Abstract 4141978: Surveying Healthcare Professionals' Awareness and Management of Inflammation as a Residual Cardiovascular Risk Factor.
Bibliographic record
Abstract
Introduction: Inflammation is a recognized residual CVD risk factor. However, the knowledge, diagnosis, and management of inflammation-related CVD risk among healthcare professionals (HCPs) remain scarce. Methods: The survey, consisting of 20 questions dedicated to HCPs, was developed by the International Lipid Expert Panel (ILEP). It was launched in March 2024 and promoted through websites, SoMe channels, and newsletters. Many questions allowed for multiple responses. The questionnaire is ongoing and available at the ILEP webpage. Results: We collected 264 responses within 3 months (64.4% males; 50.8% between 40-59 yrs.), mostly from physicians (72.7%, of which 49.6% were cardiologists, and 16.3% internal medicine specialists), but also researchers (6.8%) and academics (6.4%). HCPs from 50 countries participated in the survey. The highest response rates were from Poland: 26.9%, USA: 17.4%, Greece and Romania (4.5% for both). Only 43.4% of responders routinely measure hsCRP for CVD risk stratification, and only 20% had possibilities to measure both CRP, hsCRP, and IL-6. 28% knew the difference between CRP and hsCRP tests, and only 54.9% knew the approved hsCRP ranges to stratify CVD risk. 47.7% of the respondents recognized CRP as a causal risk factor of CVD, with only every 5 th recognizing IL-6 ( Fig.1 ). 71.2% of HCPs accepted statins, colchicine, and bempedoic acid as available therapies that might effectively reduce hsCRP elevated levels ( Fig.1&2 ); 11% suggested that one should only reduce general CVD risk. Besides having rather general knowledge of the anti-inflammatory role of statins or colchicine, there are still 23.1% and 39.8% of responders that recognized anti-inflammatory properties of ezetimibe and PCSK9 modulators, respectively ( Fig.2 ). A lot of inconsistency exists on the knowledge of the potential anti-inflammatory role of natural products, with the highest number of responses indicating curcumin and omega-3 acids (61.4% for both) ( Fig.1 ). In the case of elevated hsCRP, 74.2% of HCPs recommended intensification of lifestyle changes and background CVD therapies, while 9.8% suggested using nutraceuticals, and 6.8% were prone to just monitoring the patients ( Fig.2 ). Conclusions: There is a significant gap in knowledge regarding the diagnosis, biomarkers, and management of inflammation in CVD risk stratification. Enhanced education for medical students, physicians, and patients is crucial before targeted therapies become widely available.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".