scholarly journals Utilizing two-tiered screening for early detection of autism spectrum disorder

Autism ◽  
2017 ◽  
Vol 22 (7) ◽  
pp. 881-890 ◽  
Author(s):  
Meena Khowaja ◽  
Diana L Robins ◽  
Lauren B Adamson

Despite advances in autism screening practices, challenges persist, including barriers to implementing universal screening in primary care and difficulty accessing services. The high false positive rate of Level 1 screening methods presents especially daunting difficulties because it increases the need for comprehensive autism evaluations. This study explored whether two-tiered screening—combining Level 1 (Modified Checklist for Autism in Toddlers, Revised with Follow-Up) and Level 2 (Screening Tool for Autism in Toddlers and Young Children) measures—improves the early detection of autism. This study examined a sample of 109 toddlers who screened positive on Level 1 screening and completed a Level 2 screening measure prior to a diagnostic evaluation. Results indicated that two-tiered screening reduced the false positive rate using published Screening Tool for Autism in Toddlers and Young Children cutoffs compared to Level 1 screening alone, although at a cost to sensitivity. However, alternative Screening Tool for Autism in Toddlers and Young Children scoring in the two-tiered screening improved both positive predictive value and sensitivity. Exploratory analyses were conducted, including comparison of autism symptoms and clinical profiles across screening subsamples. Recommendations regarding clinical implications of two-tiered screening and future areas of research are presented.

2019 ◽  
Author(s):  
Rayees Rahman ◽  
Arad Kodesh ◽  
Stephen Z Levine ◽  
Sven Sandin ◽  
Abraham Reichenberg ◽  
...  

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.


2020 ◽  
Vol 63 (1) ◽  
Author(s):  
Rayees Rahman ◽  
Arad Kodesh ◽  
Stephen Z. Levine ◽  
Sven Sandin ◽  
Abraham Reichenberg ◽  
...  

Abstract Background. Current approaches for early identification of individuals at high risk for autism spectrum disorder (ASD) in the general population are limited, and 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. The aim of the current study was to test the ability of machine learning (ML) models applied to electronic medical records (EMRs) to predict ASD early in life, in a general population sample. Methods. We used EMR data from a single Israeli Health Maintenance Organization, including EMR information for parents of 1,397 ASD children (ICD-9/10) and 94,741 non-ASD children born between January 1st, 1997 and December 31st, 2008. Routinely available parental sociodemographic information, parental medical histories, and prescribed medications data were used to generate features to train various ML algorithms, including multivariate logistic regression, artificial neural networks, and random forest. Prediction performance was evaluated with 10-fold cross-validation by computing the area under the receiver operating characteristic curve (AUC; C-statistic), sensitivity, specificity, accuracy, false positive rate, and precision (positive predictive value [PPV]). Results. All ML models tested had similar performance. The average performance across all models had C-statistic of 0.709, sensitivity of 29.93%, specificity of 98.18%, accuracy of 95.62%, false positive rate of 1.81%, and PPV of 43.35% for predicting ASD in this dataset. Conclusions. We conclude that ML algorithms combined with EMR capture early life ASD risk as well as reveal previously unknown features to be associated with ASD-risk. Such approaches may be able to enhance the ability for accurate and efficient early detection of ASD in large populations of children.


PEDIATRICS ◽  
1979 ◽  
Vol 64 (4) ◽  
pp. 438-441
Author(s):  
S. Jean Emans ◽  
Estherann Grace ◽  
Robert P. Masland

Of 500 asymptomatic adolescent girls who were screened for bacteriuria by three methods—dipslide (Uricult), dipstrip (Microstix-3 reagent strips), and home nitrite test (Microstix-Nitrite reagent strips)—eight cases (1.6%) were detected: 6/8 by dipslide and dipstrip; 5/8 by nitrite testing. The false-positive-rate (> 104 colonies/ml) of the dipslide test was 6.4%, and the dipstrip test, 2.8%. A history of vaginal discharge was not associated with "contaminated" specimens. False-positive nitrite tests were reported by 0.6% of the patients who returned the postcards. Overall, 70.4% of the patients returned the postcards for the home nitrite test. The patients were divided by method of payment (Medicaid vs non-Medicaid) in order to provide an approximation of socioeconomic status; non-Medicaid patients were significantly more likely to return postcards than Medicaid patients (75.8% vs 63.7%). Of the group reporting previous urinary tract infection, 79% of both Medicaid and non-Medicaid patients returned postcards, suggesting that a prior experience with the diagnosis increased compliance with a home test.


