scholarly journals Identification of Atypical Diabetes Using Algorithms to Search the Electronic Medical Record

2020 ◽  
Vol 3 ◽  
Author(s):  
Veronica Salichs-Perez ◽  
Daniel Robert Hood ◽  
Zeb Saeed ◽  
Carmella Evans-Molina
Keyword(s):  
Chart Review ◽  
False Positive Rate ◽  
Diabetic Patients ◽  
Therapeutic Approaches ◽  
Diagnostic Codes ◽  
Positive Rate ◽  
Age Of Diagnosis ◽  
Atypical Diabetes ◽  
Insulin Use ◽  
Final Cohort

Background and Hypothesis:  Atypical diabetes (DM) comprises phenotypically and potentially genotypically distinct forms of DM not fitting current sub-categories of classification. Understanding these rare and uncharacterized types of DM can potentially inform the application of personalized therapeutic approaches and is the emphasis of a recent NIH-funded Consortium focused on Rare and Atypical Diabetes (RADIANT). We aimed to employ informatic-based algorithms to identify potentially atypical DM cases from electronic medical records (EMR) to identify candidates for inclusion in RADIANT.    Project Methods:  Diabetic patients were identified based on two DM diagnostic codes, treatment with anti-diabetic medication, and two diagnostic labs elevated.  We filtered for patients with BMI <25 at diagnosis and normal lipid profile. Charts were reviewed manually.  Demographic and clinical data were extracted from EMR and entered into a REDCap database. SPSS was used for statistical analysis.     Results:   A total of 21,820 individuals met criteria for DM; 208 were identified as potentially atypical. Chart review was completed for 126 cases. Fifteen were deceased and removed from the final cohort. Of those remaining, 12 (11%) exhibited features consistent with atypical diabetes. The remainder were classified as typical T2D. No significant differences regarding ethnicity or diabetes complication status were identified between typical and atypical cases. Demographics of atypical cases were, 66% female, and 33% male. The average age of diagnosis was 46.8 ± 19.3 yrs. Average BMI was 23.7 ± 4.1. Atypical diabetes individuals were more likely to present with ketoacidosis (p=0.01) exhibiting a trend towards increased insulin use (50% vs. 14%; p=0.09).     Conclusion:   Our study suggests that using EMR may be effective in flagging phenotypically distinct forms of DM in real world settings, associated with a high false positive rate. Data suggests this form of atypical diabetes represents a small percentage of overall DM cases (0.05%). Future studies will focus on application of algorithms to identify other atypical diabetes subsets. 

Properly collected plasma metanephrines excludes PPGL after false positive screening tests

2021 ◽  
Author(s):  
Gregory A Kline ◽  
Jessica Boyd ◽  
Brenda Polzin ◽  
Adrian Harvey ◽  
Janice L Pasieka ◽  
...  
Keyword(s):  
False Positive ◽  
Adrenal Mass ◽  
Chart Review ◽  
False Positive Rate ◽  
Total Positivity ◽  
Screening Tests ◽  
Positive Rate ◽  
Plasma Metanephrines ◽  
Positive Results ◽  
Urine Metanephrines

Abstract Context False positive results are common for pheochromocytoma/paraganglioma(PPGL) real-world screening. Objective Determine the correlation between screening urine and seated plasma metanephrines in outpatients where PPGL was absent, compared to meticulously prepared and supine-collected plasma metanephrines with age-adjusted references. Design Retrospective cohort study Setting Databases from a single-provider provincial laboratory(2012-2018), a validated PPGL registry and a manual chart review from a specialized endocrine testing unit. Patients PPGL registry data excluded known PPGL cases from the laboratory database. Outpatients having both urine and plasma metanephrines &lt;90 days apart. Methods The correlation between urine and seated plasma measures along with the total positivity rate. All cases of plasma metanephrines drawn in the endocrine unit were reviewed for test indication and test positivity rate. Results There were 810 non-PPGL pairs of urine and plasma metanephrines in the laboratory database; 46.1% of urine metanephrines were reported high. Of seated outpatient plasma metanephrines drawn a median of 5.9 days later, 19.2% were also high (r=0.33 and 0.50 for normetanephrine and metanephrine, respectively). In contrast, the meticulously prepared and supine collected patients(n=139, 51% prior high urine metanephrines) had &lt;3% rate of abnormal high results in patients without known PPGL/adrenal mass. Conclusions There was a poor-to-moderate correlation between urine and seated plasma metanephrines. Up to 20% of those with high urine measures also had high seated plasma metanephrines in the absence of PPGL. Properly prepared and collected supine plasma metanephrines had a false positive rate of &lt;3% in the absence of known PPGL/adrenal mass.

