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Purpose: Cerebral DSA is a routine procedure with few complications. However, it is associated with presumably clinically inapparent lesions detectable on diffusion-weighted MRI imaging (DWI lesions). However, there are insufficient data regarding incidence, etiology, clinical relevance, and longitudinal development of these lesions. This study prospectively evaluated subjects undergoing elective diagnostic cerebral DSA for the occurrence of DWI lesions, potentially associated clinical symptoms and risk factors, and longitudinally monitored the lesions using state-of-the-art MRI.
Materials And Methods: Eighty-two subjects were examined by high-resolution MRI within 24 h after elective diagnostic DSA and lesion occurrence was qualitatively and quantitatively evaluated. Subjects' neurological status was assessed before and after DSA by clinical neurological examination and a perceived deficit questionnaire. Patient-related risk factors and procedural DSA data were documented. Subjects with lesions received a follow-up MRI and were questioned for neurological deficits after a median of 5.1 months.
Results: After DSA, 23(28%) subjects had a total of 54 DWI lesions. Significantly associated risk factors were number of vessels probed, intervention time, age, arterial hypertension, visible calcified plaques, and less examiner experience. Twenty percent of baseline lesions converted to persistent FLAIR lesions at follow-up. After DSA, none of the subjects had a clinically apparent neurological deficit. Self-perceived deficits were nonsignificantly higher at follow-up.
Conclusion: Cerebral DSA is associated with a considerable number of postinterventional lesions, some persisting as scars in brain tissue. Presumably because of the small lesion size and inconsistent location, no clinically apparent neurological deficits have been observed. However, subtle self-perceived changes may occur. Therefore, special attention is needed to minimize avoidable risk factors.
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http://dx.doi.org/10.1007/s00270-023-03415-z | DOI Listing |
World J Pediatr Congenit Heart Surg
September 2025
Postgraduate Program in Health Sciences, Medical School, Federal University of Amazonas (UFAM), Manaus, Amazonas, Brazil.
To analyze in-hospital mortality in children undergoing congenital heart interventions in the only public referral center in Amazonas, North Brazil, between 2014 and 2022. This retrospective cohort study included 1041 patients undergoing cardiac interventions for congenital heart disease, of whom 135 died during hospitalization. Records were reviewed to obtain demographic, clinical, and surgical data.
View Article and Find Full Text PDFJAMA Netw Open
September 2025
Social and Behavioral Sciences Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland.
Importance: Higher intellectual abilities have been associated with lower mortality risk in several longitudinal cohort studies. However, these studies did not fully account for early life contextual factors or test whether the beneficial associations between higher neurocognitive functioning and mortality extend to children exposed to early adversity.
Objective: To explore how the associations of child neurocognition with mortality changed according to the patterns of adversity children experienced.
Int J Surg
September 2025
Department of Gynecology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Background: Ovarian cancer remains the most lethal gynecological cancer, with fewer than 50% of patients surviving more than five years after diagnosis. This study aimed to analyze the global epidemiological trends of ovarian cancer from 1990 to 2021 and also project its prevalence to 2050, providing insights into these evolving patterns and helping health policymakers use healthcare resources more effectively.
Methods: This study comprehensively analyzes the original data related to ovarian cancer from the GBD 2021 database, employing a variety of methods including descriptive analysis, correlation analysis, age-period-cohort (APC) analysis, decomposition analysis, predictive analysis, frontier analysis, and health inequality analysis.