The Performance of a Calcaneal Quantitative Ultrasound Device, CM-200, in Stratifying Osteoporosis Risk among Malaysian Population Aged 40 Years and Above

Background: Calcaneal quantitative ultrasound (QUS) is widely used in osteoporosis screening, but the cut-off values for risk stratification remain unclear. This study validates the performance of a calcaneal QUS device (CM-200) using dual-energy X-ray absorptiometry (DXA) as the reference and establishes a new set of cut-off values for CM-200 in identifying subjects with osteoporosis. Methods: The bone health status of Malaysians aged ≥40 years was assessed using CM-200 and DXA. Sensitivity, specificity, area under the curve (AUC) and the optimal cut-off values for risk stratification of CM-200 were determined using receiver operating characteristic (ROC) curves and Youden’s index (J). Results: From the data of 786 subjects, CM-200 (QUS T-score <−1) showed a sensitivity of 82.1% (95% CI: 77.9–85.7%), specificity of 51.5% (95% CI: 46.5–56.6%) and AUC of 0.668 (95% CI: 0.630–0.706) in identifying subjects with suboptimal bone health (DXA T-score <−1) (p < 0.001). At QUS T-score ≤−2.5, CM-200 was ineffective in identifying subjects with osteoporosis (DXA T-score ≤−2.5) (sensitivity 14.4% (95% CI: 8.1–23.0%); specificity 96.1% (95% CI: 94.4–97.4%); AUC 0.553 (95% CI: 0.488–0.617); p > 0.05). Modified cut-off values for the QUS T-score improved the performance of CM-200 in identifying subjects with osteopenia (sensitivity 67.7% (95% CI: 62.8–72.3%); specificity 72.8% (95% CI: 68.1–77.2%); J = 0.405; AUC 0.702 (95% CI: 0.666–0.739); p < 0.001) and osteoporosis (sensitivity 79.4% (95% CI: 70.0–86.9%); specificity 61.8% (95% CI: 58.1–65.5%); J = 0.412; AUC 0.706 (95% CI: 0.654–0.758); p < 0.001). Conclusion: The modified cut-off values significantly improved the performance of CM-200 in identifying individuals with osteoporosis. Since these values are device-specific, optimization is necessary for accurate detection of individuals at risk for osteoporosis using QUS.

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Clot imaging characteristics predict first pass effect of aspiration—first approach to thrombectomy

Interventional Neuroradiology ◽

10.1177/15910199211019174 ◽

2021 ◽

pp. 159101992110191

Author(s):

Muhammad Waqas ◽

Weizhe Li ◽

Tatsat R Patel ◽

Felix Chin ◽

Vincent M Tutino ◽

...

Keyword(s):

Internal Carotid ◽

Validation Cohort ◽

Area Under The Curve ◽

Large Vessel Occlusion ◽

Vessel Occlusion ◽

First Pass Effect ◽

Imaging Characteristics ◽

First Pass ◽

Sensitivity Specificity ◽

Youden’S Index

Background The value of clot imaging in patients with emergent large vessel occlusion (ELVO) treated with thrombectomy is unknown. Methods We performed retrospective analysis of clot imaging (clot density, perviousness, length, diameter, distance to the internal carotid artery (ICA) terminus and angle of interaction (AOI) between clot and the aspiration catheter) of consecutive cases of middle cerebral artery (MCA) occlusion and its association with first pass effect (FPE, TICI 2c-3 after a first attempt). Results Patients ( n = 90 total) with FPE had shorter clot length (9.9 ± 4.5 mm vs. 11.7 ± 4.6 mm, P = 0.07), shorter distance from ICA terminus (11.0 ± 7.1 mm vs. 14.7 ± 9.8 mm, P = 0.048), higher perviousness (39.39 ± 29.5 vs 25.43 ± 17.6, P = 0.006) and larger AOI (153.6 ± 17.6 vs 140.3 ± 23.5, P = 0.004) compared to no-FPE patients. In multivariate analysis, distance from ICA terminus to clot ≤13.5 mm (odds ratio (OR) 11.05, 95% confidence interval (CI) 2.65–46.15, P = 0.001), clot length ≤9.9 mm (OR 7.34; 95% CI 1.8–29.96, P = 0.005), perviousness ≥ 19.9 (OR 2.54, 95% CI 0.84–7.6, P = 0.09) and AOI ≥ 137°^ (OR 6.8, 95% CI 1.55–29.8, P = 0.011) were independent predictors of FPE. The optimal cut off derived using Youden’s index was 6.5. The area under the curve of a score predictive of FPE success was 0.816 (0.728–0.904, P < 0.001). In a validation cohort ( n = 30), sensitivity, specificity, positive and negative predictive value of a score of 6–10 were 72.7%, 73.6%, 61.5% and 82.3%. Conclusions Clot imaging predicts the likelihood of achieving FPE in patients with MCA ELVO treated with the aspiration-first approach.

