Patient Comorbidities Associated With Acute Infection After Open Tibial Fractures
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".