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Record W4402602680 · doi:10.1007/s00264-024-06317-y

Evaluating the impact of surgery sequence on infection rates in hip or knee arthroplasty: does sequence matter?

2024· article· en· W4402602680 on OpenAlexaffabout
Pakpoom Ruangsomboon, Onlak Ruangsomboon, Sebastian Tomescu, Cristal Rahman, Daniel Pincus, Bheeshma Ravi

Bibliographic record

VenueInternational Orthopaedics · 2024
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsHealth Sciences CentreUniversity of TorontoInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineOrthopedic surgeryPropensity score matchingInterquartile rangeCohortSurgeryIncidence (geometry)ArthroplastyCohort studyHazard ratioRetrospective cohort studyInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

PURPOSE: The potential influence of surgical sequence of elective hip-and-knee reconstructive surgery in relation to an infection-related procedure on postoperative infection rates is not clearly understood. Therefore, we aimed to examine the impact of surgical sequence on the incidence of postoperative infections within one-year and the longest available follow-up period in patients undergoing hip-and-knee reconstructive surgery. METHODS: A case-control study with propensity matching was utilized to examine elective surgeries conducted at Sunnybrook Holland Orthopaedic & Arthritic centre, Toronto, Canada between 2015 and 2018. We determined and categorized them based on their operating room (OR) sequence in relation to an infected case; the cases were those performed right after (post-infection cohort), and the controls were those performed before an infection-related procedure in the same OR (pre-infection cohort). We employed survival analysis to compare the infection incidence within one year and at the longest available follow-up among the propensity-matched cohort. RESULTS: A total of 13,651 cases were identified during the four year period. We successfully matched 153 cases (21 post-infection and 132 pre-infection) using propensity scores. Demographic and clinical characteristics were balanced through matching. Kaplan-Meier survival analysis showed no significant difference in infection-free survival within one year and at a median follow-up of 2.2 years [interquartile range 0.9-5.0] between surgeries conducted before and after infected cases (both log-rank p-values = 0.4). The hazard ratios for infection within one year and the longest follow-up period were both 0.37 [95%Confidence Interval 0.03-4.09, p = 0.418], as no more events occurred after one year. CONCLUSION: The sequence of surgical procedures, whether or not an elective arthroplasty or lower limb reconstructive procedure occurs before or after an infection-related case in the same OR, does not significantly affect postoperative infection rates. This finding supports the efficacy of the current infection control measures and suggests a reconsideration of surgical scheduling standards.

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)0.006
metaresearch head score (Gemma)0.020
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 score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.111
GPT teacher head0.437
Teacher spread0.327 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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