Diagnostic Accuracy
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2022 ◽  
Vol 12 (1) ◽  
pp. 67-70
Author(s):  
Unathi Ntja ◽  
Jacques Janse van Rensburg ◽  
Gina Joubert
Keyword(s):  

2022 ◽  
Vol 38 (3) ◽  
Author(s):  
Liqin Jing ◽  
Yanchun Song

Objective: To investigate the comparative diagnostic accuracy of cardiac computed tomography (CT) and transoesophageal echocardiography (TEE) for detecting infective endocarditis. Methods: Original publications published in English language before July, 2021 were thoroughly search in PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and Google Scholar literature databases. Studies were included if they used CT and/or TEE as an index test, presented data on valvular complications related to infective endocarditis, and used surgical findings as to the reference standard. Results:­­­ Literature screening identified fifteen studies that fulfilled the inclusion criteria. Meta-analysis showed that CT sensitivity for detecting valvular abscesses was higher than that of TEE [0.88 (95% confidence interval [CI]: 0.82 to 0.94; 11 studies involving 842 subjects) versus 0.74 (95% CI: 0.65 to 0.84) P = 0.015; 12 studies involving 917 subjects]. TEE showed statistically significantly greater sensitivity than CT for detecting valvular vegetation [0.91 (95% CI: 0.84 to 0.97, 11 studies involving 971 subjects) versus 0.80 (95% CI: 0.69 to 0.82), 12 studies involving 915 subjects, P =0.019. In case of leaflet detection, TEE showed statistically significantly higher sensitivity than CT (0.76 vs 0.46, P =0.010). Conclusion: CT performs statistically significantly better than TEE for detecting abscesses while TEE provides statistically significant superior results for detecting vegetation. There is a need for well-designed prospective studies to further corroborate these findings. doi: https://doi.org/10.12669/pjms.38.3.5139 How to cite this:Jing L, Song Y. Comparing the diagnostic accuracy of computed tomography vs transoesophageal echocardiography for infective endocarditis − A meta-analysis . Pak J Med Sci. 2022;38(3):---------. doi: https://doi.org/10.12669/pjms.38.3.5139 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


2022 ◽  
Author(s):  
Henry Chen ◽  
Xiao Chun Ling ◽  
Da-Wen Lu ◽  
Lan-Hsing Chuang ◽  
Wei-Wen Su ◽  
...  

Abstract The risks of misdiagnosing a healthy individual as glaucomatous or vice versa may be high in a population with a large majority of highly myopic individuals, due to considerable morphologic variability in high myopic fundus. This study aims to compare the diagnostic ability of the regular and long axial length databases in the RS-3000 Advance SD-OCT (Nidek) device to correctly diagnose glaucoma with high myopia. Patients with high myopia (axial length ≥ 26.0 mm) in Chang Gung Memorial Hospital, Taiwan between 2015 and 2020 were included. Glaucoma was diagnosed based on glaucomatous discs, visual field defects and corresponding retinal nerve fiber layer defects. The sensitivity, specificity, diagnostic accuracy and likelihood ratios of diagnosing glaucoma via mGCC thickness in both superior/inferior and GChart mapping using the regular and long axial length normative databases. The specificity and diagnostic accuracy of mGCC thickness for distinguishing glaucomatous eyes from nonglaucomatous eyes among highly myopic eyes were significantly improved using the long axial length database (p=0.046). There were also significant proportion changes in S/I mapping as well as GChart mapping (37.3% and 48.0%, respectively; p<0.01) from abnormal to normal in the myopic normal eye group when using the long axial length normative database. The study revealed that clinicians could utilize a long axial length database to effectively decrease the number of false-positive diagnoses or to correctly identify highly myopic normal eyes misdiagnosed as glaucomatous eyes.


2022 ◽  
Author(s):  
James Devasia ◽  
Hridyanand Goswami ◽  
Subitha Lakshminarayanan ◽  
Manju Rajaram ◽  
Subathra Adithan ◽  
...  

Abstract Chest X-ray based diagnosis of active Tuberculosis (TB) is one of the oldest ubiquitous tests in medical practice. Artificial Intelligence (AI) based automated detection of abnormality in chest radiography is crucial in radiology workflow. Most deep convolutional neural networks (DCNN) for diagnosing TB by transfer learning from natural images and using the same dataset to evaluate the model performance and diagnostic accuracy. However, dataset shift is a known issue in predictive models in AI, which is unexplored. In this work, we fine-tuned, validated, and tested two benchmark architectures and utilized the transfer learning methodology to measure the diagnostic accuracy on cross-population datasets. We achieved remarkable calcification accuracy of 100% and area under the receiver operating characteristic (AUC) 1.000 [1.000 – 1.000] (with a sensitivity 0.985 [0.971 – 1.000] and a specificity of 0.986 [0.971 – 1.000]) on intramural test set, but significant drop in extramural test set. Accuracy on various extramural test sets varies 50% - 70%, AUC ranges 0.527 – 0.865 (sensitivity and specificity fluctuate 0.394 – 0.995 and 0.443 – 0.864 respectively). Diagnostic performance on the intramural test set observed in this study shows that DCNN can accurately classify active TB and normal chest radiographs, however the external test set shows DCNN is less likely to generalize well on models trained on specific population dataset.