2017 ◽  
Vol 45 (6) ◽  
pp. 683-687
Author(s):  
D. Coric ◽  
N. A. Smith

Elevated troponin levels within three days of surgery are strongly linked to major adverse cardiac events (MACE). However the value of screening with troponin measurements is controversial. The extent to which this is done in routine practice is uncertain. We examined the medical records of all patients ≥45 years of age undergoing moderate or major non-cardiac surgery in our tertiary referral hospital over a six-month period. We determined how many patients had a troponin (TnT) measurement recorded in the first three days postoperatively, how many of these were abnormal, and the occurrence of MACE within 30 days. Two thousand and two hundred patients underwent 2,577 operations that met the study criteria. A postoperative TnT was measured after 4.5% of operations. Thirty-eight percent of patients with a recorded TnT measurement, and 44% of those with an abnormal measurement, experienced a MACE within 30 days. The sensitivity of an abnormal TnT to detect MACE was 86%. The specificity was low at 32% with a false positive rate of 56%. Patients with an abnormal TnT result had an increased risk of MACE (23%). The ‘number needed to measure’ to detect one patient with MACE was 4.4. In our institution, postoperative TnT levels were rarely measured and were used as a diagnostic rather than as a screening tool. The high false positive rate for MACE prediction limits its potential value as a screening tool. The test could be considered useful if it leads to further investigation, and may be best considered as one component of a multivariate approach to cardiac risk evaluation and diagnosis.


2017 ◽  
Vol 52 (12) ◽  
pp. 1168-1170 ◽  
Author(s):  
Zachary K. Winkelmann ◽  
Ashley K. Crossway

Reference/Citation:  Harmon KG, Zigman M, Drezner JA. The effectiveness of screening history, physical exam, and ECG to detect potentially lethal cardiac disorders in athletes: a systematic review/meta-analysis. J Electrocardiol. 2015;48(3):329–338. Clinical Question:  Which screening method should be considered best practice to detect potentially lethal cardiac disorders during the preparticipation physical examination (PE) of athletes? Data Sources:  The authors completed a comprehensive literature search of MEDLINE, CINAHL, Cochrane Library, Embase, Physiotherapy Evidence Database (PEDro), and SPORTDiscus from January 1996 to November 2014. The following key words were used individually and in combination: ECG, athlete, screening, pre-participation, history, and physical. A manual review of reference lists and key journals was performed to identify additional studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed for this review. Study Selection:  Studies selected for this analysis involved (1) outcomes of cardiovascular screening in athletes using the history, PE, and electrocardiogram (ECG); (2) history questions and PE based on the American Heart Association recommendations and guidelines; and (3) ECGs interpreted following modern standards. The exclusion criteria were (1) articles not in English, (2) conference abstracts, and (3) clinical commentary articles. Study quality was assessed on a 7-point scale for risk of bias; a score of 7 indicated the highest quality. Articles with potential bias were excluded. Data Extraction:  Data included number and sex of participants, number of true- and false-positives and negatives, type of ECG criteria used, number of cardiac abnormalities, and specific cardiac conditions. The sensitivity, specificity, false-positive rate, and positive predictive value of each screening tool were calculated and summarized using a bivariate random-effects meta-analysis model. Main Results:  Fifteen articles reporting on 47 137 athletes were fully reviewed. The overall quality of the 15 articles ranged from 5 to 7 on the 7-item assessment scale (ie, participant selection criteria, representative sample, prospective data with at least 1 positive finding, modern ECG criteria used for screening, cardiovascular screening history and PE per American Heart Association guidelines, individual test outcomes reported, and abnormal screening findings evaluated by appropriate diagnostic testing). The athletes (66% males and 34% females) were ethnically and racially diverse, were from several countries, and ranged in age from 5 to 39 years. The sensitivity and specificity of the screening methods were, respectively, ECG, 94% and 93%; history, 20% and 94%; and PE, 9% and 97%. The overall false-positive rate for ECG (6%) was less than that for history (8%) or PE (10%). The positive likelihood ratios of each screening method were 14.8 for ECG, 3.22 for history, and 2.93 for PE. The negative likelihood ratios were 0.055 for ECG, 0.85 for history, and 0.93 for PE. A total of 160 potentially lethal cardiovascular conditions were detected, for a rate of 0.3%, or 1 in 294 patients. The most common conditions were Wolff-Parkinson-White syndrome (n = 67, 42%), long QT syndrome (n = 18, 11%), hypertrophic cardiomyopathy (n = 18, 11%), dilated cardiomyopathy (n = 11, 7%), coronary artery disease or myocardial ischemia (n = 9, 6%), and arrhythmogenic right ventricular cardiomyopathy (n = 4, 3%). Conclusions:  The most effective strategy to screen athletes for cardiovascular disease was ECG. This test was 5 times more sensitive than history and 10 times more sensitive than PE, and it had a higher positive likelihood ratio, lower negative likelihood ratio, and lower false-positive rate than history or PE. The 12-lead ECG interpreted using modern criteria should be considered the best practice in screening athletes for cardiovascular disease, and the use of history and PE alone as screening tools should be reevaluated.


