RETRACTED: Analysis of the associated factors in postoperative wound infection following open reduction and internal fixation for elbow fracture
Abstract
Postoperative wound infections (PWIs) following open reduction and internal fixation (ORIF) for elbow fractures can significantly affect patient outcomes. Identifying associated risk factors is crucial for improving clinical practices and patient care. A retrospective analysis (June 2020–June 2023) at our institution involved 90 patients who underwent elbow ORIF. Thirty patients developed PWIs (case group), compared to 60 who did not (control group). Variables like anaemia, operation duration, hospital stay, blood loss, body mass index (BMI), age, hypoalbuminemia, smoking status, diabetes mellitus and open fractures were examined. Univariate and multivariate analyses determined the impact of these variables on PWI incidence, with statistical significance set at p < 0.05. The main pathogens identified were Escherichia coli among Gram-negative bacteria (59.46%) and Staphylococcus aureus among Gram-positive bacteria (40.54%). In the univariate analysis, hypoalbuminemia, anaemia, and lifestyle factors such as smoking showed higher prevalence in patients with PWIs. However, age and length of hospital stay did not significantly influence infection rates. The multivariate analysis further elucidated that anaemia, smoking, diabetes mellitus and open fractures were independent, significant predictors of PWIs. These findings highlight the complexity of factors influencing infection risk post-ORIF, underscoring the importance of both individual health conditions and surgical complications in patient outcomes. Anaemia, smoking, diabetes mellitus and open fractures significantly increase the risk of PWI after elbow ORIF. Early identification and management of these risk factors are imperative to reduce infection rates and improve postoperative recovery.
1 INTRODUCTION
Elbow fractures, often the result of acute trauma, present a substantial challenge in orthopaedic practice, impacting both the function of the upper extremity and the complexity of treatment and rehabilitation.1, 2 The intricate anatomy of the elbow necessitates precise surgical intervention, particularly when conservative treatments are insufficient for managing non-displaced fractures. Open reduction and internal fixation (ORIF) have emerged as a pivotal surgical technique for these injuries, focusing on restoring the elbow joint's normal anatomy and ensuring its stability. The main goal of ORIF in elbow fractures is to re-align and stabilise the joint, which is crucial for enabling early mobilisation and fostering optimal functional recovery.3, 4 This surgical approach is instrumental in facilitating the healing process by ensuring proper alignment of bone fragments and securing them, which is essential for early joint movement and reducing risks such as joint stiffness and muscle atrophy.
While ORIF is a critical surgical intervention for elbow fractures, aimed at restoring normal anatomy and ensuring joint stability for optimal functional recovery, this technique is not without its challenges. Specifically, ORIF for elbow fractures carries a quantifiable risk of postoperative wound infections (PWIs), which can complicate patient outcomes. These infections may not only delay healing and extend hospitalisation but also potentially necessitate additional surgical interventions, such as hardware removal or revision surgeries. The risk of PWIs after elbow ORIF is influenced by a comprehensive array of factors, including patient health status, lifestyle choices, injury characteristics and surgical procedures.5, 6 It is imperative to acknowledge and address these risk factors to enhance surgical outcomes and minimise the incidence of postoperative infections. Infections following elbow ORIF are influenced by a spectrum of factors that encompass patient health, the specifics of the injury and surgical variables. These factors can significantly impact the risk and management of postoperative infections. For instance, systemic health conditions, lifestyle choices and the severity and nature of the injury play a role in the patient's susceptibility to infection.7, 8 Additionally, surgical aspects, such as the duration of the operation, the techniques employed and the standards of care maintained during the procedure, are critical elements in infection risk. Recognising the multifaceted nature of these risk factors is crucial in developing comprehensive prevention and management strategies. This realisation underscores the necessity of our study, which seeks to bridge the gap between understanding these risk factors and applying this knowledge to improve clinical outcomes. This understanding is not only vital for mitigating risks but also for enhancing the overall efficacy of the surgical intervention.9 The current study aims to conduct an in-depth analysis of these factors, providing valuable insights that can inform both clinical practice and future research in orthopaedic surgery.
