Trends and impact of intravascular ultrasound and optical coherence tomography on percutaneous coronary intervention for myocardial infarction
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.
Bibliographic record
Abstract
Background: Intravascular imaging with either intravascular ultrasound (IVUS) or optical coherence tomography (OCT) during percutaneous coronary intervention (PCI) is associated with improved outcomes, but these techniques have previously been underutilized in the real world. We aimed to examine the change in utilization of intravascular imaging-guided PCI over the past decade in the United States and assess the association between intravascular imaging and clinical outcomes following PCI for myocardial infarction (MI). Methods: We surveyed the National Inpatient Sample from 2008 to 2019 to calculate the number of PCIs for MI guided by IVUS or OCT. Temporal trends were analyzed using Cochran-Armitage trend test or simple linear regression for categorical or continuous outcomes, respectively. Multivariable logistic regression was used to compare outcomes following PCI with and without intravascular imaging. Results: A total of 2,881,746 PCIs were performed for MI. The number of IVUS-guided PCIs increased by 309.9 % from 6,180 in 2008 to 25,330 in 2019 (P-trend < 0.001). The percentage of IVUS use in PCIs increased from 3.4 % in 2008 to 8.7 % in 2019 (P-trend < 0.001). The number of OCT-guided PCIs increased 548.4 % from 246 in 2011 to 1,595 in 2019 (P-trend < 0.001). The percentage of OCT guidance in all PCIs increased from 0.0 % in 2008 to 0.6 % in 2019 (P-trend < 0.001). Intravascular imaging-guided PCI was associated with lower odds of in-hospital mortality (adjusted odds ratio 0.66, 95 % confidence interval 0.60-0.72, p < 0.001). Conclusions: Although the number of intravascular imaging-guided PCIs have been increasing, adoption of intravascular imaging remains poor despite an association with lower mortality.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it