The role of red cell distribution width in the differential diagnosis of iron deficiency anemia and non-transfusion dependent thalassemia patients

This study aims to find the cut-off value and diagnostic accuracy of the use of RDW as initial investigation in enabling the differentiation between IDA and NTDT patients. Patients with microcytic anemia were enrolled in the training set and used to plot a receiving operating characteristics (ROC) curve to obtain the cut-off value of RDW. A second set of patients were included in the validation set and used to analyze the diagnostic accuracy. We recruited 94 IDA and 64 NTDT patients into the training set. The area under the curve of the ROC in the training set was 0.803. The best cut-off value of RDW in the diagnosis of NTDT was 21.0% with a sensitivity and specificity of 81.3% and 55.3% respectively. In the validation set, there were 34 IDA and 58 NTDT patients using the cut-off value of >21.0% to validate. The sensitivity, specificity, positive predictive value and negative predictive value were 84.5%, 70.6%, 83.1% and 72.7% respectively. We can therefore conclude that RDW >21.0% is useful in differentiating between IDA and NTDT patients with high diagnostic accuracy

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

Otolaryngology ◽

10.1177/0194599820939071 ◽

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.

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New screening approach to detecting congenital syphilis in China: a retrospective cohort study

Archives of Disease in Childhood ◽

10.1136/archdischild-2020-320549 ◽

2020 ◽

pp. archdischild-2020-320549

Author(s):

Fang Hu ◽

Shuai-Jun Guo ◽

Jian-Jun Lu ◽

Ning-Xuan Hua ◽

Yan-Yan Song ◽

...

Keyword(s):

Predictive Value ◽

Congenital Syphilis ◽

Area Under The Curve ◽

Diagnostic Tools ◽

Operating Characteristics ◽

Loss To Follow Up ◽

Sensitivity Specificity ◽

Mother To Child ◽

Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

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Diagnosis of asthma in children: findings from the Swiss Paediatric Airway Cohort

European Respiratory Journal ◽

10.1183/13993003.00132-2020 ◽

2020 ◽

Vol 56 (5) ◽

pp. 2000132

Author(s):

Carmen C.M. de Jong ◽

Eva S.L. Pedersen ◽

Rebeca Mozun ◽

Dominik Müller-Suter ◽

Anja Jochmann ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Predictive Value ◽

Respiratory Symptoms ◽

Real Life ◽

Area Under The Curve ◽

Specific Ige ◽

Diagnostic Algorithms ◽

Asthma In Children ◽

Global Initiative ◽

Sensitivity Specificity

IntroductionDiagnosing asthma in children remains a challenge because respiratory symptoms are not specific and vary over time.AimIn a real-life observational study, we assessed the diagnostic accuracy of respiratory symptoms, objective tests and two paediatric diagnostic algorithms (proposed by the Global Initiative for Asthma (GINA) and the National Institute for Health and Care Excellence (NICE)) in the diagnosis of asthma in school-aged children.MethodsWe studied children aged 5–17 years who were referred consecutively to pulmonary outpatient clinics for evaluation of suspected asthma. Symptoms were assessed by parental questionnaire. The investigations included specific IgE measurement or skin prick tests, measurement of exhaled nitric oxide fraction (FeNO), spirometry, body plethysmography and bronchodilator reversibility (BDR). Asthma was diagnosed by paediatric pulmonologists based on all available data. We assessed diagnostic accuracy of symptoms, tests and diagnostic algorithms by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC).ResultsAmong 514 participants, 357 (70%) were diagnosed with asthma. The combined sensitivity and specificity was highest for any wheeze (sensitivity=75%, specificity=65%), dyspnoea (sensitivity=56%, specificity=76%) and wheeze triggered by colds (sensitivity=58%, specificity=78%) or by exercise (sensitivity=55%, specificity=74%). Of the diagnostic tests, the AUC was highest for specific total airway resistance (sRtot; AUC=0.73) and lowest for the residual volume (RV)/total lung capacity (TLC) ratio (AUC=0.56). The NICE algorithm had sensitivity=69% and specificity=67%, whereas the GINA algorithm had sensitivity=42% and specificity=90%.ConclusionThis study confirms the limited usefulness of single tests and existing algorithms for the diagnosis of asthma. It highlights the need for new and more appropriate evidence-based guidance.

