Application of apical myocardial perfusion quantitative analysis by contrast-enhanced ultrasound utilizing high-frequency linear probe.

BACKGROUND: Due to insufficient near-field resolution and artifacts, it is challenging to evaluate the left ventricular apical perfusion with phased-array probes. By combining high-frequency linear probe and contrast-enhanced ultrasound (CEUS), imaging of apical myocardial perfusion could be improved. The study aims to evaluate the preliminary application of CEUS by high-frequency linear probes to assess the apical perfusion. METHODS: The study enrolled retrospectively 91 patients to test the feasibility of the novel method. In protocol 1, patients were stratified into a group with left anterior descending artery (LAD) stenosis (N = 40) and a group without LAD stenosis or coronary artery disease (N = 41) based on the degree of coronary artery narrowing, quantified by >50% stenosis in coronary angiography. Receiver operating characteristics (ROC) analysis was performed to test the diagnostic value of perfusion parameters. In protocol 2, the reproducibility of high-frequency linear probe in apical perfusion analysis was compared with the conventional phased-array probe in 30 patients. RESULTS: (1) The novel method is feasible in 81(89.01%) patients. (2) In protocol 1, to detect LAD stenosis, the best cut-off of ß, T, A, and MBF were 10.32, 3.28, 9.39, and 4.99, respectively. Area under the curve of ß, T, A, and MBF were .880, .881, .761, and .880, respectively. (3) In protocol 2, compared with phased-array probe, the quantitative analysis of high-frequency linear probe is of high reproducibility and could get good curve fitting (R2 = .29 vs. R2 = .71, P < .01). CONCLUSION: Observation of apical perfusion using this method is feasible and quantitative analysis allows an accurate and convenient identification of LAD stenosis. This method provides an alternative for patients who have difficulties in visualizing the apical region with a phased-array probe.

Detectability of intracranial vessel wall atherosclerosis using black-blood spectral CT: a phantom and clinical study.

BACKGROUND: Computed tomography (CT) is the usual modality for diagnosing stroke, but conventional CT angiography reconstructions have limitations. METHODS: A phantom with tubes of known diameters and wall thickness was scanned for wall detectability, wall thickness, and contrast-to-noise ratio (CNR) on conventional and spectral black-blood (SBB) images. The clinical study included 34 stroke patients. Diagnostic certainty and conspicuity of normal/abnormal intracranial vessels using SBB were compared to conventional. Sensitivity/specificity/accuracy of SBB and conventional were compared for plaque detectability. CNR of the wall/lumen and quantitative comparison of remodeling index, plaque burden, and eccentricity were obtained for SBB imaging and high-resolution magnetic resonance imaging (hrMRI). RESULTS: The phantom study showed improved detectability of tube walls using SBB (108/108, 100% versus conventional 81/108, 75%, p < 0.001). CNRs were 75.9 ± 62.6 (mean ± standard deviation) for wall/lumen and 22.0 ± 17.1 for wall/water using SBB and 26.4 ± 15.3 and 101.6 ± 62.5 using conventional. Clinical study demonstrated (i) improved certainty and conspicuity of the vessels using SBB versus conventional (certainty, median score 3 versus 0; conspicuity, median score 3 versus 1 (p < 0.001)), (ii) improved sensitivity/specificity/accuracy of plaque (≥ 1.0 mm) detectability (0.944/0.981/0.962 versus 0.239/0.743/0.495) (p < 0.001), (iii) higher wall/lumen CNR of SBB of (78.3 ± 50.4/79.3 ± 96.7) versus hrMRI (18.9 ± 8.4/24.1 ± 14.1) (p < 0.001), and (iv) excellent reproducibility of remodeling index, plaque burden, and eccentricity using SBB versus hrMRI (intraclass correlation coefficient 0.85-0.94). CONCLUSIONS: SBB can enhance the detectability of intracranial plaques with an accuracy similar to that of hrMRI. RELEVANCE STATEMENT: This new spectral black-blood technique for the detection and characterization of intracranial vessel atherosclerotic disease could be a time-saving and cost-effective diagnostic step for clinical stroke patients. It may also facilitate prevention strategies for atherosclerosis. KEY POINTS: • Blooming artifacts can blur vessel wall morphology on conventional CT angiography. • Spectral black-blood (SBB) images are generated from material decomposition from spectral CT. • SBB images reduce blooming artifacts and noise and accurately detect small plaques.

