Diagnostics最新文献

Background/Objectives: Intervertebral disc degeneration is the most common cause of low back pain (LBP), and lumbosciatica is a major challenge to healthcare systems worldwide. For years, ozone therapy has been used with excellent results in intervertebral disc disease and in patients with LBP. In vitro studies have demonstrated the positive action of porcine collagen in extracellular matrix remodeling and homeostasis. These tissue changes, associated with LBP, may suggest an indication for combined ozone/collagen treatment in patients with LBP. However, no studies have been reported regarding this combination of treatments. Methods: The present work compared retrospective data of two treatment groups (each of 10 LBP patients): (A) oxygen-ozone therapy (OOT) vs. (B) OOT plus porcine collagen type 1 injections (COL I). Pain intensity and physiological function were assessed by the numerical rating scale (NSR) method. The Roland-Morris questionnaire was used to assess disability. Patient data were acquired before, during, and at the six-month follow-up. Significant differences were assessed by ANOVA and Student's t-test. Results: The analyses revealed significant statistical differences comparing the two arms, where the (OOT+COL I) treatment demonstrated a booster efficacy in pain (a reduction of 62% vs. 35%), while the questionnaire revealed a reduction in disability (70% vs. 31%). Conclusions: Therefore, this combination therapy (oxygen-ozone plus porcine injectable collagen) might be a promising approach for the management of patients with LBP.

Background/objectives: Besides a multitude of consequences patients on chronic renal replacement therapy have, anemia is one of the most prominent factors making a significant number of patients dependent on erythropoiesis-stimulating agent (ESA) therapy. The aim of this study was to examine the relationship between the levels of a broad spectrum of thrombo-inflammatory and oxidative stress-related biomarkers and the presence and level of ESA hyporesponsiveness in patients undergoing regular chronic hemodialysis.

Methods: This cross-sectional study included 96 patients treated with chronic hemodialysis. Levels of several thrombo-inflammatory and oxidative stress-related biomarkers, as well as demographic, clinical, and laboratory analyses, were collected and analyzed based on the calculated value of the ESA-hyporesponsiveness index (EHRI).

Results: In the analyzed sample, 58 patients received ESAs. Of all the investigated parameters, only body mass index (BMI), level of plasminogen activator inhibitor-1, and level of L-type fatty acid binding protein (L-FABP) were observed as significant predictors of EHRI. A significant diagnostic potential for ESA resistance has been observed in BMI and L-FABP between ESA-resistant and ESA-non-resistant groups of patients (p = 0.004, area under the curve 0.763 and p = 0.014, area under the curve 0.712, respectively) with the cut-off values of 25.46 kg/m² and 5355.24 ng/mL, respectively. Having a BMI of 25.46 kg/m² or less and an L-FABP level higher than 5355.24 ng/mL were observed as significant predictors of ESA resistance (odds ratio 9.857 and 6.125, respectively).

Conclusions: EHRI was positively predicted by low BMI and high levels of plasminogen activator inhibitor-1 and L-FABP. High levels of L-FABP and low BMI have been observed as strong predictors of ESA resistance.

Objectives: Our objective was to investigate the prevalence of macular complications detected by spectral-domain optical coherence tomography (SD-OCT) in a large Caucasian cohort of RP patients, highlight the major alterations in chorioretinal structure, and compare the macular structural changes in eyes affected by retinal dystrophies with those in healthy controls.

Methods: This was an observational, retrospective, and cross-sectional study. Three hundred and seven patients with RP were consecutively enrolled and underwent clinical assessment. In particular, SD-OCT images were used to ascertain the morphology of the posterior pole of patients with RP by evaluating the residual ellipsoid zone (EZ), the volume and thickness of the outer nuclear layer (ONLT), and subfoveal choroid thickness (SCT). At the same time, the pathological finding that the patients' vision was reduced under treatment was analyzed.

Results: A total of 436 eyes of 218 patients with RP were studied. Considering all of the eyes studied, 103 had cystoid macular edema (CME) (23.62%), 123 (28.21%) had vitreomacular traction (VMT), and 199 (45.75%) had epiretinal membranes (ERMs). There were also 12 (2.75%) cases of lamellar macular holes (LMHs), of which 3 (1.38% of all patients) cases were bilateral. Only 137 eyes (31.42%) did not have the above-mentioned alterations. SCT was significantly reduced compared to that of the control group (193.03 µm ± 67.90 SD vs. 295 µm ± 69.04 SD), while the foveal central macular thickness (FCMT) was greater (270.91 μm ± 74.04 SD vs. 221 µm ± 37.25 SD).