2022 ◽  
Vol 11 ◽  
Author(s):  
Lei Chen ◽  
Luzeng Chen ◽  
Zhenwei Liang ◽  
Yuhong Shao ◽  
Xiuming Sun ◽  
...  

ObjectiveTo evaluate the diagnostic performance of preoperative contrast-enhanced ultrasound (CEUS) in the detection of extracapsular extension (ECE) and cervical lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) and the added value of CEUS in the evaluation of PTC invasiveness to conventional ultrasound (US).Materials and MethodsA total of 62 patients were enrolled retrospectively, including 30 patients with invasive PTCs (Group A, ECE or LNM present) and 32 patients with non-invasive PTCs (Group B). All patients underwent US and CEUS examinations before surgery. US and CEUS features of PTCs and lymph nodes were compared between groups. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of US, CEUS, and the combination of the two in the detection of ECE and LNM of PTCs were calculated. Logistic regression was used to analyze relationships between variables.ResultsThe PTC size was larger in group A on both US and CEUS (P = 0.001, P = 0.003). More PTCs showed hyper-enhancement in group A (P = 0.013) than in group B. More PTCs had &gt;25% contact between PTC and the thyroid capsule and discontinued capsule on US and CEUS (all P &lt; 0.05) in group A than in group B. More absent hilum and calcification of lymph nodes were observed in group A (both P &lt; 0.05) than in group B on US. More centripetal perfusion and enlarged lymph nodes were observed in group A (both P &lt; 0.05) than in group B on CEUS. CEUS alone and US combined with CEUS manifested higher diagnostic accuracy (79.0%) than US alone (72.6%) in the detection of ECE. The combination of US and CEUS manifested the highest diagnostic accuracy (95.2%) than CEUS alone (90.3%) and US alone (82.2%) in the detection of LNM. Diagnoses of ECE and LNM by the combination of US and CEUS were independent risk factors for PTC invasiveness [odds ratio (OR) = 29.49 and 97.20, respectively; both P = 0.001].ConclusionCEUS or US combined with CEUS is recommended for the detection of PTC ECE, while the combination of US and CEUS is most recommended for LNM detection. CEUS plays an essential role in the preoperative evaluation of PTC invasiveness.


2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Chris K. Kim ◽  
Ji Whae Choi ◽  
Zhicheng Jiao ◽  
Dongcui Wang ◽  
Jing Wu ◽  
...  

AbstractWhile COVID-19 diagnosis and prognosis artificial intelligence models exist, very few can be implemented for practical use given their high risk of bias. We aimed to develop a diagnosis model that addresses notable shortcomings of prior studies, integrating it into a fully automated triage pipeline that examines chest radiographs for the presence, severity, and progression of COVID-19 pneumonia. Scans were collected using the DICOM Image Analysis and Archive, a system that communicates with a hospital’s image repository. The authors collected over 6,500 non-public chest X-rays comprising diverse COVID-19 severities, along with radiology reports and RT-PCR data. The authors provisioned one internally held-out and two external test sets to assess model generalizability and compare performance to traditional radiologist interpretation. The pipeline was evaluated on a prospective cohort of 80 radiographs, reporting a 95% diagnostic accuracy. The study mitigates bias in AI model development and demonstrates the value of an end-to-end COVID-19 triage platform.


2022 ◽  
Vol 16 (1) ◽  
pp. e0010109
Author(s):  
Ana Hernández-González ◽  
Belén González-Bertolín ◽  
Laura Urrea ◽  
Agnes Fleury ◽  
Elizabeth Ferrer ◽  
...  

