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Record W3202326452 · doi:10.1016/j.jacep.2021.08.009

Risk Factors for CIED Infection After Secondary Procedures

2021· article· en· W3202326452 on OpenAlex
Khaldoun G. Tarakji, Andrew D. Krahn, Jeanne E. Poole, Suneet Mittal, Charles Kennergren, Mauro Biffi, Panagiotis Korantzopoulos, Paolo Dallaglio, Daniel R. Lexcen, Jeff Lande, Gregory Hilleren, Reece Holbrook, Bruce L. Wilkoff

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACC. Clinical electrophysiology · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsUniversity of British Columbia
FundersSapheonMedtronic
KeywordsMedicinePerioperativeMultivariate analysisAntibiotic prophylaxisRisk factorRandomized controlled trialInfection controlSurgeryBody mass indexAntibioticsInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aimed to identify risk factors for infection after secondary cardiac implantable electronic device (CIED) procedures. BACKGROUND: Risk factors for CIED infection are not well defined and techniques to minimize infection lack supportive evidence. WRAP-IT (World-wide Randomized Antibiotic Envelope Infection Prevention trial), a large study that assessed the safety and efficacy of an antibacterial envelope for CIED infection reduction, offers insight into procedural details and infection prevention strategies. METHODS: This analysis included 2,803 control patients from the WRAP-IT trial who received standard preoperative antibiotics but not the envelope (44 patients with major infections through all follow-up). A multivariate least absolute shrinkage and selection operator machine learning model, controlling for patient characteristics and procedural variables, was used for risk factor selection and identification. Risk factors consistently retaining predictive value in the model (appeared >10 times) across 100 iterations of imputed data were deemed significant. RESULTS: Of the 81 variables screened, 17 were identified as risk factors with 6 being patient/device-related (nonmodifiable) and 11 begin procedure-related (potentially modifiable). Patient/device-related factors included higher number of previous CIED procedures, history of atrial arrhythmia, geography (outside North America and Europe), device type, and lower body mass index. Procedural factors associated with increased risk included longer procedure time, implant location (non-left pectoral subcutaneous), perioperative glycopeptide antibiotic versus nonglycopeptide, anticoagulant, and/or antiplatelet use, and capsulectomy. Factors associated with decreased risk of infection included chlorhexidine skin preparation and antibiotic pocket wash. CONCLUSIONS: In WRAP-IT patients, we observed that several procedural risk factors correlated with infection risk. These results can help guide infection prevention strategies to minimize infections associated with secondary CIED procedures.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.089
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.369
Teacher spread0.340 · 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