Prolonged surgical duration, higher body mass index and current smoking increases risk of surgical site infection after intra-articular fracture of distal femur

-A machine learning model to predict surgical site infection after surgery of lower extremity fractures

PURPOSE

This study aimed to develop machine learning algorithms for identifying predictive factors associated with the risk of postoperative surgical site infection in patients with lower extremity fractures.

METHODS

A machine learning analysis was conducted on a dataset comprising 1,579 patients who underwent surgical fixation for lower extremity fractures to create a predictive model for risk stratification of postoperative surgical site infection. We evaluated different clinical and demographic variables to train four machine learning models (neural networks, boosted generalised linear model, naïve bayes, and penalised discriminant analysis). Performance was measured by the area under the curve score, Youdon's index and Brier score. A multivariate adaptive regression splines (MARS) was used to optimise predictor selection.

RESULTS

The final model consisted of five predictors. (1) Operating room time, (2) ankle region, (3) open injury, (4) body mass index, and (5) age. The best-performing machine learning algorithm demonstrated a promising predictive performance, with an area under the ROC curve, Youdon's index, and Brier score of 77.8%, 62.5%, and 5.1%-5.6%, respectively.

CONCLUSION

The proposed predictive model not only assists surgeons in determining high-risk factors for surgical site infections but also empowers patients to closely monitor these factors and take proactive measures to prevent complications. Furthermore, by considering the identified predictors, this model can serve as a reference for implementing preventive measures and reducing postoperative complications, ultimately enhancing patient outcomes. However, further investigations involving larger datasets and external validations are required to confirm the reliability and applicability of our model.

Risk factors contributing to postoperative surgical site infections in patients undergoing ankle fracture fixation: A systematic review and meta-analysis

Surgical site infections (SSIs) following ankle fracture fixation pose significant challenges in patient recovery and healthcare management. Identifying risk factors contributing to SSIs can aid in developing targeted prevention and treatment strategies. This systematic review and meta-analysis were conducted according to the PRISMA guidelines and the PICO framework. A comprehensive literature search across major databases, including PubMed, Embase, Web of Science and the Cochrane Library, was completed on September 26, 2023. The inclusion criteria encompassed peer-reviewed studies of various designs that investigated risk factors for SSIs post-ankle fracture fixation. Quality assessment was performed using the Newcastle-Ottawa Scale. Statistical analyses assessed heterogeneity and calculated combined effect sizes using fixed- or random-effects models, depending on the heterogeneity observed. The initial search yielded 1250 articles, with seven meeting the inclusion criteria after rigorous screening and full-text review. The included studies, conducted between 2006 and 2019, predominantly utilized case-control designs. The meta-analysis identified diabetes, open fractures, smoking, age, alcohol consumption, ASA score ≥3, high BMI, contaminated incisions, fracture dislocation and heart disease as significant risk factors for postoperative SSIs. Publication bias assessment showed no significant bias across studies. The identification of key risk factors such as diabetes, open fractures, smoking, advanced age, alcohol consumption, high ASA score, elevated BMI, contaminated incisions, fracture dislocation and heart disease is essential in managing SSIs post-ankle fracture fixation. Targeted interventions addressing these risk factors are crucial to reduce the incidence of SSIs and improve overall patient outcomes.

Establishment and validation of a nomogram model for postoperative surgical site infection after transforaminal lumbar interbody fusion: A retrospective observational study

BACKGROUND

Surgical site infection is one of the serious complications of transforaminal lumbar interbody fusion surgery, and many factors affect its occurrence.

METHODS

A total of 1,277 patients who underwent transforaminal lumbar interbody fusion between 2018 and 2021 were enrolled in this study. Subsequently, 1,277 patients were randomly assigned to a training cohort (N = 958) and a validation cohort (N = 319) in a 3:1 ratio. We developed a nomogram according to the results of binary logistic regression analysis in the training cohort. The nomogram's predictive accuracy and discriminative ability were evaluated by calibration curve and receiver operating characteristic analysis. Decision curve analysis was performed to estimate the clinical value of our nomogram.

RESULTS

In univariate and multivariate analysis, smoking, diabetes, intraoperative blood loss, American Society of Anesthesiologists class ≥III, serum calcium, albumin, and serum glucose were identified as significant independent predictors. The nomogram was developed using these independent predictors, which showed good diagnostic accuracy for surgical site infection of the training and validation cohorts. The calibration curves for the 2 cohorts showed optimal agreement between nomogram prediction and actual observation. The decision curve analysis of the nomogram model showed the great clinical use of the nomogram.

CONCLUSION

The nomogram based on smoking, diabetes, intraoperative blood loss, American Society of Anesthesiologists class, serum calcium, albumin, and serum glucose has the potential as a clinically useful predictive tool of surgical site infection after transforaminal lumbar interbody fusion surgery. It is helpful to visualize the risk factors of surgical site infection.

