Screening for Hypertensive Pregnancy Complications through Maternal Serum PAPP-A 5th and 10th Percentiles during the 11-14 Weeks Gestational  Age Interval

The aim of our study was to assess the predictive values for hypertensive complications of pregnancy of the multiples of median (MoM) of serum pregnancy associated plasma protein A (PAPP-A), measured in 128 pregnant patients between 11 and 14 weeks gestational age. The 5th and the 10th percentile for MoM PAPP-A were 0.27 and 0.33, respectively. The detection rate for pregnancy induced hypertension, mild preeclampsia, severe preeclampsia, all preeclampsia and all hypertensive complications was 0%, 9.09%, 0%, 7.69%, and 6.25% for MoM PAPP-A below the 5th percentile (for a false positive rate of 5%), and 33.33%, 9.09%, 0%, 7.69%, and 12.5% for MoM PAPP-A below the 10th percentile (for a false positive rate of 10%), respectively. The specificity ranged from 89.57% to 95.73%, the positive predictive value from 0% to 16.67%, and the negative predictive value from 87.70% to 98.36%.

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30 Predicting gestational age improves newborn screening for congenital adrenal hyperplasia

Paediatrics & Child Health ◽

10.1093/pch/pxaa068.029 ◽

2020 ◽

Vol 25 (Supplement_2) ◽

pp. e11-e11

Author(s):

Danny Jomaa ◽

Matthew Henderson ◽

Steven Hawken ◽

Pranesh Chakraborty

Keyword(s):

Positive Predictive Value ◽

Congenital Adrenal Hyperplasia ◽

Newborn Screening ◽

Gestational Age ◽

Predictive Value ◽

False Positive ◽

False Positive Rate ◽

Adrenal Hyperplasia ◽

Positive Rate ◽

17 Hydroxyprogesterone

Abstract Background Newborn screening for congenital adrenal hyperplasia is performed using a two-tier approach. The first tier involves comparison of neonate 17-hydroxyprogesterone levels to gestational age (GA)-based thresholds. When GA is unreported, which occurs in approximately 5% of births, birth weight (BW)-based thresholds are the only available option. However, these have a lower specificity and result in more false positive results. Recently, a predictive model was developed to estimate GA based on newborn demographics and the screening analytes measured in a blood sample. Objectives The objective of this study was to determine whether supplying a predicted GA to newborns with unreported GA, and subsequent GA-based screening, has a higher positive predictive value than BW-based screening. Design/Methods Screening data was obtained for approximately 700,000 births that occurred in Canada between 2011 and 2015. Predicted GA was calculated using a model composed of demographic and screening analyte factors. The positive predictive values of BW- and predicted GA-based screening were calculated for newborns with unreported GA. A sequential approach was then developed whereby newborns with unreported GA were first screened by BW-based screening. Newborns that screened positive were then supplied with their predicted GA and screened using GA-based thresholds. Results First-tier CAH screening using GA-based 17-hydroxyprogesterone thresholds had a higher positive predictive value than using BW-based thresholds (1.30% vs. 0.82%). In the study time period, 3.61% of newborns had an unreported GA. For these newborns, predicted GA-based screening had a higher positive predictive value than BW-based screening (0.83% vs. 0.76%) and correctly identified the 2 infants with CAH whose GA was unreported. A sequential screening approach was then used: BW-based screening and, for the screen positive population, predicted GA-based screening. This further increased the positive predictive value compared to BW-based screening (0.95% vs. 0.76%), reduced the false positive rate, and correctly identified true positive cases. Conclusion Reducing the false positive rate of CAH screening is important to prevent unnecessary second-tier screening and referrals. For newborns with unreported GA (4-5% of all births), BW-based screening is the only currently available approach. However, this approach has a poor specificity and a high false positive rate compared to GA-based screening. This study is the first to demonstrate an alternative screening strategy with a higher positive predictive value for newborns with unreported GA.

