Faculty Opinions recommendation of Positive predictive value estimates for cell-free noninvasive prenatal screening from data of a large referral genetic diagnostic laboratory.

2019 ◽  
Author(s):  
Tomas Szemes
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Prenatal Screening ◽  
Diagnostic Laboratory ◽  
Noninvasive Prenatal Screening

scholarly journals Improving the Positive Predictive Value of Non-Invasive Prenatal Screening (NIPS)

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0167130 ◽  
Author(s):  
Charles M. Strom ◽  
Ben Anderson ◽  
David Tsao ◽  
Ke Zhang ◽  
Yan Liu ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Predictive Value ◽  
Prenatal Screening ◽  
Non Invasive

scholarly journals Efficiency of Non-invasive Prenatal Screening in Pregnant Women at Advanced Maternal Age

2020 ◽  
Author(s):  
Hui Zhu ◽  
Xiaoxiao Jin ◽  
Yuqing Xu ◽  
Weihua Zhang ◽  
Xiaodan Liu ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Predictive Value ◽  
Trisomy 21 ◽  
Maternal Age ◽  
Prenatal Screening ◽  
Screening Method ◽  
Advanced Maternal Age ◽  
Trisomy 13 ◽  
Noninvasive Prenatal Screening ◽  
Fetal Aneuploidies

Abstract Background: To evaluate the efficiency of noninvasive prenatal screening (NIPS) in the prenatal screening for fetal aneuploidies in pregnant women at advanced maternal age (AMA). Results: From February 1, 2015, to December 31, 2018, 29,443 pregnant women at AMA underwent NIPS and followed-up were recruited. Their detailed clinical data and follow-up outcomes were collected and analyzed. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of NIPS for detecting fetal trisomy 21 were 99.11%, 99.96%, 90.98%, and 100%, respectively. These same parameters for detecting fetal trisomy 18 were 100%, 99.94%, 67.92%, and 100%, respectively. Finally, these parameters for detecting trisomy 13 were 100%, 99.96%, 27.78%, and 100%, respectively. The prevalence of fetal trisomy 21 increased with maternal age. There were significant differences in the prevalence of fetal trisomy 21 among the groups I (35-37-year-old), II (38-40-year-old) and III (41-year-old and older) ( P <0.05). Conclusion: It is indicated that NIPS is an effective prenatal screening method in pregnant women at AMA. Keywords: Advanced maternal age, Trisomy, Noninvasive prenatal screening, Fetal aneuploidies , Prenatal screening method

Diagnosis of cerebral hemorrhage before the era of computed tomography

2013 ◽  
Vol 154 (44) ◽  
pp. 1743-1746
Author(s):  
Gergely Hofgárt ◽  
Rita Szepesi ◽  
Bertalan Vámosi ◽  
László Csiba
Keyword(s):  
Computed Tomography ◽  
Cerebrospinal Fluid ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Hemorrhagic Stroke ◽  
Cranial Computed Tomography ◽  
Cerebral Stroke ◽  
Daily Routine ◽  
Stroke Patients ◽  
The Difference

Introduction: During the past decades there has been a great progress in neuroimaging methods. Cranial computed tomography is part of the daily routine now and its use allows a fast diagnosis of parenchymal hemorrhage. However, before the availability of computed tomography the differentiation between ischemic and hemorrhagic stroke was based on patient history, physical examination, percutan angiography and cerebrospinal fluid sampling, and the clinical utility could be evaluated by autopsy of deceased patients. Aim: The authors explored the diagnostic performance of cerebrospinal fluid examination for the diagnosis of ischemic and hemorrhagic stroke. Method: Data of 200 deceased stroke patients were retrospectively evaluated. All patients had liquor sampling at admission and all of them had brain autopsy. Results: Bloody or yellowish cerebrospinal fluid at admission had a positive predictive value of 87.5% for hemorrhagic stroke confirmed by autopsy, while clear cerebrospinal fluid had positive predictive value of 90.7% for ischemic stroke. Patients who had clear liquor, but autopsy revealed hemorrhagic stroke had higher protein level in the cerebrospinal fluid, but the difference was not statistically significant (p = 0.09). Conclusions: The results confirm the importance of pathological evaluation of the brain in cases deceased from cerebral stroke. With this article the authors wanted to salute for those who contributed to the development of the Hungarian neuropathology. In this year we remember the 110th anniversary of the birth, and the 60th anniversary of the death of professor Kálmán Sántha. Professor László Molnár would be 90 years old in 2013. Orv. Hetil., 154 (44), 1743–1746.

