External Validation of Different Scoring Systems for Suspected Choledocholithiasis

2019 ◽  
Vol 36 (6) ◽  
pp. 530-538
Author(s):  
Nicolò Tamini ◽  
Davide Paolo Bernasconi ◽  
Luca Gianotti
Keyword(s):  
Operating Characteristic ◽  
Bile Duct Stone ◽  
Characteristic Curve ◽  
External Validation ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Youden Index ◽  
Predictive Values ◽  
Sensitivity Specificity ◽  
Symptoms And Signs

Aim of the Study: The diagnosis of choledocholithiasis is challenging. Previously published scoring systems designed to calculate the risk of choledocholithiasis were evaluated to appraise the diagnostic performance. Patients and Methods: Data of patients who were admitted between 2013 and 2015 with the following characteristics were retrieved: bile stone-related symptoms and signs, and indication to laparoscopic cholecystectomy. To validate and appraise the performance of the 6 scoring systems, the acknowledged domains of each metrics were applied to the present cohort. Sensitivity, specificity, positive, negative predictive, Youden index, and receiver operating characteristic curve with the area under the curve (AUC) values of the scores were calculated. Results: Two-hundred patients were analyzed. The highest sensitivity and specificity were obtained from the Menezes’ (96.6%) and Telem’s (99.3%) metrics respectively. The Telem’s and Menezes’ scores had the best positive (75.0%) and negative (96.4%) predictive values respectively. The best accuracy, as computed by the Youden index and AUC, was found for the Soltan’s scoring system (0.628 and 0.88, respectively). Conclusion: The available scoring systems are precise only in identifying patients with a negligible risk of common bile duct stone, but overall insufficiently accurate to suggest the routine use in clinical practice.

Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS

2020 ◽  
Vol 163 (6) ◽  
pp. 1156-1165
Author(s):  
Juan Xiao ◽  
Qiang Xiao ◽  
Wei Cong ◽  
Ting Li ◽  
Shouluan Ding ◽  
...  
Keyword(s):  
Thyroid Nodules ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Study ◽  
Diagnostic Efficiency ◽  
Training Set ◽  
Multivariable Logistic Regression Model ◽  
Predictive Values ◽  
Validation Set ◽  
Sensitivity Specificity

Objective To develop an easy-to-use nomogram for discrimination of malignant thyroid nodules and to compare diagnostic efficiency with the Kwak and American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS). Study Design Retrospective diagnostic study. Setting The Second Hospital of Shandong University. Subjects and Methods From March 2017 to April 2019, 792 patients with 1940 thyroid nodules were included into the training set; from May 2019 to December 2019, 174 patients with 389 nodules were included into the validation set. Multivariable logistic regression model was used to develop a nomogram for discriminating malignant nodules. To compare the diagnostic performance of the nomogram with the Kwak and ACR TI-RADS, the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values were calculated. Results The nomogram consisted of 7 factors: composition, orientation, echogenicity, border, margin, extrathyroidal extension, and calcification. In the training set, for all nodules, the area under the curve (AUC) for the nomogram was 0.844, which was higher than the Kwak TI-RADS (0.826, P = .008) and the ACR TI-RADS (0.810, P < .001). For the 822 nodules >1 cm, the AUC of the nomogram was 0.891, which was higher than the Kwak TI-RADS (0.852, P < .001) and the ACR TI-RADS (0.853, P < .001). In the validation set, the AUC of the nomogram was also higher than the Kwak and ACR TI-RADS ( P < .05), each in the whole series and separately for nodules >1 or ≤1 cm. Conclusions When compared with the Kwak and ACR TI-RADS, the nomogram had a better performance in discriminating malignant thyroid nodules.

scholarly journals Value and Diagnostic Efficacy of Fetal Morphology Assessment Using Ultrasound in A Poor-Resource Setting

Diagnostics ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 109 ◽  
Author(s):  
Ukweh ◽  
Ugbem ◽  
Okeke ◽  
Ekpo
Keyword(s):  
Predictive Value ◽  
Performance Metrics ◽  
Area Under The Curve ◽  
Youden Index ◽  
Likelihood Ratios ◽  
Diagnostic Efficacy ◽  
Predictive Values ◽  
Resource Setting ◽  
Post Test ◽  
Sensitivity Specificity

