scholarly journals Does the Porter formula hold its promise? A weight estimation formula for macrosomic fetuses put to the test

2019 ◽  
Vol 301 (1) ◽  
pp. 129-135
Author(s):  
Christoph Weiss ◽  
Sabine Enengl ◽  
Simon Hermann Enzelsberger ◽  
Richard Bernhard Mayer ◽  
Peter Oppelt
Keyword(s):  
Clinical Practice ◽  
False Positive ◽  
False Positive Rate ◽  
Normal Weight ◽  
Fetal Weight ◽  
Weight Estimation ◽  
Data Set ◽  
Detection Rates ◽  
Estimation Formula ◽  
Positive Rate

Abstract Purpose Estimating fetal weight using ultrasound measurements is an essential task in obstetrics departments. Most of the commonly used weight estimation formulas underestimate fetal weight when the actual birthweight exceeds 4000 g. Porter et al. published a specially designed formula in an attempt to improve detection rates for such macrosomic infants. In this study, we question the usefulness of the Porter formula in clinical practice and draw attention to some critical issues concerning the derivation of specialized formulas of this type. Methods A retrospective cohort study was carried out, including 4654 singleton pregnancies with a birthweight ≥ 3500 g, with ultrasound examinations performed within 14 days before delivery. Fetal weight estimations derived using the Porter and Hadlock formulas were compared. Results Of the macrosomic infants, 27.08% were identified by the Hadlock formula, with a false-positive rate of 4.60%. All macrosomic fetuses were detected using the Porter formula, with a false-positive rate of 100%; 99.96% of all weight estimations using the Porter formula fell within a range of 4300 g ± 10%. The Porter formula only provides macrosomic estimates. Conclusions The Porter formula does not succeed in distinguishing macrosomic from normal-weight fetuses. High-risk fetuses with a birthweight ≥ 4500 g in particular are not detected more precisely than with the Hadlock formula. For these reasons, we believe that the Porter formula should not be used in clinical practice. Newly derived weight estimation formulas for macrosomic fetuses must not be based solely on a macrosomic data set.

Predicting Fetal Chromosome Anomalies in the First Trimester Using Pregnancy Associated Plasma Protein-A: A Comparison of Statistical Methods

1993 ◽  
Vol 32 (02) ◽  
pp. 175-179 ◽  
Author(s):  
B. Brambati ◽  
T. Chard ◽  
J. G. Grudzinskas ◽  
M. C. M. Macintosh
Keyword(s):  
Logistic Regression ◽  
General Population ◽  
Likelihood Ratio ◽  
False Positive ◽  
False Positive Rate ◽  
Ratio Method ◽  
Detection Rates ◽  
Gaussian Distributions ◽  
Positive Rate ◽  
Likelihood Ratio Method

Abstract:The analysis of the clinical efficiency of a biochemical parameter in the prediction of chromosome anomalies is described, using a database of 475 cases including 30 abnormalities. A comparison was made of two different approaches to the statistical analysis: the use of Gaussian frequency distributions and likelihood ratios, and logistic regression. Both methods computed that for a 5% false-positive rate approximately 60% of anomalies are detected on the basis of maternal age and serum PAPP-A. The logistic regression analysis is appropriate where the outcome variable (chromosome anomaly) is binary and the detection rates refer to the original data only. The likelihood ratio method is used to predict the outcome in the general population. The latter method depends on the data or some transformation of the data fitting a known frequency distribution (Gaussian in this case). The precision of the predicted detection rates is limited by the small sample of abnormals (30 cases). Varying the means and standard deviations (to the limits of their 95% confidence intervals) of the fitted log Gaussian distributions resulted in a detection rate varying between 42% and 79% for a 5% false-positive rate. Thus, although the likelihood ratio method is potentially the better method in determining the usefulness of a test in the general population, larger numbers of abnormal cases are required to stabilise the means and standard deviations of the fitted log Gaussian distributions.

