2022
DOI: 10.7717/peerj.13816
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Five-year LDL-cholesterol trend and its predictors among type 2 diabetes patients in an upper-middle-income country: a retrospective open cohort study

Abstract: Background Patients with diabetes have increased risks of cardiovascular diseases (CVD), and their LDL-cholesterol (LDL-C) has to be treated to target to prevent complications. We aim to determine the LDL-C trend and its predictors among patients with type 2 diabetes (T2D) in Malaysia. Methods This was a retrospective open cohort study from 2013 to 2017 among T2D patients in public primary health care clinics in Negeri Sembilan state, Malay… Show more

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Cited by 4 publications
(3 citation statements)
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References 19 publications
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“…The disconnection between guideline recommendations and actual prescribing practices and the deficiency in clinical care processes threaten the quality of disease management 20 , 39 . Our current analysis and other emerging evidence strongly suggest therapeutic inertia in diabetes, hypertension, and dyslipidaemia management among T2DM patients in Malaysia 16 , 20 , 27 , 40 . However, therapeutic inertia is inadequately described in the local clinical practice guidelines for diabetes and hypertension management 7 , 23 .…”
Section: Discussionsupporting
confidence: 51%
“…The disconnection between guideline recommendations and actual prescribing practices and the deficiency in clinical care processes threaten the quality of disease management 20 , 39 . Our current analysis and other emerging evidence strongly suggest therapeutic inertia in diabetes, hypertension, and dyslipidaemia management among T2DM patients in Malaysia 16 , 20 , 27 , 40 . However, therapeutic inertia is inadequately described in the local clinical practice guidelines for diabetes and hypertension management 7 , 23 .…”
Section: Discussionsupporting
confidence: 51%
“…However, a registry-based study is restricted to variables already captured in the registry, which may limit the ability to include additional important factors. 9 This study also focuses on traditional ML models over deep learning algorithms for their simplicity, interpretability, less computational resources and robustness to noise and outliers in the data. 17 Unfortunately, this may limit the ability to fully harness the potential of machine learning acquired through deep learning algorithms in capturing complex nonlinear relationships for predicting diabetes complications.…”
Section: Discussionmentioning
confidence: 99%
“…However, our patients fared worse than the global average in all lipid targets 20 . This is worrying because the gaps between actual performance and guideline recommendation represent a preventable burden of cardiovascular complications and should be optimised for better clinical and public health outcomes 46 .…”
Section: Discussionmentioning
confidence: 99%