PWIs following elbow fracture ORIF are a significant concern, with various patient, fracture and surgical factors contributing to the risk. Understanding these factors is essential for developing effective prevention and management strategies. This study aims to provide a comprehensive analysis of these factors, offering valuable insights for clinicians and researchers in orthopaedic surgery.
2 METHODS
2.1 Study design
An extensive retrospective analysis was performed at our institution to ascertain the risk factors associated with PWIs in patients who underwent ORIF of the elbow joint. This investigation spanned a period from June 2020 to June 2023. A total of 30 patients who developed PWIs following the surgery were included in the case group for this study. To facilitate a comparative analysis, a control group was constituted, comprising 60 patients who underwent the same procedure within the same timeframe but did not experience PWIs. This approach was designed to ensure a high degree of comparability between the two groups. Informed consent was obtained from all participants prior to inclusion in the study. The research methodology, including the study's objectives and protocols, was thoroughly reviewed and approved by the ethics committee of our institution. This review process affirmed that the study conformed to strict ethical standards, particularly regarding the protection of patient confidentiality and rights. The design of this study was meticulously structured to align with ethical guidelines and ensure the integrity and scientific rigour of the findings.
2.2 Inclusion and exclusion criteria
2.2.1 Inclusion criteria
- Patient demographics: Adults aged 18 years and above.
- Surgical procedure: Patients who underwent ORIF for elbow fractures.
- Postoperative follow-up: Patients with a minimum postoperative follow-up duration of 6 months.
- Medical records: Availability of complete medical records including operative notes, postoperative care details and follow-up data.
- Informed consent: Patients who provided written informed consent for participation in the study.
2.2.2 Exclusion criteria
- Prior infections: Patients with a history of pre-existing wound or systemic infections prior to the ORIF procedure.
- Additional surgical interventions: Patients who required additional surgical procedures unrelated to the primary ORIF for elbow fracture within the study timeframe.
- Immunocompromised status: Individuals with immunocompromised conditions, including but not limited to HIV/AIDS, chronic steroid use or chemotherapy within the past year.
- Chronic diseases: Patients with uncontrolled chronic diseases such as diabetes mellitus, rheumatoid arthritis or other conditions known to affect wound healing.
2.3 Diagnostic criteria for surgical site infections
The diagnosis of PWIs in patients following surgical interventions, particularly in cases of open reduction and internal fixation for elbow fractures, is based on a combination of clinical and laboratory findings. Firstly, a core symptom includes an elevated body temperature of 38°C or higher, which often accompanies localised tenderness at the incision site. This may be further evidenced by incision dehiscence or the emergence of purulent exudate during surgical debridement or exploratory procedures. Secondly, clinical signs at the incision site, such as noticeable erythema, oedema, localised warmth and pain, especially when accompanied by the discharge of purulent material, are indicative of infection. Thirdly, the extraction of purulent exudate from the deep tissue layers of the incision site through percutaneous aspiration is a significant diagnostic marker. Lastly, the confirmation of pathogenic organisms in incisional secretion specimens through positive microbiological cultures is a critical component in establishing the diagnosis of PWIs.
2.4 Data collection and variables examined
In our study, a thorough data collection was undertaken to ascertain variables that might impact surgical outcomes. This encompassed an extensive range of clinical and demographic parameters. Key data points included the presence of anaemia, prolonged operation duration (exceeding 5 h), extended hospitalisation (beyond 5 days), significant intraoperative blood loss (300 mL or more), elevated body mass index (BMI ≥25 kg/m2), advanced age (50 years or older), hypoalbuminemia (albumin levels below 35 g/L), smoking status, the presence of diabetes mellitus and the occurrence of open fractures. The rationale for selecting these particular variables was grounded in their potential to influence both the immediate surgical results and longer term postoperative outcomes, including the risk of developing PWIs. Each factor was chosen based on its recognised impact on patient recovery and complication rates in orthopaedic and surgical practices. The data collection process was rigorously conducted, adhering to the highest ethical standards.