VALUE OF COMBINATION OF HAP SCORE AND BISAP SCORE IN PREDICTING SEVERITY IN PATIENTS OF ACUTE PANCREATITIS

2019 ◽  
pp. 96-100
Author(s):  
Thi Ngoc Suong Le ◽  
Pham Chi Tran ◽  
Van Huy Tran
Keyword(s):  
Acute Pancreatitis ◽  
Positive Predictive Value ◽  
Roc Curve ◽  
Predictive Value ◽  
Prognostic Value ◽  
Acute Inflammation ◽  
Clinical Symptoms ◽  
Mortality Rates ◽  
Multiple Organ ◽  
Central Hospital

Acute pancreatitis (AP) is an acute inflammation of the pancreas, usually occurs suddenly with a variety of clinical symptoms, complications of multiple organ failure and high mortality rates. Objectives: To determine the value of combination of HAP score and BISAP score in predicting the severity of acute pancreatitis of the Atlanta 2012 Classification. Patients and Methods: 75 patients of acute pancreatitis hospitalized at Hue Central Hospital between March 2017 and July 2018; HAP and BISHAP score is calculated within the first 24 hours. The severity of AP was classified by the revised Atlanta criteria 2012. Results: When combining the HAP and BISAP scores in predicting the severity of acute pancreatitis, the area under the ROC curve was 0,923 with sensitivity value was 66.7%, specificity value was 97.1%; positive predictive value was 66.7%, negative predictive value was 97.1%. Conclusion: The combination of HAP and BISAP scores increased the sensitivity, predictive value, and prognostic value in predicting the severity of acute pancreatitis of the revised Atlanta 2012 classification in compare to each single scores. Key words: HAPscore, BiSAP score, acute pancreatitis, predicting severity

scholarly journals Accuracy of MSCT Coronary Angiography with 64 Row CT Scanner—Facing the Facts

2010 ◽  
Vol 4 ◽  
pp. CMC.S3864 ◽  
Author(s):  
M. Wehrschuetz ◽  
E. Wehrschuetz ◽  
H. Schuchlenz ◽  
G. Schaffler
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Coronary Angiography ◽  
Positive Predictive Value ◽  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Diagnostic Potential ◽  
Coronary Artery Stenoses ◽  
Artery Disease ◽  
Msct Angiography

Improvements in multislice computed tomography (MSCT) angiography of the coronary vessels have enabled the minimally invasive detection of coronary artery stenoses, while quantitative coronary angiography (QCA) is the accepted reference standard for evaluation thereof. Sixteen-slice MSCT showed promising diagnostic accuracy in detecting coronary artery stenoses haemodynamically and the subsequent introduction of 64-slice scanners promised excellent and fast results for coronary artery studies. This prompted us to evaluate the diagnostic accuracy, sensitivity, specificity, and the negative und positive predictive value of 64-slice MSCT in the detection of haemodynamically significant coronary artery stenoses. Thirty-seven consecutive subjects with suspected coronary artery disease were evaluated with MSCT angiography and the results compared with QCA. All vessels were considered for the assessment of significant coronary artery stenosis (diameter reduction ≥ 50%). Thirteen patients (35%) were identified as having significant coronary artery stenoses on QCA with 6.3% (35/555) affected segments. None of the coronary segments were excluded from analysis. Overall sensitivity for classifying stenoses of 64-slice MSCT was 69%, specificity was 92%, positive predictive value was 38% and negative predictive value was 98%. The interobserver variability for detection of significant lesions had a κ-value of 0.43. Sixty-four-slice MSCT offers the diagnostic potential to detect coronary artery disease, to quantify haemodynamically significant coronary artery stenoses and to avoid unnecessary invasive coronary artery examinations.

