Diagnostics最新文献

Background: This study aimed to compare the reproducibility and reliability of the AI-supported WebCeph and app-aided OneCeph cephalometric analysis programs with a manual analysis method and to evaluate the analysis times. Methods: The study material consisted of pretreatment lateral cephalograms from 110 cases. Cephalometric analyses were performed manually, using the WebCeph program, and using the OneCeph application. A total of 11 skeletal, 6 dental, and 3 soft tissue parameters were measured. Cephalometric analyses of 30 randomly selected cases were performed again using three methods. The analysis times were recorded. Results: The WebCeph program and OneCeph application are highly compatible with the manual analysis method in terms of all parameters, except for SN measurement. It was found that the WebCeph program and the OneCeph application demonstrated moderate agreement in U1-NA distance measurement, while statistically high agreement was observed among all three methods for other dental parameters. It was determined that there was a moderate agreement among the methods in terms of nasolabial angle, whereas a statistically high level of agreement was found for the other soft tissue parameters. The analysis time was found to be the lowest in the WebCeph program and the highest in the manual analysis method. Conclusions: The WebCeph program and OneCeph application showed a high degree of compatibility with the manual analysis method, except for SN, SNA, Gonial angle, Articular angle, U1-NA distance and nasolabial angle measurements. Due to the higher correlation between OneCeph and the manual method, it can be concluded that the OneCeph application is the best alternative to the manual method.

Objectives: This study evaluated the diagnostic performance of the S-Detect ultrasound system's three selectable AI modes-high-sensitivity (HSe), high-accuracy (HAc), and high-specificity (HSp)-for breast lesion diagnosis, comparing their performance in a clinical setting. Methods: This retrospective analysis evaluated 260 breast lesions from ultrasound images of 232 women (mean age: 50.2 years) using the S-Detect system. Each lesion was analyzed under the HSe, HAc, and HSp modes. The study employed ROC curve analysis to comprehensively compare the diagnostic performance of the AI modes against radiologist diagnoses. Subgroup analyses focused on the age (<45, 45-55, >55 years) and lesion size (<1 cm, 1-2 cm, >2 cm). Results: Among the 260 lesions, 73% were identified as benign and 27% as malignant. Radiologists achieved a sensitivity of 98.6%, specificity of 64.2%, and accuracy of 73.5%. The HSe mode exhibited the highest sensitivity at 95.7%. The HAc mode excelled with the highest accuracy (86.2%) and positive predictive value (71.3%), while the HSp mode had the highest specificity at 95.8%. In the age-based subgroup analyses, the HAc mode consistently showed the highest area under the curve (AUC) across all categories. The HSe mode achieved the highest AUC (0.726) for lesions smaller than 1 cm. In the case of lesions sized 1-2 cm and larger than 2 cm, the HAc mode showed the highest AUCs of 0.906 and 0.776, respectively. Conclusions: The S-Detect HSe mode matches radiologists' performance. Alternative modes provide sensitivity and specificity adjustments. The patient age and lesion size influence the diagnostic performance across all S-Detect modes.

Background/Objectives: The diagnosis of oral lichen planus (OLP) is challenging because many other oral diseases demonstrate similar clinical and microscopic features. Clinicopathological discrepancy and inter- and intraobserver variability in the histological assessment of OLP have been shown in the literature, as there are no unified diagnostic criteria for the disease. In 2016, the American Academy of Oral and Maxillofacial Pathology (AAOMP) proposed a new diagnostic set for OLP. The aim of the study was to assess the reliability of the AAOMP histological criteria in diagnosing OLP. Methods: In this retrospective study, 34 histological sections, once diagnosed as OLP, were revised by a second pathologist using the WHO criteria. Then, all specimens were analyzed for the presence (P) or absence (A) of the criteria listed in the AAOMP diagnostic set. The reproducibility of the histological diagnosis of OLP when applying the different sets of diagnostic criteria was assessed. Results: From the AAOMP diagnostic criteria, hydropic degeneration was found in 35.2%, lymphocytic exocytosis in 32.3%, mild epithelial dysplasia in 2.9%, verrucous epithelial architectural change in 0% and band-like lymphocytic infiltrate, confined to the epithelium-lamina propria interface in 55.8% of the samples. Reproducibility of the histological diagnosis of OLP was achieved in only 19.3% of the cases when applying the 1978 WHO criteria versus the newly proposed AAOMP criteria. Conclusions: A large number of OLP cases failed to meet the AAOMP histological criteria in the present study. Further studies are needed to assess the validity of the proposed diagnostic set.