Conclusions: This research highlights the high incidence of macular complications. The results of our study indicate the importance of regular monitoring of RP patients and early intervention to avoid further complications in this group of subjects with severe visual field impairment to avoid further central vision loss.

Objective: Neurofilament light chain proteins (NfLs) are considered a promising biomarker of neuroaxonal damage in several neurological diseases. Their measurement in the serum and cerebrospinal fluid (CSF) of patients with dementia may be especially useful. Our aim was to compare the NfL measurement performance of two advanced technologies, specifically the Ella™ microfluidic platform and the Lumipulse™ fully automated system, in patients with cognitive disorders.

Methods: Thirty subjects with neurodegenerative cognitive disorders (10 with Alzheimer's Disease, 10 with Frontotemporal Dementia, and 10 with non-progressive Mild Cognitive Impairment) seen at the Cognitive Neurology Clinic of Modena University Hospital (Italy) underwent CSF and serum NfL measurement with both the Ella™ microfluidic platform (Bio-Techne, Minneapolis, MN, USA)) and the Lumipulse™ fully automated system for the CLEIA (Fujirebio Inc., Ghent, Belgium). Correlation and regression analyses were applied to assess the association between NfL concentrations obtained with the two assays in CSF and serum. The Passing-Bablok regression method was employed to evaluate the agreement between the assays.

Results: There were high correlations between the two assays (r = 0.976, 95% CI. 0.950-0.989 for CSF vs. r = 0.923, 95% CI 0.842-0.964 for serum). A Passing-Bablok regression model was estimated to explain the relationship between the two assays, allowing us to switch from one to the other when only one assay was available.

Conclusions: We found a good degree of correlation between the two methods in patients with neurocognitive disorders. We also established a method that will allow comparisons between results obtained with either technique, allowing for meta-analyses and larger sample sizes.

Recent advances have broadened the range of therapeutic options for mCRPC, with several new treatments, including novel hormonal therapies (enzalutamide, abiraterone), chemotherapeutic agents (docetaxel, cabazitaxel), immunotherapies (sipuleucel-T), and bone targeting radiopharmaceuticals (radium-223) showing improved clinical outcomes and receiving U.S. Food and Drug Administration approval. These new treatments provide new avenues for improving patient survival and quality of life. Radium-223, a targeted alpha-emitter, specifically targets bone metastases, offering palliative benefits and a potential increase in life expectancy. The integration of radium-223 with other treatments shows promise for managing mCRPC. However, the optimal sequencing and combination of radium-223 with other therapies are still being explored, with various clinical trials investigating new therapeutic approaches. The integration of these therapies, especially to provide more effective, personalized treatment strategies, requires further investigation. A thorough literature review was conducted on current treatments for mCRPC, including chemotherapeutic agents, oral hormonal therapies targeting the androgen receptor axis, immunotherapies, and radium-223. Ongoing clinical trials investigating radium-233 in the context of other therapies for the treatment of mCRPC patients were also reviewed. Further studies should focus on determining the optimal sequencing and dosing and identifying biomarkers that predict treatment response to enhance outcomes of mCRPC patients. This review underlines the rational strategies of combining radium-223 with other therapies, investigating their impact on bone in terms of delaying skeletal-related events, and managing bone disease progression in mCRPC patients.

Background/objectives: A cardiovascular complication of type 2 diabetes mellitus like coronary artery disease is influenced by a complex interplay between environmental, phenotypic, and genetic factors. The genetic mechanisms in the development of this pathology are not established. This study aims to evaluate the association of polymorphisms rs1011970, rs62560775, and rs564398 from the 9p21.3 locus with coronary artery disease in diabetic patients of the Kazakh population.

Methods: A total of 343 people participated in the case-control study: the control group consisted of 109 people with type 2 diabetes and coronary artery disease, while the control group included 234 people. Genotyping was performed using real-time PCR. Statistical analysis was carried out using Chi-square methods and calculating odds ratios (OR) with 95% confidence intervals (CI).

Results: According to the results, only the rs564398 polymorphism of the ANRIL gene was associated with coronary artery disease (p = 0.04). The CC genotype increased the risk of developing coronary artery disease by more than 1.5 times (1.62 (1.02-2.56)), whereas the TT genotype reduced the risk of coronary artery disease (0.39 (0.17-0.91)). The remaining polymorphisms, rs1011970 and rs62560775, were not associated with coronary artery disease.

Conclusions: Thus, this research further elicits the association of the ANRIL gene with cardiometabolic disease.