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Improving diagnosis of acute appendicitis with atypical findings by Tc-99m HMPAO leukocyte scan

Nuklearmedizin ◽

10.1055/s-0038-1623994 ◽

2002 ◽

Vol 41 (01) ◽

pp. 37-41 ◽

Cited By ~ 3

Author(s):

S. Shung-Shung ◽

S. Yu-Chien ◽

Y. Mei-Due ◽

W. Hwei-Chung ◽

A. Kao

Keyword(s):

Acute Appendicitis ◽

False Positive ◽

False Positive Rate ◽

Accurate Method ◽

Clinical Findings ◽

Pathological Findings ◽

Lower Quadrant ◽

Predictive Values ◽

Positive Rate

Summary Aim: Even with careful observation, the overall false-positive rate of laparotomy remains 10-15% when acute appendicitis was suspected. Therefore, the clinical efficacy of Tc-99m HMPAO labeled leukocyte (TC-WBC) scan for the diagnosis of acute appendicitis in patients presenting with atypical clinical findings is assessed. Patients and Methods: Eighty patients presenting with acute abdominal pain and possible acute appendicitis but atypical findings were included in this study. After intravenous injection of TC-WBC, serial anterior abdominal/pelvic images at 30, 60, 120 and 240 min with 800k counts were obtained with a gamma camera. Any abnormal localization of radioactivity in the right lower quadrant of the abdomen, equal to or greater than bone marrow activity, was considered as a positive scan. Results: 36 out of 49 patients showing positive TC-WBC scans received appendectomy. They all proved to have positive pathological findings. Five positive TC-WBC were not related to acute appendicitis, because of other pathological lesions. Eight patients were not operated and clinical follow-up after one month revealed no acute abdominal condition. Three of 31 patients with negative TC-WBC scans received appendectomy. They also presented positive pathological findings. The remaining 28 patients did not receive operations and revealed no evidence of appendicitis after at least one month of follow-up. The overall sensitivity, specificity, accuracy, positive and negative predictive values for TC-WBC scan to diagnose acute appendicitis were 92, 78, 86, 82, and 90%, respectively. Conclusion: TC-WBC scan provides a rapid and highly accurate method for the diagnosis of acute appendicitis in patients with equivocal clinical examination. It proved useful in reducing the false-positive rate of laparotomy and shortens the time necessary for clinical observation.

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Identification of newborns at risk for autism using electronic medical records and machine learning

10.1101/19008367 ◽

2019 ◽

Author(s):

Rayees Rahman ◽

Arad Kodesh ◽

Stephen Z Levine ◽

Sven Sandin ◽

Abraham Reichenberg ◽

...

Keyword(s):

Machine Learning ◽

Autism Spectrum Disorder ◽

Positive Predictive Value ◽

Electronic Medical Records ◽

Predictive Value ◽

False Positive ◽

Medical Records ◽

False Positive Rate ◽

Autism Spectrum ◽

Positive Rate

AbstractImportanceCurrent approaches for early identification of individuals at high risk for autism spectrum disorder (ASD) in the general population are limited, where most ASD patients are not identified until after the age of 4. This is despite substantial evidence suggesting that early diagnosis and intervention improves developmental course and outcome.ObjectiveDevelop a machine learning (ML) method predicting the diagnosis of ASD in offspring in a general population sample, using parental electronic medical records (EMR) available before childbirthDesignPrognostic study of EMR data within a single Israeli health maintenance organization, for the parents of 1,397 ASD children (ICD-9/10), and 94,741 non-ASD children born between January 1st, 1997 through December 31st, 2008. The complete EMR record of the parents was used to develop various ML models to predict the risk of having a child with ASD.Main outcomes and measuresRoutinely available parental sociodemographic information, medical histories and prescribed medications data until offspring’s birth were used to generate features to train various machine learning algorithms, including multivariate logistic regression, artificial neural networks, and random forest. Prediction performance was evaluated with 10-fold cross validation, by computing C statistics, sensitivity, specificity, accuracy, false positive rate, and precision (positive predictive value, PPV).ResultsAll ML models tested had similar performance, achieving an average C statistics of 0.70, sensitivity of 28.63%, specificity of 98.62%, accuracy of 96.05%, false positive rate of 1.37%, and positive predictive value of 45.85% for predicting ASD in this dataset.Conclusion and relevanceML algorithms combined with EMR capture early life ASD risk. Such approaches may be able to enhance the ability for accurate and efficient early detection of ASD in large populations of children.Key pointsQuestionCan autism risk in children be predicted using the pre-birth electronic medical record (EMR) of the parents?FindingsIn this population-based study that included 1,397 children with autism spectrum disorder (ASD) and 94,741 non-ASD children, we developed a machine learning classifier for predicting the likelihood of childhood diagnosis of ASD with an average C statistic of 0.70, sensitivity of 28.63%, specificity of 98.62%, accuracy of 96.05%, false positive rate of 1.37%, and positive predictive value of 45.85%.MeaningThe results presented serve as a proof-of-principle of the potential utility of EMR for the identification of a large proportion of future children at a high-risk of ASD.