Background: Point-of-care diagnostic tests are essential for confirming Onchocerca volvulus transmission in remote, resource-limited, onchocerciasis-endemic communities. In Maridi, South Sudan, we field-tested a novel "biplex A" rapid diagnostic test (RDT) developed by Drugs & Diagnostics for Tropical Diseases (DDTD), San Diego, California. Methods: In February 2023, children aged 3-9 years were recruited from study sites at different distances from the Maridi Dam, a known blackfly breeding site. O. volvulus antibodies were detected using the DDTD biplex A RDT, which detects antibodies to Ov16 and OvOC3261 at test line 1 and to Ov33.3 and OvOC10469 at test line 2, along with the commercially available Ov16 SD Bioline RDT. Both tests were performed on whole blood obtained via finger prick. The feasibility and acceptability of the DDTD biplex A RDT were assessed, and its results were compared with those of the Ov16 SD Bioline RDT. Results: A total of 239 children participated in the study. The anti-Ov16 seroprevalence detected by the Ov16 SD Bioline RDT was 30.2% (72/239), with the highest prevalence observed in children living closest to the Maridi Dam (p < 0.001). Testing with the DDTD biplex A RDT was determined to be feasible, acceptable, and easy to use in a field setting. The DDTD biplex A RDT test line 1 (anti-Ov16 and anti-OvOC3261) was positive in 35.1% (84/239) of children, while test line 2 (anti-Ov33.3 and anti-OvOC10469) was positive in 18.4% (44/239). Both lines were simultaneously visible in 15.5% (37/239). Conclusions: The DDTD biplex A RDT prototype was user-friendly and practical for field deployment. However, additional research is needed to evaluate its performance relative to the commercially available Ov16 SD Bioline RDT. The high anti-Ov16 seroprevalence that was observed underscores the ongoing O. volvulus transmission near the Maridi Dam. Strengthening the onchocerciasis elimination program in Maridi should be prioritized as a critical public health intervention.

Background/Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as a significant global burden, attributed to its increasing prevalence and strong correlation with metabolic syndrome and related conditions. Timely diagnosis and intervention are essential for minimizing the impact of MASLD. This study sought to analyze the efficacy of advanced anthropometric indices and non-invasive steatosis markers in diagnosing MASLD. Methods: This cross-sectional retrospective study evaluated the data from 578 Turkish patients admitted to our gastroenterology clinic. MASLD was diagnosed based on internationally recognized criteria. The evaluated parameters included body mass index (BMI); waist-hip ratio (WHR); waist-height ratio (WHtR); body roundness index (BRI); conicity index (CI); a body shape index (ABSI); visceral adiposity index (VAI); abdominal volume index (AVI); lipid accumulation product (LAP); fatty liver index (FLI); hepatic steatosis index (HSI); and triglyceride-glucose index (TyG) and its variants TyG-waist circumference(WC) and TyG-BMI. Results: Among 215 men, 103 (56.9%) met the criteria for MASLD, while 260 out of 363 women (65.5%) fulfilled the criteria. In the receiver operating characteristic (ROC) analysis for identifying MASLD, TyG-WC (0.826), TyG-BMI (0.820), and FLI (0.830) achieved the highest area under the curve (AUC) values, with statistically significant differences observed in their pairwise comparisons against the other parameters. Conclusions: TyG-WC and TyG-BMI are comparable to FLI in terms of simplicity of calculation and superior diagnostic accuracy, making them valuable non-invasive alternatives for MASLD screening and diagnosis.

