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Patient Comorbidities Associated With Acute Infection After Open Tibial Fractures

2022· article· en· W4297261484 on OpenAlexaff
Augustine M. Saiz, Dustin Stwalley, Philip R. Wolinsky, Anna N. Miller

Bibliographic record

VenueJAAOS Global Research and Reviews · 2022
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsObject Research Systems (Canada)
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineComorbidityOdds ratioConfidence intervalDiabetes mellitusInternal medicineSurgeryOpen fractureOrthopedic surgery

Abstract

fetched live from OpenAlex

INTRODUCTION: Open tibial shaft fractures are high-risk injuries for developing acute infection. Prior research has focused on injury characteristics and treatment options associated with acute inpatient infection in these injuries without primary analysis of host factors. The purpose of this study was to determine the patient comorbidities associated with increased risk of acute infection after open tibial shaft fractures during initial hospitalization. METHODS: A total of 147,535 open tibial shaft fractures in the National Trauma Data Bank from 2007 to 2015 were identified that underwent débridement and stabilization. Infection was defined as a superficial surgical site infection or deep infection that required subsequent treatment. The International Classification of Diseases, ninth revision codes were used to determine patient comorbidities. Comparative statistical analyses including odds ratios (ORs) for patient groups who did develop infection and those who did not were conducted for each comorbidity. RESULTS: The rate of acute inpatient infection was 0.27% with 396 patients developing infection during hospital management of an open tibial shaft fracture. Alcohol use (OR, 2.26, 95% confidence interval [CI], 1.73-2.96, P < 0.0001), bleeding disorders (OR, 4.50, 95% CI, 3.13-6.48, P < 0.0001), congestive heart failure (OR, 3.25, 95% CI, 1.97-5.38, P < 0.0001), diabetes (OR, 1.73, 95% CI, 1.29-2.32, P = 0.0002), psychiatric illness (OR, 2.17, 95% CI, 1.30-3.63, P < 0.0001), hypertension (OR, 1.56, 95% CI, 1.23-1.95, P < 0.0001), obesity (OR, 3.05, 95% CI, 2.33-3.99, P < 0.0001), and chronic obstructive pulmonary disease (OR, 2.09, 95% CI, 1.51-2.91, P < 0.0001) were all associated with increased infection rates. Smoking (OR, 0.957, 95% CI, 0.728-1.26, P = 0.722) and drug use (OR, 1.11, 95% CI, 0.579-2.11, P = 0.7607) were not associated with any difference in infection rates. DISCUSSION: Patients with open tibial shaft fractures who have congestive heart failure, bleeding disorders, or obesity are three to 4.5 times more likely to develop an acute inpatient infection than patients without those comorbidities during their initial hospitalization. Patients with diabetes, psychiatric illness, hypertension, or chronic obstructive pulmonary disease are 1.5 to 2 times more likely to develop subsequent infection compared with patients without those comorbidities. Patients with these comorbidities should be counseled about the increased risks. Furthermore, risk models for the infectious complications after open tibial shaft fractures can be developed to account for this more at-risk patient population to serve as modifiers when evaluating surgeon/hospital performance. CONCLUSION: Patient comorbidities are associated with increased risk of acute inpatient infection of open tibial shaft fractures during hospitalization.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.067
GPT teacher head0.419
Teacher spread0.352 · 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 designNot applicable
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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Citations13
Published2022
Admission routes1
Has abstractyes

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