This study aimed to compare the diagnostic capability of Pulsar perimetry (Pulsar) in pre-perimetric glaucoma (PPG) and early glaucoma (EG) with that of Flicker perimetry (Flicker) and spectral-domain optical conference tomography (SD-OCT). This prospective cross-sectional study included 25 eyes of 25 PPG patients, 35 eyes of 35 EG patients, and 42 eyes of 42 healthy participants. The diagnostic capability using the area under the curve (AUC) of the best parameter and agreement of detectability between structural and functional measurements were compared. For PPG patients, the AUC of Pulsar, Flicker, OCT-disc, and OCT-macular was 0.733, 0.663, 0.842, and 0.780, respectively. The AUC of Flicker was significantly lower than that of OCT-disc (p = 0.016). For EG patients, the AUC of Pulsar, Flicker, OCT-disc, and OCT-macular were 0.851, 0.869, 0.907, and 0.861, respectively. There was no significant difference in AUC among these methods. The agreement between structural and functional measurements expressed by kappa value ranged from -0.16 to 0.07 for PPG and from 0.01 to 0.25 for EG. Although the diagnostic capability of Pulsar in the PPG and EG groups was equal to that of Flicker and SD-OCT, the agreements between structural and functional measurements for both PPG and EG were poor.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5468287 | PMC |
| http://dx.doi.org/10.1038/s41598-017-03550-x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach.
JMIR Form Res
January 2025
Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems.
View Article and Find Full Text PDFEnhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.
J Med Internet Res
January 2025
Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
Background: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.
View Article and Find Full Text PDFDelayed fracture healing (DFH), a common complication of post-fracture surgery, exhibits an incompletely understood pathogenesis. The present study endeavors to investigate the roles and underlying mechanisms of miR-656-3p and Bone Morphogenetic Protein-2 (BMP-2) in DFH. It was recruited 94 patients with normal fracture healing (NFH) and 88 patients with DFH of the femoral neck.
View Article and Find Full Text PDFExamining Mammalian facial behavior using Facial Action Coding Systems (FACS) and combinatorics.
PLoS One
January 2025
Department of Psychology, Lyon College, Batesville, Arkansas, United States of America.
There has been an increased interest in standardized approaches to coding facial movement in mammals. Such approaches include Facial Action Coding Systems (FACS), where individuals are trained to identify discrete facial muscle movements that combine to create a facial configuration. Some studies have utilized FACS to analyze facial signaling, recording the quantity of morphologically distinct facial signals a species can generate.
View Article and Find Full Text PDFDeep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma.
PLoS One
January 2025
Department of Pathology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Background: Ras-GTPase-activating protein (GAP)-binding protein 1 (G3BP1) emerges as a pivotal oncogenic gene across various malignancies, notably including nasopharyngeal carcinoma (NPC). The use of automated image analysis tools for immunohistochemical (IHC) staining of particular proteins is highly beneficial, as it could reduce the burden on pathologists. Interestingly, there have been no prior studies that have examined G3BP1 IHC staining using digital pathology.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!