scholarly journals Added value of diffusion-weighted MRI in assessment of pleural lesions

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Youssriah Yahia Sabri ◽  
Ikram Hamed Mahmoud ◽  
Lamis Tarek El-Gendy ◽  
Mohamed Raafat Abd El-Mageed ◽  
Sally Fouad Tadros
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Diagnostic Value ◽  
Added Value ◽  
Adc Value ◽  
Pleural Diseases ◽  
Conventional Mri ◽  
Malignant Lesions

Abstract Background There are many causes of pleural disease including variable benign and malignant etiologies. DWI is a non-enhanced functional MRI technique that allows qualitative and quantitative characterization of tissues based on their water molecules diffusivity. The aim of this study was to evaluate the diagnostic value of DWI-MRI in detection and characterization of pleural diseases and its capability in differentiating benign from malignant pleural lesions. Results Conventional MRI was able to discriminate benign from malignant lesions by using morphological features (contour and thickness) with sensitivity 89.29%, specificity 76%, positive predictive value 89%, negative predictive value 76.92%, and accuracy 85.37%. ADC value as a quantitative parameter of DWI found that ADC values of malignant pleural diseases were significantly lower than that of benign lesions (P < 0.001). Hence, we discovered that using ADC mean value of 1.68 × 10-3 mm2/s as a cutoff value can differentiate malignant from benign pleural diseases with sensitivity 89.3%, specificity 100%, positive predictive value 100%, negative predictive value 81.2%, and accuracy 92.68% (P < 0.001). Conclusion Although DWI-MRI is unable to differentiate between malignant and benign pleural effusion, its combined morphological and functional information provide valid non-invasive method to accurately characterize pleural soft tissue diseases differentiating benign from malignant lesions with higher specificity and accuracy than conventional MRI.

scholarly journals A machine learning approach for predicting suicidal thoughts and behaviours among college students

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Melissa Macalli ◽  
Marie Navarro ◽  
Massimiliano Orri ◽  
Marie Tournier ◽  
Rodolphe Thiébaut ◽  
...  
Keyword(s):  
Mental Health ◽  
College Students ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Screening Tools ◽  
Receiver Operating Curve ◽  
Depression Symptoms ◽  
Suicidal Thoughts ◽  
One Year

AbstractSuicidal thoughts and behaviours are prevalent among college students. Yet little is known about screening tools to identify students at higher risk. We aimed to develop a risk algorithm to identify the main predictors of suicidal thoughts and behaviours among college students within one-year of baseline assessment. We used data collected in 2013–2019 from the French i-Share cohort, a longitudinal population-based study including 5066 volunteer students. To predict suicidal thoughts and behaviours at follow-up, we used random forests models with 70 potential predictors measured at baseline, including sociodemographic and familial characteristics, mental health and substance use. Model performance was measured using the area under the receiver operating curve (AUC), sensitivity, and positive predictive value. At follow-up, 17.4% of girls and 16.8% of boys reported suicidal thoughts and behaviours. The models achieved good predictive performance: AUC, 0.8; sensitivity, 79% for girls, 81% for boys; and positive predictive value, 40% for girls and 36% for boys. Among the 70 potential predictors, four showed the highest predictive power: 12-month suicidal thoughts, trait anxiety, depression symptoms, and self-esteem. We identified a parsimonious set of mental health indicators that accurately predicted one-year suicidal thoughts and behaviours in a community sample of college students.

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