Purpose: To investigate longitudinal changes in choroidal thickness (CT) and ganglion cell-inner plexiform layer thickness (GC-IPLT) across distinct phenotypes of type 2 diabetes mellitus (T2DM) patients.
Design: Prospective cohort study.
Methods: T2DM patients were categorized into 5 groups (SAID, SIDD, SIRD, MOD, and MARD) using K-means clustering based on β-cell function and insulin resistance. Swept-source optical coherence tomography measured baseline and 4-year follow-up CT and GC-IPLT. Linear mixed-effects models assessed absolute and relative changes in CT and GC-IPLT across subtypes.
Results: Over a median 4.11-year follow-up, CT and GC-IPLT decreased significantly across all groups. Choroidal thinning rates were most pronounced in SIDD (-6.5 ± 0.53 µm/year and -3.5 ± 0.24%/year) and SAID (-6.27 ± 0.8 µm/year and -3.19 ± 0.37%/year), while MARD showed the slowest thinning rates (-3.63 ± 0.34 µm/year and -1.98 ± 0.25%/year). SIRD exhibited the greatest GC-IPLT loss (-0.66 ± 0.05 µm/year and -0.91 ± 0.07%/year), with the least in SIDD (-0.36 ± 0.05 µm/year and -0.49 ± 0.07%/year), all statistically significant (all P < 0.001). Adjusted for confounding variables, SIDD and SAID groups showed faster CT thinning than MARD [-2.57 µm/year (95% CI: -4.16 to -0.97; P = 0.002) and -2.89 µm/year (95% CI: -4.12 to -1.66; P < 0.001), respectively]. GC-IPLT thinning was notably accelerated in SIRD versus MARD, but slowed in SIDD relative to MARD [differences of -0.16 µm/year (95% CI: -0.3 to -0.03; P = 0.015) and 0.15 µm/year (95% CI: 0.03 to 0.27; P = 0.015), respectively].
Conclusions: Microvascular damage in the choroid is associated with SIDD patients, whereas early signs of retinal neurodegeneration are evident in SIRD patients. All these changes may precede the onset of DR.
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http://dx.doi.org/10.1016/j.ajo.2024.08.039 | DOI Listing |
JAMA Netw Open
November 2024
Department of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Importance: Little is known about the epidemiology of out-of-hospital cardiac arrest (OHCA) in patients with asystole in countries where prehospital resuscitation is not withheld or terminated.
Objective: To investigate the secular trends in the patient outcomes and advanced life support (ALS) procedures and evaluate the association of ALS procedures with favorable outcomes among patients with OHCA and asystole.
Design, Setting, And Participants: This cohort study analyzed data from a nationwide prospective OHCA registry in Japan.
Circ Cardiovasc Interv
October 2024
Department of Cardiology, Maasstad Hospital, Rotterdam, the Netherlands (P.C.S., V.P.).
Objectives: The aim was to assess the prevalence of never events (NEs) specific to urology in the United Kingdom and identify commonly occurring themes.
Methods: Data from the National Health Service (NHS) NEs website were obtained and all NEs from 2012 to 2022 were reviewed. Urology-specific NEs were identified and further analysed in their respective categories.
J Card Fail
April 2024
Emory University School of Medicine, Division of Cardiology, Atlanta, GA. Electronic address:
Background: Among patients with advanced heart failure (HF), treatment with a left ventricular assist device (LVAD) improves health-related quality of life (HRQOL). We investigated the association between psychosocial risk factors, HRQOL and outcomes after LVAD implantation.
Methods: A retrospective cohort (n = 9832) of adults aged ≥ 19 years who received durable LVADs between 2008 and 2017 was identified by using the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS).
Europace
March 2024
Department of Cardiology, Heart Center, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, Netherlands.
Aims: Recently, a genetic variant-specific prediction model for phospholamban (PLN) p.(Arg14del)-positive individuals was developed to predict individual major ventricular arrhythmia (VA) risk to support decision-making for primary prevention implantable cardioverter defibrillator (ICD) implantation. This model predicts major VA risk from baseline data, but iterative evaluation of major VA risk may be warranted considering that the risk factors for major VA are progressive.
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