Clinical Cardiology最新文献

The recent article by Erbay et al. reporting improved sleep quality, anxiety, and quality of life in heart failure patients receiving SGLT2 inhibitors [1] addresses a clinically important but underexplored area. However, several methodological limitations merit attention before these findings are generalized.

First, there was a significant baseline imbalance in Pittsburgh Sleep Quality Index (PSQI) scores between groups (5.0 vs. 6.0, p = 0.036). This difference, favoring the SGLT2 inhibitor group at baseline, may partially explain the magnitude of improvement observed. While within-group analyses were performed, regression models should have included baseline PSQI as a covariate to mitigate this confounding [2].

Second, the multivariate logistic regression did not adjust for several potential confounders that could influence patient-reported outcomes, including changes in diuretic dosing, concurrent initiation of other guideline-directed medical therapies, and intercurrent hospitalizations. These variables are known to impact congestion, sleep, and mood in heart failure [3, 4].

Third, the subgroup analyses by ejection fraction status are based on small sample sizes, limiting statistical power and precision. Without reporting interaction p-values, the assertion of consistent benefit across EF strata is premature [5].

Fourth, multiple SF-36 domains and other secondary outcomes were tested without correction for multiplicity. In this setting, the risk of false-positive findings is high, particularly in small observational cohorts [6].

Lastly, the study's observational, single-center design precludes definitive causal inference, yet several statements in the discussion imply a treatment effect. This language should be tempered to reflect association rather than causation [7].

Given the increasing integration of SGLT2 inhibitors into heart failure care, it is critical that conclusions about novel patient-reported benefits be supported by rigorous methodology. Randomized controlled trials incorporating objective sleep measures (e.g., polysomnography) and adequate adjustment for confounding are needed to validate these intriguing findings.

Use of AI for paraphrasing and in analyzing the statistical model used in the study.

The authors declare no conflicts of interest.

We welcome the recent analysis of acute myocardial infarction (AMI) death in US adults aged ≥ 65 with documented psychoactive substance abuse disorders [1]. Attention by the authors to an elderly population is well-timed, in light of increased co-occurrence of cardiovascular disease and substance abuse in the elderly. Two important limitations—one clinical, the other methodological—are acknowledged, however, because they affect substantially both validity and interpretability of the results.

Epidemiological studies that use death certificate data for employment are fraught with a very high potential for case ascertainment bias in this particular situation. In elderly populations, AMI is frequently listed on death certificates by clinical history or circumstantial information in place of verifying electrocardiography or cardiac biomarker tests [2]. Challenging presentations, cross-competing comorbidities, and silent myocardial infarction are not uncommon in this group and make both under- and overattribution of AMI as a cause of death more likely [3].

Equally problematic is the determination of psychoactive substance use. Toxicology is not the norm for older deaths unless there is obvious suspicion, and when it is done, it can be a restricted panel only [4]. This results in severe underreporting of drug use. Social stigma, clinician refusal to report, and ignorance regarding how to distinguish from prescribed versus nonprescribed use contribute to the risk of misclassification. When both outcome and exposure are tainted by classification error, cause-specific mortality rate estimates can distort changes in reporting patterns rather than capturing epidemiologic trends. Follow-up analyses using mortality registry data here need to be controlled for this dual-source bias to maintain interpretive validity.

Second, operationalization of exposure—reducing all ICD-10 F10–F19 categories into a single combined “psychoactive substance use disorder” category—is clinically restrictive. All of those codes cannot be collapsed into one usefully homogeneous category from the viewpoint of cardiovascular pathophysiology. Risk of AMI due to alcohol is secondary to chronic remodeling and arrhythmogenesis of the myocardium; cocaine and amphetamines via acute coronary vasospasm and proarrhythmic effects; opioids via hypoxia and bradyarrhythmia; sedatives via induction of hypotension and delay in conduction [5].

By combining these mechanistically different exposures, the study conceals substance-specific patterns of mortality and prevents investigators from being able to determine whether trends are a result of stimulant-induced acute events, alcohol-induced chronic damage, or polypharmacy effects. This limitation reduces the value of the study for cardiologists, addiction specialists, and policymakers who need substance-specific data to implement effective interventions. Further

The authors demonstrated a striking and consistent rise in atrial fibrillation (AF)–related mortality involving obstructive sleep apnea (OSA), particularly among elderly, female, rural, and minority populations [1]. This important analysis highlights the growing public health burden of AF–OSA overlap. However, several issues merit further clarification and discussion.

The authors report a steep increase in AF-related mortality involving OSA over the past two decades [1]. However, as AF prevalence and mortality have also generally increased in the U.S. population [2], it is unclear whether the observed trend is specific to patients with comorbid OSA or merely reflects overall AF epidemiology. A comparative analysis of mortality trends in AF patients without OSA would be helpful to determine the additive risk associated with OSA.