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Gastric cancer detection using the serum pepsinogen test method

Tumori Journal ◽

10.1177/03008916211014961 ◽

2021 ◽

pp. 030089162110149

Author(s):

Dragan Trivanovic ◽

Stjepko Plestina ◽

Lorena Honovic ◽

Renata Dobrila-Dintinjana ◽

Jelena Vlasic Tanaskovic ◽

...

Keyword(s):

Gastric Cancer ◽

Early Detection ◽

Predictive Value ◽

Area Under The Curve ◽

Test Method ◽

Operating Characteristics ◽

Roc Curve Analysis ◽

Laboratory Assessment ◽

Pepsinogen I ◽

Sensitivity Specificity

Background: Gastric cancer (GC) is the eighth most common cause of cancer deaths in Croatia and one of the most common causes of cancer deaths worldwide. A reliable diagnostic tool for the early detection of GC is essential. Objective: We previously suggested a pepsinogen test method to reduce the mortality from GC by allowing early detection. Here, we report an updated analysis from a prospective single-center clinical study to evaluate the sensitivity and specificity of the pepsinogen test method and to determine whether this test can be used as a part of routine laboratory assessment of high-risk patients. Methods: We present mature data of the pepsinogen test method in the Croatian population after a median follow-up of 36 months. Statistical analyses were performed using a Mann-Whitney U test, multiple logistic regression, and receiver operating characteristics (ROC) to evaluate the predictive power of the assayed biomarkers. Results: Of the 116 patients, 25 patients had GC and 91 demonstrated a nonmalignant pathology based on tissue biopsy. Cutoff values were pepsinogen I ⩽70 and pepsinogen I/II ratio ⩽3.0. Using ROC curve analysis, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were determined to be 87.22%, 78.12%, 90.10%, 71.43%, and 92.86%, respectively, for the diagnosis of GC. The area under the curve was 0.700 (95% confidence interval 0.57–0.83). Conclusion: Pepsinogen tests are valuable for screening a population in need of further diagnosis and could help to avoid unnecessary invasive endoscopic procedures.

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Discriminant value of %microcytic cells/%hypochromic cells ratio in the differential diagnosis of microcytic anemia

Thalassemia Reports ◽

10.4081/thal.2020.8388 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Eloisa Urrechaga

Keyword(s):

Differential Diagnosis ◽

Area Under The Curve ◽

Microcytic Anemia ◽

Deficiency Anemia ◽

Youden Index ◽

Discriminant Functions ◽

False Negatives ◽

Mean Cell Volume ◽

Group 5 ◽

Validation Set

The Mindray 6800 Plus analyzer reports red cells (RBC) extended parameters, which represent the subsets of erythrocytes. We aimed to evaluate the reliability of RBC extended parameters in the differential diagnosis of microcytic anemia. The learning set comprised samples from 250 patients with microcytic anemia mean cell volume <80 fL. MH ratio (%microcytic cells/%hypochromic cells) and other discriminant functions were calculated. Optimal cut offs were established using receiver operator curves. This value was used in the validation set of 135 patients 50 carriers and 85 with mild iron deficiency anemia (IDA). Area under the curve 0.945 (95% confidence interval 0.890 to 0.977), cut off >10 rendered the best Youden index (0.798), sensitivity 93.2%, specificity 86.2%. In the validation set using MH ratio >10, 45 in 50 patients were correctly classified as carriers. All of 40 beta carriers were correctly classified, while the 5 false negatives resulted to be alpha carriers. In the IDA group 5 patients had MH ratio >10 and thus considered carriers, but all of them had Hyper <3%. The combination of MH ratio >10 and %Hyper <3% correctly classified 100% of IDA patients. An algorithm derived from RBC extended parameters provided by the Mindray 6800 Plus analyzer could be a useful tool in the differential diagnosis of microcytic anemia.

