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Record W2115165412 · doi:10.1186/1471-2474-13-91

Prophylactic antibiotic regimens in tumor surgery (PARITY) survey

2012· article· en· W2115165412 on OpenAlexaffabout
Khaled Hasan, Antonella Racano, Benjamin Deheshi, Forough Farrokhyar, Jay S. Wunder, Peter C. Ferguson, Ginger E. Holt, Herbert S. Schwartz, Brad Petrisor, Mohit Bhandari, Michelle Ghert

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2012
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineAntibioticsMedical prescriptionOrthopedic surgerySports medicineInternal medicineCephalosporinSurgeryIntensive care medicineFamily medicinePhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Deep infection following endoprosthetic limb reconstruction for sarcoma of the long bones is a devastating complication occurring in 15% of sarcoma patients. Optimizing infection protocols and conducting definitive surgical trials are critical to improving outcomes. In this study, the PARITY (Prophylactic Antibiotic Regimens in Tumor Surgery) investigators aimed to examine surgeon preferences in antibiotic prophylaxis and perceptions about current evidence, as well as to ascertain interest in resolving uncertainty in the evidence with clinical trials. METHODS: We used a cross-sectional survey to examine current practice in the prescription of prophylactic antibiotics in Musculoskeletal Tumor Surgery. The survey was approved by our institution's Ethics Board and emailed to all Active Members of the Musculoskeletal Tumor Society (MSTS) and Canadian Orthopaedic Oncology Society (CANOOS). Survey answers were collected using an anonymous online survey tool. RESULTS: Of the 96 surgeons who received the questionnaire, 72 responded (75% response rate (% CI: 65.5, 82.5%)). While almost all respondents agreed antibiotic regimens were important in reducing the risk of infection, respondents varied considerably in their choices of antibiotic regimens and dosages. Although 73% (95% CI: 61, 82%) of respondents prescribe a first generation cephalosporin, 25% favor additional coverage with an aminoglycoside and/or Vancomycin. Of those who prescribe a cephalosporin, 33% prescribe a dosage of one gram for all patients and the reminder prescribe up to 2 grams based on body weight. One in three surgeons (95% CI: 25, 48%) believes antibiotics could be discontinued after 24 hours but 40% (95% CI: 30, 53%) continue antibiotics until the suction drain is removed. Given the ongoing uncertainty in evidence to guide best practices, 90% (95% CI: 81, 95%) of respondents agreed that they would change their practice if a large randomized controlled trial showed clear benefit of an antibiotic drug regimen different from what they are currently using. Further support for a clinical trial was observed by an overwhelming surgeon interest (87%; 95% CI: 77, 93%) in participating in a multi-center randomized controlled study. CONCLUSION: The current lack of guidelines for the prescription of prophylactic antibiotics in Musculoskeletal Tumor Surgery has left Orthopaedic Oncologists with varying opinions and practices. The lack of current evidence and strong surgeon support for participating in a definitive study provides strong rationale for clinical trials.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.293
Teacher spread0.258 · 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

Citations31
Published2012
Admission routes2
Has abstractyes

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