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Identification of the most specific markers to differentiate primary pulmonary carcinoma from metastatic gastrointestinal carcinoma to the lung

Diagnostic Pathology ◽

10.1186/s13000-021-01184-2 ◽

2022 ◽

Vol 17 (1) ◽

Author(s):

Bachar Alabdullah ◽

Amir Hadji-Ashrafy

Keyword(s):

Gastrointestinal Tract ◽

Predictive Value ◽

Regression Models ◽

Area Under The Curve ◽

Roc Curves ◽

Multivariate Models ◽

Gastrointestinal Carcinoma ◽

Lung Tumours ◽

Napsin A ◽

Sensitivity Specificity

Abstract Background A number of biomarkers have the potential of differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract, however, a standardised panel for that purpose does not exist yet. We aimed to identify the smallest panel that is most sensitive and specific at differentiating between primary lung tumours and secondary lung tumours from the gastrointestinal tract. Methods A total of 170 samples were collected, including 140 primary and 30 non-primary lung tumours and staining for CK7, Napsin-A, TTF1, CK20, CDX2, and SATB2 was performed via tissue microarray. The data was then analysed using univariate regression models and a combination of multivariate regression models and Receiver Operating Characteristic (ROC) curves. Results Univariate regression models confirmed the 6 biomarkers’ ability to independently predict the primary outcome (p < 0.001). Multivariate models of 2-biomarker combinations identified 11 combinations with statistically significant odds ratios (ORs) (p < 0.05), of which TTF1/CDX2 had the highest area under the curve (AUC) (0.983, 0.960–1.000 95% CI). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 75.7, 100, 100, and 37.5% respectively. Multivariate models of 3-biomarker combinations identified 4 combinations with statistically significant ORs (p < 0.05), of which CK7/CK20/SATB2 had the highest AUC (0.965, 0.930–1.000 95% CI). The sensitivity, specificity, PPV, and NPV were 85.1, 100, 100, and 41.7% respectively. Multivariate models of 4-biomarker combinations did not identify any combinations with statistically significant ORs (p < 0.05). Conclusions The analysis identified the combination of CK7/CK20/SATB2 to be the smallest panel with the highest sensitivity (85.1%) and specificity (100%) for predicting tumour origin with an ROC AUC of 0.965 (p < 0.001; SE: 0.018, 0.930–1.000 95% CI).

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Usefulness of calcaneal quantitative ultrasound stiffness for the evaluation of bone health in HIV-1-infected subjects: comparison with dual X-ray absorptiometry

HIV/AIDS - Research and Palliative Care ◽

10.2147/hiv.s99904 ◽

2016 ◽

pp. 109

Author(s):

Ivano Mezzaroma ◽

Alessandra Fantauzzi ◽

Fabrizio Ceci ◽

Francesco Cacciatore ◽

Vincenzo Vullo ◽

...

Keyword(s):

Quantitative Ultrasound ◽

Bone Health ◽

X Ray ◽

Calcaneal Quantitative Ultrasound ◽

Hiv 1

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Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs

Dentomaxillofacial Radiology ◽

10.1259/dmfr.20200513 ◽

2021 ◽

pp. 20200513

Author(s):

Su-Jin Jeon ◽

Jong-Pil Yun ◽

Han-Gyeol Yeom ◽

Woo-Sang Shin ◽

Jong-Hyun Lee ◽

...