Predictors of Deep Infection After Distal Femur Fracture: A Multicenter Study

OBJECTIVES

To identify potentially modifiable risk factors for deep surgical site infection after distal femur fracture.

DESIGN

Multicenter retrospective cohort study.

SETTING

Ten Level-I trauma centers.

PATIENTS/PARTICIPANTS

Patients with OTA/AO 33A or C distal femur fractures (n = 1107).

INTERVENTION

Surgical fixation of distal femur fracture.

MAIN OUTCOME MEASUREMENT

The outcome of interest was deep surgical site infection.

RESULTS

There was a 7% rate (79/1107) of deep surgical site infection. In the multivariate analysis, predictive factors included alcohol abuse [odds ratio (OR) = 2.36; 95% confidence interval (CI), 1.17-4.46; P = 0.01], intra-articular injury (OR = 1.73; 95% CI, 1.01-3.00; P = 0.05), vascular injury (OR = 3.90; 95% CI, 1.63-8.61; P < 0.01), the use of topical antibiotics (OR = 0.50; 95% CI, 0.25-0.92; P = 0.03), and the duration of the surgery (OR = 1.15 per hour; 95% CI, 1.01-1.30; P = 0.04). There was a nonsignificant trend toward an association between infection and type III open fracture (OR = 1.73; 95% CI, 0.94-3.13; P = 0.07) and lateral approach (OR = 1.60; 95% CI, 0.95-2.69; P = 0.07). The most frequently cultured organisms were methicillin-resistant Staphylococcus aureus (22%), methicillin-sensitive Staphylococcus aureus (20%), and Enterobacter cloacae (11%).

CONCLUSIONS

Seven percent of distal femur fractures developed deep surgical site infections. Alcohol abuse, intra-articular fracture, vascular injury, and increased surgical duration were risk factors, while the use of topical antibiotics was protective.

LEVEL OF EVIDENCE

Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Fracture, nonunion and postoperative infection risk in the smoking orthopaedic patient: a systematic review and meta-analysis

This systematic review and meta-analysis aimed to analyse negative effects of smoking in orthopaedic and trauma patients.

A PubMed search was carried out for studies published until July 2020 regarding effects of smoking on fracture risk, nonunion, infection after orthopaedic surgery, and persisting nonunion after scaphoid nonunion surgery. Random effects models calculated for outcome parameters, and relative risks (RR) with 95% confidence intervals are provided. No adjustments for covariates were made. Heterogeneity was assessed with Higgins’ I2, publication bias with Harbord’s p (Hp), sensitivity analysis performed on funnel plots and quality of studies was analysed using the Newcastle-Ottawa Scale.

Of 3362 retrieved entries, 69 were included in the final analysis. Unadjusted RR for smokers to develop vertebral (six studies, seven entries; RR: 1.61; p = 0.008; I2 = 89.4%), hip (11 studies, 15 entries; RR: 1.28; p = 0.007; I2 = 84.1%), and other fractures (eight studies, 10 entries; RR: 1.75; p = 0.019; I2 = 89.3%) was significantly higher. Postoperative infection risk was generally higher for smokers (21 studies; RR: 2.20; p < 0.001; I2 = 58.9%), and remained upon subgroup analysis for elective spinal (two studies; RR: 4.38; p < 0.001; I2 = 0.0%) and fracture surgery (19 studies; RR: 2.10; p < 0.001; I2 = 58.5%). Nonunion risk after orthopaedic (eight studies; RR: 2.15; p < 0.001; I2 = 35.9%) and fracture surgery (11 studies; RR: 1.85; p < 0.001; I2 = 39.9%) was significantly higher for smokers, as was persisting nonunion risk after surgery for scaphoid nonunion (five studies; RR: 3.52; p < 0.001; I2 = 0.0%). Sensitivity analysis for each model reduced heterogeneity whilst maintaining significance (all I2 < 20.0%).

Smoking has a deleterious impact on fracture incidence, and (subsequent) development of nonunions and postoperative infections.

Cite this article: EFORT Open Rev 2021;6:1006-1019. DOI: 10.1302/2058-5241.6.210058

Smoking increases the risk of infectious diseases: A narrative review

Smoking is relevant to infectious diseases resulting in increased prevalence and mortality. In this article, we aim to provide an overview of the effects of smoking in various infections and to explain the potential mechanisms. We searched PubMed and other relevant databases for scientific studies that explored the relationship between smoking and infection. The mechanisms of susceptibility to infection in smokers may include alteration of the structural, functional and immunologic host defences. Smoking is one of the main risk factors for infections in the respiratory tract, digestive tract, reproductive tract, and other systems in humans, increasing the prevalence of HIV, tuberculosis, SARS-CoV, and the current SARS-CoV-2. Smoking cessation can reduce the risk of infection. Smoking increases the incidence of infections and aggravates the progress and prognosis of infectious diseases in a dose-dependent manner. Smoking cessation promotion and education are the most practical and economical preventive measures to reduce aggravation of disease infection owing to tobacco use.