Objective: Personality disorders (PDs) often remain unrecognized in older adults by doctors in general practice. Therefore, this study evaluated the diagnostic accuracy of a screening instrument, the Gerontological Personality Disorder Scale (GPS), in a Dutch general-practice population of older adults.
Method: The psychometric properties of the GPS patient (GPS-pv) and informant (GPS-iv) versions were assessed in a sample of 302 (144 male) patients (average age: 69.9 years) and 302 (124 male) informants (average age: 64.7 years), respectively, using an informant-based personality questionnaire (the Hetero-Anamnestische Persoonlijkheidsvragenlijst ) as a reference criterion.
Results: The internal consistency (average item correlation) of the subscale and total scores of the GPS-pv and GPS-iv were .12 (HAB), .16 (BIO), and .10 (total); and .16 (HAB), .15 (BIO), and .12 (total), respectively. The test--retest reliability was strong for both the GPS-pv (rs = .56 [HAB], rs = .67 [BIO], rs = .66 [total]) and the GPS-iv (rs = .52 [HAB], rs = .65 [BIO], rs = .68 [total]) versions. The sensitivity and specificity of the GPS-pv were .83 and .27, respectively, with a cutoff score of ≥1. Raising the cutoff score to ≥2, the sensitivity dropped to .59, whereas the specificity rose to .57. For the GPS-iv, a cutoff score of ≥3 maximized the sensitivity (.78) and specificity (.65).
Conclusion: The diagnostic accuracy of the GPS-iv was preferable to that of the GPS-pv. This is the first psychometric study to use the GPS as an age-specific screening instrument for PDs.
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http://dx.doi.org/10.1080/13607863.2015.1008989 | DOI Listing |
Fluids Barriers CNS
January 2025
Medical Image Processing Department, CHU Amiens-Picardie University Hospital, Amiens, France.
Background: The pressure gradient between the ventricles and the subarachnoid space (transmantle pressure) is crucial for understanding CSF circulation and the pathogenesis of certain neurodegenerative diseases. This pressure can be approximated by the pressure difference across the aqueduct (ΔP). Currently, no dedicated platform exists for quantifying ΔP, and no research has been conducted on the impact of breathing on ΔP.
View Article and Find Full Text PDFBiomark Res
January 2025
Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.
Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.
Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).
BMC Cancer
January 2025
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Objective: Rapid on-site evaluation (ROSE) of respiratory cytology specimens is a critical technique for accurate and timely diagnosis of lung cancer. However, in China, limited familiarity with the Diff-Quik staining method and a shortage of trained cytopathologists hamper utilization of ROSE. Therefore, developing an improved deep learning model to assist clinicians in promptly and accurately evaluating Diff-Quik stained cytology samples during ROSE has important clinical value.
View Article and Find Full Text PDFBMC Neurol
January 2025
Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, School of Medicine, College of Medicine, National Sun Yat-Sen University, No. 123 Ta-Pei Road, Niao-Sung Dist, Kaohsiung, 83305, Taiwan.
Background And Purpose: White matter hyperintensities in brain MRI are key indicators of various neurological conditions, and their accurate segmentation is essential for assessing disease progression. This study aims to evaluate the performance of a 3D convolutional neural network and a 3D Transformer-based model for white matter hyperintensities segmentation, focusing on their efficacy with limited datasets and similar computational resources.
Materials And Methods: We implemented a convolution-based model (3D ResNet-50 U-Net with spatial and channel squeeze & excitation) and a Transformer-based model (3D Swin Transformer with a convolutional stem).
Sci Rep
January 2025
College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830017, China.
Hepatic cystic echinococcosis (HCE), a life-threatening liver disease, has 5 subtypes, i.e., single-cystic, polycystic, internal capsule collapse, solid mass, and calcified subtypes.
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