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The use of mean platelet volume for distinguishing the causes of thrombocytopenia in adult patients

Hematology Reports ◽

10.4081/hr.2019.7732 ◽

2019 ◽

Vol 11 (1) ◽

Cited By ~ 2

Author(s):

Lalita Norrasethada ◽

Wichan Khumpoo ◽

Ekarat Rattarittamrong ◽

Thanawat Rattanathammethee ◽

Chatree Chai-Adisaksopha ◽

...

Keyword(s):

Bone Marrow ◽

Mean Platelet Volume ◽

Bone Marrow Examination ◽

Primary Objective ◽

Operating Characteristics ◽

Training Set ◽

Platelet Volume ◽

Secondary Objective ◽

Validation Set ◽

Sensitivity Specificity

Establishment and analysis of mean platelet volume (MPV) may be helpful in the discrimination between underproduction or over-destruction of platelets as the causes of thrombocytopenia. The primary objective is to find the cut-off point of MPV for distinguishing causes of thrombocytopenia. The secondary objective is to validate the cut-off value of the MPV by using bone marrow examination. Thrombocytopenic patients were enrolled in a training set and a receiving operating characteristics (ROC) curve was plotted to obtain the cut-off value of MPV. A validation set of patients was recruited to validate the cut-off value. The training set included 240 patients. Half with with underproductive (n=120) and half with over-destructive thrombocytopenia (n=120). The best cut-off value of MPV was 8.8 fL. The validation set included 119 patients in total, again in 2 groups, those with underproductive (n=84) and those with overdestructive thrombocytopenia (n=35). The sensitivity, specificity, PPV and NPV when MPV ≥8.8 fL indicating over-destructive thrombocytopenia were 77%, 89%, 89% and 77%, respectively. MPV is useful for differentiating the cause of thrombocytopenia. The value of MPV ≥8.8 fL has acceptable sensitivity and specificity for diagnosis of over-destructive thrombocytopenia.

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Comparison of biparametric and multiparametric MRI in the diagnosis of prostate cancer

Cancer Imaging ◽

10.1186/s40644-019-0274-9 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 5

Author(s):

Lili Xu ◽

Gumuyang Zhang ◽

Bing Shi ◽

Yanhan Liu ◽

Tingting Zou ◽

...

Keyword(s):

Prostate Cancer ◽

Diagnostic Accuracy ◽

Predictive Value ◽

Area Under The Curve ◽

Roc Curves ◽

Multiparametric Mri ◽

Dce Mri ◽

Prostate Imaging ◽

The Difference ◽

Sensitivity Specificity

Abstract Purpose To compare the diagnostic accuracy of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for prostate cancer (PCa) and clinically significant prostate cancer (csPCa) and to explore the application value of dynamic contrast-enhanced (DCE) MRI in prostate imaging. Methods and materials This study retrospectively enrolled 235 patients with suspected PCa in our hospital from January 2016 to December 2017, and all lesions were histopathologically confirmed. The lesions were scored according to the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2). The bpMRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC]) and mpMRI (T2WI, DWI/ADC and DCE) scores were recorded to plot the receiver operating characteristic (ROC) curves. The area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for each method were calculated and compared. The patients were further stratified according to bpMRI scores (bpMRI ≥3, and bpMRI = 3, 4, 5) to analyse the difference in DCE MRI between PCa and non-PCa lesions (as well as between csPCa and non-csPCa). Results The AUC values for the bpMRI and mpMRI protocols for PCa were comparable (0.790 [0.732–0.840] and 0.791 [0.733–0.841], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for PCa were 76.2, 79.5, 72.6, 75.8, and 76.6%, respectively, and the values for mpMRI were 77.4, 84.4, 69.9, 75.2, and 80.6%, respectively. The AUC values for the bpMRI and mpMRI protocols for the diagnosis of csPCa were similar (0.781 [0.722–0.832] and 0.779 [0.721–0.831], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for csPCa were 74.0, 83.8, 66.9, 64.8, and 85.0%, respectively; and 73.6, 87.9, 63.2, 63.2, and 87.8%, respectively, for mpMRI. For patients with bpMRI scores ≥3, positive DCE results were more common in PCa and csPCa lesions (both P = 0.001). Further stratification analysis showed that for patients with a bpMRI score = 4, PCa and csPCa lesions were more likely to have positive DCE results (P = 0.003 and P < 0.001, respectively). Conclusion The diagnostic accuracy of bpMRI is comparable with that of mpMRI in the detection of PCa and the identification of csPCa. DCE MRI is helpful in further identifying PCa and csPCa lesions in patients with bpMRI ≥3, especially bpMRI = 4, which may be conducive to achieving a more accurate PCa risk stratification. Rather than omitting DCE, we think further comprehensive studies are required for prostate MRI.