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A Study of the Diagnostic Accuracy of an Existing Multivariable Test to Predict Shoulder Dystocia

American Journal of Perinatology Reports ◽

10.1055/s-0039-1693162 ◽

2019 ◽

Vol 09 (03) ◽

pp. e262-e267

Author(s):

Henry Alexander Easley ◽

Todd Michael Beste

Keyword(s):

Diagnostic Accuracy ◽

Prediction Model ◽

Study Design ◽

False Positive ◽

False Positive Rate ◽

Shoulder Dystocia ◽

The Other ◽

Predictive Values ◽

Positive Rate ◽

Sensitivity Specificity

Objectives To evaluate the diagnostic accuracy of a multivariable prediction model, the Shoulder Screen (Perigen, Inc.), and compare it with the American College of Obstetricians and Gynecologists (ACOG) guidelines to prevent harm from shoulder dystocia. Study Design The model was applied to two groups of 199 patients each who delivered during a 4-year period. One group experienced shoulder dystocia and the other group delivered without shoulder dystocia. The model's accuracy was analyzed. The performance of the model was compared with the ACOG guideline. Results The sensitivity, specificity, positive, and negative predictive values of the model were 23.1, 99.5, 97.9, and 56.4%, respectively. The sensitivity of the ACOG guideline was 10.1%. The false-positive rate of the model was 0.5%. The accuracy of the model was 61.3%. Conclusion A multivariable prediction model can predict shoulder dystocia and is more accurate than ACOG guidelines.

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Venous Flow Coupler in Head and Neck Free Flap Reconstruction

Otolaryngology ◽

10.1177/0194599820953098 ◽

2020 ◽

pp. 019459982095309

Author(s):

Scott H. Troob ◽

Quinn Self ◽

Deniz Gerecci ◽

Macgregor Hodgson ◽

Javier González-Castro ◽

...

Keyword(s):

Free Flap ◽

Predictive Value ◽

False Positive ◽

False Positive Rate ◽

Case Series ◽

Arterial Flow ◽

Retrospective Case ◽

Venous Flow ◽

Retrospective Case Series ◽

Positive Rate

Objective To describe the utility of venous flow couplers in monitoring free tissue flaps in the immediate postoperative setting. Study Design Retrospective case series. Setting Otolaryngology department at a single tertiary care institution. Methods A retrospective case series of free flap reconstructions in which venous flow couplers were employed to supplement flap monitoring. All free flap cases performed over the past 4 years were reviewed. Inclusion criteria were venous flow coupler and arterial flow Doppler monitored for 5 days postoperatively. Results From July 2014 through May 2018, the venous flow coupler was used with the arterial flow Doppler and clinical monitoring in 228 cases. Eleven cases did not meet criteria for inclusion; thus, 217 cases were analyzed. Twenty cases (9.2%) returned to the operating room with concern for flap compromise, and 16 were salvaged. The combination of venous flow coupler and arterial flow Doppler identified 19 of these flaps. Venous flow couplers identified 5 compromised flaps before there was an arterial signal change, and all were salvaged. Additionally, there was a 24.1% false-positive rate when 2 venous flow couplers were used in parallel. For the venous flow coupler, the positive predictive value was 64.3% and the negative predictive value, 98.9%. The false-positive rate in the series was 5.1%. The sensitivity was 90% and the specificity, 94.9%. Conclusion The venous flow coupler is able to detect venous thrombosis in the absence of arterial thrombosis and may contribute to improved flap salvage rates.

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Protein Expression Signatures Determined by Reverse Phase Proteins Arrays (RPPA) Accurately Predict FLT3-ITD Mutation Status in AML.

Blood ◽

10.1182/blood.v110.11.2398.2398 ◽

2007 ◽

Vol 110 (11) ◽

pp. 2398-2398

Author(s):

Steven M. Kornblau ◽

YiHua Qiu ◽

Wenjing Chen ◽

Srdan Verstovsek ◽

Kevin R. Coombes ◽

...

Keyword(s):

