Modified balloon-stent kissing technique avoid side-branch compromise for simple true bifurcation lesions
Bibliographic record
Abstract
BACKGROUND: Coronary bifurcation remains one of the most challenging lesion subsets in interventinal cardiology. Provisional stenting (PS) is the dominate technique for bifurcation lesions, but the key problem is the deterioration of side branch. Balloon-stent kissing technique (BSKT) as a new systematic approach which is based on modified jailed balloon technique is applied to improve the procedure success. In our center, we proposed a modified balloon-stent kissing technique(M-BSKT), which routine usage of proximal optimizing technique (POT) after rewiring was added as an optimization step to BSKT. Thus, whether M-BSKT for addressing simple true coronary bifurcation lesions can provide more benefits in intra-operation effect and long term outcomes is still unknown. METHODS: A cohort of 120 consecutive patients underwent Percutaneous Coronary Intervention (PCI) with simple true coronary bifurcation lesions satisfied the criteria were included in this retrospective, single-center registry. To assemble a cohort with similar baseline characteristics, a 1:1 propensity-matched score was used. The primary outcomes were the rate of device and procedural success, the situation of side branch (SB) after main vessel (MV) inflation and the complications during intra-operative. The secondary outcomes were the clinical prognosis at 12 months such as rehospitalization for unstable angina and MACEs. RESULTS: Before propensity matching, there were no significant differences in primary and secondary outcomes between two groups. After propensity-matched was used, 68 patients with similar propensity scores were included. At immediate procedural, M-BSKT was associated with a lower risk of SB deterioration and the application of final kissing balloon inflation (FKBI)[P = 0.036]. For ACS patients, besides the significant differences of immediate SB deterioration [P = 0.014] and FKBI application [P = 0.033], the incidence of TIMI flow< 3 in the PS was statistically significant higher than M-BSKT [P= 0.042]. The prognosis at 12 months such as rehospitalization for unstable angina and MACEs were similar for two groups [P = 0.613]. CONCLUSION: These observations prove that the M-BSKT enables side branch to be better protected in simple true bifurcation lesions, by a narrow margin. It may improve the angiographic outcomes about side branch deterioration and final kissing balloon performing compared with PS, especially in ACS patients. However, long-term clinical outcomes did not differ between patients treated for M-BSKT and PS at 12 months.
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How this classification was reachedexpand
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) | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".