Objective: To examine demographic and clinical characteristics associated with diagnostic delay in psoriatic arthritis (PsA).
Methods: We characterized a retrospective, population-based cohort of incident adult (≥ 18 yrs) patients with PsA from Olmsted County, Minnesota, from 2000-2017. All patients met the classification criteria. Diagnostic delay was defined as the time from any patient-reported PsA-related joint symptom to a physician diagnosis of PsA. Factors associated with delay in PsA diagnosis were identified through logistic regression models.
Results: Of the 164 incident PsA cases from 2000 to 2017, 162 had a physician or rheumatologist diagnosis. Mean (SD) age was 41.5 (12.6) years and 46% were female. Median time from symptom onset to physician diagnosis was 2.5 years (IQR 0.5-7.3). By 6 months, 38 (23%) received a diagnosis of PsA, 56 (35%) by 1 year, and 73 (45%) by 2 years after symptom onset. No significant trend in diagnostic delay was observed over calendar time. Earlier age at onset of PsA symptoms, higher BMI, and enthesitis were associated with a diagnostic delay of > 2 years, whereas sebopsoriasis was associated with a lower likelihood of delay.
Conclusion: In our study, more than half of PsA patients had a diagnostic delay of > 2 years, and no significant improvement in time to diagnosis was noted between 2000 and 2017. Patients with younger age at PsA symptom onset, higher BMI, or enthesitis before diagnosis were more likely to have a diagnostic delay of > 2 years, whereas patients with sebopsoriasis were less likely to have a diagnostic delay.
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http://dx.doi.org/10.3899/jrheum.201199 | DOI Listing |
QJM
January 2025
HRB Clinical Research Facility Galway, School of Medicine, University of Galway, Galway, Ireland.
Background: The optimal approach to the diagnosis of atrial fibrillation in primary care is unclear.
Aim: To determine if external loop recorder (ELR) screening improves atrial fibrillation detection in community dwelling adults with a CHA2DS2-VASc score of greater than two.
Design: Randomised cross-over clinical trial.
Background: Phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI4) began in 2023. This time-period corresponded to MRI vendors introducing product sequences with compressed sensing (CS), cross-vendor adoption of arterial spin-labelling (ASL) and multi-band slice excitation, and hardware improvements (head-coils, increased gradient amplitudes). These advances enabled the acquisition of new imaging measures and reduced scan times.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Neuroimage Analytics Laboratory and Glenn Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Diseases, University of Texas Health San Antonio, San Antonio, TX, USA.
Background: The location of proposed brain MRI markers of small vessel disease (SVD) might reflect their pathogenesis and may translate into differential associations with cognition. We derived regional MRI markers of SVD and studied: (i) associations with cognitive performance, (ii) patterns most likely to reflect underlying SVD, (iii) mediating effects on the relationships of age and cardiovascular disease (CVD) risk with cognition.
Method: In 891 participants from The Multi-Ethnic Study of Atherosclerosis, we segmented enlarged perivascular spaces (ePVS), white matter hyperintensities (WMH) and microbleeds (MBs) using deep learning-based algorithms, and calculated white matter (WM) microstructural integrity measures of fractional anisotropy (FA), trace (TR) and free water (FW) using automated DTI-processing pipelines.
Alzheimers Dement
December 2024
University of California San Francisco (UCSF), San Francisco, CA, USA.
Background: As new anti-amyloid immunotherapies emerge for Alzheimer's disease (AD), it is clear that early diagnosis of AD pathology is crucial for treatment success. This can be challenging in atypical presentations of AD and, together with our reliance on CSF or PET scans, can, at times, lead to delayed diagnosis. Here, we further explore the possible role of plasma tau phosphorylated at threonine 217 (P-tau217) for the detection of primary AD or AD co-pathology when frontotemporal dementia spectrum disorders are the main clinical presentation.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Hanyang University, Seoul, Seoul, Korea, Republic of (South).
Background: This study investigates the impact of cognitive impairments on the acoustic characteristics of speech and explores the development of a non-invasive AI model for the diagnosis of Mild Cognitive Impairment (MCI).
Method: Specifically, using conversational speech data from MCI patients and healthy controls in the DementiaBank, the autocorrelation function (ACF) of the speech signal according to delay time was analyzed. Through such analysis, key acoustic indicators of the speech signal such as τ, ϕ, and τ, were calculated, and these were used to employ the concept of pitch strength in the diagnosis of MCI.
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