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Influence of age on the diagnostic accuracy of soluble biomarkers for tuberculous pleural effusion: a post hoc analysis

10.21203/rs.3.rs-15542/v1 ◽

2020 ◽

Author(s):

Chun-Guo Jiang ◽

Wen Wang ◽

Qiong Zhou ◽

Xiu-Zhi Wu ◽

Xiao-Juan Wang ◽

...

Keyword(s):

Pleural Effusion ◽

Confidence Interval ◽

Diagnostic Accuracy ◽

Predictive Value ◽

Older Patients ◽

Young Patients ◽

Area Under The Curve ◽

Tuberculous Pleural Effusion ◽

Ifn Γ ◽

Sensitivity Specificity

Abstract Background: Accurately diagnosing pleural effusion is a frequent and significant problem in clinical practice. We sought to evaluate the influence of age on the diagnostic values of pleural adenosine deaminase (ADA), interferon-gamma (IFN-γ), and interleukin 27 (IL-27) for tuberculous pleural effusion (TPE). Methods: Two hundred seventy-four consecutive adult patients with pleural effusion were selected from Beijing (154 patients) and Wuhan (120 patients) during the same period and their pleural fluid concentrations of ADA, IFN-γ, and IL-27 were tested. Biomarker performance was analyzed by standard receiver operating characteristic (ROC) curves according to different ages. Results: Data from the Beijing cohort showed that ADA, IFN-γ, and IL-27 could all accurately diagnose TPE in young patients (≤ 40 years of age). With a cutoff of 21.4 U/L, the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ADA for diagnosing TPE were 1.000 (95% confidence interval: 0.884–1.000), 100.0%, 100.0%, 100.0, and 100.0, respectively. In older patients (> 40 years of age), IL-27 and IFN-γ were excellent biomarkers for discriminating TPE versus non-TPE cases. With a cutoff of 591.4 ng/L, the AUC, sensitivity, specificity, PPV, and NPV of IL-27 for diagnosing TPE were 0.976 (95% confidence interval: 0.932–0.995), 96.3%, 99.0%, 96.3, and 99.0, respectively. Similar diagnostic accuracy among the three pleural biomarkers was validated in the Wuhan cohort. Conclusions: Among young patients, ADA is reliable for diagnosing TPE. Conversely, in older patients, IL-27 is an excellent biomarker to differentiate TPE versus non-TPE cases.

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Acute Myocardial Infarction Detection Using Deep Learning-Enabled Electrocardiograms

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.654515 ◽

2021 ◽

Vol 8 ◽

Author(s):