Positive Predictive Value ◽

Protein Expression ◽

Mutation Analysis ◽

Predictive Value ◽

False Positive ◽

False Positive Rate ◽

Myelogenous Leukemia ◽

Reverse Phase ◽

Mutation Status ◽

Positive Rate

Abstract We have used Reverse Phase Protein Arrays (RPPA) to perform proteomic profiling in Acute Myelogenous Leukemia (AML) focusing on cell cycle, apoptosis and signal transduction pathway proteins (ASH 2006, abstract #107). Protein expression signatures were derived from this dataset of 436 AML patients, analyzed for 30 total and 22 phopho- proteins. The predictive ability of these RPPA derived protein expression signatures has not been prospectively tested to determine if they are valid. This dataset presented an opportunity to validate this as there was a population of patients with known FLT3-ITD and D835 mutation status (n=297) and another population where the status was unknown (n=139), among which 55 had sufficient sample available for mutation analysis. Prior to performing the mutation analysis a predictive model was built using linear regression with part of the data utilized for training and the reminder for validation. The model was designed to predict for the presence of mutation, either ITD or D835, although there are differences int eh signature of each. The total population had 85 cases with FLT3-ITD and 15 with the D835 mutation. The optimal model that was developed, using 30%, 50% and 70% of the samples for training and the remainder for validation, had a median validation accuracy of 68%, 70% and 72% respectively. Prospective predictions of FLT3-ITD or D835 mutation status were then made for all samples lacking FLT3-ITD or D835 mutation data. Mutation analysis was then performed using PCR amplification followed by 2-D gel electrophoresis (FLT3-ITD) to evaluate for PCR product size, or sequencing (D835) on 55 samples. This revealed 9 cases with FLT3-ITD, 3 with a D835 mutation, 1 with both and 43 without mutation. Among these 55 cases the model correctly predicted that 8 of the 12 mutant cases would be mutant including 8 of 10 with a FLT3-ITD, but 0 of 2 with only the D835 mutation. Among the 43 wildtype cases 36 were accurately predicted to be wildtype, while 7 were incorrectly predicted to have the mutation mutant. This yields an overall accuracy (OA) of 80%, Sensitivity =66%, Specificity=90%, Positive Predictive Value (PPV) of 53%, False positive rate of (FPR) of 16%. Since most patients with FLT3-ITD have Diploid cytogenetics we also looked at the predictive accuracy of the protein expression signature in that population. Among 23 patients with Diploid cytogenetics the overall accuracy was OA) of 83%, Sensitivity =75%, Specificity=87%, Positive Predictive Value (PPV) of 75%, False positive rate of (FPR) of 13%. Since FLT3-ITD and D835 carry different prognostic impact, and had different protein expression signatures, greater accuracy might be achieved if separate models were developed for each mutation individually. The model demonstrated that RPPA derived protein expression signatures can accurately be used to predict mutation status providing the first prospective validation of protein expression signatures in AML.

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Is D2 surgery necessary for clinical T1 gastric cancer with nodal swelling?

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.4_suppl.288 ◽

2020 ◽

Vol 38 (4_suppl) ◽

pp. 288-288

Author(s):

Takeyuki Wada ◽

Takaki Yoshikawa ◽

Ayako Kamiya ◽

Keichi Date ◽

Tsutomu Hayashi ◽

...

Keyword(s):

Risk Factors ◽

Gastric Cancer ◽

Positive Predictive Value ◽

Predictive Value ◽

False Positive ◽

False Positive Rate ◽

False Positivity ◽

Positive Rate ◽

D2 Surgery ◽

Sensitivity Specificity

288 Background: D2 surgery is required for clinical T1 gastric cancer with nodal swelling, however, D2 has a higher risk for morbidity than D1/D1+. Moreover, previous study demonstrated that the false positive rate for nodal diagnosis in clinical T1 was very high. To select optimal surgery with high probability, we explored risk factors for false positivity in clinical T1 disease. Methods: Patients who underwent radical gastrectomy for clinical T1 gastric cancer between April 2015 and June 2019 were enrolled. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for nodal diagnosis were retrospectively investigated. The risk factors for false positivity were also analyzed by the following factors; age, sex, histological type, tumor size, tumor depth, location, tumor type, presence of ulcer, and timing of CT that is (1) the patients who underwent primary endoscopic mucosal dissection (ESD) but resulted in non-curative resection, then received CT to proceed to surgery (delayed CT group) or (2) the other patients who had received CT before primary surgery or before non-curative ESD (primary CT group). Results: A total of 679 patients were examined in the present study. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 83.5% (567/679), 14.3% (13/91), 94.2% (554/588), 27.7% (13/47), and 87.7% (554/632), respectively. The false positive rate was 72.3% (34/47). In univariate analysis, differentiated tumor ( p= 0.012) and delayed CT (p < 0.001) were associated with the false positivity. Multivariate analysis revealed that delayed CT (OR, 4.534; p < 0.001) was a sole significant risk factor for false positivity. False positive rate was 100% (13/13) in the delayed CT group and 61.8% (21/34) in the primary CT group ( p= 0.009). Conclusions: False positive rate was high in clinical T1 disease, especially when the patients received delayed CT after non-curative ESD. D2 surgery would be unnecessary even though nodal swelling was detected in CT after non-curative ESD.