Background: Reduced bone mass and density, hallmark features of osteopenia and osteoporosis, significantly increase the risk of fractures, falls, and loss of mobility, especially in post-menopausal women and the elderly. Methods: This quantitative 7T MRI study examines the features of fibular bone thinning and bone mineral density loss (BMD) in 107 individuals (43F/64M) across various ages, body mass indices (BMIs), and ethnicities. Results: Women had significantly lower cross-sectional bone wall thickness (BT) and bone tissue area (BA), along with greater BMD loss compared to men in those over age 50 (n = 77), but not in the younger group (n = 30). The bone g-factor, defined as the ratio of inner-to-outer bone diameters, increased with bone thinning, bone marrow expansion (BME), and muscle fat infiltration (MFI) but was independent of subcutaneous fat thickness (SFT). Bone thinning and BMD loss both tend to increase with BME and MFI. Additionally, bone density decrease correlated with bone mass loss, with a stronger association observed with BT than BA. Conclusions: These findings offer insights into the effects of aging and sex on skeletomuscular health, with implications for strategies to mitigate bone loss in osteoporosis and osteosarcopenia.

Background/Objectives: Paediatric osteoarticular infections (POAIs) present unique diagnostic and therapeutic challenges. Microbiological culture (MC) is typically time-consuming and lacks sensitivity, especially when patients have received antibiotics. The BIOFIRE^® Joint Infection Panel (BJIP) is a syndromic molecular assay for the direct identification of most pathogens causing POAIs. Methods: We evaluated BJIP in 17 synovial fluids, and then, we retrospectively assessed its utility in 93 off-label specimens (i.e., 25 purulent fluids/biopsies and 68 whole blood samples). All specimens were collected from October 2022 to March 2024 from paediatric patients admitted at the Bambino Gesù Children's Hospital in Rome. Results: A bacterial pathogen was isolated in only one of 17 synovial fluid cultures, while BJIP identified eight additional microorganisms in MC-negative cases. The most frequently detected pathogen was S. aureus (44.5%, 4/9). BJIP performance in synovial fluids showed an overall positive percentage agreement (PPA) and negative percentage agreement (NPA) of 100% and 88.1%, respectively, compared to MC. All positive results (n/N = 9/17) were considered medically significant, with an increase in NPA to 100%. In purulent fluids/biopsies, BJIP and MC were concordant in 72% of cases (n/N = 18/25), with a per-sample PPA and NPA of 90% and 60%, respectively. For whole blood samples, almost all samples were negative by both methods (i.e., reference blood culture and BJIP), and the molecular test did not enable any further microbiological diagnosis. Conclusions: The BIOFIRE^® Joint Infection Panel rapidly and accurately enabled or excluded a diagnosis of a POAI (~1 vs. 24-96 h for MC), optimising antimicrobial therapy.

Background: Aortic stenosis (AS) is one of the most common valvular heart diseases, particularly in the elderly, with a prevalence of approximately 3% in individuals over 75 years of age. Aortic valve replacement (AVR) remains the standard treatment, yet postoperative hemodynamic assessment is often complicated by variations in prosthetic valve size, left ventricular ejection fraction (LVEF), effective orifice area (EOA), and body surface area (BSA). These factors significantly influence prosthetic valve function and contribute to patient-prosthesis mismatch (PPM), which has been associated with worse clinical outcomes. Traditional transvalvular gradient measurements often fail to account for these patient-specific variables. This study introduces a novel approach to standardized gradient calculations, aiming to enhance the accuracy and comparability of prosthetic valve assessments. Methods: A retrospective analysis was conducted on 115 patients who underwent mechanical AVR at a single center. Patients were categorized into three groups based on the prosthetic valve type: St. Jude Medical (SJM) HP (n = 31); SJM Regent (n = 54); and those who underwent aortic root enlargement (ARE) (n = 30). Preoperative and postoperative transthoracic echocardiography (TTE) was performed to measure conventional and standardized transvalvular gradients. Four novel standardized gradient calculations were developed to adjust for individual hemodynamic differences, improving the accuracy of prosthetic valve function assessment. Results: Standardized gradient calculations demonstrated significant differences between prosthesis types. Postoperative standardized gradients were significantly higher in the SJM HP group compared to the SJM Regent and aortic-root-enlargement groups (p < 0.001, p < 0.05). The lowest standardized gradients were observed in patients who received the SJM Regent prostheses (p < 0.05). Although conventional measurements showed no significant differences, standardized calculations revealed that patients with 19 mm prostheses exhibited significantly higher transvalvular gradients than those with 21 mm prostheses (p < 0.05), emphasizing the clinical importance of prosthesis size in postoperative hemodynamics. Conclusions: Standardized gradient calculations provide a more objective, reliable, and patient-specific assessment of prosthetic valve function by minimizing interpatient variability. This approach improves the detection of patient-prosthesis mismatch and optimizes postoperative hemodynamic evaluation, potentially leading to better prosthesis selection and surgical decision-making. However, further validation is required in larger cohorts before these methods can be widely adopted into clinical practice. Future studies should assess their impact on long-term clinical outcomes, including left ventricular remodeling and patient survival.