Diagnostic performance of ultrasonography in pre-operative assessment of lymph nodes in patients with cervical cancer.

OBJECTIVES: To assess the diagnostic performance of ultrasonography in pre-operative assessment of lymph nodes in patients with cervical cancer, to compare the outcomes for pelvic and para-aortic regions, and to detect macrometastases and micrometastases separately. METHODS: Patients were retrospectively included if they met the following inclusion criteria: pathologically verified cervical cancer; ultrasonography performed by one of four experienced sonographers; surgical lymph node staging, at least in the pelvic region-sentinel lymph node biopsy or systematic pelvic lymphadenectomy or debulking. The final pathological examination was the reference standard. RESULTS: 390 patients met the inclusion criteria between 2009 and 2019. Pelvic node macrometastases (≥2 mm) were confirmed in 54 patients (13.8%), and micrometastases (≥0.2 mm and <2 mm) in another 21 patients (5.4%). Ultrasonography had sensitivity 72.2%, specificity 94.0%, and area under the curve (AUC) 0.831 to detect pelvic macrometastases, while sensitivity 53.3%, specificity 94.0%, and AUC 0.737 to detect both pelvic macrometastases and micrometastases (pN1). Ultrasonography failed to detect pelvic micrometastases, with sensitivity 19.2%, specificity 85.2%, and AUC 0.522. There was no significant impact of body mass index on diagnostic accuracy. Metastases in para-aortic nodes (macrometastases only) were confirmed in 16 of 71 patients who underwent para-aortic lymphadenectomy. Ultrasonography yielded sensitivity 56.3%, specificity 98.2%, and AUC 0.772 to identify para-aortic node macrometastases. CONCLUSION: Ultrasonography performed by an experienced sonographer can be considered a sufficient diagnostic tool for pre-operative assessment of lymph nodes in patients with cervical cancer, showing similar diagnostic accuracy in detection of pelvic macrometastases as reported for other imaging methods (18F-fluorodeoxyglucose positron emission tomography/CT or diffusion-weighted imaging/MRI). It had low sensitivity for detection of small-volume macrometastases (largest diameter <5 mm) and micrometastases. The accuracy of para-aortic assessment was comparable to that for pelvic lymph nodes, and assessment of the para-aortic region should be an inseparable part of the examination protocol.

Hepatitis C risk score as a tool to identify individuals with HCV infection: a demonstration and cross-sectional epidemiological study in Egypt.

OBJECTIVES: Hepatitis C virus (HCV) infection poses a global health challenge. By the end of 2021, the WHO estimated that less than a quarter of global HCV infections had been diagnosed. There is a need for a public health tool that can facilitate the identification of people with HCV infection and link them to testing and treatment, and that can be customised for each country. METHODS: We derived and validated a risk score to identify people with HCV in Egypt and demonstrated its utility. Using data from the 2008 and 2014 Egypt Demographic and Health Surveys, two risk scores were constructed through multivariable logistic regression analysis. A range of diagnostic metrics was then calculated to evaluate the performance of these scores. RESULTS: The 2008 and 2014 risk scores exhibited similar dependencies on sex, age and type of place of residence. Both risk scores demonstrated high and similar areas under the curve of 0.77 (95% CI: 0.76 to 0.78) and 0.78 (95% CI: 0.77 to 0.80), respectively. For the 2008 risk score, sensitivity was 73.7% (95% CI: 71.5% to 75.9%), specificity was 68.5% (95% CI: 67.5% to 69.4%), positive predictive value (PPV) was 27.8% (95% CI: 26.4% to 29.2%) and negative predictive value (NPV) was 94.1% (95% CI: 93.5% to 94.6%). For the 2014 risk score, sensitivity was 64.0% (95% CI: 61.5% to 66.6%), specificity was 78.2% (95% CI: 77.5% to 78.9%), PPV was 22.2% (95% CI: 20.9% to 23.5%) and NPV was 95.7% (95% CI: 95.4% to 96.1%). Each score was validated by applying it to a different survey database than the one used to derive it. CONCLUSIONS: Implementation of HCV risk scores is an effective strategy to identify carriers of HCV infection and to link them to testing and treatment at low cost to national programmes.