Background: Ultrasound is operator-dependent, and its value and efficacy in fetal morphology assessment in a low-resource setting is poorly understood. We assessed the value and efficacy of fetal morphology ultrasound assessment in a Nigerian setting. Materials and Methods: We surveyed fetal morphology ultrasound performed across five facilities and followed-up each fetus to ascertain the outcome. Fetuses were surveyed in the second trimester (18th–22nd weeks) using the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guideline. Clinical and surgical reports were used as references to assess the diagnostic efficacy of ultrasound in livebirths, and autopsy reports to confirm anomalies in terminated pregnancies, spontaneous abortions, intrauterine fetal deaths, and still births. We calculated sensitivity, specificity, positive and negative predictive values, Area under the curve (AUC), Youden index, likelihood ratios, and post-test probabilities. Results: In total, 6520 fetuses of women aged 15–46 years (mean = 31.7 years) were surveyed. The overall sensitivity, specificity, and AUC were 77.1 (95% CI: 68–84.6), 99.5 (95% CI: 99.3–99.7), and 88.3 (95% CI: 83.7–92.2), respectively. Other performance metrics were: positive predictive value, 72.4 (95% CI: 64.7–79.0), negative predictive value, 99.6 (95% CI: 99.5–99.7), and Youden index (77.1%). Abnormality prevalence was 1.67% (95% CI: 1.37–2.01), and the positive and negative likelihood ratios were 254 (95% CI: 107.7–221.4) and 0.23 (95% CI: 0.16–0.33), respectively. The post-test probability for positive test was 72% (95% CI: 65–79). Conclusion: Fetal morphology assessment is valuable in a poor economics setting, however, the variation in the diagnostic efficacy across facilities and the limitations associated with the detection of circulatory system anomalies need to be addressed.

scholarly journals Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis

2020 ◽  
Author(s):  
Michael Michail ◽  
Abdul-Rahman Ihdayhid ◽  
Andrea Comella ◽  
Udit Thakur ◽  
James D. Cameron ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Diagnostic Accuracy ◽  
Operating Characteristic ◽  
Severe Aortic Stenosis ◽  
Characteristic Curve ◽  
Fractional Flow ◽  
Predictive Values ◽  
Flow Reserve ◽  
Artery Disease ◽  
Sensitivity Specificity

Background: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. Methods: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). Results: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R =0.64, P <0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72–0.93, P <0.0001), which was higher than that of CTA and quantitative coronary angiography ( P =0.01 and P <0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67–0.95, P <0.0001). Conclusions: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement.

Abstract 18: External Validation of the RACE Scale After Its Implementation in the Stroke Code Protocol in Catalonia

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Natalia Perez de la Ossa ◽  
Sonia Abilleira ◽  
Marc Ribó ◽  
Millan Monica ◽  
Pere Cardona ◽  
...  
Keyword(s):  
Validation Study ◽  
External Validation ◽  
Area Under The Curve ◽  
Final Diagnosis ◽  
Youden Index ◽  
Vessel Occlusion ◽  
Basilar Occlusion ◽  
Race 2 ◽  
Ischemic Attack ◽  
Sensitivity Specificity