scholarly journals Reduced False Positives in Autism Screening Via Digital Bio-markers Inferred from Deep Co-morbidity Patterns

2021 ◽  
Author(s):  
Ishanu Chattopadhyay ◽  
Dmytro Onishchenko ◽  
Yi Huang ◽  
Peter J. Smith ◽  
Michael M. Msall ◽  
...  
Keyword(s):  
Developmental Trajectories ◽  
Characteristic Curve ◽  
False Positive Rate ◽  
Autism Spectrum ◽  
Superior Performance ◽  
Behavioral Challenges ◽  
Diagnostic Codes ◽  
Co Morbidity ◽  
Positive Rate ◽  
The Individual

Abstract Autism spectrum disorder (ASD) is a developmental disability associated with significant social and behavioral challenges. There is a need for tools that help identify children with ASD as early as possible. Our current incomplete understanding of ASD pathogenesis, and the lack of reliable biomarkers hampers early detection, intervention, and developmental trajectories. In this study we develop and validate machine inferred digital biomarkers for autism using individual diagnostic codes already recorded during medical encounters. Our risk estimator identifies children at high risk with a corresponding area under the receiver operating characteristic curve (AUC) exceeding 80% from shortly after two years of age for either sex, and across two independent databases of patient records. Thus, we systematically leverage ASD co-morbidities - with no requirement of additional blood work, tests or procedures - to compute the Autism Co-morbid Risk Score (ACoR) which predicts elevated risk during the earliest childhood years, when interventions are the most effective. By itself, ACoR has superior performance to common questionnaires-based screenings such as the M-CHAT/F, and has the potential to reduce socio-economic, ethnic and demographic biases. In addition to superior standalone performance, independence from questionnaire based screening allows us to further boost performance by conditioning on the individual M-CHAT/F scores - we can either halve the false positive rate of current screening protocols or boost sensitivity to over 60%, while maintaining specificity above 95%. Adopted in practice, ACoR could significantly reduce the median diagnostic age for ASD, and reduce long post-screen wait-times experienced by families for confirmatory diagnoses and access to evidence based interventions.

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

2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
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.

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.

Identification of and Correction for Publication Bias: Comment

2019 ◽  
Author(s):  
Amanda Kvarven ◽  
Eirik Strømland ◽  
Magnus Johannesson
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Large Scale ◽  
Meta Analysis ◽  
False Positive Rate ◽  
Effect Sizes ◽  
Replication Studies ◽  
Moderate Reduction ◽  
Positive Rate ◽  
Meta Analyses

Andrews &amp; Kasy (2019) propose an approach for adjusting effect sizes in meta-analysis for publication bias. We use the Andrews-Kasy estimator to adjust the result of 15 meta-analyses and compare the adjusted results to 15 large-scale multiple labs replication studies estimating the same effects. The pre-registered replications provide precisely estimated effect sizes, which do not suffer from publication bias. The Andrews-Kasy approach leads to a moderate reduction of the inflated effect sizes in the meta-analyses. However, the approach still overestimates effect sizes by a factor of about two or more and has an estimated false positive rate of between 57% and 100%.

Forms, Importance, and Ineffability of Factor Interactions to Define Personality Disorders: Comment on Lilienfeld et al. (2019)

2019 ◽  
Author(s):  
Stephen D Benning ◽  
Edward Smith
Keyword(s):  
Personality Disorders ◽  
False Positive Rate ◽  
Empirical Work ◽  
Design Studies ◽  
Linear Threshold ◽  
Positive Rate ◽  
Saturation Effects ◽  
Factor Interactions ◽  
Main Effects ◽  
Criterion Variables

The emergent interpersonal syndrome (EIS) approach conceptualizes personality disorders as the interaction among their constituent traits to predict important criterion variables. We detail the difficulties we have experienced finding such interactive predictors in our empirical work on psychopathy, even when using uncorrelated traits that maximize power. Rather than explaining a large absolute proportion of variance in interpersonal outcomes, EIS interactions might explain small amounts of variance relative to the main effects of each trait. Indeed, these interactions may necessitate samples of almost 1,000 observations for 80% power and a false positive rate of .05. EIS models must describe which specific traits’ interactions constitute a particular EIS, as effect sizes appear to diminish as higher-order trait interactions are analyzed. Considering whether EIS interactions are ordinal with non-crossing slopes, disordinal with crossing slopes, or entail non-linear threshold or saturation effects may help researchers design studies, sampling strategies, and analyses to model their expected effects efficiently.