Background/objectives: Predicting patient readmission is an important task for healthcare risk management, as it can help prevent adverse events, reduce costs, and improve patient outcomes. In this paper, we compare various conventional machine learning models and deep learning models on a multimodal dataset of electronic discharge records from an Irish acute hospital.

Methods: We evaluate the effectiveness of several widely used machine learning models that leverage patient demographics, historical hospitalization records, and clinical diagnosis codes to forecast future clinical risks. Our work focuses on addressing two key challenges in the medical fields, data imbalance and the variety of data types, in order to boost the performance of machine learning algorithms. Furthermore, we also employ SHapley Additive Explanations (SHAP) value visualization to interpret the model predictions and identify both the key data features and disease codes associated with readmission risks, identifying a specific set of diagnosis codes that are significant predictors of readmission within 30 days.

Results: Through extensive benchmarking and the application of a variety of feature engineering techniques, we successfully improved the area under the curve (AUROC) score from 0.628 to 0.7 across our models on the test dataset. We also revealed that specific diagnoses, including cancer, COPD, and certain social factors, are significant predictors of 30-day readmission risk. Conversely, bacterial carrier status appeared to have minimal impact due to lower case frequencies.

Conclusions: Our study demonstrates how we effectively utilize routinely collected hospital data to forecast patient readmission through the use of conventional machine learning while applying explainable AI techniques to explore the correlation between data features and patient readmission rate.

Background/objectives: To assess the impact of a vendor-agnostic deep learning model (DLM) on image quality parameters and noise reduction in dental cone-beam computed tomography (CBCT) reconstructions.

Methods: This retrospective study was conducted on CBCT scans of 93 patients (41 males and 52 females, mean age 41.2 years, SD 15.8 years) from a single center using the inclusion criteria of standard radiation dose protocol images. Objective and subjective image quality was assessed in three predefined landmarks through contrast-to-noise ratio (CNR) measurements and visual assessment using a 5-point scale by three experienced readers. The inter-reader reliability and repeatability were calculated.

Results: Eighty patients (30 males and 50 females; mean age 41.5 years, SD 15.94 years) were included in this study. The CNR in DLM reconstructions was significantly greater than in native reconstructions, and the mean CNR in regions of interest 1-3 (ROI1-3) in DLM images was 11.12 ± 9.29, while in the case of native reconstructions, it was 7.64 ± 4.33 (p < 0.001). The noise level in native reconstructions was significantly higher than in the DLM reconstructions, and the mean noise level in ROI1-3 in native images was 45.83 ± 25.89, while in the case of DLM reconstructions, it was 35.61 ± 24.28 (p < 0.05). Subjective image quality assessment revealed no statistically significant differences between native and DLM reconstructions.

Conclusions: The use of deep learning-based image reconstruction algorithms for CBCT imaging of the oral cavity can improve image quality by enhancing the CNR and lowering the noise.

We present the case of a 36-year-old woman who presented to our clinic for a second opinion. After multiple previous surgeries, she presented with an abdominal wound infection, which was initially treated conservatively. In the further course, catamenial bleeding occurred as an unusual symptom, and the suspicion of a fistula formation was postulated. Subsequent surgical repair and consecutive histopathological diagnosis revealed evidence of a fistula with endometriosis genitalis externa and thus gave an explanation for this striking clinical case presentation.

Objectives: Can the type of implant rehabilitation influence peri-implant bone loss in case of full-arch mandibular prosthesis? The purpose of the study was to assess, using orthopantomograms (OPGs), the bone loss around implants in different types of implant-supported prosthetic rehabilitations and identify potential risk factors, associated with the number and location of implants, that may have an association with bone defects.

Methods: A radiographic study was conducted on 22,317 OPGs from 2010 to 2024. All OPGs with implant-supported prosthetic mandibular rehabilitations were included in the study.

Results: A total of 155 OPGs were evaluated, with peri-implant bone loss identified in 64 (41.3%). Distal implants (furthest from the center) across various positioning patterns were most susceptible to bone loss, with positions 3.6 and 4.6 demonstrating the most frequent occurrence (25 and 26 cases, respectively). The χ² test revealed significant associations between both the implant positioning pattern (p < 0.001) and number of implants (p < 0.001) with peri-implant bone loss. Also, by updating the sample of OPGs, increased susceptibility to bone resorption was found for implants placed distal to the mental foramen compared to mesial ones in full-arch-implant-supported fixed prostheses.

Conclusions: Prospective clinical studies will therefore be useful in investigating this finding further.