Introduction: We aimed to revalidate the RACE scale as a pre-hospital tool to identify patients with large vessel occlusion (LVO) and patients receiving endovascular treatment (EVT) after its implementation in the Stroke Code protocol of Catalonia (7.5 M inhabitants). Methods: We used data from the CICAT registry (Feb to Jun 2016), a government-mandated, prospective, hospital-based dataset that includes all Stroke Code activations. CICAT is linked to the EMS database to capture information about the pre-hospital care. RACE score, pre-hospital and in-hospital delays, final diagnostic, presence of LVO (TICA, MCA M1 or M2, tandem or basilar occlusion) and revascularization treatment were registered. Sensitivity, specificity and area under the curve (AUC) to identify LVO and patients receiving EVT were calculated for the pre-established cut off RACE≥5. Results: From the 1600 stroke code activations we included in the study the 962 patients in which the RACE scale was available (60%). The RACE scale showed a strong correlation with the NIHSS evaluated at hospital arrival (r=0.74, p<0.001). Distribution of final diagnosis and median RACE scores were: ischemic with LVO (22.1%), RACE 7 [5-8], ischemic without LVO (29.3%), RACE 3 [2-5], hemorrhagic(17.8%), RACE 6 [4-7], mimic(21.0%), RACE 2 [1-4] and transient ischemic attack(9.7%), RACE 3 [1-5]. A RACE cut-off score ≥5 showed sensitivity 0.80 and specificity 0.63 to detect LVO (AUC 0.78, Youden index 0.45), similar to results obtained in the validation study. In patients with RACE≥5 the rates of LVO (42% Vs 9%;p<0.001) and EVT (21% Vs 6%;p<0.001) were significantly higher than in patients with RACE<5. Conclusion: This large validation study performed after implementation of the RACE scale in the real clinical practice in the region of Catalonia confirms RACE accuracy to identify candidates to EVT. A RACE score ≥5 detected 77% of patients that finally underwent EVT confirming the scale as a valuable tool at the prehospital level.

Erythrocyte sedimentation rate and C-reactive protein compared in the elderly.

1989 ◽  
Vol 35 (3) ◽  
pp. 466-468 ◽  
Author(s):  
P R Katz ◽  
S I Gutman ◽  
G Richman ◽  
J Karuza ◽  
W R Bartholomew ◽  
...  
Keyword(s):  
Erythrocyte Sedimentation Rate ◽  
Sedimentation Rate ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
The Elderly ◽  
C Reactive Protein ◽  
Predictive Values ◽  
Reactive Protein ◽  
Erythrocyte Sedimentation ◽  
Sensitivity Specificity

Abstract The erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) concentrations were studied in 101 elderly individuals (mean age 72 y) to determine their utility as diagnostic aids in subjects with underlying infection/inflammation. Whereas ESR and CRP were both significantly increased in patients with infection or inflammation, or both, analysis of variance indicated that those subjects still alive six months later had significantly lower ESR values. Analysis of sensitivity, specificity, and positive predictive values indicated that neither test satisfactorily discriminated between patients with and those without ongoing active or chronic disease. Receiver-operating characteristic curve analysis confirmed the low true-positive/false-positive ratios of both ESR and CRP. In the elderly, neither CRP nor ESR has distinct advantages over the other, and both tests evidently have limited utility.

Abstract TP13: External Validation of Stroke Prognostication Scales - A Retrospective Cohort Study

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Nauman Jahangir ◽  
Nicholas Lanzotti ◽  
Kyle Gollon ◽  
Mehwish Farooqi ◽  
Michael Buhnerkempe ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Characteristic Curve ◽  
External Validation ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Scoring Systems ◽  
Predictive Performance ◽  
Discriminatory Ability ◽  
Single Center Study

Introduction: In recent years, many scoring models have been proposed to predict clinical outcomes after acute ischemic stroke. Aim of our study was to perform a comparative analysis of these scoring systems to assess predictive reliability. Method: This retrospective single center study included 166 community-based patients presenting with an acute ischemic stroke between 2015 and 2018 who had undergone mechanical thrombectomy with or without IV r-tPA administration prior to the procedure. Patients with unknown 90 day Modified Ranking Scale (mRS) were excluded from the study. We included SPAN-100, THRIVE, HIAT2, iScore , TPI, DRAGON, ASTRAL and HAT predictive models to our study. To predict MRS at 90 days, we first dichotomize mRS into two groups: scores of 0 and 1 and scores 2 and above. We then used logistic regression to find the association between a stroke score and the probability of having a 90-day mRS of 2 or above. Separate univariate logistic regressions were fit for each stroke score. We assessed the ability of each stroke score to predict 90-day mRS using the area-under-the-curve (AUC) of the receiver operating characteristic curve (ROC - plot of sensitivity against 1-specificity). AUC values range from 0.5 to 1 with values above 0.7 showing good discriminatory ability. Results: SPAN-100, HIAT2, iScore, and ASTRAL scores have similar predictive ability with AUC values over 0.7 (Table 1). The ASTRAL score had the highest predictive ability with a score above 31.5 indicating a high likelihood of a 90-day MRS ≥ 2 (Table 1). The TPI, DRAGON, and HAT scores all had AUCs below 0.65 indicating poor predictive performance in our data. Conclusion: The SPAN-100, HIAT2, iScore, and ASTRAL scores reliably predicts 90-day mRS of 2 or greater in patients with acute ischemic stroke.