Keyword(s):

Deep Learning ◽

Cone Beam Ct ◽

Area Under The Curve ◽

Roc Curves ◽

Learning System ◽

Operating Characteristics ◽

Panoramic Radiographs ◽

Test Sets ◽

Sensitivity Specificity ◽

Deep Learning Model

Objective: The aim of this study was to evaluate the use of a convolutional neural network (CNN) system for predicting C-shaped canals in mandibular second molars on panoramic radiographs. Methods: Panoramic and cone beam CT (CBCT) images obtained from June 2018 to May 2020 were screened and 1020 patients were selected. Our dataset of 2040 sound mandibular second molars comprised 887 C-shaped canals and 1153 non-C-shaped canals. To confirm the presence of a C-shaped canal, CBCT images were analyzed by a radiologist and set as the gold standard. A CNN-based deep-learning model for predicting C-shaped canals was built using Xception. The training and test sets were set to 80 to 20%, respectively. Diagnostic performance was evaluated using accuracy, sensitivity, specificity, and precision. Receiver-operating characteristics (ROC) curves were drawn, and the area under the curve (AUC) values were calculated. Further, gradient-weighted class activation maps (Grad-CAM) were generated to localize the anatomy that contributed to the predictions. Results: The accuracy, sensitivity, specificity, and precision of the CNN model were 95.1, 92.7, 97.0, and 95.9%, respectively. Grad-CAM analysis showed that the CNN model mainly identified root canal shapes converging into the apex to predict the C-shaped canals, while the root furcation was predominantly used for predicting the non-C-shaped canals. Conclusions: The deep-learning system had significant accuracy in predicting C-shaped canals of mandibular second molars on panoramic radiographs.

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Circular RNA FUNDC1 improves prediction of stroke associated infection in acute ischemic stroke patients with high risk

Bioscience Reports ◽

10.1042/bsr20200902 ◽

2020 ◽

Vol 40 (6) ◽

Author(s):

Lei Zuo ◽

Cai Li ◽

Juan Zu ◽

Honghong Yao ◽

Fuling Yan

Keyword(s):

Ischemic Stroke ◽

High Risk ◽

Acute Ischemic Stroke ◽

Risk Model ◽

Area Under The Curve ◽

Preventive Treatment ◽

Roc Curves ◽

Circular Rna ◽

Diagnosis And Prognosis ◽

Sensitivity Specificity

Abstract Identifying those patients who were at high risk of stroke associated infection (SAI) for preventive antibiotic therapy was imperative for patients’ benefits, thus improving prediction of SAI was critical for all acute ischemic stroke (AIS) patients. Circular RNA FUNDC1 (circFUNDC1) has been reported to be the diagnosis and prognosis biomarker of AIS. Therefore, the present study aimed to figure out whether circFUNDC1 could be the potential predictor of SAI that could help to guide preventive treatment. In total, 68 patients were included in the study, 26 of which had infection and 42 without. Copy number of circFUNDC1 in plasma were quantified by quantitative real-time polymerase chain reaction (qPCR). Platelet spike-in experiment and correlation analysis were conducted to explore possible origins of circFUNDC1 in plasma. A significantly elevated level of circFUNDC1 was found in SAI patients compared with not infected AIS patients (P=0.0258). Receiver operating characteristic (ROC) curves demonstrated the prediction significance of circFUNDC1, with the area under the curve (AUC) at 0.6612 and sensitivity, specificity at 69.23%, 61.90% respectively in predicting SAI. Then, when adding circFUNDC1 in the risk model, the AUC increased from 0.7971 in model A to 0.8038 in model B. Additionally, positive correlation was observed between circFUNDC1 level and neutrophils counts. WBC and neutrophil ratios were significantly elevated in SAI patients compared with non-SAI patients. Therefore, circFUNDC1 could be used to construct a risk model for the prediction of SAI that is beneficial for AIS patients’ preventive treatment.

