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Record W4402126310 · doi:10.1016/j.xjon.2024.08.013

Pediatric cardiac surgical site infections: A single-center quality improvement initiative

2024· article· en· W4402126310 on OpenAlexaff
Nhat Chau, Crystal Tran, Megan A. Clarke, J.M. Kilburn, Cecilia St. George-Hyslop, Diana Young, Sandra L. Merklinger, Erica Mosolanczki, Vivian Trinder, J. A. O’Hare, Karen Clarke, Kate McCormick, Rachel D. Vanderlaan

Bibliographic record

VenueJTCVS Open · 2024
Typearticle
Languageen
FieldMedicine
TopicSurgical site infection prevention
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineCohortSurgical site infectionSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Objective Pediatric cardiac surgery site infections (SSI) represent significant morbidity. Our institution reported elevated SSI rates of 3.48 per 100 cases over a 5-year period above target rates of 2.5 per 100 cases. Therefore, as a quality improvement initiative, we implemented interventions with the goal of decreasing SSI rates by 30%. Methods Pediatric cardiovascular surgery patients (January 2021 to August 2023) who had SSI within 30 days of index operation were included (n = 1514) based on the National Healthcare Safety Network definition. Descriptive statistics were used to compare our preintervention cohort (pre-IV) (January 2021 to April 2022; n = 753) and postintervention cohort (post-IV) (May 2022 to August 2023; n = 761). Results In the post-IV cohort, we found a significant decrease in total SSI (1.97 SSIs per 100 cases [15 out of 761]) versus pre-IV (3.85 SSIs per 100 cases [29 out of 753]), demonstrating a 48% reduction ( P = .029). In our post-IV cohort, there was a significant reduction in superficial SSIs (pre-IV, 3.19 SSIs per 100 cases [24 out of 753] vs post-IV, 1.58 SSIs out of 100 cases [12 out of 761]; P = .04). Wounds presenting at 1 to 3 weeks were also reduced in our post-IV cohort (pre-IV, 2.66 SSIs per100 cases [20 out of 753] vs post-IV, 0.66 SSIs per 100 cases [5 out of 761]; P = .002). A significant reduction in SSIs in nonneonates was also noted (pre-IV, 2.79 SSIs per 100 cases [21 out of 753] vs post-IV, 0.92 SSIs per 100 cases [7 out of 761]; P = .007). Additionally, there was a significant reduction in SSIs associated with the Society of Thoracic Surgeons–European Association for Cardio-Thoracic Surgery Congenital Heart Surgery 1 mortality category ( P = .033) and the number of readmissions in the post-IV cohort ( P = .042). Conclusions A new surgical site dressing and multidisciplinary surveillance plan effectively reduced the overall burden of SSI rates at our institution. Future studies will address risk factors in specific subpopulations to further reduce SSIs at our institution.

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)0.024
metaresearch head score (Gemma)0.028
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 score0.024
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.382
Teacher spread0.317 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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