2.5 Statistical analysis
For our study, statistical analysis was meticulously carried out in two primary phases: univariate and multivariate analysis. The univariate analysis was employed initially to identify potential risk factors by comparing each variable independently with the surgical outcomes. This method involved the application of chi-square tests or Fisher's exact tests for categorical variables and Student's t-tests or Mann–Whitney U tests for continuous variables, depending on the data distribution. Following the identification of significant factors in the univariate analysis, a multivariate logistic regression analysis was conducted. This approach was utilised to adjust for confounding variables and to ascertain the independent effect of each variable on the surgical outcomes. Variables with a p-value of less than 0.05 in the univariate analysis were included in the multivariate model. The results from the multivariate analysis provided insight into the variables that independently influenced the surgical outcomes, offering a more nuanced understanding of the factors contributing to these outcomes. The statistical significance was set at a p-value of less than 0.05. All analyses were performed using SPSS software (Version 27.0).
3 RESULTS
3.1 Post-treatment outcomes in patients
In our study, the post-treatment outcomes of 90 patients were analysed to assess the effectiveness of the treatment protocols. The time taken for fracture healing ranged from 10 to 13 weeks, with an average healing duration of 12.33 ± 2.53 weeks. This healing timeframe is indicative of the efficacy of the applied therapeutic approach in facilitating bone regeneration and recovery. Additionally, the duration for the resolution of swelling and pain post-treatment was observed to be between 4 and 8 days, averaging at 6.38 ± 2.42 days. This rapid alleviation of symptoms is a critical indicator of the immediate effectiveness of the treatment in managing acute post-operative discomfort and inflammation. Furthermore, the timeline for patients to achieve complete weight-bearing capacity post-treatment varied from 12 to 19 weeks, with an average time of 14.72 ± 2.31 weeks.
3.2 Microbial aetiology of incision infections
In the study, the bacteriological analysis of surgical incision sites was conducted to identify the prevalent pathogens. The results demonstrated a bifurcation of the isolated pathogens into two major categories: Gram-negative and Gram-positive bacteria. Among the Gram-negative bacteria, the predominant species included Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae and Enterobacter cloacae. Notably, these Gram-negative bacteria accounted for ~59.46% of the isolated strains. E. coli was identified as the most prevalent among these Gram-negative species, indicating its significant role in postoperative infections. On the other hand, the Gram-positive bacterial spectrum was primarily composed of Enterococcus species, Staphylococcus aureus, Staphylococcus epidermidis, coagulase-negative staphylococci and Enterococcus faecalis. Collectively, these Gram-positive bacteria constituted about 40.54% of the isolates.
3.3 Univariate analysis of factors associated with PWIs
Upon examining the correlation between patient-related factors and the incidence of postoperative infections, several notable trends were observed. The analysis showed that 73.3% of both the infected and non-infected groups were patients aged 50 years or over, indicating no direct link between age and infection likelihood. Similarly, the length of hospital stays, which was more than 5 days for 53.3% of infected patients compared to 46.7% of non-infected patients, did not show a clear association with infection rates. The quantity of blood loss during surgery, with 50.0% of infected patients experiencing blood loss of 300 mL or more versus 60.0% of non-infected patients, also did not demonstrate a significant relationship with the occurrence of infections. However, a distinct pattern emerged where 80.0% of infected patients had albumin levels below 35 g/L, while this was true for 58.3% of non-infected patients, suggesting a higher risk of infection with lower albumin levels. For body mass index, 66.7% of infected patients had a BMI of 25 kg/m2 or greater, as opposed to 45.0% in the non-infected group, though this did not significantly correlate with infection incidence. In contrast, 43.3% of infected patients were anaemic, compared to only 16.6% among the non-infected, indicating a higher occurrence of infections in patients with anaemia. The effect of lifestyle was evident, as 56.7% of infected patients were smokers against 20.0% of non-smokers in the non-infected group. Additionally, diabetes mellitus was present in 76.7% of the infected group versus 26.7% in the non-infected group, and a similar trend was seen with open fractures, where 76.7% of infected patients had open fractures compared to 21.7% in the non-infected group. These results reveal that while certain patient characteristics such as prolonged hospital stays and age may not be indicative of infection risk, factors such as hypoalbuminemia, anaemia, lifestyle choices like smoking and clinical conditions such as diabetes mellitus and open fractures are more prevalent in patients who developed postoperative infections (Table 1).
