Diagnostics最新文献

Background: This study used diffusion tensor imaging (DTI) to detect brain microstructural changes in participants with mild traumatic brain injury (mTBI) who experienced post-traumatic headaches, a common issue that affects quality of life and rehabilitation. Despite its prevalence, the mechanisms behind post-traumatic headache are not well understood. Methods: Participants were recruited from Level 1 trauma centers, and MRI scans, including T1-weighted anatomical imaging and DTI, were acquired 1 month post-injury. Advanced imaging techniques corrected artifacts and extracted diffusion tensor measures reflecting white-matter integrity. Pain sensitivity assays were collected at 1 and 6 months post-injury, including quantitative sensory testing and psychological assessments. Results: Significant aberrations in axial diffusivity in the forceps major were observed in mTBI participants (n = 12) compared to healthy controls (n = 10) 1 month post-injury (p = 0.02). Within the mTBI group, DTI metrics at 1 month were significantly associated with pain-related and psychological outcomes at 6 months. Statistical models revealed group differences in the right sagittal stratum (p < 0.01), left insula (p < 0.04), and left superior longitudinal fasciculus (p < 0.05). Conclusions: This study shows that DTI metrics at 1 month post-injury are sensitive to mTBI and predictive of chronic pain and psychological outcomes at 6 months.

Background/Objectives: This paper is significant in highlighting the importance of early and precise diagnosis of Parkinson's Disease (PD) that affects both motor and non-motor functions to achieve better disease control and patient outcomes. This study seeks to assess the effectiveness of machine learning algorithms optimized to classify PD based on vocal characteristics to serve as a non-invasive and easily accessible diagnostic tool. Methods: This study used a publicly available dataset of vocal samples from 188 people with PD and 64 controls. Acoustic features like baseline characteristics, time-frequency components, Mel Frequency Cepstral Coefficients (MFCCs), and wavelet transform-based metrics were extracted and analyzed. The Chi-Square test was used for feature selection to determine the most important attributes that enhanced the accuracy of the classification. Six different machine learning classifiers, namely SVM, k-NN, DT, NN, Ensemble and Stacking models, were developed and optimized via Bayesian Optimization (BO), Grid Search (GS) and Random Search (RS). Accuracy, precision, recall, F1-score and AUC-ROC were used for evaluation. Results: It has been found that Stacking models, especially those fine-tuned via Grid Search, yielded the best performance with 92.07% accuracy and an F1-score of 0.95. In addition to that, the choice of relevant vocal features, in conjunction with the Chi-Square feature selection method, greatly enhanced the computational efficiency and classification performance. Conclusions: This study highlights the potential of combining advanced feature selection techniques with hyperparameter optimization strategies to enhance machine learning-based PD diagnosis using vocal characteristics. Ensemble models proved particularly effective in handling complex datasets, demonstrating robust diagnostic performance. Future research may focus on deep learning approaches and temporal feature integration to further improve diagnostic accuracy and scalability for clinical applications.

Background/Objectives: Gastroesophageal reflux disease (GERD) is associated with extraesophageal syndromes that require an objective assessment of abnormal acid exposure to establish the diagnosis. The COuGH RefluX score has been proposed as a diagnostic tool for GERD in patients with chronic laryngopharyngeal symptoms. The aim of the study was to evaluate the diagnostic performance of the COuGH RefluX score in the Mexican population. Methods: A cross-sectional study was conducted in patients with chronic laryngopharyngeal symptoms. Patients with cough, globus, sore throat, dysphonia, and/or throat clearing of ≥8 weeks duration, 24 h pH-impedance monitoring (pH-IM), and without objective evidence of GERD (defined as acid exposure time >6%) were included in the study. The COuGH RefluX score tool was applied and stratified as low probability with ≤2.5 points, intermediate probability with 3.0 to 4.5 points, and high probability with ≥5.0 points. The kappa test assessed the concordance between both tests; the area under the curve (AUR), sensitivity (S), specificity (E), positive predictive value (PPV), and negative predictive value (NPV) were calculated for each result. Results: 164 patients were included; the prevalence of GERD by pH-IM was 32% vs. 40.3% by COuGH RefluX score, the agreement was weak (κ = 0.34; p < 0.001), but the AUR was good (0.720 ± 0.17; p < 0.001). A score ≤ 2.5 had S = 49%, E = 88%, PPV = 89%, and NPV = 42% to rule out proven GERD, while a score ≥ 5 had S = 65%, E = 71%, PPV = 52%, and NPV = 82% for proven GERD. Conclusions: The COuGH RefluX score has low sensitivity but adequate specificity for GERD diagnosis in Mexican patients with chronic laryngopharyngeal symptoms.