Efficacy and Accuracy of Diagnosing Septic Arthritis: How Effective are Current Methods for Timely Diagnosis of Septic Arthritis?

The diagnosis of septic arthritis requires a reliance on ancillary tests, including synovial fluid white blood cell count (jWBC), percentage of polymorphonuclear leukocytes (%PMN), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP). This study evaluated these tests to determine their diagnostic utility in suspected septic arthritis. A retrospective chart review was performed on patients admitted to an urban hospital who underwent arthrocentesis. The authors evaluated the jWBC, %PMN, ESR, and CRP with receiver operating characteristic (ROC) curve analyses. Two hundred sixty-five patients met inclusion criteria. Sixty-three had a culture-positive aspirate. ROC curve analysis resulted in an area under the curve (AUC) of 0.80 for jWBC with cutoff point of 22,563 cells/mm3 and an AUC of 0.71 for %PMN with cutoff point of 90.5%. CRP and ESR had AUC values of 0.62 and 0.61, respectively. The culture-positive cohort had higher elevations in all assessed diagnostic tests. However, AUC data for ESR and CRP showed little diagnostic utility. Additionally, sensitivities and specificities of jWBC and %PMN were too low. Associated cutoff points would result in excessive unnecessary operative intervention. Further studies should incorporate synovial fluid biomarkers into the workup of a suspected septic joint. (Journal of Surgical Orthopaedic Advances 33(2):108-111, 2024).

AI-enhanced Mammography With Digital Breast Tomosynthesis for Breast Cancer Detection: Clinical Value and Comparison With Human Performance.

Purpose To compare two deep learning-based commercially available artificial intelligence (AI) systems for mammography with digital breast tomosynthesis (DBT) and benchmark them against the performance of radiologists. Materials and Methods This retrospective study included consecutive asymptomatic patients who underwent mammography with DBT (2019-2020). Two AI systems (Transpara 1.7.0 and ProFound AI 3.0) were used to evaluate the DBT examinations. The systems were compared using receiver operating characteristic (ROC) analysis to calculate the area under the ROC curve (AUC) for detecting malignancy overall and within subgroups based on mammographic breast density. Breast Imaging Reporting and Data System results obtained from standard-of-care human double-reading were compared against AI results with use of the DeLong test. Results Of 419 female patients (median age, 60 years [IQR, 52-70 years]) included, 58 had histologically proven breast cancer. The AUC was 0.86 (95% CI: 0.85, 0.91), 0.93 (95% CI: 0.90, 0.95), and 0.98 (95% CI: 0.96, 0.99) for Transpara, ProFound AI, and human double-reading, respectively. For Transpara, a rule-out criterion of score 7 or lower yielded 100% (95% CI: 94.2, 100.0) sensitivity and 60.9% (95% CI: 55.7, 66.0) specificity. The rule-in criterion of higher than score 9 yielded 96.6% sensitivity (95% CI: 88.1, 99.6) and 78.1% specificity (95% CI: 73.8, 82.5). For ProFound AI, a rule-out criterion of lower than score 51 yielded 100% sensitivity (95% CI: 93.8, 100) and 67.0% specificity (95% CI: 62.2, 72.1). The rule-in criterion of higher than score 69 yielded 93.1% (95% CI: 83.3, 98.1) sensitivity and 82.0% (95% CI: 77.9, 86.1) specificity. Conclusion Both AI systems showed high performance in breast cancer detection but lower performance compared with human double-reading. Keywords: Mammography, Breast, Oncology, Artificial Intelligence, Deep Learning, Digital Breast Tomosynthesis © RSNA, 2024.

