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Record W4303981511 · doi:10.3389/fvets.2022.960865

Serum amyloid A and fibrinogen as markers for early detection of surgical site infection associated with internal fixation in the horse

2022· article· en· W4303981511 on OpenAlexaff
Catherine C. Thurston, Darko Stefanovski, Melissa C. MacKinnon, Hannah‐Sophie Chapman, Dean W. Richardson, David G. Levine

Bibliographic record

VenueFrontiers in Veterinary Science · 2022
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFibrinogenSerum amyloid AMedicineReceiver operating characteristicArea under the curveHorseInternal medicineInternal fixationSurgeryGastroenterologyBiology

Abstract

fetched live from OpenAlex

The objective of this study was to determine the diagnostic ability of serum amyloid A (SAA) and fibrinogen for early detection of surgical site infection (SSI) after equine internal fixation. Horses undergoing internal fixation for fracture, arthrodesis, or osteotomy with internal fixation for limb deformity were included in the study. SAA and fibrinogen were measured on blood samples preoperatively and on days 1, 3, 5, 7, 10, and 14 postoperatively. Statistical analysis included use of Spearman's rank correlation, logistic regression, and calculating the area under the receiver operating characteristic (ROC) curve. SAA and fibrinogen measurements were both associated with SSI, with SAA being considered an excellent marker (area under the ROC curve 0.8) and fibrinogen being considered acceptable (<0.8). As the amount of time postoperatively increased, SAA elevations indicated a higher likelihood of SSI (area under the ROC curve 0.8 compared with fibrinogen 0.7). SAA and fibrinogen were predictive markers of SSI and SAA is of greater diagnostic utility when compared with fibrinogen. Persistent elevations of SAA postoperatively are associated with the development of SSI. Serial monitoring of SAA can be used to help predict the development of SSI in horses undergoing internal fixation. This may lead to earlier suspicion, and therefore recognition and treatment of SSI.

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 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)0.003
metaresearch head score (Gemma)0.000
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 score0.274
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.321
Teacher spread0.289 · 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 teacher head, 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

Citations5
Published2022
Admission routes1
Has abstractyes

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