Assessment of the Validity of Self-Report as a Measure of Smoking Status in Patients Post-Myocardial Infarction
Bibliographic record
Abstract
Self-report is the standard method for assessment of smoking status in the outpatient setting for myocardial infarction (MI) patients. However, the validity of self-report in this patient population has not been previously investigated. Using data from a double-blind, placebocontrolled, randomized trial we examined the validity of self-report for assessment of smoking status in an outpatient setting for MI patients. Smoking was assessed by self-report and biochemical validation by expired carbon monoxide (CO). Abstinence was defined by a selfreport of no cigarettes smoked in the past week and a CO level of less than or equal to 10 parts per million (ppm). At 12 months, number of cigarettes smoked was positively correlated with CO level (r = 0.70). Results show that biochemical validation by CO does not substantially increase the likelihood of detecting smokers in MI patients. However, it may discourage patients from denying their smoking status and therefore should be considered for routine assessment of smoking status in the outpatient cardiac setting. Current clinical guidelines for secondary prevention in myocardial infarction (MI) patients recommend routine assessment of smoking status.1 In clinical trials, biochemical validation in conjunction with self-report is the conventional method for assessment of smoking status.2–4 In the outpatient
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.
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 | 0.022 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".