scholarly journals Urinary MicroRNAs as Potential Markers for Non-Invasive Diagnosis of Bladder Cancer

2020 ◽  
Vol 21 (11) ◽  
pp. 3814 ◽  
Author(s):  
Kati Erdmann ◽  
Karsten Salomo ◽  
Anna Klimova ◽  
Ulrike Heberling ◽  
Andrea Lohse-Fischer ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
High Specificity ◽  
Specific Expression ◽  
Predictive Values ◽  
Non Invasive ◽  
Diagnostic Potential ◽  
Urinary Levels ◽  
Sensitivity Specificity

Currently, voided urine cytology (VUC) serves as the gold standard for the detection of bladder cancer (BCa) in urine. Despite its high specificity, VUC has shortcomings in terms of sensitivity. Therefore, alternative biomarkers are being searched, which might overcome these disadvantages as a useful adjunct to VUC. The aim of this study was to evaluate the diagnostic potential of the urinary levels of selected microRNAs (miRs), which might represent such alternative biomarkers due to their BCa-specific expression. Expression levels of nine BCa-associated microRNAs (miR-21, -96, -125b, -126, -145, -183, -205, -210, -221) were assessed by quantitative PCR in urine sediments from 104 patients with primary BCa and 46 control subjects. Receiver operating characteristic (ROC) curve analyses revealed a diagnostic potential for miR-96, -125b, -126, -145, -183, and -221 with area under the curve (AUC) values between 0.605 and 0.772. The combination of the four best candidates resulted in sensitivity, specificity, positive and negative predictive values (NPV), and accuracy of 73.1%, 95.7%, 97.4%, 61.1%, and 80.0%, respectively. Combined with VUC, sensitivity and NPV could be increased by nearly 8%, each surpassing the performance of VUC alone. The present findings suggested a diagnostic potential of miR-125b, -145, -183, and -221 in combination with VUC for non-invasive detection of BCa in urine.

scholarly journals Evaluation of the Mini Nutritional Assessment in the elderly, Tehran, Iran

2010 ◽  
Vol 13 (9) ◽  
pp. 1373-1379 ◽  
Author(s):  
Bahareh Amirkalali ◽  
Farshad Sharifi ◽  
Hossein Fakhrzadeh ◽  
Mojde Mirarefin ◽  
Maryam Ghaderpanahi ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Serum Albumin ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Nutritional Assessment ◽  
Characteristic Curve ◽  
Mini Nutritional Assessment ◽  
Youden Index ◽  
Predictive Values ◽  
Sensitivity Specificity

AbstractObjectiveTo determine whether the Mini Nutritional Assessment (MNA) can screen and diagnose for malnutrition in the Iranian elderly.DesignThe MNA was administered to all volunteers. Each patient underwent anthropometric and serum albumin measurements. Reliability, validity, sensitivity, specificity, positive- and negative-predictive values were estimated. To identify optimal threshold values for predicting malnutrition, receiver-operating characteristic curve analysis was performed for MNA scores.SettingKahrizak Charity Foundation (Tehran, Iran).SubjectsTwo hundred and twenty-one consecutive elderly patients entered into the cross-sectional study. Amputees and patients with liver or renal disorders, oedema or any end-stage diseases were excluded.ResultsAccording to MNA score, 3·2 % were malnourished, 43·4 % were at risk of malnutrition and 53·4 % were well nourished. The proportions in these categories according to ideal body weight and serum albumin were 2·3 %, 17·1 % and 80·6 %, respectively. Cronbach’s α coefficient (reliability) was 0·61. The correlations between total MNA score, anthropometric values and serum albumin (criterion-related validity) were all significant. There were significant differences in total MNA score between two BMI groups but not between two categories according to serum albumin and skin ulcers (construct validity). The sensitivity and specificity of the MNA according to its established cut-off points were 82 % and 63 %, respectively. Positive-predictive value was 35 % and negative-predictive value was 93 %. By using the best cut-off point (MNA score of 22 according to Youden index), the sensitivity, specificity, positive-predictive value and negative-predictive value were 88 %, 62 %, 57 % and 89 %, respectively.ConclusionsThe MNA with its established cut-off points may not be a good fit for Asian populations, including Iranian elderly.