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Recalibrating the Non-Communicable Diseases Risk Prediction Tools for the Rural Population of Western India

10.21203/rs.3.rs-657433/v1 ◽

2021 ◽

Author(s):

Manoj Kumar Gupta ◽

Pankaja Raghav ◽

Tooba Tanvir ◽

Vaishali Gautam ◽

Amit Mehto ◽

...

Keyword(s):

Risk Prediction ◽

Predictive Value ◽

Area Under The Curve ◽

Vascular Diseases ◽

High Sensitivity ◽

Roc Curves ◽

Risk Scores ◽

Western India ◽

Anthropometric Parameters ◽

Youden’S Index

Abstract Background: The present study was conducted to recalibrate the effectiveness of Indian Diabetes Risk Scores (IDRS) and Community-Based Assessment Checklist (CBAC) by opportunistically screening for Diabetes Mellitus (DM) and Hypertension (HT) among the patients attending health centres, and to estimate the risk of fatal and non-fatal Cardio-Vascular Diseases (CVDs) using WHO/ISH chartMethods: All the people of age ≥30 years attending the health centers were screened for DM and HT. Weight, height, and waist and hip circumferences were measured and BMI and Waist Hip Ratio (WHR) were calculated. Risk categorization of all participants was done using IDRS, CBAC, and WHO/ISH risk prediction charts. Individuals diagnosed with DM or HT were started on treatment. The data was recorded using Epicollect5 and was analyzed using SPSS v.23 and MedCalc v.19.8. ROC curves were plotted for DM and HT with the IDRS, CBAC score and anthropometric parameters. Sensitivity (SN), specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV), Accuracy and Youden’s index were calculated for different cut-offs of IDRS and CBAC scores.Results: A total of 942 participants were included for the screening, out of them, 6.42 % (95% CI: 4.92-8.20) were diagnosed with DM. Hypertension was detected among 25.7% (95% CI: 22.9-28.5) of the participants. A total of 447 (47.3%) participants were found with IDRS score ≥ 60, and 276 (29.3%) with CBAC score >4. As much as 26.1% were at moderate to higher risk (≥10%) of developing CVDs. Area Under the Curve (AUC) for IDRS in predicting DM was 0.64 (0.58-0.70), with 67.1% SN and 55.2% SP (Youden's Index= 0.22). While the AUC for CBAC was 0.59 (0.53-0.65). For hypertension the both the AUCs were 0.66 (0.62-0.71) and 0.63 (0.59-0.67), respectively.Conclusions: Instead of CBAC, the present study emphasizes the usefulness of IDRS as an excellent tool for screening for both DM and HT. This is the time to expose the hidden part of the NCDs iceberg by having high sensitivity of non-invasive instruments (like IDRS), so, we propose a cut-off value of 50 for the IDRS to screen for diabetes in the rural Indian population.

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The IBIS-Q [IBd Identification of Spondyloarthritis Questionnaire]: A Novel Tool to Detect Both Axial and Peripheral Arthritis in Inflammatory Bowel Disease Patients

Journal of Crohn s and Colitis ◽

10.1093/ecco-jcc/jjaa096 ◽

2020 ◽

Vol 14 (12) ◽

pp. 1680-1686

Author(s):

Angela Variola ◽

Maria Elisabetta Zanolin ◽

Giovanni Cipriano ◽

Pierluigi Macchioni ◽

Federica Martinis ◽

...

Keyword(s):