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Is N-Hacking Ever OK? A simulation-based study

10.1101/2019.12.12.868489 ◽

2019 ◽

Cited By ~ 1

Author(s):

Pamela Reinagel

Keyword(s):

Positive Predictive Value ◽

Sample Size ◽

Predictive Value ◽

False Positive ◽

Hypothesis Test ◽

False Positive Rate ◽

False Positives ◽

Wide Range ◽

Positive Rate ◽

Incremental Sampling

AbstractAfter an experiment has been completed and analyzed, a trend may be observed that is “not quite significant”. Sometimes in this situation, researchers incrementally grow their sample size N in an effort to achieve statistical significance. This is especially tempting in situations when samples are very costly or time-consuming to collect, such that collecting an entirely new sample larger than N (the statistically sanctioned alternative) would be prohibitive. Such post-hoc sampling or “N-hacking” is condemned, however, because it leads to an excess of false positive results. Here Monte-Carlo simulations are used to show why and how incremental sampling causes false positives, but also to challenge the claim that it necessarily produces alarmingly high false positive rates. In a parameter regime that would be representative of practice in many research fields, simulations show that the inflation of the false positive rate is modest and easily bounded. But the effect on false positive rate is only half the story. What many researchers really want to know is the effect N-hacking would have on the likelihood that a positive result is a real effect that will be replicable: the positive predictive value (PPV). This question has not been considered in the reproducibility literature. The answer depends on the effect size and the prior probability of an effect. Although in practice these values are not known, simulations show that for a wide range of values, the PPV of results obtained by N-hacking is in fact higher than that of non-incremented experiments of the same sample size and statistical power. This is because the increase in false positives is more than offset by the increase in true positives. Therefore in many situations, adding a few samples to shore up a nearly-significant result is in fact statistically beneficial. In conclusion, if samples are added after an initial hypothesis test this should be disclosed, and if a p value is reported it should be corrected. But, contrary to widespread belief, collecting additional samples to resolve a borderline p value is not invalid, and can confer previously unappreciated advantages for efficiency and positive predictive value.

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Commercial Laboratory IgM Testing forToxoplasma gondiiin Pregnancy: A 20-Year Experience

Infectious Diseases in Obstetrics and Gynecology ◽

10.1080/10647440500148024 ◽

2005 ◽

Vol 13 (3) ◽

pp. 151-153 ◽

Cited By ~ 15

Author(s):

David J. Garry ◽

Andrew Elimian ◽

Vandy Wiencek ◽

David A. Baker

Keyword(s):

Predictive Value ◽

False Positive ◽

False Positive Rate ◽

Reference Laboratory ◽

Antibody Testing ◽

Commercial Laboratory ◽

Laboratory Results ◽

Positive Rate ◽

Acute Toxoplasmosis ◽

Positive Results

Objective.This study was performed to review the clinical utility of commercial laboratoryToxoplasmosis-specific IgM testing during pregnancy and outcomes of the gestation at our institution.Methods.A retrospective review of all women referred for suspected acuteToxoplasma gondiiinfection during pregnancy from 1984 through 2004 was performed. Women were diagnosed with suspected acute toxoplasmosis based on commercial laboratory serologic antibody testing. All women had blood sent to a recognized reference laboratory for antibody testing within 2 weeks of the commercial laboratory results. The study protocol was approved by the Institutional Review Board. Chi-square analysis were used with a significance ofP< .05.Results.A total of 130 women were evaluated during the study period with 116 IgM positive results from the commercial laboratories. The commercial laboratory antibodies were as follows: IgM positive with IgG negative (n= 20), IgM positive with IgG positive (n= 96), and IgM negative with IgG positive (n= 14). There was a significant reduction in the IgM positive results when comparing commercial laboratory (n= 116) with the reference laboratory results (n= 28;p< .001). Acute toxoplasmosis infection was diagnosed in 7 (5%) of the women. All cases of acute toxoplasmosis infection had a positive commercial laboratory IgM result. The false positive rate for the commercial laboratory IgM was 88.6% and the diagnostic indices were sensitivity 100%, specificity 11.4%, positive predictive value 6% and negative predictive value 100%.Conclusion.Commercial laboratoryToxoplasmosis-specific IgM is associated with a high false positive rate. The commercial and reference laboratory IgM results identified all cases of acute toxoplasmosis infection. Commercial laboratories reflexively obtaining reference laboratory confirmation of positive results could reduce costs associated with testing, referrals, retesting, and invasive procedures.

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