UNASSIGNED: To identify biomarkers in human blood or urine at an early stage of knee osteoarthritis (OA) and to elucidate if any can accurately differentiate between healthy controls and early knee OA patients and be considered as a candidate for widespread clinical use for early diagnosis of the disease.
UNASSIGNED: Medline, Embase and Web of Science were screened to identify comparative studies measuring differences in blood or urine biomarkers between healthy controls and knee OA patients at an early stage (grade 1 or 2 Kellgren-Laurence). Two independent reviewers screened the abstracts for eligibility, reviewed the full texts, assessed the methodological quality and extracted the data. The Joanna Briggs Institute critical appraisal tool for diagnostic test accuracy studies was used to assess the quality of the included studies. Due to relevant heterogeneity, meta-analysis was not appropriate.
UNASSIGNED: Five studies met the eligibility criteria. The examined biomarkers were adropin, collagen type II metabolite, C-terminal cross-linked telopeptide of type II collagen, C-terminal cross-linked telopeptide of type I collagen, cartilage oligomeric matrix protein, matrix metalloproteinase 3, N-terminal propeptide of procollagen type IIA, type I procollagen N-terminal propeptides, N-terminal osteocalcin, angiopoietin-2, follistatin, granulocyte colony-stimulating factor, hepatocyte growth factor, interleukin-8, leptin, platelet-derived growth factor-BB, platelet endothelial cell adhesion molecule-1, vascular endothelial growth factor and calprotectin and totalling 19 biomarkers. All of the biomarkers were studied only once in the selected papers.
UNASSIGNED: There is no reliable biomarker available to differentiate between early knee OA in patients and healthy controls, but a potential role of a cluster of biomarkers to close this gap. There are several limitations, including inappropriate study designs, small sample sizes, nonconsecutive patient groups and inadequate statistical methods for evaluating biomarker performance in studies included.
UNASSIGNED: Level III.

UNASSIGNED: This paper was to assess the diagnostic performance and clinical value of three-dimensional ultrasonography (3DUS), three-dimensional ultrasonography power Doppler (3DPD), and 3DUS combined with 3DPD in ovarian cancer (OC).
UNASSIGNED: The study was registered with PROSPERO (CRD 42023405765). PubMed and Web of Science were searched from inception to 25 January 2022, and reference lists of potentially eligible studies were also manually searched. Patient and study characteristics were extracted by two independent reviewers. Any discrepancies were addressed through discussion. The sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR, respectively), and the area under the receiver operating characteristic curve (AUC) were pooled separately.
UNASSIGNED: We retrieved 2,566 studies, of which 18 were finally enrolled, with 2,548 cases. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS were 0.89 (95% CI: 0.85-0.93), 0.93 (95% CI: 0.88-0.96), 13.1 (95% CI: 7.3-23.4), 0.11 (95% CI: 0.08-0.16), and 0.90 (95% CI: 0.87-0.93), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DPD were 0.90 (95% CI: 0.80-0.95), 0.85 (95% CI: 0.71-0.92), 5.8 (95% CI: 3.0-11.2), 0.12 (95% CI: 0.06-0.24), and 0.94 (95% CI: 0.91-0.96), respectively. The pooled sensitivity, specificity, PLR, NLR, and AUC for 3DUS combined with 3DPD were 0.99 (95% CI: 0.73-1.00), 0.95 (95% CI: 0.85-0.99), 21.9 (95% CI: 6.1-78.9), 0.01 (95% CI: 0.00-0.37), and 0.99 (95% CI: 0.98-1.00), respectively.
UNASSIGNED: 3DUS, 3DPD, and 3DUS combined with 3DPD are promising diagnostic tools for OC, alongside elevated sensitivity and specificity. However, the combination of 3DUS and 3DPD techniques has higher diagnostic efficiency.
UNASSIGNED: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42023405765.

The newly identified refractory adult-onset autoinflammatory syndrome known as VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome is brought on by somatic mutations in the ubiquitin-like modifier-activating enzyme 1 (UBA1) gene in hematopoietic stem and progenitor cells that change the expression of the UBA1 isoform. As a result, patients have a variety of hematologic and systemic inflammatory symptoms. All types of medical professionals should treat VEXAS syndrome seriously due to the high fatality rate. To better comprehend the condition and enhance the prognosis for VEXAS syndrome, this review article describes the essential traits and clinical signs of the condition. The discussion of future directions in the study of systemic inflammatory disorders brought on by somatic mutations concludes.