| Factors (Note) | Infected (n = 30) | Non-infected (n = 60) | χ2 | p-value |
|---|---|---|---|---|
| Age (≥50 years) | 22 (73.3%) | 44 (73.3%) | 0 | >0.05 |
| Hospital Stay (>5 days) | 16 (53.3%) | 28 (46.7%) | 0.19 | >0.05 |
| Intraoperative blood loss (≥300 mL) | 15 (50.0%) | 36 (60.0%) | 0.36 | >0.05 |
| Operation time (≥5 h) | 14 (46.7%) | 20 (33.3%) | 0.98 | >0.05 |
| ALB <35 g/L | 24 (80.0%) | 35 (58.3%) | 1.41 | <0.05 |
| BMI (≥25 kg/m2) | 20 (66.7%) | 27 (45.0%) | 1.77 | >0.05 |
| Anaemia | 13 (43.3%) | 10 (16.6%) | 5.62 | <0.05 |
| Smoking | 17 (56.7%) | 12 (20.0%) | 9.12 | <0.01 |
| Diabetes mellitus | 23 (76.7%) | 16 (26.7%) | 11.27 | <0.01 |
| Open fracture | 23 (76.7%) | 13 (21.7%) | 16.31 | <0.01 |
3.4 Multivariate logistic regression analysis of factors associated with PWIs
Our multivariate logistic regression analysis highlighted a set of factors that are significantly linked to an increased risk of PWIs. The analysis revealed that conditions such as anaemia and lifestyle habits like smoking are prominent predictors of infection risk, with both showing a notably higher likelihood of postoperative complications. Similarly, patients with diabetes mellitus were found to be at a substantially increased risk, emphasising the impact of this metabolic condition on surgical recovery. Furthermore, the data indicated that individuals who sustained open fractures faced a significantly heightened risk of infection following surgery. These associations were all statistically significant, reinforcing the importance of these factors in the postoperative infection risk profile (Table 2).
| Factors | β-value | Standard error value | Wald value | OR value | 95% CI for OR | p-value |
|---|---|---|---|---|---|---|
| Anaemia | 0.365 | 1.504 | 4.17 | 3.879 | 1.338–5.102 | <0.01 |
| Smoking | 0.331 | 1.282 | 3.925 | 3.718 | 1.306–4.520 | <0.01 |
| Diabetes mellitus | 0.25 | 1.102 | 2.827 | 2.642 | 1.105–3.905 | <0.01 |
| Open fracture | 0.347 | 1.408 | 4.103 | 3.83 | 1.329–4.905 | <0.01 |
4 DISCUSSION
PWI following ORIF for elbow fractures presents a significant challenge for orthopaedic surgery. These infections can lead to devastating consequences, including prolonged hospitalisation, delayed wound healing, and in severe cases, may necessitate surgical revision or lead to permanent functional impairment.10 In the context of elbow fractures, the complexity of the surgical procedure and the proximity of the incision to the joint space increase the susceptibility to microbial contamination and infection. Moreover, the elbow's extensive use in daily activities can make postoperative care and infection prevention more challenging. The anatomical structure of the elbow, along with the potential for hematoma formation in the highly vascular area, further complicates the scenario, providing a niche for bacterial growth.11, 12 Our analysis specifically aimed to dissect the myriad factors that predispose patients to such infections following ORIF of the elbow. It is crucial to recognise that the risk of infection is not solely dependent on the surgical technique but is also influenced by patient-specific factors, such as comorbid conditions and lifestyle habits. Understanding these factors is paramount for developing effective strategies to minimise infection risk and improve surgical outcomes.13
The findings from our study provide a compelling narrative on the multifaceted nature of PWI risks. The microbial landscape of the incisions, dominated by Gram-negative bacteria, particularly E. coli, reflects the broader trends seen in hospital-acquired infections. The presence of Gram-positive bacteria, including S. aureus, aligns with their well-documented pathogenicity in surgical sites. The resistance of these microbes to perioperative antibiotic prophylaxis, their virulence and the potential for biofilm formation on surgical hardware could explain their significant role in postoperative infections. The univariate analysis revealed that hypoalbuminemia and anaemia were significantly associated with increased infection rates. Hypoalbuminemia may be indicative of a poor nutritional state or a chronic inflammatory response, both of which are known to impair wound healing and immune function. Anaemia, on the other hand, can reduce tissue oxygenation, a crucial factor for wound healing processes, thus potentially increasing