Inflammatory Bowel Disease ◽

Bowel Disease ◽

Area Under The Curve ◽

Roc Curves ◽

Factorial Analysis ◽

Youden Index ◽

Patient Identification ◽

Asas Criteria ◽

Inflammatory Bowel ◽

Sensitivity Specificity

Abstract Background and Aims Both peripheral and axial spondyloarthritis [SpA] occur in inflammatory bowel disease [IBD] and represent the commonest extra-intestinal manifestation. We aimed to develop an easy and quick questionnaire through psychometric analysis, to identify peripheral and axial SpA in IBD patients within an integrated combined multidisciplinary rheumatological-gastroenterology clinic. Methods Initially, SpA-IBD experts generated a 42-item list covering SpA manifestations including spinal, articular, and entheseal involvement. The new questionnaire was administered before routine clinical IBD assessment. On the same day, rheumatological assessment, blinded to both history and questionnaire results, was performed to explore the presence of the Assessment of SpondyloArthritis International Society [ASAS] criteria for SpA, diagnostic criteria for fibromyalgia [FM], and non-specific low back pain [NSLB]. Factorial analysis of questionnaire items to identify the main factors—receiver operating characteristic [ROC] curves for sensitivity/specificity and Youden index for cut-off—were performed. Results Of the 181 consecutive patients, 56 met the ASAS SpA criteria [prevalence of 30%] with 10 new cases detected [5.5%: seven peripheral and three axial]. Through the psychometric and factorial analysis, we selected 14 items for the final questionnaire [named IBIS-Q]. The IBIS-Q was quick and performed well for detection of axial SpA and peripheral SpA (area under the curve [AUC] 0.88 with 95% confidence interval [CI] 0.830.93). A cut-off of three positive questions had a sensitivity 93% and specificity 77% for SpA patient identification. Conclusions The IBIS-Q is a useful and simple tool to use in IBD clinics for SpA detection, with a good statistical performance. Further studies are needed to validate it.

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The association between bone health indicated by calcaneal quantitative ultrasound and metabolic syndrome in Malaysian men

Journal of Diabetes & Metabolic Disorders ◽

10.1186/s40200-015-0136-3 ◽

2015 ◽

Vol 14 (1) ◽

Cited By ~ 5

Author(s):

Kok-Yong Chin ◽

Soelaiman Ima-Nirwana ◽

Isa Naina Mohamed ◽

Fairus Ahmad ◽

Elvy Suhana Mohd Ramli ◽

...

Keyword(s):

Metabolic Syndrome ◽

Quantitative Ultrasound ◽

Bone Health ◽

Calcaneal Quantitative Ultrasound

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Significance of CAVI, hs-CRP and Homocysteine in subclinical arteriosclerosis among a healthy population in China

Clinical & Investigative Medicine ◽

10.25011/cim.v36i2.19570 ◽

2013 ◽

Vol 36 (2) ◽

pp. 81 ◽

Cited By ~ 1

Author(s):

Jinpeng Zhong ◽

Yonghong Wang ◽

Xiaoling Wang ◽

Fengzeng Li ◽

Yulei Hou ◽

...

Keyword(s):

Predictive Value ◽

Area Under The Curve ◽

High Sensitivity ◽

Intima Media Thickness ◽

Roc Curves ◽

Carotid Intima Media Thickness ◽

Youden Index ◽

Healthy Population ◽

Hs Crp ◽

Sensitivity Specificity

Purpose: The purpose of this study is to evaluate the ability of cardio-ankle vascular index (CAVI), high-sensitivity C-reactive protein (hs-CRP) levels and homocysteine (Hcy) levels to screen for subclinical arteriosclerosis (subAs) in an apparently healthy population, with the view to obtaining an optimal diagnostic marker or profile for subAs. Methods: Subjects (152) undergoing routine health examinations were recruited and divided into two groups: carotid arteriosclerosis (CA) and non-carotid arteriosclerosis (NCA), according to carotid intima-media thickness (CMIT). CAVI was calculated based on blood pressure and pulse wave velocity. Serum hs-CRP and Hcy levels were also measured. A Receiver Operating Characteristic (ROC) curve was plotted to evaluate the efficacy of each in carotid arteriosclerosis screening. Ten parameter combinations, designated W1 to W10, were compared in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Results: The levels of all three parameters were significantly higher in the CA group, compared with the NCA group. ROC curves showed that the area under the curve (AUC) for CAVI was 0.708 (95%CI: 0.615-0.800), which is significantly larger than that of either hs-CRP (0.622) or Hcy (0.630), respectively (P < 0.001). Maximum sensitivity (100%) and NPV (100%) were attained with W10, while maximum specificity (86.2%) and PPV (46.7%) were obtained with W7. With W9, the maximum Youden index (0.416) was obtained, with a sensitivity of 77.8% and specificity of 63.8%. Conclusions: CAVI is more effective than hs-CRP or Hcy for subAs screening. The optimal profile was obtained with a combination of CAVI and other parameters.

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