Revista Científica
Formato: text/html

Publicado em 01/12/2014
EN

Relevância na Pesquisa

35.88%

#Dengue, epidemiology#Epidemics, statistics &#numerical data#Disease Notification#Sensitivity and Specificity#Epidemiological Surveillance

OBJECTIVE To assess the validity of dengue fever reports and how they relate to the definition of case and severity. METHODS Diagnostic test assessment was conducted using cross-sectional sampling from a universe of 13,873 patients treated during the fifth epidemiological period in health institutions from 11 Colombian departments in 2013. The test under analyses was the reporting to the National Public Health Surveillance System, and the reference standard was the review of histories identified by active institutional search. We reviewed all histories of patients diagnosed with dengue fever, as well as a random sample of patients with febrile syndromes. The specificity and sensitivity of reports were estimated for this purpose, considering the inverse of the probability of being selected for weighting. The concordance between reporting and the findings of the active institutional search was calculated using Kappa statistics. RESULTS We included 4,359 febrile patients, and 31.7% were classified as compatible with dengue fever (17 with severe dengue fever; 461 with dengue fever and warning signs; 904 with dengue fever and no warning signs). The global sensitivity of reports was 13.2% (95%CI 10.9;15.4) and specificity was 98.4% (95%CI 97.9;98.9). Sensitivity varied according to severity: 12.1% (95%CI 9.3;14.8) for patients presenting dengue fever with no warning signs; 14.5% (95%CI 10.6;18.4) for those presenting dengue fever with warning signs...

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