Three plasma-based microRNAs as potent diagnostic biomarkers for endometrial cancer

2021 ◽  
pp. 1-12
Author(s):  
Xingchen Fan ◽  
Minmin Cao ◽  
Cheng Liu ◽  
Cheng Zhang ◽  
Chunyu Li ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
External Validation ◽  
Diagnostic Value ◽  
Diagnostic Biomarkers ◽  
Non Invasive ◽  
Polymerase Chain ◽  
Public Datasets ◽  
Plasma Mirnas

BACKGROUND: MicroRNAs (miRNAs), with noticeable stability and unique expression pattern in plasma of patients with various diseases, are powerful non-invasive biomarkers for cancer detection including endometrial cancer (EC). OBJECTIVE: The objective of this study was to identify promising miRNA biomarkers in plasma to assist the clinical screening of EC. METHODS: A total of 93 EC and 79 normal control (NC) plasma samples were analyzed using Quantitative Real-time Polymerase Chain Reaction (qRT-PCR) in this four-stage experiment. The receiver operating characteristic curve (ROC) analysis was conducted to evaluate the diagnostic value. Additionally, the expression features of the identified miRNAs were further explored in tissues and plasma exosomes samples. RESULTS: The expression of miR-142-3p, miR-146a-5p, and miR-151a-5p was significantly overexpressed in the plasma of EC patients compared with NCs. Areas under the ROC curve of the 3-miRNA signature were 0.729, 0.751, and 0.789 for the training, testing, and external validation phases, respectively. The diagnostic performance of the identified signature proved to be stable in the three public datasets and superior to the other miRNA biomarkers in EC diagnosis. Moreover, the expression of miR-151a-5p was significantly elevated in EC plasma exosomes. CONCLUSIONS: A signature consisting of 3 plasma miRNAs was identified and showed potential for the non-invasive diagnosis of EC.

scholarly journals Development and Verification of a Deep Learning Algorithm to Evaluate Small-Bowel Preparation Quality

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1127
Author(s):  
Ji Hyung Nam ◽  
Dong Jun Oh ◽  
Sumin Lee ◽  
Hyun Joo Song ◽  
Yun Jeong Lim
Keyword(s):  
Deep Learning ◽  
Small Bowel ◽  
Scoring System ◽  
Operating Characteristic ◽  
Clinical Evidence ◽  
Learning Algorithm ◽  
Characteristic Curve ◽  
External Validation ◽  
Test Results ◽  
Deep Learning Algorithm

Capsule endoscopy (CE) quality control requires an objective scoring system to evaluate the preparation of the small bowel (SB). We propose a deep learning algorithm to calculate SB cleansing scores and verify the algorithm’s performance. A 5-point scoring system based on clarity of mucosal visualization was used to develop the deep learning algorithm (400,000 frames; 280,000 for training and 120,000 for testing). External validation was performed using additional CE cases (n = 50), and average cleansing scores (1.0 to 5.0) calculated using the algorithm were compared to clinical grades (A to C) assigned by clinicians. Test results obtained using 120,000 frames exhibited 93% accuracy. The separate CE case exhibited substantial agreement between the deep learning algorithm scores and clinicians’ assessments (Cohen’s kappa: 0.672). In the external validation, the cleansing score decreased with worsening clinical grade (scores of 3.9, 3.2, and 2.5 for grades A, B, and C, respectively, p < 0.001). Receiver operating characteristic curve analysis revealed that a cleansing score cut-off of 2.95 indicated clinically adequate preparation. This algorithm provides an objective and automated cleansing score for evaluating SB preparation for CE. The results of this study will serve as clinical evidence supporting the practical use of deep learning algorithms for evaluating SB preparation quality.

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