Background Neurocysticercosis (NCC), and cystic echinococcosis (CE) are two neglected diseases caused by cestodes, co-endemic in many areas of the world. Imaging studies and serological tests are used in the diagnosis of both parasitic diseases, but cross-reactions may confound the results of the latter. The novel multiplex bead-based assay with recombinant antigens has been reported to increases the diagnostic accuracy of serological techniques. Methodology We set-up an immunoassay based on the multiplex bead-based platform (MBA), using the rT24H (against Cysticercus cellulosae, causing cysticercosis) and r2B2t (against Echinococcus granulosus sensu lato, causing CE) recombinant antigens, for simultaneous and differential diagnosis of these infections. The antigens were tested on 356 sera from 151 patients with CE, 126 patients with NCC, and 79 individuals negative for both diseases. Specificity was calculated including sera from healthy donors, other neurological diseases and the respective NCC or CE sera counterpart. The diagnostic accuracy of this assay was compared with two commercial ELISA tests, Novalisa and Ridascreen, widely used in the routine diagnosis of cysticercosis and CE, respectively. Main findings For the diagnosis of NCC, sensitivity ranged from 57.94–63.49% for the rT24H-MBA, and 40.48–46.03% for Novalisa ELISA depending on exclusion or inclusion of sera having equivocal results on ELISA from the analysis; specificities ranged from 90.87–91.30% and 70.43–76.96%, respectively. AUC values of the ROC curve were 0.783 (rT24H) and 0.619 (Novalisa) (p-value < 0.001). For the diagnosis of CE, the sensitivity of the r2B2t-MBA ranged from 68.87–69.77% and of Ridascreen ELISA from 50.00–57.62%; specificities from 92.47–92.68% and from 74.15–80.98%, respectively. AUC values were 0.717 and 0.760, respectively. Conclusions/Significance Overall, the recombinant antigens tested with the bead-based technology showed better diagnostic accuracy than the commercial assays, particularly for the diagnosis of NCC. The possibility of testing the same serum sample simultaneously for the presence of antibodies against both antigens is an added value particularly in seroprevalence studies for cysticercosis linked to control programs in endemic areas where these two parasites coexist.


2022 ◽  
Vol 11 ◽  
Author(s):  
Dengke Teng ◽  
Chunhui Dong ◽  
Daju Sun ◽  
Zhuo Liu ◽  
Hui Wang

A randomized comparison of ultrasound (US)-guided core needle biopsy (CNB) under the assistance of hydrodissection with fine needle aspiration (FNA) was performed to evaluate the feasibility, safety and effectiveness for the diagnosis of high-risk cervical lymph nodes. Patients from December 2018 to May 2020 were randomly assigned to the CNB group and the FNA group at a ratio of 1:1. This study protocol was approved by the Ethics Committee of our hospital and registered in the Chinese Clinical Trial Registry (ChiCTR1800019370). The feasibility of CNB for high-risk cervical lymph nodes was evaluated by observing and recording the separation success rate (SSR) and technical success rate (TSR) of the CNB group. Safety was evaluated by comparing the incidence of major complications in the two groups. The diagnostic efficacy was evaluated by comparing the diagnostic accuracy, sensitivity, and specificity of the two groups. A total of 84 patients (84 lymph nodes) were randomized into the CNB (n = 42) and FNA (n = 42) groups. All patients in the CNB group achieved successful hydrodissection and biopsy. The SSR and TSR were both 100% in the CNB group. There were no major complications during or after the process in the two groups. Compared with the FNA group, the CNB group was significantly superior in terms of diagnostic accuracy and sensitivity (100% vs. 81.0%, P = 0.009; 100% vs. 79.2%, P = 0.035, respectively). The specificity of the two groups was 100%, and there was no significant difference. Compared with FNA, CNB under the assistance of hydrodissection is a feasible and safe method but is more effective for the diagnosis of high-risk cervical lymph nodes.Clinical Trial Registrationhttp://www.medresman.org, ChiCTR1800019370.


Cancers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 384
Author(s):  
Teresa Resende Neves ◽  
Mariana Tomé Correia ◽  
Maria Ana Serrado ◽  
Mariana Horta ◽  
António Proença Caetano ◽  
...  

Endometrial cancer is the eighth most common cancer worldwide, and its prognosis depends on various factors, with myometrial invasion having a major impact on prognosis. Optimizing MRI protocols is essential, and it would be useful to improve the diagnostic accuracy without the need for other sequences. We conducted a retrospective, single-center study, which included a total of 87 patients with surgically confirmed primary endometrial cancer, and who had undergone a pre-operative pelvic MRI. All exams were read by an experienced radiologist dedicated to urogenital radiology, and the depth of myometrial invasion was evaluated using T2-Weighted Images (T2WI) and fused T2WI with Diffusion-Weighted Images (DWI). Both results were compared to histopathological evaluations. When comparing both sets of imaging (T2WI and fused T2WI-DWI images) in diagnosing myometrial invasion, the fused images had better accuracy, and this difference was statistically significant (p < 0.001). T2WI analysis correctly diagnosed 82.1% (70.6–88.7) of cases, compared to 92.1% correctly diagnosed cases with fused images (79.5–97.2). The addition of fused images to a standard MRI protocol improves the diagnostic accuracy of myometrial invasion depth, encouraging its use, since it does not require more acquisition time.


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