Objectives: Non-ST-elevation myocardial infarction (NSTEMI) is a common and severe condition that requires rapid and accurate risk assessment and treatment. The Naples prognostic score (NPS) is a novel risk score that integrates nutritional and inflammatory parameters. The aim of this study was to investigate the NPS as a predictor of one-year mortality in NSTEMI patients undergoing percutaneous coronary intervention (PCI). Methods: This retrospective study included 197 NSTEMI patients who underwent selective PCI from January 2020 to December 2020. The NPS was calculated based on the total cholesterol, serum albumin, neutrophil/lymphocyte ratio, and lymphocyte/monocyte ratio. Patients were categorized into two groups based on their NPS values: Group 1 (NPS 0-2) and Group 2 (NPS 3 or 4). The one-year mortality status of the patients was determined through phone calls or by querying the national death registry system. Results: During the follow-up period, the overall mortality rate was 19.3% (n = 38). The high NPS group exhibited a significantly higher mortality rate compared to the low NPS group, with rates of 33.7% and 8.1%, respectively (p < 0.001). A Cox regression analysis indicated that a high NPS score is an independent predictor of one-year mortality, with a hazard ratio of 4.52 (95% CI: 1.93-10.58; p < 0.001). Conclusions: The NPS is a simple, cheap, and easily accessible tool that can be used for risk stratification and treatment selection in NSTEMI patients. It also highlights the importance of inflammatory and nutritional status in influencing the prognosis of NSTEMI patients.

Background/Objectives: We aimed to evaluate asprosin and peptide tyrosine-tyrosine (PYY) levels in schizophrenia patients and the relationships between these levels and clinical severity, as well as whether these two hormones have a role in determining the disease and/or the phases of the disease. Methods: This study included 50 patients with schizophrenia in the remission phase, 50 in the acute phase, and 50 controls. The Positive and Negative Syndrome Scale (PANSS) was filled out for patients. The patients' biochemical parameters and asprosin and PYY levels were measured. Results: Levels of asprosin and PYY were significantly different in all three groups (p < 0.001, p < 0.001). In the remission phase group, asprosin levels had a negative effect on PANSS general symptomatology scores (p: 0.002, p < 0.001). In the acute phase group, while PYY levels showed a negative effect on PANSS general symptomatology scores (p: 0.031), asprosin levels had a negative effect on all subscales of PANSS (p < 0.001). In the acute phase, a one-unit decrease in asprosin levels was associated with a 93% increase in PANSS total scores. The results of the receiver operating characteristic (ROC) analysis to distinguish the acute phase showed that PYY could not be used for diagnosis (p: 0.066), but asprosin was associated with the acute phase of schizophrenia (p < 0.001) and both asprosin and PYY were associated with the disease (p < 0.001, p < 0.001). Conclusions: We think that both asprosin and PYY can be used as potential biomarkers to identify schizophrenia, and only asprosin to identify the phases of the disease. PYY and asprosin levels may be markers that can be used to determine clinical severity.

Background/Objectives: To investigate the mid- and long-term postoperative follow-up results of corneal crosslinking (CXL) treatment (using epi-on and epi-off techniques) in progressive keratoconus. Methods: This was a retrospective single center study conducted between October 2013 and July 2020. Patients who received CXL treatment with a diagnosis of progressive keratoconus were included in the study. Preoperative and postoperative recorded examination findings of autorefractometry, visual acuity, endothelial cell counts by specular microscopy, and corneal topography were analyzed retrospectively. According to the latest measurements, the results were divided into two groups: measurements between 6 and 12 months and measurements between 1 and3 years. Results: A total of 290 operated eyes of 201 patients were included in the study. The mean age of the patients was 21.34 ± 5.77 years, and 119 (59.2%) were male. Epi-off CXL was performed on 269 (92.8%) eyes and epi-on procedure was performed on 21 (7.2%) eyes. CXL had no significant effect on visual acuity. Significant improvement was observed in topographic/keratometric features of the cornea both after 6-12 months and after 1-3 years. Significant decreases were observed in K1 (p < 0.001), K2 (p < 0.001), KM (p < 0.001) values compared to the initial level. Conclusions: CXL treatment is an important treatment method in the treatment of keratoconus, preserving visual functions, significantly reducing the severity of astigmatism, and stopping the progression of keratoconus. Additionally, although epi-off and epi-on CXL methods were compared in our study, the sample size was limited, and more comprehensive and long-term studies are needed.

We report in this clinical case Mallory-Weiss syndrome suspected on computed tomography (CT) and confirmed on endoscopy. Mallory-Weiss syndrome is a rare cause of upper gastrointestinal bleeding from vomiting-induced mucosal laceration(s) at the gastroesophageal junction. The description of Mallory-Weiss Syndrome is rare on imaging and this observation provides CT semiological elements useful in detecting signs of Mallory-Weiss syndrome.