Author(s):  
M Fabre ◽  
S Ruiz-Martinez ◽  
ME Monserrat Cantera ◽  
A Cortizo Garrido ◽  
Z Beunza Fabra ◽  
...  

Background An increasing body of evidence has revealed that SARS-CoV-2 infection in pregnant women could increase the risk of adverse maternal and fetal outcomes. Careful monitoring of pregnancies with COVID-19 and measures to prevent neonatal infection are warranted. Therefore, rapid antibody tests have been suggested as an efficient screening tool during pregnancy. Cases We analysed the clinical performance during pregnancy of a rapid, lateral-flow immunochromatographic assay for qualitative detection of SARS-CoV-2 IgG/IgM antibodies. We performed a universal screening including 169 patients during their last trimester of pregnancy. We present a series of 14 patients with positive SARS-CoV-2 immunochromatographic assay rapid test result. Immunochromatographic assay results were always confirmed by chemiluminescent microparticle immunoassays for quantitative detection of SARS-CoV-2 IgG and IgM+IgA antibodies as the gold standard. We observed a positive predictive value of 50% and a false positive rate of 50% in pregnant women, involving a significantly lower diagnostic performance than reported in non-pregnant patients. Discussion Our data suggest that although immunochromatographic assay rapid tests may be a fast and profitable screening tool for SARS-CoV-2 infection, they may have a high false positive rate and low positive predictive value in pregnant women. Therefore, immunochromatographic assay for qualitative detection of SARS-CoV-2 IgG/IgM antibodies must be verified by other test in pregnant patients.


Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 924 ◽  
Author(s):  
Mohammed Anouar Belaid ◽  
Maria Rodriguez-Prado ◽  
Eric Chevaux ◽  
Sergio Calsamiglia

Bulls (n = 770, average age = 127 days, SD = 53 days of age) were fitted with an activity monitoring device for three months to study if behavior could be used for early detection of diseases. The device measured the number of steps, lying time, lying bouts, and frequency and time of attendance at the feed bunk. All healthy bulls (n = 699) throughout the trial were used to describe the normal behavior. A match-pair test was used to assign healthy bulls for the comparison vs. sick bulls. The model was developed with 70% of the data, and the remaining 30% was used for the validation. Healthy bulls did 2422 ± 128 steps/day, had 28 ± 1 lying bouts/day, spent 889 ± 12 min/day lying, and attended the feed bunk 8 ± 0.2 times/d for a total of 95 ± 8 min/day. From the total of bulls enrolled in the study, 71 (9.2%) were diagnosed sick. Their activities changed at least 10 days before the clinical signs of disease. Bulls at risk of becoming sick were predicted 9 days before clinical signs with a sensitivity and specificity of 79% and 81%, respectively. The validation of the model resulted in a sensitivity, specificity, and accuracy of 92%, 42%, and 82 %, respectively, and a 50% false positive and 12.5% false negative rates. Results suggest that activity-monitoring systems may be useful in the early identification of sick bulls. However, the high false positive rate may require further refinement.


2002 ◽  
Vol 41 (01) ◽  
pp. 37-41 ◽  
Author(s):  
S. Shung-Shung ◽  
S. Yu-Chien ◽  
Y. Mei-Due ◽  
W. Hwei-Chung ◽  
A. Kao

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.


1993 ◽  
Vol 32 (02) ◽  
pp. 175-179 ◽  
Author(s):  
B. Brambati ◽  
T. Chard ◽  
J. G. Grudzinskas ◽  
M. C. M. Macintosh

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.


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