BACKGROUND: The rapid progress in imaging techniques has led to an upsurge in the incidence of optic nerve arteriovenous malformations (AVMs) diagnoses. Nevertheless, a comprehensive integration addressing their diagnostic and therapeutic attributes remains elusive.
UNASSIGNED: In this report, we present a case of optic nerve AVM in a patient who initially presented with progressive visual deterioration in the right eye. An orbital magnetic resonance imaging (MRI) scan revealed an abnormal signal intensity within the optic nerve region of the affected eye, and Computed Tomography Angiography (CTA) demonstrated the presence of a vascular malformation involving the optic nerve in the right eye. The diagnosis of optic nerve AVMs relies on Digital Subtraction Angiography (DSA). Given the challenging nature of surgical intervention, the patient opted for conservative management. Upon subsequent evaluation, no significant changes were observed in the patient\'s right visual acuity and visual field. Furthermore, a comprehensive literature review was conducted.
CONCLUSIONS: In summary, the principal clinical presentations associated with optic nerve AVMs include a deterioration in both visual acuity and visual field. Angiography serves as the preferred diagnostic modality to confirm optic nerve AVMs. Microsurgical intervention or interventional embolization techniques may offer effective management approaches to address this complex condition.

Breast cancer, the most prevalent malignant tumor among women, poses a significant threat to patients\' physical and mental well-being. Recent advances in early screening technology have facilitated the early detection of an increasing number of breast cancers, resulting in a substantial improvement in patients\' overall survival rates. The primary techniques used for early breast cancer diagnosis include mammography, breast ultrasound, breast MRI, and pathological examination. However, the clinical interpretation and analysis of the images produced by these technologies often involve significant labor costs and rely heavily on the expertise of clinicians, leading to inherent deviations. Consequently, artificial intelligence(AI) has emerged as a valuable technology in breast cancer diagnosis. Artificial intelligence includes Machine Learning(ML) and Deep Learning(DL). By simulating human behavior to learn from and process data, ML and DL aid in lesion localization reduce misdiagnosis rates, and improve accuracy. This narrative review provides a comprehensive review of the current research status of mammography using traditional ML and DL algorithms. It particularly highlights the latest advancements in DL methods for mammogram image analysis and offers insights into future development directions.

The increasing worldwide incidence of nontuberculous mycobacterial lung disease (NTM-LD) and the similarity of its manifestations to those of tuberculosis (TB) pose huge challenges in the diagnosis and treatment of NTM-LD, which is commonly misdiagnosed and mistreated as TB. Proper diagnosis and treatment at an early stage can greatly improve patient outcomes.
Mycobacterium avium was identified by mNGS in lung tissue of case 1 and bronchioalveolar fluid from case 2 that was not identified using conventional microbiological methods. Multiple NTM species were detected in the blood mNGS samples from case 3 who had disseminated NTM infection. Although NTM was isolated from blood culture, conventional methods failed to identify the organisms to the level of species. All three patients were suffering from and being treated for myelodysplastic syndrome, rheumatoid arthritis, systemic lupus erythematosus, or acute lymphoblastic leukemia, making them immunosuppressed and susceptible to NTM infections. Case 1 and Case 2 significantly improved after anti-NTM treatment, but case 3 succumbed to the infection due to her underlying medical illness despite aggressive treatment.
The cases in this study demonstrate the effectiveness of mNGS in facilitating and improving the clinical diagnosis of NTM infections. We propose combining mNGS with traditional diagnostic methods to identify pathogens at the early stages of the disease so that targeted treatment can be implemented.

Paediatric pleural tuberculosis (TB) is a paucibacillary disease, which increases the difficulty of examination. We aimed to assess the performance of pleural fluid adenosine deaminase (ADA) in the detection of paediatric pleural TB.
PubMed, Web of Science Core Collection, Embase and Cochrane Library databases were searched up to 20 December 2021. We used the bivariate and hierarchical summary receiver operating characteristic models to compute pooled estimates for the overall diagnostic accuracy parameters of ADA for diagnosing paediatric pleural TB.
Eight studies, including 290 pleural fluid samples, met the inclusion criteria. The pooled sensitivity of ADA was 0.85 (95% CI: 0.78-0.90, I2: 55.63% < 75%) for detecting patients with paediatric pleural TB. A total of 262 pleural fluid samples from four studies were included to differentiate patients with paediatric pleural TB from controls. At a unified cut-off value of 40 U/L, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the summary receiver operating characteristic curve of ADA were 0.89, 0.58, 2.09, 0.20, 10.48 and 0.89, respectively.
At a cut-off value of 40 U/L, the overall performance of ADA was good for detecting paediatric pleural TB, with relatively high sensitivity and low specificity. Key messageAccurate identification of paediatric pleural TB will help eliminate TB in children. At a cut-off value of 40 U/L, the overall performance of ADA was good for detecting paediatric pleural TB, with relatively high sensitivity and low specificity.

