Background: Advanced age is a major determinant of impaired prognosis among patients with ST-segment elevation myocardial infarction (STEMI). However, the mechanisms associated with suboptimal reperfusion and enhanced complications are still largely undefined. The aim of the present study was to assess the impact of age on the angiographic findings and the procedural results of primary percutaneous coronary intervention (pPCI) in patients with STEMI.
Methods: A consecutive cohort of patients admitted for STEMI treated with pPCI were included. Infarct-related artery (IRA) patency was defined for preprocedural TIMI flow 3.
Results: We included 520 patients, divided according to age tertiles (<61; 61-72; ≥73). Elderly patients were more often females, with hypertension, renal failure, prior myocardial infarction or PCI, with lower rates of smoking history, haemoglobin, leukocytes and cholesterol (P < 0.001), lower ejection fraction (P = 0.02), higher use of renin angiotensin system inhibitors, statins, ASA, calcium antagonists, diuretics and beta blockers. At angiography, for the IRA, percentage of thrombus (P = 0.02) and stenosis (P = 0.01), direct stenting (P = 0.02) and glycoprotein IIb-IIIa inhibitors (P = 0.04) inversely related with age, but for higher restenosis (P = 0.04). IRA patency was more common in patients aged ≥73 years (27.9% vs. 32.3% vs. 41.1%, P = 0.01). The impact of age on preprocedural TIMI flow was confirmed at multivariate analysis [adjusted odds ratio (95% confidence interval) = 0.68 (0.47-0.98), P = 0.04].
Conclusion: The present study shows that among STEMI patients undergoing primary PCI, more advanced age represents an independent predictor of preprocedural IRA patency. Future studies will define the implications on procedural results and long-term prognosis.
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http://dx.doi.org/10.2459/JCM.0000000000001482 | DOI Listing |
Diabetes Obes Metab
January 2025
Endocrinologie, Diabétologie Et Gynécologie Pédiatrique, Hopital Necker-Enfants Malades, Université Paris Cité, AP-HP centre, Paris, France.
Background: Transition from paediatric to adult healthcare is a turning point for patients with Type 1 diabetes (T1D). A gradual coordinated process connecting paediatric and adult healthcare providers may improve adherence to adult follow-up.
Aims: To describe a transition process developed jointly by paediatric and adult diabetology units and compare patients progressing or not to follow-up in adult care setting.
Otolaryngol Head Neck Surg
January 2025
Department of Otolaryngology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Objective: To evaluate factors impacting access to and timing of surgery in patients with submucous cleft palate (SMCP) and velopharyngeal dysfunction (VPD).
Study Design: Retrospective cohort study.
Setting: Single academic medical center.
Wound Repair Regen
January 2025
Research Unit for Plastic Surgery, University of Southern Denmark, Odense, Denmark.
The WOUND-Q is a patient-reported outcome measure for individuals with any type of chronic wound. This study aimed to identify patient and wound factors associated with the four WOUND-Q health-related quality of life (HRQL) scales: Life impact, Psychological, Sleep, and Social. Adults with a chronic wound were recruited internationally through clinical settings between August 2018 and May 2020, and through an online platform (i.
View Article and Find Full Text PDFEClinicalMedicine
December 2024
Nottingham Digestive Diseases Centre (NDDC), Translational Medical Sciences, School of Medicine, University of Nottingham, NG7 2UH, UK.
Background: Despite the availability of various pharmacological and behavioural interventions, alcohol-related mortality is rising. This systematic review aimed to critically evaluate the existing literature on the association between glucagon-like peptide-1 receptor agonists use (GLP-1 RAs) and alcohol consumption.
Methods: Electronic searches were conducted on Ovid Medline, EMBASE, PsycINFO, clintrials.
World J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
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