susceptibility to infections. Furthermore, our study substantiates the critical impact of smoking and diabetes mellitus on PWIs. Smoking, by impairing microvascular blood flow, and diabetes mellitus, through its effects on hyperglycemia and immune function, significantly contribute to infection risks. These findings highlight the importance of addressing such modifiable lifestyle factors preoperatively, including smoking cessation and glycemic control, as integral components of surgical planning and patient optimization. Our multivariate logistic regression analysis further substantiated these findings, establishing anaemia and hypoalbuminemia as significant independent predictors of PWIs. Smoking and diabetes mellitus also emerged as critical factors.14, 15 Smoking, through its impairment of microvascular blood flow, can considerably hinder tissue repair and immune response. Diabetes mellitus, characterised by hyperglycemia, can disrupt normal immune function and create an environment conducive to bacterial proliferation.16
Furthermore, the clear association between open fractures and infection risk can be attributed to the increased exposure of the wound to environmental pathogens, the complexity of the surgical procedure, and the extensive tissue damage that often accompanies such injuries. These factors can dramatically complicate the postoperative course, offering more opportunities for microbial invasion and colonisation. It's also noteworthy that some factors, such as age and length of hospital stay, did not show a direct correlation with infection rates. This could be due to the heterogeneity of the patient population and the successful implementation of infection control measures within the hospital setting.17 Our analysis delineates a scenario where the risk of postoperative infection is closely tied to pre-existing patient conditions and perioperative environmental exposures. These findings underscore the necessity for a comprehensive, multidimensional approach to patient care. Strategies that encompass preoperative optimization of nutritional status, meticulous blood management, smoking cessation programs, tight glycemic control and vigilant postoperative surveillance for open fracture cases may mitigate the infection risk.
The study's primary limitation lies in its retrospective design, which inherently restricts the ability to establish causation due to potential confounders and biases. Additionally, the sample size and single-institution setting may not fully represent the broader population, thus limiting the external validity and generalizability of our results. Another constraint is the potential underreporting of comorbidities and lifestyle factors, such as smoking and diet, which are reliant on patient disclosure and accurate medical recording. The study also does not account for variations in surgical technique or postoperative care protocols, which can influence the rate of infection. Future research should aim to conduct prospective, multicentre trials with larger and more diverse populations to enhance the robustness and applicability of the findings. Longitudinal studies examining the long-term effects of these risk factors on patient outcomes post-ORIF would be valuable. Additionally, interventional studies to test preoperative optimization strategies and postoperative care protocols could be pivotal in improving patient outcomes and reducing the incidence of PWIs.
5 CONCLUSIONS
In conclusion, anaemia, smoking, diabetes mellitus and the occurrence of open fractures are identified as significant risk factors for surgical site infections following elbow ORIF. Clinical practice should prioritise the prompt identification and proactive management of these elements to mitigate the incidence of infections and enhance patient outcomes post-surgery.
FUNDING INFORMATION
Basic and Clinical Research on the Relationship Between Minimally Invasive Surgical Approaches to the Elbow Joint and Surrounding Nerves and Blood Vessels, Grant Number ZF2024076.
CONFLICT OF INTEREST STATEMENT
The authors declare that they have no competing interests.
ETHICS STATEMENT
Ethics Committee of the Third Hospital of Hebei Medical University. Written informed consent for publication was obtained from all patients and their families included in this retrospective analysis.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
