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Record W2943816072 · doi:10.1136/bmjebm-2018-111070.99

99 Antibiotics-impregnated calcium sulfate in surgery: a case of broader use of innovative medical practice

2018· article· en· W2943816072 on OpenAlexaff
Renée Drolet, Geneviève Asselin, Alice Nourissat, Martin Coulombe, Marc Rhainds

Bibliographic record

VenueOral Presentations · 2018
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineOrthopedic surgeryAntibioticsSurgeryData extractionMEDLINE

Abstract

fetched live from OpenAlex

Objectives Surgical site infections (SSI) are a major source of mortality and morbidity, especially with prosthesis or medical implants. Prevention and control of SSI refer to numerous prophylactic measures, including administration of systemic antibiotic therapy. Local antibiotherapy mediated by bioresorbable bone substitute impregnated with antibiotics has been suggested as a complementary strategy. Beads of synthetic calcium sulfate (CaSO4) impregnated with antibiotics are prepared in the operating room and implemented at the surgical site to ensure local diffusion of antibiotics. A health technology assessment (HTA) was carried out in our university hospital to assess the effectiveness and safety of antibiotics-impregnated CaSO4 (AI-CaSO4) for the prevention and treatment of SSI in orthopedic, vascular and neuromodulation surgeries. Method A literature review was conducted in several indexed databases and gray literature. Systematic review, primary studies, and guidelines on the efficacy and safety of AI-CaSO4 used for prevention or treatment of SSI in orthopedic, vascular or neuromodulation (neurostimulator implant) surgeries were retrieved. Two reviewers independently performed selection, quality assessment, and data extraction.The primary outcome was SSI. Secondary outcomes included infection eradication, time to eradicate infections and additional interventions related to infections. Data extraction from Electronic Patient Record (EPR) was performed to review local use. A cohort of 99 patients for whom AI-CaSO4 was used during orthopedic, vascular or neuromodulation surgeries between August 18th2015 and July 31th2018 was analyzed. Evidence-based review and local perspective were shared with an interdisciplinary group including orthopedic and vascular surgeons, pharmacists, infectiologists, and hospital managers. Results Twenty-one studies on the efficacy of AI-CaSO4 were included. Available evidence suggests a beneficial effect of AI-CaSO4 in the surgical treatment of osteomyelitis whereas any conclusion can be drawn for other indications. There is insufficient evidence to support the use of AI-CaSO4 in the prevention of SSI. Few cases of hypercalcemia and renal insufficiency have been reported with AI-CaSO4 use. Data from 99 EPRs totaling 113 surgical procedures (orthopedic n=54, vascular n=37 and neuromodulation n=22) showed rapid adoption and broader use of with AI-CaSO4 since its introduction in 2015. Osteomyelitis treatment represents 2.7% of cases in our hospital. AI-CaSO4 was used mainly in the context of revision surgeries (74%) and prevention of SSI (65%). A lack of standardization for the preparation and documentation of the use of AI-CaSO4 was observed. Conclusions Limited evidence supports the use of AI-CaSO4 in osteomyelitis treatment whereas safety profile remains to be proven. Broader indications with AI-CaSO4 use than those assessed in the literature, advocate for a better control and surveillance when a new medical practice is introduce in healthcare.

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)0.021
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.068
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.014
Science and technology studies0.0020.005
Scholarly communication0.0050.006
Open science0.0020.003
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.092
GPT teacher head0.400
Teacher spread0.309 · 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 designCase report
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
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