Background: Several thrombotic risk assessment models have been proposed for identifying patients with a high risk of thrombosis (the IMPEDE venous thromboembolism (VTE), SAVED, and PRISM scores) in multiple myeloma (MM). Recently, adding a biomarker (D-dimer) for the IMPEDE VTE score has shown that it can boost the detection power of IMPEDED VTE. However, data from studies comparing these models in MM are scarce. Even real-world data arguing the utility of thrombotic risk assessment models in MM from low- or middle-income countries like Türkiye are lacking. Methods: We aimed to show the possibility of detecting VTE using the IMPEDED VTE score in our cohort by retrospectively screening MM patients. Therefore, we aimed to compare the IMPEDE VTE, SAVED and IMPEDED VTE scoring models. Results: We conducted a retrospective analysis of 455 MM patients from three centers in Bursa, Türkiye, evaluating the incidence of VTE within six months of the treatment. The IMPEDED VTE score showed superior predictive accuracy (c-statistic of 0.701), compared to the IMPEDE VTE (0.618) and SAVED (0.633) scores, demonstrating the added value of D-dimer as a biomarker. The cumulative incidence of VTE in the cohort was 10.7%, comparable to rates observed in real-world studies. Conclusions: Despite the interventions and thrombotic risk assessment models, thrombosis remains a high-risk entity. Personalized risk assessment tools, such as IMPEDED VTE, could be used to manage thrombotic risk in MM patients, particularly in resource-limited settings. Albeit the thromboprophylaxis (51.6%), our findings support the utility of biomarker-enhanced models for better VTE-risk stratification, particularly in resource-limited settings.

Background: Prostate cancer management optimally requires non-invasive, objective, quantitative, accurate evaluation of prostate tumors. The current research applies visual inspection and quantitative approaches, such as artificial intelligence (AI) based on deep learning (DL), to evaluate MRI. Recently, a different spectral/statistical approach has been used to successfully evaluate spatially registered biparametric MRIs for prostate cancer. This study aimed to further assess and improve the spectral/statistical approach through benchmarking and combination with AI. Methods: A zonal-aware self-supervised mesh network (Z-SSMNet) was applied to the same 42-patient cohort from previous spectral/statistical studies. Using the probability of clinical significance of prostate cancer (PCsPCa) and a detection map, the affiliated tumor volume, eccentricity was computed for each patient. Linear and logistic regression were applied to the International Society of Urological Pathology (ISUP) grade and PCsPCa, respectively. The R, p-value, and area under the curve (AUROC) from the Z-SSMNet output were computed. The Z-SSMNet output was combined with the spectral/statistical output for multiple-variate regression. Results: The R (p-value)-AUROC [95% confidence interval] from the Z-SSMNet algorithm relating ISUP to PCsPCa is 0.298 (0.06), 0.50 [0.08-1.0]; relating it to the average blob volume, it is 0.51 (0.0005), 0.37 [0.0-0.91]; relating it to total tumor volume, it is 0.36 (0.02), 0.50 [0.0-1.0]. The R (p-value)-AUROC computations showed a much poorer correlation for eccentricity derived from the Z-SSMNet detection map. Overall, DL/AI showed poorer performance relative to the spectral/statistical approaches from previous studies. Multi-variable regression fitted AI average blob size and SCR results at a level of R = 0.70 (0.000003), significantly higher than the results for the univariate regression fits for AI and spectral/statistical approaches alone. Conclusions: The spectral/statistical approaches performed well relative to Z-SSMNet. Combining Z-SSMNet with spectral/statistical approaches significantly enhanced tumor grade prediction, possibly providing an alternative to current prostate tumor assessment.

The vulva is a complex anatomical organ that may present with a wide range of pathologies. Even if it can be easily investigated, correctly interpreting vulvar appearance is often challenging. Vulvar ultrasound is an emerging diagnostic technique that may be helpful in different aspects of vulvar pathology. We aimed to summarize the state of the art of vulvar ultrasound, provide the necessary theoretical bases of embryology and anatomy, describe the normal and pathological vulvar sonographic characteristics, and propose a feasible and reproducible methodology for vulvar ultrasound. Vulvar sonographic scan should be performed with a linear probe, preferably > 15 mHz, following a standardized methodology. The sonographic appearance of the normal vulva reflects the different histology of its structures and, thus, their embryogenetic origin. The description of a suspected vulvar lesion should include localization, dimensions, volume, type of growth, shape, appearance of the edges, depth of invasion, echogenicity, and identification of vascularization. Cystic dilatation of obstructed Bartolini ducts is the most common benign finding in the vulva (fluctuant structures in the posterior third of the labia majora containing clear mucous fluid). Malignant vulvar lesions appear as hypoechogenic or heterogeneous solid lesions with irregular margins and a high degree of vascularization. Extramammary Paget Disease presents a homogeneous hypoechogenic creeping area in the epidermis due to neoplastic cells typical of this disease. The potential applications of vulvar ultrasound are examining the content of a vulvar swelling to guide its management and assessing the response to medical treatment in the case of lichen sclerosus. In managing patients affected by vulvar malignancies, it may play a critical role in local staging, stromal invasion determination, measuring the distance from the midline, and assessing the eligibility for sentinel lymph node procedure. Vulvar ultrasound is a minimally invasive and economical test that can be performed with minimal equipment. Further studies will be necessary to validate the clinical applications, quantify the diagnostic performance, and evaluate the agreement between operators.