Investigating the clinical usefulness of definitions of progression with 10-2 visual field

2021 ◽  
pp. bjophthalmol-2020-318188
Author(s):  
Shotaro Asano ◽  
Hiroshi Murata ◽  
Yuri Fujino ◽  
Takehiro Yamashita ◽  
Atsuya Miki ◽  
...  
Keyword(s):  
Visual Field ◽  
False Positive ◽  
False Positive Rate ◽  
Clinical Validity ◽  
Data Set ◽  
Humphrey Field Analyzer ◽  
Positive Rate ◽  
Using Data ◽  
Sensitivity Specificity ◽  
Higher Sensitivity

Background/AimTo investigate the clinical validity of the Guided Progression Analysis definition (GPAD) and cluster-based definition (CBD) with the Humphrey Field Analyzer 10-2 test in diagnosing glaucomatous visual field (VF) progression, and to introduce a novel definition with optimised specificity by combining the ‘any-location’ and ‘cluster-based’ approaches (hybrid definition).Methods64 400 stable glaucomatous VFs were simulated from 664 pairs of 10-2 tests (10 sets × 10 VF series × 664 eyes; data set 1). Using these simulated VFs, the specificity to detect progression and the effects of changing the parameters (number of test locations or consecutive VF tests, and percentile cut-off values) were investigated. The hybrid definition was designed as the combination where the specificity was closest to 95.0%. Subsequently, another 5000 actual glaucomatous 10-2 tests from 500 eyes (10 VFs each) were collected (data set 2), and their accuracy (sensitivity, specificity and false positive rate) and the time needed to detect VF progression were evaluated.ResultsThe specificity values calculated using data set 1 with GPAD and CBD were 99.6% and 99.8%. Using data set 2, the hybrid definition had a higher sensitivity than GPAD and CBD, without detriment to the specificity or false positive rate. The hybrid definition also detected progression significantly earlier than GPAD and CBD (at 3.1 years vs 4.2 years and 4.1 years, respectively).ConclusionsGPAD and CBD had specificities of 99.6% and 99.8%, respectively. A novel hybrid definition (with a specificity of 95.5%) had higher sensitivity and enabled earlier detection of progression.

Impact of Including or Removing Nuchal Translucency Measurement on the Detection and False-Positive Rates of First-Trimester Down Syndrome Screening

2015 ◽  
Vol 40 (3) ◽  
pp. 214-218 ◽  
Author(s):  
Emmanuel Spaggiari ◽  
Isabelle Czerkiewicz ◽  
Corinne Sault ◽  
Sophie Dreux ◽  
Armelle Galland ◽  
...  
Keyword(s):  
Down Syndrome ◽  
False Positive ◽  
False Positive Rate ◽  
Method Comparison ◽  
First Trimester ◽  
Nuchal Translucency ◽  
Routine Practice ◽  
Detection Rates ◽  
Significant Difference ◽  
Positive Rate

Introduction: First-trimester Down syndrome (DS) screening combining maternal age, serum markers (pregnancy-associated plasma protein-A and beta-human chorionic gonadotropin) and nuchal translucency (NT) gives an 85% detection rate for a 5% false-positive rate. These results largely depend on quality assessment of biochemical markers and of NT. In routine practice, despite an ultrasound quality control organization, NT images can be considered inadequate. The aim of the study was to evaluate the consequences for risk calculation when NT measurement is not taken into account. Material and Method: Comparison of detection and false-positive rates of first-trimester DS screening (PerkinElmer, Turku, Finland), with and without NT, based on a retrospective study of 117,126 patients including 274 trisomy 21-affected fetuses. NT was measured by more than 3,000 certified sonographers. Results: There was no significant difference in detection rates between the two strategies including or excluding NT measurement (86.7 vs. 81.8%). However, there was a significant difference in the false-positive rates (2.23 vs. 9.97%, p < 0.001). Discussion: Sonographers should be aware that removing NT from combined first-trimester screening would result in a 5-fold increase in false-positive rate to maintain the expected detection rates. This should be an incentive for maintaining quality in NT measurement.

