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This letter critiques a cross-sectional study on pulse pressure in diabetes, noting that the design precludes causal inference and lacks adjustment for key covariates like antihypertensive drugs.
This letter critiques a cross-sectional study on pulse pressure in cardiovascular-kidney-metabolic disease, highlighting limitations such as inability to prove causality, residual confounding, and lack of generalizability.
To the Editor, Although the authors are to be commended on the large study population of type 2 diabetes mellitus,[1] the cross-sectional study design per SE stands out as a major weakness of this study. Cross-sectional studies evaluate both exposure and outcomes at the same point in time and therefore cannot define the relationship and causality between the pulse pressure (PP) and the outcomes of the cardiovascular, kidney, and metabolic (CKM) risk factors. Even though the outcomes show statistically significant associations for the PPs and their relationship to age, Hemoglobin A1c, and the albumin–creatinine ratio, these outcomes have not demonstrated the ability to show causality for the progression either of PP to metabolic diseases or to the metabolic diseases to PP. This is especially pertinent to the studies concerning the diseases that have bidirectional interactions concerning the cardiovascular, kidney, and metabolic function over time periods. The usage of the longitudinal cohort study designs might have improved the relationship concerning the time periods and the prediction for the independent prognostication of the outcomes.[2] An additional significant drawback is the propensity for residual confounding by imprecisely adjusting for clinically important covariates. Though adjustments were made using multivariate regression analysis, it did not adjust for some important covariates that have established relationships with PP, including the use of antihypertensive drugs, in particular, the use of renin-angiotensin system inhibitors, diabetes duration, smoking status, and presence of established cardiovascular disease. The use of drugs such as angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and sodium-glucose cotransporter-2 inhibitors has established relationships with arterial stiffness and PP, and failure to adjust for these covariates may have led to distortions in the relationships established. Moreover, using single-visit laboratory and blood pressure (BP) results may contain some variability in measurement, which may not establish a clear picture of the patients’ chronic metabolic or hemodynamic state. It is essential to adopt appropriate standards in epidemiology to address appropriate confounders and may overestimate the association in large datasets.[3] Finally, the external validity of this research is impacted by the fact that the data are derived from only one specialized center within the Middle East, catering to patients with diabetes. Furthermore, people accessing specialized centers may systematically differ from other diabetics regarding the severity of the condition, treatment accessibility, and comorbidities, which may lead to selection bias. Moreover, the exclusion of renal failures may impede the generalizability of the findings to more advanced cases of CKM syndrome, where PP may be a better prognostic indicator. Since there is evidence of regional variation regarding arterial stiffness, BP, and cardiovascular risk factors, care should be exercised while generalizing these findings to more diverse populations across different healthcare settings, and multicentric, more representative research is required to confirm its universality as a risk indicator of CKM syndrome.[4] Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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Bhatti et al. (2026) conducted a letter in Type 2 diabetes mellitus and cardiovascular-kidney-metabolic disease. Pulse pressure was evaluated. This letter critiques a cross-sectional study on pulse pressure in diabetes, noting that the design precludes causal inference and lacks adjustment for key covariates like antihypertensive drugs.
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