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Record W2953250157 · doi:10.1136/heartjnl-2018-ics.18

18 Rotational atherectomy in the modern cardiac catheterisation laboratory patient demographics, procedural characteristics and clinical outcomes

2018· article· en· W2953250157 on OpenAlexaboutno aff
J J Coughlan, Samer Arnous, Thomas J. Kiernan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConventional PCIAnginaDemographicsAspirinRetrospective cohort studyCreatinineMedical recordCanadian Cardiovascular SocietyInternal medicineSurgeryMyocardial infarctionCardiology

Abstract

fetched live from OpenAlex

Aim The objective of this study was to define the patient demographics, periprocedural characteristics and mid to long term outcomes associated with rotational atherectomy in modern clinical practice in Ireland. Methods We performed a retrospective analysis of all patients who underwent rotational atherectomy in two Irish centres. Data on all patients was collected from the electronic patient records system. Baseline characteristics were collected for all patients. This included demographic and procedural characteristics. Demographic characteristics included age, co-morbidities, medications and presentation. Long term follow up was obtained at 3 and 12 months to assess clinical response. NYHA functional class and CCS angina scores were evaluated at 3 months and 12 months post procedure. 66 cases were identified over the study period and a database of patients was produced. Results 66% of patients were male. Mean age was 72±8.12 years (Range 54–86 years). 90.6% of our patients were hypertensive, 32.3% were diabetic. 28.33% had CKD and 96.88% had hypercholesterolaemia. 44% were current smokers, 35.6% never smokers and 20.33% ex-smokers. Mean weight was 79.66±17.67 kg (Range 42.6–124 kg) and mean creatinine was 104.77±70.03 (Range 56–398). 40.6% of patients had previous PCI, 31.25% had previous failed attempts at PCI and 15.625% had previously had coronary artery bypass grafting. 98.5% of patients were on Aspirin and 92.3% were on a second antiplatelet agent. Periprocedural complications were detailed for all procedures based on pre-specified criteria. The most common complications reported were coronary artery dissection (9.09%) and bleeding (9.2%). 2 patients required dialysis post procedure (3.03%), 1 patient required emergency CABG (1.5%) and 1 patient suffered cardiac death (1.5%). Coronary artery rupture and cardiac tamponade did not occur in any cases. We also analysed for any association between outcomes and categorical variables. These included burr size, femoral vs radial access and age (Over/Under 75). We found no statistically significant difference between complication rates between cases with burr size 1.25 mm and cases using burr size of over 1.25 mm (18.4% vs 10%, p=0.33). Similarly complication rates were not significantly different for radial versus femoral access (23.5% vs 23.9%, p=0.974) and age over/under 75 (17.8% vs 28%, p=0.900919) Patients were assessed at 3 months and 12 months to assess clinical status post rotational atherectomy. Canadian cardiovascular society grading of angina pectoris and New York heart association functional scores were utilised. Mean CCS score at 3 months was 0.26±0.77 (Range 0–3) and this persisted out until 12 months (0.25±0.657). NYHA score at 3 months was 0.5±0.993 and again, this persisted until 12 months (0.457±0.816), indicating that the clinical benefit of rotational atherectomy is maintained until 1 year post procedure. Conclusions Whilst less commonly used in modern day intervention, rotational atherectomy still has a role in the drug eluting stent era to modify heavily calcified plaque. The risk of MACEs remains higher than conventional PCI, reflecting the complexity of the disease and increased procedural technical difficulty.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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