Abstract Aims The association of glycemic variability with microvascular disease complications in type 2 diabetes (T2D) has been under-studied and remains unclear. We investigated this relationship using both Action to Control Cardiovascular Risk in Diabetes (ACCORD) and the Veteran Affairs Diabetes Trial (VADT). Methods In ACCORD, fasting plasma glucose (FPG) was measured 1 to 3 times/year for up to 84 months in 10 251 individuals. In the VADT, FPG was measured every 3 months for up to 87 months in 1791 individuals. Variability measures included coefficient of variation (CV) and average real variability (ARV) for fasting glucose. The primary composite outcome was time to either severe nephropathy or retinopathy event and secondary outcomes included each outcome individually. To assess the association, we considered variability measures as time-dependent covariates in Cox proportional hazard models. We conducted a meta-analysis across the 2 trials to estimate the risk of fasting glucose variability as well as to assess the heterogenous effects of FPG variability across treatment arms. Results In both ACCORD and the VADT, the CV and ARV of FPG were associated with development of future microvascular outcomes even after adjusting for other risk factors, including measures of average glycemic control (ie, cumulative average of HbA1c). Meta-analyses of these 2 trials confirmed these findings and indicated FPG variation may be more harmful in those with less intensive glucose control. Conclusions This post hoc analysis indicates that variability of FPG plays a role in, and/or is an independent and readily available marker of, development of microvascular complications in T2D.
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Heterogeneous treatment effects of intensive glycemic control on major adverse cardiovascular events in the ACCORD and VADT trials: a machine-learning analysis
Abstract Background Evidence to guide type 2 diabetes treatment individualization is limited. We evaluated heterogeneous treatment effects (HTE) of intensive glycemic control in type 2 diabetes patients on major adverse cardiovascular events (MACE) in the Action to Control Cardiovascular Risk in Diabetes Study (ACCORD) and the Veterans Affairs Diabetes Trial (VADT). Methods Causal forests machine learning analysis was performed using pooled individual data from two randomized trials (n = 12,042) to identify HTE of intensive versus standard glycemic control on MACE in patients with type 2 diabetes. We used variable prioritization from causal forests to build a summary decision tree and examined the risk difference of MACE between treatment arms in the resulting subgroups. Results A summary decision tree used five variables (hemoglobin glycation index, estimated glomerular filtration rate, fasting glucose, age, and body mass index) to define eight subgroups in which risk differences of MACE ranged from − 5.1% (95% CI − 8.7, − 1.5) to 3.1% (95% CI 0.2, 6.0) (negative values represent lower MACE associated with intensive glycemic control). Intensive glycemic control was associated with lower MACE in pooled study data in subgroups with low (− 4.2% [95% CI − 8.1, − 1.0]), intermediate (− 5.1% [95% CI − 8.7, − 1.5]), and high (− 4.3% [95% CI − 7.7, − 1.0]) MACE rates with consistent directions of effect in ACCORD and VADT alone. Conclusions This data-driven analysis provides evidence supporting the diabetes treatment guideline recommendation of intensive glucose lowering in diabetes patients with low cardiovascular risk and additionally suggests potential benefits of intensive glycemic control in some individuals at higher cardiovascular risk.
