Dear Editor, The authors are to be commended for examining the lipid profiles among patients with acute coronary syndrome in a real-world clinical setting and for using standard biochemical assays.1 Observational work of this kind is important for understanding the risk factor patterns in routine practice. Several methodological issues, however, may affect interpretation of the reported “distinct” dyslipidemia patterns across ST-elevation myocardial infarction, non-ST elevation myocardial infarction, and unstable angina. First, there are internal inconsistencies in subgroup reporting. The number of patients classified as having non–ST-elevation myocardial infarction versus unstable angina differs between the descriptive table and the subsequent analytical tables. In addition, the column headers in one table report identical sample sizes for all three groups despite clearly unequal denominators. Such inconsistencies conflict with reporting guidance for observational studies, which stresses transparent and internally coherent presentation of study populations and outcomes.2 They also make it difficult for readers to be confident about which lipid distributions correspond to each clinical subgroup. Second, the authors define dyslipidemia as the presence of any abnormality in several lipid indices, yet the analyses and tables focus on each component separately rather than on the composite exposure. Therefore, the study does not directly test the association between acute coronary syndrome subtype and dyslipidemia as defined in the Methods. Clear specification and consistent use of primary exposures and outcomes are central to contemporary observational reporting frameworks.2,3 Third, the study draws the strong conclusions about differences between acute coronary syndrome subtypes despite very small subgroup sizes for non-ST elevation myocardial infarction and unstable angina and largely nonsignificant between group comparisons. The cardiovascular methods literature highlights that subgroup comparisons with small cell counts yield unstable estimates with wide uncertainty and are prone to spurious differences or nondifferences.4 In addition, methodological work on the reporting of nonsignificant findings cautions against inferring absence of effect or asserting distinct patterns when statistical evidence is weak or inconclusive.5 In this context, the language describing clearly differentiated lipid patterns across subtypes appears stronger than warranted by the data shown. These limitations do not negate the contribution of the study, but they do suggest that the apparent differences in dyslipidemia profiles between acute coronary syndrome subtypes should be interpreted cautiously and viewed as hypothesis generating rather than definitive. More rigorous reporting and adequately powered subgroup analyses in future studies would strengthen inferences about lipid phenotypes in this population. We hope these comments are received in the constructive spirit intended and help guide both interpretation of the current findings and the design of future work in this area. Ethics clearance Not applicable. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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Ankur Sharma
Shadan Hospital and Institute of Medical Sciences
Sushma Narsing Katkuri
Dr. Reddy's Laboratories (India)
Varshini Vadhithala
Dr. D. Y. Patil Medical College, Hospital and Research Centre
Journal of the Practice of Cardiovascular Sciences
Saveetha University
Jaypee Institute of Information Technology
Graphic Era University
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Sharma et al. (Thu,) studied this question.
synapsesocial.com/papers/69fd7e79bfa21ec5bbf06ba6 — DOI: https://doi.org/10.4103/jpcs.jpcs_103_25