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Predictors and Prevalence of Obstructive Coronary Artery Disease in Patients Who Underwent Elective Invasive Coronary Angiography for Chronic Coronary Syndrome [Letter]
Authors Nugroho HSW
Received 20 May 2024
Accepted for publication 26 May 2024
Published 29 May 2024 Volume 2024:15 Pages 33—34
DOI https://doi.org/10.2147/RRCC.S479147
Checked for plagiarism Yes
Editor who approved publication: Dr Richard Kones
Heru Santoso Wahito Nugroho
Health Department, Poltekkes Kemenkes Surabaya, Surabaya, Indonesia
Correspondence: Heru Santoso Wahito Nugroho, Health Department, Poltekkes Kemenkes Surabaya, Pucang Jajar Tengah-56, Surabaya, Indonesia, Email [email protected]
View the original paper by Dr Beka and colleagues
Dear editor
The research with the title above has produced very valuable findings, which can be used as a basis for decision-making in order to improve the quality of service. In this case, researchers found four significant predictors of obstructive coronary artery disease (CAD) in patients who underwent elective invasive coronary angiography for chronic coronary syndrome, namely typical chest pain, diabetes mellitus (DM), chronic kidney disease, and smoking. Meanwhile, five other factors (age, sex, hypertension, pre-test probability and Framingham score) were not proven to be significant predictors.1
In this case, the researchers used logistic regression test, so that in the hypothesis, it was assumed that these nine factors had a direct effect on obstructive CAD. However, we believe that there are actually several factors that have an indirect effect, such as age and sex. For example, increasing age increases the risk of DM, and DM further increases the risk of obstructive CAD. We also consider that the Framingham score and pre-test probability are not independent predictors of other factors including age, sex, chest pain, hypertension, smoking, diabetes and dyslipidemia, so they can be excluded from the analysis.
Thus, we recommend that further analysis be carried out, so that the significance of the influence of each predictor can be determined, both directly and indirectly, with an appropriate method, namely path-analysis.2,3 This analysis will be much easier to carry out if it is done using a diagram-based statistical program. Because the researcher involves categorical data, an appropriate statistical program must be selected. In this case, one of the recommended programs is Smart-PLS because it is very popular, easy to operate with or without involving other statistical programs, and is specifically for modeling involving categorical data.2–5
It is hoped that this further analysis will provide more complete and in-depth information so that it can become the basis for accurate decision-making for the hospitals concerned. It would be very valuable if the results of this analysis could be published again in this journal as a response to our letter, so that it also provides new information that is useful for a wide audience.
Disclosure
The author reports no conflicts of interest in this communication.
References
1. Beka G, Demissie Z, Alemayehu B. Predictors and prevalence of obstructive coronary artery disease in patients who underwent elective invasive coronary angiography for chronic coronary syndrome at catheterization laboratory of tikur anbessa specialized hospital and gesund cardiac and medical center, Addis Ababa Ethiopia: retrospective study. Res Rep Clin Cardiol. 2024;15:5–16.
2. Nugroho HSW, Suiraoka IP, Sunarto. Comment: prevalence of hypercholesterolemia and awareness of risk factors, prevention and management among adults. Vasc Health Risk Manag. 2023;19:505–506. doi:10.2147/VHRM.S419214
3. Susatia B, Martiningsih W, Nugroho HSW. Response to “Prevalence and associated factors of musculoskeletal disorders among cleaners Working at Mekelle University, Ethiopia”. J Pain Res. 2020;13:2707–2708. doi:10.2147/JPR.S281683
4. Nugroho HSW, Suiraoka IP, Sunarto S. Response to: patients’ perception of patient-centered care and associated factors among patients admitted in private and public hospitals. Patient Prefer Adherence. 2023;17:1257–1259. doi:10.2147/PPA.S418973
5. Nugroho HSW, Alvarado AE, Mercado MA. Psychological status of primary medical staff during the COVID-19 outbreak. J Multidiscip Healthc. 2021;14:1181–1182. doi:10.2147/JMDH.S318246
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