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- Award ID(s):
- 1914937
- NSF-PAR ID:
- 10391919
- Date Published:
- Journal Name:
- Cardiovascular Diabetology
- Volume:
- 21
- Issue:
- 1
- ISSN:
- 1475-2840
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Introduction Studies have reported that antidiabetic medications (ADMs) were associated with lower risk of dementia, but current findings are inconsistent. This study compared the risk of dementia onset in patients with type 2 diabetes (T2D) treated with sulfonylurea (SU) or thiazolidinedione (TZD) to patients with T2D treated with metformin (MET). Research design and methods This is a prospective observational study within a T2D population using electronic medical records from all sites of the Veterans Affairs Healthcare System. Patients with T2D who initiated ADM from January 1, 2001, to December 31, 2017, were aged ≥60 years at the initiation, and were dementia-free were identified. A SU monotherapy group, a TZD monotherapy group, and a control group (MET monotherapy) were assembled based on prescription records. Participants were required to take the assigned treatment for at least 1 year. The primary outcome was all-cause dementia, and the two secondary outcomes were Alzheimer’s disease and vascular dementia, defined by International Classification of Diseases (ICD), 9th Revision, or ICD, 10th Revision, codes. The risks of developing outcomes were compared using propensity score weighted Cox proportional hazard models. Results Among 559 106 eligible veterans (mean age 65.7 (SD 8.7) years), the all-cause dementia rate was 8.2 cases per 1000 person-years (95% CI 6.0 to 13.7). After at least 1 year of treatment, TZD monotherapy was associated with a 22% lower risk of all-cause dementia onset (HR 0.78, 95% CI 0.75 to 0.81), compared with MET monotherapy, and 11% lower for MET and TZD dual therapy (HR 0.89, 95% CI 0.86 to 0.93), whereas the risk was 12% higher for SU monotherapy (HR 1.12 95% CI 1.09 to 1.15). Conclusions Among patients with T2D, TZD use was associated with a lower risk of dementia, and SU use was associated with a higher risk compared with MET use. Supplementing SU with either MET or TZD may partially offset its prodementia effects. These findings may help inform medication selection for elderly patients with T2D at high risk of dementia.more » « less
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Abstract Background The metabolic changes that ultimately lead to gestational diabetes mellitus (GDM) likely begin before pregnancy. Cannabis use might increase the risk of GDM by increasing appetite or promoting fat deposition and adipogenesis.
Objectives We aimed to assess the association between preconception cannabis use and GDM incidence.
Methods We analysed individual‐level data from eight prospective cohort studies. We identified the first, or index, pregnancy (lasting ≥20 weeks of gestation with GDM status) after cannabis use. In analyses of pooled individual‐level data, we used logistic regression to estimate study‐type‐specific odds ratios (OR) and 95% confidence intervals (CI), adjusting for potential confounders using random effect meta‐analysis to combine study‐type‐specific ORs and 95% CIs. Stratified analyses assessed potential effect modification by preconception tobacco use and pre‐pregnancy body mass index (BMI).
Results Of 17,880 participants with an index pregnancy, 1198 (6.7%) were diagnosed with GDM. Before the index pregnancy, 12.5% of participants used cannabis in the past year. Overall, there was no association between preconception cannabis use in the past year and GDM (OR 0.97, 95% CI 0.79, 1.18). Among participants who never used tobacco, however, those who used cannabis more than weekly had a higher risk of developing GDM than those who did not use cannabis in the past year (OR 2.65, 95% CI 1.15, 6.09). This association was not present among former or current tobacco users. Results were similar across all preconception BMI groups.
Conclusions In this pooled analysis of preconception cohort studies, preconception cannabis use was associated with a higher risk of developing GDM among individuals who never used tobacco but not among individuals who formerly or currently used tobacco. Future studies with more detailed measurements are needed to investigate the influence of preconception cannabis use on pregnancy complications.
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Abstract Background Compared with medical therapy, catheter ablation of atrial fibrillation (AF) in patients with heart failure (HF) improves cardiovascular outcomes. Risk scores (CAAP‐AF and APPLE) have been developed to predict the likelihood of AF recurrence after ablation, have not been validated specifically in patients with AF and HF.
Methods We analyzed baseline characteristics, risk scores, and rates of AF recurrence 12 months postablation in a cohort of 230 consecutive patients with AF and HF undergoing PVI in the Duke Center for Atrial Fibrillation registry from 2009‐2013.
Results During a follow‐up period of 12 months, 76 of 230 (33%) patients with HF experienced recurrent AF after ablation. The median APPLE and CAAP‐AF scores were 1.5 ([Q1, Q3]: [1.0, 2.0]) and 4.0 ([Q1, Q3]: [3.0, 5.0]), respectively and were not different from those patients with and without recurrent AF. Freedom from AF was not different according to APPLE and CAAP‐AF scores. Discrimination for recurrent AF with the CAAP‐AF score was modest with a C‐statistic of 0.60 (95% CI 0.52‐0.67). Discrimination with the APPLE score was similarly modest, with a C‐statistic of 0.54 (95% CI: 0.47‐0.62).
Conclusions Validated predictive risk scores for recurrent AF after catheter ablation exhibit limited predictive ability in cohorts of AF and HF. Additional tools are needed to facilitate risk stratification and patient selection for AF ablation in patients with concomitant HF.
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1186/s12933-022-01496-7