Metagenomic Next-Generation Sequencing as an Effective Diagnostic Tool for Talaromycosis in HIV-Negative Patients.

The diagnosis of Talaromyces marneffei infection in HIV-negative patients remains challenging. There is an urgent need for rapid and convenient methods to diagnose this complicated disease. The aim of this study was to evaluate the diagnostic efficiency of metagenomic next-generation sequencing (mNGS) for talaromycosis in non-HIV-infected patients by comparing mNGS with traditional microbial culture. In total, 66 samples from 57 patients were analyzed via both mNGS and microbial culture. The ROC curve showed a sensitivity for mNGS of 97.22%, which was greater than that of microbial culture (61.11%). Samples from the respiratory tract, infectious skin lesions, and lymph nodes are recommended as routine samples for talaromycosis detection via mNGS. Furthermore, mNGS significantly reduced the diagnostic time compared to microbial culture. Overall, our study demonstrated that mNGS is a promising tool for rapid and accurate pathogenic detection in HIV-negative patients with talaromycosis.

A rapid and ultra-sensitive dual readout platform for Klebsiella pneumoniae detection based on RPA-CRISPR/Cas12a.

The bacterium Klebsiella pneumoniae (Kp) was the primary pathogen of hospital-acquired infection, but the current detection method could not rapidly and conveniently identify Kp. Recombinase polymerase amplification (RPA) was a fast and convenient isothermal amplification technology, and the clustered regularly interspaced short palindromic repeats (CRISPR) system could rapidly amplify the signal of RPA and improve its limit of detection (LOD). In this study, we designed three pairs of RPA primers for the rcsA gene of Kp, amplified the RPA signal through single-strand DNA reporter cleavage by CRISPR/Cas12a, and finally analyzed the cleavage signal using fluorescence detection (FD) and lateral flow test strips (LFTS). Our results indicated that the RPA-CRISPR/Cas12a platform could specifically identify Kp from eleven common clinical pathogens. The LOD of FD and LFTS were 1 fg/µL and 10 fg/µL, respectively. In clinical sample testing, the RPA-CRISPR/Cas12a platform was consistent with the culture method and qPCR method, and its sensitivity and specificity were 100% (16/16) and 100% (9/9), respectively. With the advantages of detection speed, simplicity, and accuracy, the RPA-CRISPR/Cas12a platform was expected to be a convenient tool for the early clinical detection of Kp.

Evaluation of the sensitivity of a measles diagnostic real-time RT-PCR assay incorporating recently observed priming mismatch variants, 2024.

We investigated a variant of measles virus that encodes three mismatches to the reverse priming site for a widely used diagnostic real-time RT-PCR assay; reduction of sensitivity was hypothesised. We examined performance of the assay in context of the variant using in silico data, synthetic RNA templates and clinical specimens. Sensitivity was reduced observed at low copy numbers for templates encoding the variant sequence. We designed and tested an alternate priming strategy, rescuing the sensitivity of the assay.

TOTEM: a multi-cancer detection and localization approach using circulating tumor DNA methylation markers.

BACKGROUND: Detection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers. METHODS: We performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach. RESULTS: A total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort. CONCLUSIONS: TOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

Evaluation of chimeric recombinant antigens for the serodiagnosis of Trypanosoma cruzi in dogs: a promising tool for Chagas disease surveillance.