Xiehui Chen ◽

Wenqin Guo ◽

Lingyue Zhao ◽

Weichao Huang ◽

Lili Wang ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Deep Learning ◽

Model Performance ◽

Area Under The Curve ◽

Training Set ◽

Residual Network ◽

Validation Set ◽

Sensitivity Specificity ◽

Testing Set

Background: Acute myocardial infarction (AMI) is associated with a poor prognosis. Therefore, accurate diagnosis and early intervention of the culprit lesion are of extreme importance. Therefore, we developed a neural network algorithm in this study to automatically diagnose AMI from 12-lead electrocardiograms (ECGs).Methods: We used the open-source PTB-XL database as the training and validation sets, with a 7:3 sample size ratio. Twenty-One thousand, eight hundred thirty-seven clinical 12-lead ECGs from the PTB-XL dataset were available for training and validation (15,285 were used in the training set and 6,552 in the validation set). Additionally, we randomly selected 205 ECGs from a dataset built by Chapman University, CA, USA and Shaoxing People's Hospital, China, as the testing set. We used a residual network for training and validation. The model performance was experimentally verified in terms of area under the curve (AUC), precision, sensitivity, specificity, and F1 score.Results: The AUC of the training, validation, and testing sets were 0.964 [95% confidence interval (CI): 0.961–0.966], 0.944 (95% CI: 0.939–0.949), and 0.977 (95% CI: 0.961–0.991), respectively. The precision, sensitivity, specificity, and F1 score of the deep learning model for AMI diagnosis from ECGs were 0.827, 0.824, 0.950, and 0.825, respectively, in the training set, 0.789, 0.818, 0.913, and 0.803, respectively, in the validation set, and 0.830, 0.951, 0.951, and 0.886, respectively, in the testing set. The AUC for automatic AMI location diagnosis of LMI, IMI, ASMI, AMI, ALMI were 0.969 (95% CI: 0.959–0.979), 0.973 (95% CI: 0.962–0.978), 0.987 (95% CI: 0.963–0.989), 0.961 (95% CI: 0.956–0.989), and 0.996 (95% CI: 0.957–0.997), respectively.Conclusions: The residual network-based algorithm can effectively automatically diagnose AMI and MI location from 12-lead ECGs.

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Noninvasive Evaluation of Coronary Artery Bypass Grafts with 16-Slice Multidetector Computed Tomography

The Heart Surgery Forum ◽

10.1532/hsf98.20111075 ◽

2012 ◽

Vol 15 (1) ◽

pp. 12 ◽

Cited By ~ 1

Author(s):

Levent Sahiner ◽

Ali Oto ◽

Kudret Aytemir ◽

Tuncay Hazirolan ◽

Musturay Karcaaltincaba ◽

...

Keyword(s):

Computed Tomography ◽

Coronary Artery ◽

Diagnostic Accuracy ◽

Multidetector Computed Tomography ◽

Coronary Artery Bypass ◽

Predictive Value ◽

Artery Bypass ◽

Time Interval ◽

Mdct Angiography ◽

Sensitivity Specificity

Background: The aim of this study was to investigate the diagnostic accuracy of 16-slice multislice, multidetector computed tomography (MDCT) angiography for the evaluation of grafts in patients with coronary artery bypass grafting (CABG).Methods: Fifty-eight consecutive patients with CABG who underwent both MDCT and conventional invasive coronary angiography were included. The median time interval between the 2 procedures was 10 days (range, 1-32 days). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MDCT for the detection of occluded grafts were calculated. The accuracy of MDCT angiography for detecting significant stenoses in patent grafts and the evaluability of proximal and distal anastomoses were also investigated.Results: Optimal diagnostic images could not be obtained for only 3 (2%) of 153 grafts. Evaluation of the remaining 150 grafts revealed values for sensitivity, specificity, PPV, NPV, and diagnostic accuracy of the MDCT angiography procedure for the diagnosis of occluded grafts of 87%, 97%, 94%, 93%, and 92%, respectively. All of the proximal anastomoses were optimally visualized. In 4 (8%) of 50 patent arterial grafts, however, the distal anastomotic region could not be evaluated because of motion and surgical-clip artifacts. The accuracy of MDCT angiography for the detection of significant stenotic lesions was relatively low (the sensitivity, specificity, PPV, and NPV were 67%, 98%, 50%, and 99%, respectively). The number of significant lesions was insufficient to reach a reliable conclusion, however.Conclusion: Our study showed that MDCT angiography with 16-slice systems has acceptable diagnostic performance for the evaluation of coronary artery bypass graft patency.

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