When investigating voice disorders a series of processes are used when including voice screening and diagnosis. Both methods have limited standardized tests, which are affected by the clinician\'s experience and subjective judgment. Machine learning (ML) algorithms have been used as an objective tool in screening or diagnosing voice disorders. However, the effectiveness of ML algorithms in assessing and diagnosing voice disorders has not received sufficient scholarly attention.
This systematic review aimed to assess the effectiveness of ML algorithms in screening and diagnosing voice disorders.
An electronic search was conducted in 5 databases. Studies that examined the performance (accuracy, sensitivity, and specificity) of any ML algorithm in detecting pathological voice samples were included. Two reviewers independently selected the studies, extracted data from the included studies, and assessed the risk of bias. The methodological quality of each study was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool via RevMan 5 software (Cochrane Library). The characteristics of studies, population, and index tests were extracted, and meta-analyses were conducted to pool the accuracy, sensitivity, and specificity of ML techniques. The issue of heterogeneity was addressed by discussing possible sources and excluding studies when necessary.
Of the 1409 records retrieved, 13 studies and 4079 participants were included in this review. A total of 13 ML techniques were used in the included studies, with the most common technique being least squares support vector machine. The pooled accuracy, sensitivity, and specificity of ML techniques in screening voice disorders were 93%, 96%, and 93%, respectively. Least squares support vector machine had the highest accuracy (99%), while the K-nearest neighbor algorithm had the highest sensitivity (98%) and specificity (98%). Quadric discriminant analysis achieved the lowest accuracy (91%), sensitivity (89%), and specificity (89%).
ML showed promising findings in the screening of voice disorders. However, the findings were not conclusive in diagnosing voice disorders owing to the limited number of studies that used ML for diagnostic purposes; thus, more investigations are needed. While it might not be possible to use ML alone as a substitute for current diagnostic tools, it may be used as a decision support tool for clinicians to assess their patients, which could improve the management process for assessment.
PROSPERO CRD42020214438; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214438.

Most parotid metastases have been reported to come from the head and neck; however, cases metastasized from the lung are extremely rare. Missed diagnoses and misdiagnoses occurred quite a few times. Thus, accurately identifying the clinical features of parotid metastasis of lung cancer is important. However, current studies about this issue are mostly case reports, and little is known about the detailed and systematic aspects. We reported three cases of parotid metastases from lung cancer and then systematically searched similar cases through \"Pub-Med\" and \"Web of Science\". Finally, twenty-three patients were included in the study. Eighty-three percent of which were males, and 19 patients were over 50 years old. In all cases with smoking history mentioned, 93% were smokers. The predominant pathological type was small cell lung cancer (SCLC, 13 patients, 56%). Seventeen combined with other site metastasis, while more than half of which were brain metastases. The survival time ranged from 3months-17years, and as for SCLCs, it was only 3months-40months. It can be concluded that clinical features, such as sex, age, smoking history, pathological types, and metastasis patterns, could provide valuable evidence for diagnosis. The lung seems to be the most common primary site of parotid metastases except for head and neck tumors. The two circumstances, SCLC coexisting with Warthin\'s tumor and parotid small cell carcinoma with lung metastasis, should be differentiated from parotid metastasis of lung cancer with caution For cases presented as SCLC, more aggressive strategies, such as chemotherapy with immunotherapy and maintenance therapy, may be more suitable. Due to the greater tendency of brain metastasis in such diseases, whole-brain radiation therapy, stereotactic radiosurgery or prophylactic cranial irradiation should be applied to corresponding patients in time. Additionally, lung cancer parotid metastases may be a marker of poor prognosis.

Nucleic acid molecular diagnostic technology plays an important role in the detection of severe fever with thrombocytopenia syndrome (SFTS). However, no relevant reports have been published on the accuracy of reverse-transcription polymerase chain reaction (RT-PCR) and reverse-transcription loop-mediated isothermal amplification (RT-LAMP) in the diagnosis of SFTS. Thus, we conducted a meta-analysis and systematic review to evaluate the accuracy of the two methods. On June 19, 2022, we comprehensively searched the PubMed, Embase, Cochrane Library, Web of Science, Scoups, Ovid, Proquest, China National Knowledge Infrastructure Database, Wan Fang Data, Traditional Chinese Medicine Database (Sinomed), VIP Database, and Reading Showing Database for articles on nucleic acid diagnostic techniques, such as RT-PCR and RT-LAMP, used to diagnose SFTS. Statistical analysis was performed using STATA 14.0 and Meta-Disc 1.4. Sixteen articles involving 2942 clinical blood samples were included in the analysis. RT-PCR and RT-LAMP were used as index tests, whereas RT-PCR or other detection methods were used as reference standards. The pooled values for the sensitivity, specificity, positive and negative likelihood ratios of the RT-PCR test were 0.97 (95% confidence interval [CI]: 0.92-0.99), 1.00 (95% CI: 0.98-1.00), 483.87 (95% CI: 58.04-4033.76), and 0.03 (95% CI:0.01-0.08), respectively. Those for the RT-LAMP test were 0.95 (95% CI: 0.91-0.97), 0.99 (95% CI: 0.93-1.00), 111.18 (95% CI: 13.96-885.27), and 0.05 (95% CI: 0.03-0.09), respectively. Both RT-PCR and RT-LAMP have high diagnostic value in SFTS and can be applied in different scenarios for laboratory confirmation or on-site screening.