BACKGROUND: Chagas disease (CD), a neglected parasitic disease caused by Trypanosoma cruzi, poses a significant health threat in Latin America and has emerged globally because of human migration. Trypanosoma cruzi infects humans and over 100 other mammalian species, including dogs, which are important sentinels for assessing the risk of human infection. Nonetheless, the serodiagnosis of T. cruzi in dogs is still impaired by the absence of commercial tests. In this study, we investigated the diagnostic accuracy of four chimeric recombinant T. cruzi IBMP antigens (IBMP-8.1, IBMP-8.2, IBMP-8.3, and IBMP-8.4) for detecting anti-T. cruzi antibodies in dogs, using latent class analysis (LCA). METHODS: We examined 663 canine serum samples, employing indirect ELISA with the chimeric antigens. LCA was utilized to establish a latent variable as a gold standard for T. cruzi infection, revealing distinct response patterns for each antigen. RESULTS: The IBMP (Portuguese acronym for the Molecular Biology Institute of Paraná) antigens achieved area under the ROC curve (AUC) values ranging from 90.9% to 97.3%. The highest sensitivity was attributed to IBMP-8.2 (89.8%), while IBMP-8.1, IBMP-8.3, and IBMP-8.4 achieved 73.5%, 79.6%, and 85.7%, respectively. The highest specificity was observed for IBMP-8.4 (98.6%), followed by IBMP-8.2, IBMP-8.3, and IBMP-8.1 with specificities of 98.3%, 94.4%, and 92.7%, respectively. Predictive values varied according to prevalence, indicating higher effectiveness in endemic settings. CONCLUSIONS: Our findings underscore the remarkable diagnostic performance of IBMP-8.2 and IBMP-8.4 for the serodiagnosis of Trypanosoma cruzi in dogs, representing a promising tool for the diagnosis of CD in dogs. These chimeric recombinant antigens may not only enhance CD surveillance strategies but also hold broader implications for public health, contributing to the global fight against this neglected tropical disease.

[Research on the classification model of chronic sinusitis based on VGG].

Objective:To build a VGG-based computer-aided diagnostic model for chronic sinusitis and evaluate its efficacy. Methods:①A total of 5 000 frames of diagnosed sinus CT images were collected. The normal group consisted of 1 000 frames（250 frames each of maxillary sinus, frontal sinus, septal sinus, and pterygoid sinus）, while the abnormal group consisted of 4 000 frames（1 000 frames each of maxillary sinusitis, frontal sinusitis, septal sinusitis, and pterygoid sinusitis）. ②The models were trained and simulated to obtain five classification models for the normal group, the pteroid sinusitis group, the frontal sinusitis group, the septal sinusitis group and the maxillary sinusitis group, respectively. The classification efficacy of the models was evaluated objectively in six dimensions: accuracy, precision, sensitivity, specificity, interpretation time and area under the ROC curve（AUC）. ③Two hundred randomly selected images were read by the model with three groups of physicians（low, middle and high seniority） to constitute a comparative experiment. The efficacy of the model was objectively evaluated using the aforementioned evaluation indexes in conjunction with clinical analysis. Results:①Simulation experiment: The overall recognition accuracy of the model is 83.94%, with a precision of 89.52%, sensitivity of 83.94%, specificity of 95.99%, and the average interpretation time of each frame is 0.2 s. The AUC for sphenoid sinusitis was 0.865（95%CI 0.849-0.881）, for frontal sinusitis was 0.924（0.991-0.936）, for ethmoidoid sinusitis was 0.895（0.880-0.909）, and for maxillary sinusitis was 0.974（0.967-0.982）. ②Comparison experiment: In terms of recognition accuracy, the model was 84.52%, while the low-seniority physicians group was 78.50%, the middle-seniority physicians group was 80.50%, and the seniority physicians group was 83.50%; In terms of recognition accuracy, the model was 85.67%, the low seniority physicians group was 79.72%, the middle seniority physicians group was 82.67%, and the high seniority physicians group was 83.66%. In terms of recognition sensitivity, the model was 84.52%, the low seniority group was 78.50%, the middle seniority group was 80.50%, and the high seniority group was 83.50%. In terms of recognition specificity, the model was 96.58%, the low-seniority physicians group was 94.63%, the middle-seniority physicians group was 95.13%, and the seniority physicians group was 95.88%. In terms of time consumption, the average image per frame of the model is 0.20 s, the average image per frame of the low-seniority physicians group is 2.35 s, the average image per frame of the middle-seniority physicians group is 1.98 s, and the average image per frame of the senior physicians group is 2.19 s. Conclusion:This study demonstrates the potential of a deep learning-based artificial intelligence diagnostic model for chronic sinusitis to classify and diagnose chronic sinusitis; the deep learning-based artificial intelligence diagnosis model for chronic sinusitis has good classification performance and high diagnostic efficacy.

