Pulse oximetry screening for detection of congenital heart defects at 1646 m in Albuquerque, New Mexico

2020 ◽  
Vol 30 (12) ◽  
pp. 1851-1855
Author(s):  
Sruti Rao ◽  
M. B. Goens ◽  
Orrin B. Myers ◽  
Emilie A. Sebesta
Keyword(s):  
New Mexico ◽  
Pulse Oximetry ◽  
Sea Level ◽  
False Positive ◽  
False Positive Rate ◽  
False Positives ◽  
Moderate Altitude ◽  
High False Positive Rate ◽  
Positive Rate ◽  
Pulse Oximetry Screening

AbstractAim:To determine the false-positive rate of pulse oximetry screening at moderate altitude, presumed to be elevated compared with sea level values and assess change in false-positive rate with time.Methods:We retrospectively analysed 3548 infants in the newborn nursery in Albuquerque, New Mexico, (elevation 5400 ft) from July 2012 to October 2013. Universal pulse oximetry screening guidelines were employed after 24 hours of life but before discharge. Newborn babies between 36 and 36 6/7 weeks of gestation, weighing >2 kg and babies >37 weeks weighing >1.7 kg were included in the study. Log-binomial regression was used to assess change in the probability of false positives over time.Results:Of the 3548 patients analysed, there was one true positive with a posteriorly-malaligned ventricular septal defect and an interrupted aortic arch. Of the 93 false positives, the mean pre- and post-ductal saturations were lower, 92 and 90%, respectively. The false-positive rate before April 2013 was 3.5% and after April 2013, decreased to 1.5%. There was a significant decrease in false-positive rate (p = 0.003, slope coefficient = −0.082, standard error of coefficient = 0.023) with the relative risk of a false positive decreasing at 0.92 (95% CI 0.88–0.97) per month.Conclusion:This is the first study in Albuquerque, New Mexico, reporting a high false-positive rate of 1.5% at moderate altitude at the end of the study in comparison to the false-positive rate of 0.035% at sea level. Implementation of the nationally recommended universal pulse oximetry screening was associated with a high false-positive rate in the initial period, thought to be from the combination of both learning curve and altitude. After the initial decline, it remained steadily elevated above sea level, indicating the dominant effect of moderate altitude.

scholarly journals Role of Pulse Oximetry Screening for Detection of Life Threatening Congenital Heart Detects in Newborn

2018 ◽  
pp. 134-139
Author(s):  
Aso Faeq Salih ◽  
Adnan Mohammed Hamawand ◽  
Riyadh Abd Aljabbar Sattar
Keyword(s):  
Pulse Oximetry ◽  
False Positive ◽  
Congenital Heart ◽  
Early Stage ◽  
Heart Defects ◽  
False Positive Rate ◽  
False Negative ◽  
Positive Rate ◽  
Life Threatening ◽  
Pulse Oximetry Screening

Most ofnewborns with Congenital Heart Defects (CHDs) can be detected by using echocardiography. However, if such defects are not diagnosed in earlier time, therefore a severe hypoxemia, shock, acidosis and death are considered of some potential sequelae. A prospective study from January 2012 to the end of 2013 was performed and 2181 neonates were enrolled in the study. The pulse oximetry screening (POS) for both hands and one foot were obtained within the first 3-6 hours of life, when post ductal saturation was below 90%, it was considered as a positive screening, while when the saturation is between 90-95% and the difference between pre-and post-ductal saturation was more than 3%, the baby was provisionally considered to be screening as a positive then echocardiography is planned. Among 100 positive POS babies, 45 (45%) of them were detected with CHS, 12 (12%) was with a major CHS and 33 (33%) was with a minor CHS. Out of 12 patients with a major CHD 6 of them (50%) were asymptomatic at the time of POS.POS result was a true negative in 2078 patients, a true positive in 45 patients, false negative in 3 patients, and false positive in 55 and 28/55 of the false positive rate with POS had other pathology. The false positive rate with pulse oximetry screening is (55/2081) = 0.26%. Sensitivity, specificity, positive and negative predictive value for POS in detection of major CHD were 80%, 97.29%, 17.9% and 99.80%, respectively. Pulse oximetry screening is significantly improving the detection of life threatening congenital heart disease at an early stage.

The Study of the Ontology and Context Verification Based Intrusion Detection Model

2014 ◽  
Vol 644-650 ◽  
pp. 3338-3341 ◽  
Author(s):  
Guang Feng Guo
Keyword(s):  
Intrusion Detection ◽  
Knowledge Base ◽  
False Positive ◽  
Intrusion Detection System ◽  
Detection System ◽  
False Positive Rate ◽  
False Positives ◽  
The Real ◽  
Detection Model ◽  
Positive Rate

During the 30-year development of the Intrusion Detection System, the problems such as the high false-positive rate have always plagued the users. Therefore, the ontology and context verification based intrusion detection model (OCVIDM) was put forward to connect the description of attack’s signatures and context effectively. The OCVIDM established the knowledge base of the intrusion detection ontology that was regarded as the center of efficient filtering platform of the false alerts to realize the automatic validation of the alarm and self-acting judgment of the real attacks, so as to achieve the goal of filtering the non-relevant positives alerts and reduce false positives.

scholarly journals A Partial Correlation Screening Approach for Controlling the False Positive Rate in Sparse Gaussian Graphical Models

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ginette Lafit ◽  
Francis Tuerlinckx ◽  
Inez Myin-Germeys ◽  
Eva Ceulemans
Keyword(s):  
Graphical Models ◽  
False Positive ◽  
Partial Correlation ◽  
State Of The Art ◽  
False Positive Rate ◽  
False Positives ◽  
Gaussian Graphical Models ◽  
Undirected Network ◽  
Partial Correlations ◽  
Positive Rate

AbstractGaussian Graphical Models (GGMs) are extensively used in many research areas, such as genomics, proteomics, neuroimaging, and psychology, to study the partial correlation structure of a set of variables. This structure is visualized by drawing an undirected network, in which the variables constitute the nodes and the partial correlations the edges. In many applications, it makes sense to impose sparsity (i.e., some of the partial correlations are forced to zero) as sparsity is theoretically meaningful and/or because it improves the predictive accuracy of the fitted model. However, as we will show by means of extensive simulations, state-of-the-art estimation approaches for imposing sparsity on GGMs, such as the Graphical lasso, ℓ1 regularized nodewise regression, and joint sparse regression, fall short because they often yield too many false positives (i.e., partial correlations that are not properly set to zero). In this paper we present a new estimation approach that allows to control the false positive rate better. Our approach consists of two steps: First, we estimate an undirected network using one of the three state-of-the-art estimation approaches. Second, we try to detect the false positives, by flagging the partial correlations that are smaller in absolute value than a given threshold, which is determined through cross-validation; the flagged correlations are set to zero. Applying this new approach to the same simulated data, shows that it indeed performs better. We also illustrate our approach by using it to estimate (1) a gene regulatory network for breast cancer data, (2) a symptom network of patients with a diagnosis within the nonaffective psychotic spectrum and (3) a symptom network of patients with PTSD.

scholarly journals Commercial assays have high false positive rate

BMJ ◽  
1995 ◽  
Vol 310 (6975) ◽  
pp. 327-328 ◽  
Author(s):  
J. Bendig ◽  
V. Meurisse ◽  
S. Chambers
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
High False Positive Rate ◽  
Positive Rate
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