An approach to optimize delta checks in test panels – The effect of the number of rules included

2020 ◽  
Vol 57 (3) ◽  
pp. 215-222 ◽  
Author(s):  
Rui Zhen Tan ◽  
Corey Markus ◽  
Tze Ping Loh
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Original Data ◽  
Random Permutation ◽  
Full Blood Count ◽  
Hypothesis Tests ◽  
Data Set ◽  
Laboratory Results ◽  
Positive Rate ◽  
Common Laboratory

Objectives The interpretation of delta check rules in a panel of tests should be different to that at the single analyte level, as the number of hypothesis tests conducted (i.e. the number of delta check rules) is greater and needs to be taken into account. Methods De-identified paediatric laboratory results were extracted, and the first two serial results for each patient were used for analysis. Analytes were grouped into four common laboratory test panels consisting of renal, liver, bone and full blood count panels. The sensitivities and specificities of delta check limits as discrete panel tests were assessed by random permutation of the original data-set to simulate a wrong blood in tube situation. Results Generally, as the number of analytes included in a panel increases, the delta check rules deteriorate considerably due to the increased number of false positives, i.e. increased number hypothesis tests performed. To reduce high false-positive rates, patient results may be rejected from autovalidation only if the number of analytes failing the delta check limits exceeds a certain threshold of the total number of analytes in the panel (N). Our study found that the use of the ([Formula: see text] rule) for panel results had a specificity >90% and sensitivity ranging from 25% to 45% across the four common laboratory panels. However, this did not achieve performance close to some analytes when considered in isolation. Conclusions The simple [Formula: see text] rule reduces the false-positive rate and minimizes unnecessary, resource-intensive investigations for potentially erroneous results.

The efficacy of combining several risk factors as a screening test

2005 ◽  
Vol 12 (4) ◽  
pp. 197-201 ◽  
Author(s):  
Nicholas J Wald ◽  
Joan K Morris ◽  
Simon Rish
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
False Positive ◽  
Detection Rate ◽  
False Positive Rate ◽  
Individual Risk ◽  
Detection Rates ◽  
Screening Performance ◽  
Positive Rate ◽  
The Individual

Objective: To determine the quantitative effect on overall screening performance (detection rate for a given false-positive rate) of using several moderately strong, independent risk factors in combination as screening markers. Setting: Theoretical statistical analysis. Methods: For the purposes of this analysis, it was assumed that all risk factors were independent, had Gaussian distributions with the same standard deviation in affected and unaffected individuals and had the same screening performance. We determined the overall screening performance associated with using an increasing number of risk factors together, with each risk factor having a detection rate of 10%, 15% or 20% for a 5% false-positive rate. The overall screening performance was estimated as the detection rate for a 5% false-positive rate. Results: Combining the risk factors increased the screening performance, but the gain in detection at a constant false-positive rate was relatively modest and diminished with the addition of each risk factor. Combining three risk factors, each with a 15% detection rate for a 5% false-positive rate, yields a 28% detection rate. Combining five risk factors increases the detection rate to 39%. If the individual risk factors have a detection rate of 10% for a 5% false-positive rate, it would require combining about 15 such risk factors to achieve a comparable overall detection rate (41%). Conclusion: It is intuitively thought that combining moderately strong risk factors can substantially improve screening performance. For example, most cardiovascular risk factors that may be used in screening for ischaemic heart disease events, such as serum cholesterol and blood pressure, have a relatively modest screening performance (about 15% detection rate for a 5% false-positive rate). It would require the combination of about 15 or 20 such risk factors to achieve detection rates of about 80% for a 5% false-positive rate. This is impractical, given the risk factors so far discovered, because there are too few risk factors and their associations with disease are too weak.

scholarly journals Starting the polypill: the use of a single age cut-off in males and females

2016 ◽  
Vol 24 (1) ◽  
pp. 50-53 ◽  
Author(s):  
Nicholas J Wald ◽  
Johannes M Luteijn ◽  
Joan K Morris
Keyword(s):  
Myocardial Infarction ◽  
False Positive ◽  
Detection Rate ◽  
False Positive Rate ◽  
Rate Sensitivity ◽  
Detection Rates ◽  
Preventive Medication ◽  
Positive Rate ◽  
Males And Females ◽  
First Myocardial Infarction