Ongoing assertion of two-dimensional measurements on differentiation type of left ventricular hypertrophy: Focus on inferior vena cava.

BACKGROUND: Left ventricular hypertrophy (LVH), including hypertensive LVH, hypertrophic cardiomyopathy (HCM) and cardiac amyloidosis (CA), is a commonly encountered condition in cardiology practice, presenting challenges in differential diagnosis. In this study, we aimed to investigate the importance of echocardiographic evaluation of the inferior vena cava (IVC) in distinguishing LVH subtypes including hypertensive LVH, HCM, and CA. METHODS: In this retrospective study, patients with common causes of LVH including hypertensive LVH, HCM, and CA were included. The role of echocardiographic evaluation of IVC diameter and collapsibility in distinguishing these causes of LVH was assessed in conjunction with other echocardiographic, clinical, and imaging methods. RESULTS: A total of 211 patients (45% HCM, 43% hypertensive heart disease, and 12% CA) were included in our study. Their mean age was 56.6 years and 62% of them were male. While mean IVC diameter was significantly dilated in CA patients (13.4 mm in hypertensive LVH, 16.0 mm in HCM, and 21.1 mm in CA, p < .001), its collapsibility was reduced (IVC collapsible in 95% of hypertensive patients, 72% of HCM patients, and 12% of CA patients, p < .001). In the analysis of diagnostic probabilities, the presence of both hypovoltage and IVC dilation is significant for CA patients. Although it is not statistically significant, the presence of IVC dilation along with atrial fibrillation supports the diagnosis of HCM. CONCLUSION: In conclusion, although advances in imaging techniques facilitate the diagnosis of LVH, simple echocardiographic methods should never be overlooked. Our study supports the notion that IVC assessment could play an important role in the differential diagnosis of LVH.

Evaluation of Somatic Antigens of Adult Toxocara helminthes for Detection of Human Toxocariasis.

We aimed to develop an indirect enzyme-linked immunosorbent assay (ELISA) to evaluate the presence of specific IgG against Toxocara canis and Toxocara cati somatic antigens on the serum of patients with toxocariasis. The sensitivity, specificity, positive and negative predictive values for indirect-ELISA were calculated by receiver operating characteristic curve (ROC) analysis and Youden's J using Likelihood ratio. All statistics were analysed and graphs are plotted using GraphPad Prism version 8.4.3 (Graph Pad Software, La Jolla, CA, USA), with 95% confidence interval (CI). The sensitivity, specificity, positive and negative predictive values for T. canis were 100%, 82%, 79% and 100%, respectively. The mentioned variables for T. cati were 97%, 82%, 78% and 98%, respectively. Five immune reactive bands of 38, 40, 72, 100 and 250 kDa were common in both species. Toxocara crude antigens were highly immunogenic in human sera. Immunoreactive bands against T. canis compared to T. cati somatic antigen were about two times more. Unlike Toxocara excretory-secretory antigen, that was homologue in two species, somatic antigens of T. canis and T. cati showed different immunoreactive bands in our western blot.

The accuracy of predicting hospital admission by emergency medical service and emergency department personnel compared to the prehospital MEWS: a prospective multicenter study.