Background: Typhoid fever remains a significant public health challenge, especially in developing countries where diagnostic resources are limited. Accurate and timely diagnosis is crucial for effective treatment and disease containment. Traditional diagnostic methods, while effective, can be time-consuming and resource-intensive. This study aims to develop a lightweight machine learning-based diagnostic tool for the early and efficient detection of typhoid fever using clinical data. Methods: A custom dataset comprising 14 clinical and demographic parameters-including age, gender, headache, muscle pain, nausea, diarrhea, cough, fever range (°F), hemoglobin (g/dL), platelet count, urine culture bacteria, calcium (mg/dL), and potassium (mg/dL)-was analyzed. A machine learning metamodel, integrating Support Vector Machine (SVM), Gaussian Naive Bayes (GNB), and Decision Tree classifiers with a Light Gradient Boosting Machine (LGBM), was trained and evaluated using k-fold cross-validation. Performance was assessed using precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). Results: The proposed metamodel demonstrated superior diagnostic performance, achieving a precision of 99%, recall of 100%, and an AUC of 1.00. It outperformed traditional diagnostic methods and other standalone machine learning algorithms, offering high accuracy and generalizability. Conclusions: The lightweight machine learning metamodel provides a cost-effective, non-invasive, and rapid diagnostic alternative for typhoid fever, particularly suited for resource-limited settings. Its reliance on accessible clinical parameters ensures practical applicability and scalability, potentially improving patient outcomes and aiding in disease control. Future work will focus on broader validation and integration into clinical workflows to further enhance its utility.

Background/Objectives: Hypospadias, a common congenital anomaly in males, presents significant challenges in diagnosis, management, and long-term care. Despite its prevalence, research into the condition has been hampered by the lack of integrated biobank cohorts linking clinical, phenotypic, and surgical data with biological samples. This study aimed to establish the Hypospadias Biobank Cohort (HBC), a comprehensive resource designed to advance the understanding of hypospadias etiology and improve patient outcomes. Methods: The HBC was developed using a multi-phase approach, enrolling participants from specialized clinics between April 2022 and September 2024. Biological samples (blood and tissue) were collected under standardized protocols following informed consent. Detailed clinical data, including hypospadias severity, associated anomalies, and surgical outcomes, were systematically recorded and integrated into a robust database to support translational research. Results: The cohort included a diverse group of patients with varying severity of hypospadias, many of whom also presented with associated anomalies. Surgical outcomes were tracked, revealing important correlations between severity and postoperative complications. Preliminary biological analyses identified potential biomarkers associated with hypospadias severity and recovery. The full details of these results will be presented in a separate publication. The comprehensive database is continuously updated with longitudinal follow-up data, supporting future translational research. Conclusions: The Hypospadias Biobank Cohort represents a groundbreaking resource for translational research, offering unprecedented insights into the clinical and phenotypic spectrum of hypospadias. By enabling the refinement of classification systems and the development of evidence-based surgical techniques, the HBC has the potential to transform the management of this congenital condition. Ongoing research leveraging the HBC will further unravel the complex interplay among clinical presentation, surgical interventions, and patient outcomes, paving the way for personalized care strategies and improved long-term results.