Objective Age screening and preventive medication for future myocardial infarction and stroke has been previously described. We aimed to ascertain whether different age cut-offs are needed for males and females. Methods We determined five parameters for each sex according to age cut-off: detection rate (sensitivity), false-positive rate, proportion of the population eligible for treatment with a polypill, proportion who benefit from taking a polypill (simvastatin 20 mg, losartan 25 mg, hydrochlorothiazide 12.5 mg, amlodipine 2.5 mg), and among these, years of life gained without a first myocardial infarction or stroke. Results Approximately one-third benefit, regardless of the age cut-off. For males and females combined, using ages 40 and 80, the detection rates are 98% and 52%, false-positive rates are 51% and 7%, population percentages eligible for treatment are 52% and 7%, and years of life gained without a first myocardial infarction or stroke are 8.4 and 3.6. Using age 50, detection rates are 93% (males) 98% (females), false-positive rates 37% (males) 40% (females), percentage of the population eligible for treatment 38% (males) 41% (females), percentage who benefit 35% (males) 33% (females), and years of life gained without an event 8.5 (males) 7.0 (females). At a given age cut-off, the sex differences are relatively small. Conclusion A single age cut-off can be used for both sexes.

scholarly journals Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data

2020 ◽  
pp. 247255522095024
Author(s):  
Johanna Nyffeler ◽  
Derik E. Haggard ◽  
Clinton Willis ◽  
R. Woodrow Setzer ◽  
Richard Judson ◽  
...  
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Signal Strength ◽  
Distance Metrics ◽  
Data Set ◽  
Positive Rate ◽  
High Concordance ◽  
Screening Assays ◽  
Hit Identification ◽  
Global Fitting

Phenotypic profiling assays are untargeted screening assays that measure a large number (hundreds to thousands) of cellular features in response to a stimulus and often yield diverse and unanticipated profiles of phenotypic effects, leading to challenges in distinguishing active from inactive treatments. Here, we compare a variety of different strategies for hit identification in imaging-based phenotypic profiling assays using a previously published Cell Painting data set. Hit identification strategies based on multiconcentration analysis involve curve fitting at several levels of data aggregation (e.g., individual feature level, aggregation of similarly derived features into categories, and global modeling of all features) and on computed metrics (e.g., Euclidean and Mahalanobis distance metrics and eigenfeatures). Hit identification strategies based on single-concentration analysis included measurement of signal strength (e.g., total effect magnitude) and correlation of profiles among biological replicates. Modeling parameters for each approach were optimized to retain the ability to detect a reference chemical with subtle phenotypic effects while limiting the false-positive rate to 10%. The percentage of test chemicals identified as hits was highest for feature-level and category-based approaches, followed by global fitting, whereas signal strength and profile correlation approaches detected the fewest number of active hits at the fixed false-positive rate. Approaches involving fitting of distance metrics had the lowest likelihood for identifying high-potency false-positive hits that may be associated with assay noise. Most of the methods achieved a 100% hit rate for the reference chemical and high concordance for 82% of test chemicals, indicating that hit calls are robust across different analysis approaches.

Accuracy of cardiac auscultation in detection of neonatal congenital heart disease by general paediatricians

2019 ◽  
Vol 29 (5) ◽  
pp. 679-683
Author(s):  
Qu-ming Zhao ◽  
Conway Niu ◽  
Fang Liu ◽  
Lin Wu ◽  
Xiao-jing Ma ◽  
...  
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Cardiac Auscultation ◽  
Detection Rates ◽  
Maternity Hospitals ◽  
High Detection ◽  
Positive Rate ◽  
Timely Fashion ◽  
A Prospective Study

AbstractBackground:Challenges remain in the judgement of pathological murmurs in newborns at maternity hospitals, and there are still many simple major CHD patients in developing countries who are not diagnosed in a timely fashion. This study aimed to evaluate the accuracy of cardiac auscultation on neonatal CHD by general paediatricians.Methods:We conducted a prospective study at three hospitals. All asymptomatic newborns underwent auscultation, pulse oximetry monitoring, and echocardiography. Major CHD was classified and confirmed through follow-up. We evaluated the accuracy of various degrees of murmurs for detecting major CHD to determine the most appropriate standards and time of auscultation.Results:A total of 6750 newborns were included. The median age of auscultation was 43 hours. Cardiac murmurs were identified in 6.6% of newborns. For all CHD, 44.4% had varying degrees of murmurs. A murmur of grade ≥2 used as a reference standard for major CHD had a sensitivity of 89.58%. The false positive rate of murmurs of grade ≥2 for detecting major CHD was significantly negatively related to auscultation time, with 84.4% of false positives requiring follow-up for non-major CHD cardiac issues. Auscultation after 27 hours of life could reduce the false positive rate of major CHD from 2.7 to 0.9%.Conclusions:With appropriate training, maternity hospital’s paediatricians can detect major CHD with high detection rates with an acceptable false positive rate.