INTRODUCTION: Overcrowding in the emergency department (ED) is a global problem. Early and accurate recognition of a patient's disposition could limit time spend at the ED and thus improve throughput and quality of care provided. This study aims to compare the accuracy among healthcare providers and the prehospital Modified Early Warning Score (MEWS) in predicting the requirement for hospital admission. METHODS: A prospective, observational, multi-centre study was performed including adult patients brought to the ED by ambulance. Involved Emergency Medical Service (EMS) personnel, ED nurses and physicians were asked to predict the need for hospital admission using a structured questionnaire. Primary endpoint was the comparison between the accuracy of healthcare providers and prehospital MEWS in predicting patients' need for hospital admission. RESULTS: In total 798 patients were included of whom 393 (49.2%) were admitted to the hospital. Sensitivity of predicting hospital admission varied from 80.0 to 91.9%, with physicians predicting hospital admission significantly more accurately than EMS and ED nurses (p < 0.001). Specificity ranged from 56.4 to 67.0%. All healthcare providers outperformed MEWS ≥ 3 score on predicting hospital admission (sensitivity 80.0-91.9% versus 44.0%; all p < 0.001). Predictions for ward admissions specifically were significantly more accurate than MEWS (specificity 94.7-95.9% versus 60.6%, all p < 0.001). CONCLUSIONS: Healthcare providers can accurately predict the need for hospital admission, and all providers outperformed the MEWS score.

Evaluation and comparison of one-step real-time PCR and one-step RT-LAMP methods for detection of SARS-CoV-2.

BACKGROUND: There is an increasing disease trend for SARS-COV-2, so need a quick and affordable diagnostic method. It should be highly accurate and save costs compared to other methods. The purpose of this research is to achieve these goals. METHODS: This study analyzed 342 samples using TaqMan One-Step RT-qPCR and fast One-Step RT-LAMP (Reverse Transcriptase Loop-Mediated Isothermal Amplification). The One-Step LAMP assay was conducted to assess the sensitivity and specificity. RESULTS: The research reported positive samples using two different methods. In the RT-LAMP method, saliva had 92 positive samples (26.9%) and 250 negative samples (73.09%) and nasopharynx had 94 positive samples (27.4%) and 248 negative samples (72.51%). In the RT-qPCR method, saliva had 86 positive samples (25.1%) and 256 negative samples (74.8%) and nasopharynx had 93 positive samples (27.1%) and 249 negative samples (72.8%). The agreement between the two tests in saliva and nasopharynx samples was 93% and 94% respectively, based on Cohen's kappa coefficient (κ) (P < 0.001). The rate of sensitivity in this technique was reported at a dilution of 1 × 101 and 100% specificity. CONCLUSIONS: Based on the results of the study the One-Step LAMP assay has multiple advantages. These include simplicity, cost-effectiveness, high sensitivity, and specificity. The One-Step LAMP assay shows promise as a diagnostic tool. It can help manage disease outbreaks, ensure prompt treatment, and safeguard public health by providing rapid, easy-to-use testing.

Diagnostic accuracy of the Xpert® MTB/XDR assay for detection of Isoniazid and second-line antituberculosis drugs resistance at central TB reference laboratory in Tanzania.

INTRODUCTION: Early diagnosis of tuberculosis (TB) and universal access to drug-susceptibility testing (DST) are critical elements of the WHO End TB Strategy. Current rapid tests (e.g., Xpert® MTB/RIF and Ultra-assays) can detect rifampicin resistance-conferring mutations, but cannot detect resistance to Isoniazid and second-line anti-TB agents. Although Line Probe Assay is capable of detecting resistance to second-line anti-TB agents, it requires sophisticated laboratory infrastructure and advanced skills which are often not readily available in settings replete with TB. A rapid test capable of detecting Isoniazid and second-line anti-TB drug resistance is highly needed. METHODS: We conducted a diagnostic accuracy study to evaluate a new automated Xpert MTB/XDR 10-colour assay for rapid detection of Isoniazid and second-line drugs, including ethionamide, fluoroquinolones, and injectable drugs (Amikacin, Kanamycin, and Capreomycin). Positive Xpert MTB/RIF respiratory specimens were prospectively collected through routine diagnosis and surveillance of drug resistance at the Central TB Reference Laboratory in Tanzania. Specimens were tested by both Xpert XDR assay and LPA against culture-based phenotypic DST as the reference standard. FINDINGS: We analysed specimens from 151 TB patients with a mean age (SD) of 36.2 (12.7) years. The majority (n = 109, 72.2%) were males. The sensitivity for Xpert MTB/XDR was 93.5% (95% CI, 87.4-96.7); for Isoniazid, 96.6 (95% CI, 92.1-98.6); for Fluoroquinolone, 98.7% (95% Cl 94.8-99.7); for Amikacin, 96.6%; and (95% CI 92.1-98.6) for Ethionamide. Ethionamide had the lowest specificity of 50% and the highest was 100% for Fluoroquinolone. The diagnostic performance was generally comparable to that of LPA with slight variations between the two assays. The non-determinate rate (i.e., invalid M. tuberculosis complex detection) of Xpert MTB/XDR was 2·96%. CONCLUSION: The Xpert MTB/XDR demonstrated high sensitivity and specificity for detecting resistance to Isoniazid, Fluoroquinolones, and injectable agents. This assay can be used in clinical settings to facilitate rapid diagnosis of mono-isoniazid and extensively drug-resistant TB.

