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Objective: The aims of this study were to provide population-based estimates of prevalence and incidence of any dementia and Alzheimer's dementia (AD) in the Campania region (South Italy) and to validate towards a clinical registry.
Methods: This was a population-based study, using routinely collected healthcare data of individuals living in the Campania region (South Italy) from 2015 to 2020. We included individuals aged ≥65 years alive at the prevalence day (January 1, 2021) who had at least one administrative record for dementia and/or AD from 2015 to 2020. Age-and sex-standardised prevalence rates were calculated using direct standardisation method (European population in 2020 as the reference population). To estimate the incidence, we tested three possible algorithms, which differed for the duration of the time interval between study baseline (January 1, 2015) and index date (first record for dementia and/or AD in administrative databases). We employed a clinical database for the validation of our algorithms towards neuropsychological test results.
Results: Among individuals aged over 65 years, 80,392 had dementia, of which 35,748 had AD. The age- and sex-standardised prevalence rates per 1,000 individuals for any dementia and AD were 77.64 (95% confidence interval [CI] = 77.57; 77.68) and 34.05 (95% CI = 34.01; 34.09), respectively. There were 82.10 incident cases of any dementia per 100,000 per year (0.79 sensitivity and 0.62 specificity) and 59.89 incident cases of AD per 100,000 per year (0.80 sensitivity and 0.59 specificity). The capture-recapture method showed a very low number of undetected cases (1.7% for any dementia and 3.0% for AD). Our algorithms showed acceptable performance with the area under the curve ranging from 0.59 to 0.72 and a double likelihood ratio of correctly identifying individuals above and below mini-mental status examination (MMSE) standard cut-offs (24 and 26).
Conclusions: Prevalence and incidence of any dementia and AD in the Campania region (South Italy) from 2015 to 2020 are in line with previous estimates from other countries. Our algorithm, integrating administrative and clinical data, holds potential for assessing dementia's epidemiological burden, identifying risk factors, planning healthcare access, and developing prevention strategies.
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http://dx.doi.org/10.1159/000539031 | DOI Listing |
J Neurochem
September 2025
Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy.
Patients with Duchenne muscular dystrophy (DMD) may experience neurobehavioral and cognitive concerns, including psychiatric symptoms, due to the absence of full-length dystrophin (Dp427), frequently accompanied by deficiencies in shorter isoforms. The lack of dystrophin affects neurophysiological processes from the uterine phase, impacting neural circuitry in brain regions such as the prefrontal cortex, hippocampus, and cerebellum. This leads to reduced inhibitory GABAergic transmission and altered hippocampal glutamatergic signaling.
View Article and Find Full Text PDFFront Public Health
September 2025
Department of Public Health, University "Federico II" of Naples, Naples, Italy.
Introduction: The prevalence and costs of dementias are rising due to demographic changes. Dementia care depends largely on informal caregivers and fragmented healthcare systems that often fail to meet the needs of people with dementia.
Objectives: This systematic review aims to identify unmet needs and barriers in European dementia care, providing a framework to improve health strategies.
Neurology
September 2025
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Background And Objectives: Multiple sclerosis (MS) is common in adults while myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is rare. Our previous machine-learning algorithm, using clinical variables, ≤6 brain lesions, and no Dawson fingers, achieved 79% accuracy, 78% sensitivity, and 80% specificity in distinguishing MOGAD from MS but lacked validation. The aim of this study was to (1) evaluate the clinical/MRI algorithm for distinguishing MS from MOGAD, (2) develop a deep learning (DL) model, (3) assess the benefit of combining both, and (4) identify key differentiators using probability attention maps (PAMs).
View Article and Find Full Text PDFLiver Int
October 2025
Gastroenterology, Hepatology and Transplantation Division, ASST Papa Giovanni XXIII, Bergamo, Italy.
Background And Aims: Hepatitis B (HBV) and Hepatitis Delta virus (HDV) infection have undergone significant changes in Italy over the past few decades, but reliable and updated prevalence of chronic hepatitis B (CHB) and Delta (CHD) data are lacking. The aim of the study was to describe the epidemiology of CHB and CHD in Italy in 2024, based on real-world data.
Methods: The number of patients with a healthcare expenditure exemption for CHB (016.
J Rehabil Med
September 2025
Department of Mental and Physical Health and Preventive Medicine, University of Campania "Luigi Vanvitelli", Naples, Italy.
Rehabilitation is increasingly recognized as a key component of health systems worldwide. To meet the growing demand for rehabilitation services, it is essential to strengthen academic capacity in Physical and Rehabilitation Medicine within universities. Academic structures are critical for training future physicians and professionals, and for advancing research and innovation in rehabilitation.
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