During the study period (1999–2020), catheter ablation became increasingly adopted for rhythm control in AF [3]. Recent studies suggest that AF ablation is associated with improved long-term outcomes, particularly in younger male patients [4]. Yet, despite these advances, AF-related mortality in patients with OSA continued to rise. How do the authors interpret this apparent contradiction? Were these procedures less commonly used or less effective in the OSA subgroup?

The study identifies AF (ICD-10 I48.x) as the “underlying” cause of death and OSA (G47.33) as a “contributing” condition [1]. However, the clinical circumstances in which AF is recorded as the primary cause of death—distinct from its role as a comorbidity in stroke, heart failure, or sudden death—are not well defined. It would be informative to clarify how “AF-related mortality” was operationalized in this study and whether misclassification or variation in coding practices may have influenced the observed trends.

The authors correctly point out the rising burden of AF-related mortality in the presence of OSA [1]. Yet over the same period, mortality from stroke and heart failure—two major downstream complications of AF—has generally declined, partly due to improvements in anticoagulation and HF management [5]. This discrepancy raises the question of whether the increase in AF-related deaths reflects actual clinical deterioration or improved documentation of AF on death certificates.

While the use of CDC WONDER provides valuable national-level insights [1], the reliance on death certificate data introduces several limitations. OSA is often underdiagnosed, particularly among women, minorities, and older adults—groups in whom mortality increases were most pronounced. Additionally, data on OSA severity, AF subtype, comorbidities (e.g., heart failure, chronic kidney disease), and continuous positive airway pressure adherence were not available. These unmeasured variables may have played an important role in shaping th

We read with interest the article titled “Effect of Statin Intensity on Cardiovascular Outcomes and Survival Following Coronary Artery Bypass Grafting” recently published in Clinical Cardiology [1]. The study addresses a crucial area concerning optimal lipid management in patients undergoing Coronary Artery Bypass Grafting (CABG), particularly the impact of statin intensity on long-term cardiovascular outcomes.

While we commend the authors for conducting this relevant and timely observational study, we would like to raise several points for clarification and discussion, which might significantly impact the interpretation of the results:

First, we note considerable discrepancies in patient numbers between the comparison groups: No-statin (156 patients), low/moderate-intensity statin (1301 patients), and high-intensity statin (397 patients). Although the authors acknowledged this statistical concern due to the observational study design, such imbalanced group sizes may inherently introduce bias and confounding, limiting the reliability and generalizability of the conclusions.

Second, the authors mentioned that older patients and women were less likely to receive statins or were prescribed lower-intensity statins. This finding raises concerns regarding potential selection bias or disparities in clinical practice. It would be helpful for the authors to elaborate further on possible reasons for these discrepancies and their potential influence on clinical outcomes.

Third, the study did not adequately track patient compliance or continued usage of statins over the follow-up period, which is pivotal to understanding the true impact of the medication. Given that statin adherence significantly influences clinical outcomes, this limitation might have considerably affected the study's conclusions.

Additionally, the authors defined Major Adverse Cardiovascular Events (MACE) broadly to include acute coronary syndrome (ACS), cerebrovascular accident (CVA), and cardiovascular mortality. However, the study did not consider graft occlusion rates directly, which could significantly affect revascularization rates and subsequent MACE. Including graft occlusion data might have provided additional critical insights into statin efficacy.

Lastly, the timing of lipid measurements, which were taken variably between 1 and 3 months postoperatively, could introduce measurement bias. This variability in follow-up LDL measurements might limit the robustness of the conclusions drawn about the efficacy of lipid management.

Despite these concerns, the findings strongly suggest potential long-term benefits associated with high-intensity statin therapy in reducing cardiovascular risks post-CABG, especially evident beyond 2 years. This underscores the importance of robust randomized controlled trials to conclusively establish the most effective lipid-lowering strategies in post-CABG patients.

We appreciate the authors'

K. Kılıckesmez, D. Aras, M. Degertekin, et al., “Physician and Patient Preferences for Oral Anticoagulation Therapy Decision Making in Atrial Fibrillation: Results From a National Best–Worst Scaling Survey in Türkiye,” Clinical Cardiology 47 (2024): e70038. https://doi.org/10.1002/clc.70038

In the published version of this article, the Pref-Af Study Group was missing in the author by-line. The correct author list should be:

K. Kılıckesmez, D. Aras, M. Degertekin, N. Ozer, B. Hacibedel, K. Helvacioglu, U. Koc, B. Ozdengulsun, E. Dundar Ahi, Pref-Af Study Group, and O. Ergene

Additionally, the Acknowledgments section has been updated as follows:

Medical writing and editorial support was provided by Ferda Kiziltas at remedium Consulting Group. The Pref-Af study group contributed to this study during the data collection and the names of the contributors as follows: Betul Balaban Kocas, Firdevs Aysenur Ekizler, Ayse Colak, Ahmet Anil Baskurt, Erdal Durmus, and Ugur Nadir Karakulak.

We apologize for this error.