Study of Diagnostic Yield of Nucleic Acid Amplification Test among Tuberculous Cervical Lymphadenitis in Immunocompetent Patients.

BACKGROUND: The most common form of extrapulmonary tuberculosis (TB) is tuberculous lymphadenitis, which constitutes about 30-40% of all extrapulmonary TB cases. A new diagnostic method like the nucleic acid amplification test (NAAT) is a very sensitive and rapid test for diagnosing tuberculous cervical lymphadenopathy. It also detects rifampicin sensitivity among positive patients. OBJECTIVES: (1) To evaluate the diagnostic yield of TrueNAT for detecting Mycobacterium tuberculosis bacteria in the fine-needle aspirated samples of cervical lymph nodes compared with Ziehl-Neelsen (ZN) staining; (2) to evaluate the diagnostic yield of TrueNAT for diagnosis of tuberculosis through comparison with the cytology report of fine-needle aspiration (FNA) sample of cervical lymph node and with necrotic cervical lymph node on ultrasonography (USG) neck. MATERIALS AND METHODS: A total of 50 patients enrolled in this prospective study from January to December 2022. Demographic profile and clinical history were noted. Fine-needle aspirate samples were sent for TrueNAT assay, cytological examination, and ZN staining. USG neck was done for necrotic findings in the cervical lymph nodes. RESULTS: The TrueNAT positivity rate was 70%. TrueNAT sensitivity and specificity were assessed according to the cytology report, acid-fast bacilli (AFB) positivity on ZN stain, and the finding of necrosis in the cervical lymph node on the USG neck. The sensitivity and specificity of the TrueNAT assay were 80.49 and 77.78%, respectively, in accordance with necrosis on FNA cytology; 17.14 and 93.33%, respectively, in accordance with AFB positivity on ZN stain; and 74.29 and 33.33%, respectively, in accordance with lymph node necrosis on USG neck. CONCLUSION: The TrueNAT assay should be used as an adjunctive test in addition to the conventional cytological examination of the FNA sample of lymph nodes for the rapid diagnosis of tuberculosis. It also detects rifampicin resistance simultaneously.

Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.

BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease (CD) is a challenge in clinical practice. AIM: To investigate the ability of radiomics combined with machine learning methods to differentiate PIL from CD. METHODS: We collected contrast-enhanced computed tomography (CECT) and clinical data from 120 patients form center 1. A total of 944 features were extracted single-phase images of CECT scans. Using the last absolute shrinkage and selection operator model, the best predictive radiographic features and clinical indications were screened. Data from 54 patients were collected at center 2 as an external validation set to verify the robustness of the model. The area under the receiver operating characteristic curve, accuracy, sensitivity and specificity were used for evaluation. RESULTS: A total of five machine learning models were built to distinguish PIL from CD. Based on the results from the test group, most models performed well with a large area under the curve (AUC) (> 0.850) and high accuracy (> 0.900). The combined clinical and radiomics model (AUC = 1.000, accuracy = 1.000) was the best model among all models. CONCLUSION: Based on machine learning, a model combining clinical data with radiologic features was constructed that can effectively differentiate PIL from CD.