scholarly journals What are steering pictures are worth? Using image-based steering features to detect drowsiness on rural roads

2019 ◽  
Vol 63 (1) ◽  
pp. 2041-2045
Author(s):  
Kartik Mutya ◽  
Jayesh Shah ◽  
Anthony D. McDonald ◽  
Jaycelyn Jefferson
Keyword(s):  
False Positive ◽  
Low Cost ◽  
False Positive Rate ◽  
Steering Wheel ◽  
Recurrence Plots ◽  
Drowsy Driving ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Angle Data ◽  
Positive Rate

Drowsy driving is a persistent and significant problem on today’s roadways. Mitigation technologies may help resolve the problem, but their success depends on effective detection algorithms. Steering-based algorithms are a promising direction for such effective algorithms because of their low cost and ease of implementation. However, steering-based approaches are often limited by high false positive detection rates. The goal of this study was to assess if image-based steering features and convolutional neural networks can reduce these high false positive rates. The analysis investigated two methods for transforming steering wheel angle data into images, Markov Transition Field and recurrence plots. Area under the ROC curve and false positive rate results suggest that both approaches nominally improve detection performance and reduce false positives relative to a benchmark, with some evidence that recurrence plots have the highest performance.

scholarly journals Evaluation by Data Mining Techniques of Fluconazole Breakpoints Established by the Clinical and Laboratory Standards Institute (CLSI) and Comparison with Those of the European Committee on Antimicrobial Susceptibility Testing (EUCAST)

2010 ◽  
Vol 54 (4) ◽  
pp. 1541-1546 ◽  
Author(s):  
Isabel Cuesta ◽  
Concha Bielza ◽  
Manuel Cuenca-Estrella ◽  
Pedro Larrañaga ◽  
Juan L. Rodríguez-Tudela
Keyword(s):  
Roc Curve ◽  
False Positive ◽  
False Positive Rate ◽  
Predictor Variable ◽  
Original Cohort ◽  
Data Set ◽  
Supervised Classifiers ◽  
Positive Rate ◽  
Set Up ◽  
Simple Logistic

ABSTRACT The EUCAST and the CLSI have established different breakpoints for fluconazole and Candida spp. However, the reference methodologies employed to obtain the MICs provide similar results. The aim of this work was to apply supervised classification algorithms to analyze the clinical data used by the CLSI to establish fluconazole breakpoints for Candida infections and to compare these data with the results obtained with the data set used to set up EUCAST fluconazole breakpoints, where the MIC for detecting failures was >4 mg/liter, with a sensitivity of 87%, a false-positive rate of 8%, and an area under the receiver operating characteristic (ROC) curve of 0.89. Five supervised classifiers (J48 and CART decision trees, the OneR decision rule, the naïve Bayes classifier, and simple logistic regression) were used to analyze the original cohort of patients (Rex's data set), which was used to establish CLSI breakpoints, and a later cohort of candidemia (Clancy's data set), with which CLSI breakpoints were validated. The target variable was the outcome of the infections, and the predictor variable was the MIC or dose/MIC ratio. For Rex's data set, the MIC detecting failures was >8 mg/liter, and for Clancy's data set, the MIC detecting failures was >4 mg/liter, in close agreement with the EUCAST breakpoint (MIC > 4 mg/liter). The sensitivities, false-positive rates, and areas under the ROC curve obtained by means of CART, the algorithm with the best statistical results, were 52%, 18%, and 0.7, respectively, for Rex's data set and 65%, 6%, and 0.72, respectively, for Clancy's data set. In addition, the correlation between outcome and dose/MIC ratio was analyzed for Clancy's data set, where a dose/MIC ratio of >75 was associated with successes, with a sensitivity of 93%, a false-positive rate of 29%, and an area under the ROC curve of 0.83. This dose/MIC ratio of >75 was identical to that found for the cohorts used by EUCAST to establish their breakpoints (a dose/MIC ratio of >75, with a sensitivity of 91%, a false-positive rate of 10%, and an area under the ROC curve of 0.90).

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