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

Ascertaining an efficient eligibility cut-off for extended Medicare items for eating disorders

2021 ◽  
pp. 103985622110286
Author(s):  
Tracey Wade ◽  
Jamie-Lee Pennesi ◽  
Yuan Zhou
Keyword(s):  
Eating Disorders ◽  
Eating Disorder ◽  
False Positive Rate ◽  
Area Under The Curve ◽  
Rate Sensitivity ◽  
True Positive Rate ◽  
Eating Disorder Examination Questionnaire ◽  
Eating Disorder Examination ◽  
Positive Rate ◽  
The Relationship

Objective: Currently eligibility for expanded Medicare items for eating disorders (excluding anorexia nervosa) require a score ⩾ 3 on the 22-item Eating Disorder Examination-Questionnaire (EDE-Q). We compared these EDE-Q “cases” with continuous scores on a validated 7-item version of the EDE-Q (EDE-Q7) to identify an EDE-Q7 cut-off commensurate to 3 on the EDE-Q. Methods: We utilised EDE-Q scores of female university students ( N = 337) at risk of developing an eating disorder. We used a receiver operating characteristic (ROC) curve to assess the relationship between the true-positive rate (sensitivity) and the false-positive rate (1-specificity) of cases ⩾ 3. Results: The area under the curve showed outstanding discrimination of 0.94 (95% CI: .92–.97). We examined two specific cut-off points on the EDE-Q7, which included 100% and 87% of true cases, respectively. Conclusion: Given the EDE-Q cut-off for Medicare is used in conjunction with other criteria, we suggest using the more permissive EDE-Q7 cut-off (⩾2.5) to replace use of the EDE-Q cut-off (⩾3) in eligibility assessments.

Evidence for Age-Adjusted D-Dimer to Rule out Pulmonary Embolism: An Institutional Study

2020 ◽  
Vol 154 (Supplement_1) ◽  
pp. S5-S5
Author(s):  
Ridin Balakrishnan ◽  
Daniel Casa ◽  
Morayma Reyes Gil
Keyword(s):  
Pulmonary Embolism ◽  
False Positive ◽  
False Positive Rate ◽  
Moderate Risk ◽  
Older Population ◽  
Statistical Measures ◽  
Positive Rate ◽  
Risk Patients ◽  
D Dimer ◽  
Rule Out

Abstract The diagnostic approach for ruling out suspected acute pulmonary embolism (PE) in the ED setting includes several tests: ultrasound, plasma d-dimer assays, ventilation-perfusion scans and computed tomography pulmonary angiography (CTPA). Importantly, a pretest probability scoring algorithm is highly recommended to triage high risk cases while also preventing unnecessary testing and harm to low/moderate risk patients. The d-dimer assay (both ELISA and immunoturbidometric) has been shown to be extremely sensitive to rule out PE in conjunction with clinical probability. In particularly, d-dimer testing is recommended for low/moderate risk patients, in whom a negative d-dimer essentially rules out PE sparing these patients from CTPA radiation exposure, longer hospital stay and anticoagulation. However, an unspecific increase in fibrin-degradation related products has been seen with increase in age, resulting in higher false positive rate in the older population. This study analyzed patient visits to the ED of a large academic institution for five years and looked at the relationship between d-dimer values, age and CTPA results to better understand the value of age-adjusted d-dimer cut-offs in ruling out PE in the older population. A total of 7660 ED visits had a CTPA done to rule out PE; out of which 1875 cases had a d-dimer done in conjunction with the CT and 5875 had only CTPA done. Out of the 1875 cases, 1591 had positive d-dimer results (&gt;0.50 µg/ml (FEU)), of which 910 (57%) were from patients older than or equal to fifty years of age. In these older patients, 779 (86%) had a negative CT result. The following were the statistical measures of the d-dimer test before adjusting for age: sensitivity (98%), specificity (12%); negative predictive value (98%) and false positive rate (88%). After adjusting for age in people older than 50 years (d-dimer cut off = age/100), 138 patients eventually turned out to be d-dimer negative and every case but four had a CT result that was also negative for a PE. The four cases included two non-diagnostic results and two with subacute/chronic/subsegmental PE on imaging. None of these four patients were prescribed anticoagulation. The statistical measures of the d-dimer test after adjusting for age showed: sensitivity (96%), specificity (20%); negative predictive value (98%) and a decrease in the false positive rate (80%). Therefore, imaging could have been potentially avoided in 138/779 (18%) of the patients who were part of this older population and had eventual negative or not clinically significant findings on CTPA if age-adjusted d-dimers were used. This data very strongly advocates for the clinical usefulness of an age-adjusted cut-off of d-dimer to rule out PE.

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