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Record W4417488450 · doi:10.1016/j.ajpc.2025.101386

Optimizing low-density lipoprotein cholesterol (LDL-C) management – a US physician survey of barriers and burdens

2025· article· en· W4417488450 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Preventive Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersMerck Sharp and DohmeMerck
KeywordsLdl cholesterolCholesterolMEDLINEDisease managementLipoprotein(a)Association (psychology)

Abstract

fetched live from OpenAlex

Background and Aims: Improving care of patients with hyperlipidemia requires an understanding of the barriers physicians perceive in prescribing low-density lipoprotein cholesterol (LDL-C)-lowering therapies. This study explores physicians' perceptions of time and resource burdens, identify perceived patient adherence barriers, and examine factors influencing physicians' decision-making in LDL-C management. Methods: This is a non-interventional, cross-sectional, online survey of US-based primary care practitioners (PCP) and cardiologists who recommended or provided lipid-lowering therapy (LLT) to ≥50 adults per month, practiced for ≥2 years, and completed the survey in English. The survey comprised multiple-choice, constant sum, and numerical questions about physician decision-making, patient management, and perceptions of patient attitudes/behaviors regarding LDL-C management. Descriptive univariate analyses were conducted. Results: 200 PCPs and 200 cardiologists completed the survey. Most physicians reported prescribing lipid-lowering therapy (LLT) and that patients declined injectable proprotein convertase subtilisin/kexin type 9 inhibitors (PCSK9i). They attributed this refusal to cost/insurance, fear/discomfort taking injections, and a preference for oral therapies. Physicians viewed patients with a history of ASCVD, with LLT experience, and those with greater understanding of ASCVD risk to have higher LLT adherence compared to those without. Most physicians spent a median of 10 min in shared decision-making conversations, regardless of therapies they prescribed. They reported needing longer to instruct patients during adherence counseling for PCSK9is than for oral therapies. Conclusions: Our findings suggest patient, clinician, and system barriers may all hinder LDL-C management and adherence. A greater understanding of the association between perceived barriers and real-world behaviors will help optimize lipid management.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.264
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it