Evidence map›Paper›PMID 36578900›Full record

ReviewJournal of the ASEAN Federation of Endocrine Societies2022

A Comparison of Statin Treatment Algorithms Based on the ACC/AHA and Philippine Guidelines for Primary Prevention of Dyslipidemia in Statin-Naive Filipino Patients.

Bayani Pocholo Maglinte, Alex Junia, Jeremyjones Robles

Abstract readReview
In one paragraph

Review in Journal of the ASEAN Federation of Endocrine Societies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Bayani Pocholo MaglinteDepartment of Internal Medicine, Cebu Institute of Medicine, Cebu Velez General Hospital, Cebu City, Philippines.
Alex JuniaDepartment of Internal Medicine, Cebu Institute of Medicine, Cebu Velez General Hospital, Cebu City, Philippines.
Jeremyjones RoblesDepartment of Internal Medicine, Cebu Institute of Medicine, Cebu Velez General Hospital, Cebu City, Philippines.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This cross-sectional study evaluates the degree of agreement between the 2018 American College of Cardiology/American Heart Association (ACC/AHA2018) and 2020 Philippine Guideline (PG2020) treatment algorithms for the primary prevention of dyslipidemia among Filipinos. Methodology: This review included 159 charts of statin-naive Filipinos who are 45-79 years old. Using risk profile and lipid measurements, statin treatment recommendation was determined through the PG2020 algorithm and ACC/AHA-ASCVD Risk Estimator Plus web application. The degree of agreement was measured by Cohen's kappa statistic with the two algorithms as independent raters. Results: A total of 159 patients were included in the final analysis. There was a slight agreement with a kappa coefficient of 0.209 or 4.4% (95% CI 0.078-0.340, Conclusions: The low degree of agreement between the two treatment algorithms highlights the key demographic and ethnic variations in dyslipidemia management necessitating outcome-based studies to translate these differences. Overestimation of ASCVD risk calculation in the ACC/AHA2018 and consideration of important, unique risk factors among Filipinos favors the applicability of the Philippine guideline.

Indexed as

Cardiovascular DiseasesDyslipidemiasHydroxymethylglutaryl-CoA Reductase InhibitorsAgedAlgorithmsCross-Sectional StudiesHumansMiddle AgedPhilippinesPrimary PreventionUnited StatesHydroxymethylglutaryl-CoA Reductase Inhibitorsalgorithmsdyslipidemiahypercholesterolemiaprimary preventionstatins

Identifiers

PMID36578900
PMCPMC9758551

What OpenQuestion holds

Texttitle and abstract
LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.