Incidence and Risk Factors for Surgical Site Infection after Femoral Neck Fracture Surgery: An Observational Cohort Study of 2218 Patients
Background. Surgical site infection (SSI) was a formidable challenge for surgical management of femoral neck fractures; however, there was a lack of studies with comprehensive variables. We conducted this study to investigate the incidence and risk factors of SSI in elderly patients with femoral neck fractures. Methods. This was a retrospective study of patients who presented with femoral neck fractures and underwent surgery in our institution between January 2016 and April 2020. All data were collected from a previously validated database. Patients were divided into SSI and non-SSI groups. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors for SSI. Results. A total of 2218 patients with femoral neck fractures were enrolled in the study, of whom 22 (1%) developed SSI, including 15 (0.7%) superficial and 7 (0.3%) deep SSIs. After multivariable adjustment for confounding factors, patients with and without SSI significantly differ in terms of gender, prolonged time to surgery, , and injury mechanism. Conclusions. Our results were helpful for stratification of SSI risk and improved management of hip fracture. Clinicians should be alert to patients with these factors and improve modifiable factors such as preoperative waiting time.
The femoral neck fracture was a common fracture type in orthopedics, especially among elderly individuals, accounting for 48.22% of hip fractures [1, 2]. At present, surgical intervention was the typical treatment modality to help patients with femoral neck fractures restore daily activities as soon as possible . However, surgical site infection (SSI) was one of the most common postoperative adverse outcomes for femoral neck fracture patients, and it was reported that 2.7%-14.9% of hip fracture patients developed SSI after surgery [4–6]. Moreover, postoperative SSI resulted in the doubled risk of mortality and prolonged duration of hospital stay, and the mean financial loss associated with an infection was £7,726 [7, 8]. Therefore, it is necessary to have a clear understanding of the incidence and risk factors of SSI, especially those modifiable, to reduce SSI occurrence.
Published studies had confirmed that age, body mass index (BMI), greater index of comorbidities, hypoalbuminemia, surgical duration, increased duration of anesthesia, current smoking, and elevated fasting blood glucose level were the risk factors of SSI for hip fracture patients [9–12]. However, most previous studies focused on hip fractures, while only a few studies focused on femoral neck fractures separately. In addition, most studies had a small sample size and limited potential factors for adjustment . It is likely that the findings from previous literature are not exactly applicable to patients with femoral neck fractures.
Given that, we incorporated as many factors as possible in the present study to determine the prevalence of SSI and identify the risk factors associated with SSI following surgery of the femoral neck fractures.
2. Patients and Methods
2.1. Inclusion and Exclusion Criteria
Data on patients who underwent operative management for femoral neck fracture at the 3rd Hospital of Hebei Medical University between January 2016 and April 2020 were extracted from the Surgical Site Infection in Orthopedic Surgery (SSIOS) database. All included patients were 18 years or older and received operative management for an acute closed femoral neck fracture. Patients were excluded if presenting any of the following: old fractures (>21 days), pathological fractures, periprosthetic fractures, not undergoing the initial surgery in our hospital, and with incomplete information (Figure 1). One-year follow-up was conducted after discharge, including the first 1-month follow-up at the outpatient clinic and every 3 months thereafter by telephone or outpatient visit until one year after surgery. The Helsinki Declaration consensus was followed, and the institutional review board approved this research. Because no patient identity information was included, the requirement for informed consent was waived.
2.2. Definition of SSI
According to the diagnosis criteria of the Center for Disease Control (CDC), SSI was diagnosed and classified into two types . Superficial SSI was defined as an infection involving the skin and subcutaneous tissue of the surgical site, with wound signs and symptoms (swelling, redness, pain, and heat) and was often resolved by physiotherapy or oral antibiotics. Deep SSI was defined as an infection involving the fascia, muscle, and deep soft tissues and was diagnosed based on at least one of the following: fascia or muscle infections, persistent wound discharge or dehiscence, visible abscess or gangrene requiring surgical debridement, and implant removal or exchange.
According to the Surgical Site Infection Guidelines developed by the American College of Surgeons and Surgical Infection Society, prophylactic antibiotics were administered for SSI prevention . Based on the hospital policy, 1 to 3 grams of cefazolin were intravenously used within 0.5 hours before the incision and 24 hours postoperatively.
2.4. Data Collection of Variables
We collected 63 variables from demographic variables, fracture-related variables, operation-related variables, and preoperative laboratory parameters. Demographic variables included gender, age, body mass index (BMI), residential location (rural or urban), and comorbidities (diabetes, hypertension, cardiovascular disease, cerebrovascular disease, and so on). Fracture-related variables included injury mechanism (low or high energy), preoperative duration, and concurrent fractures. Operation-related variables included reduction methods (closed or open reduction), American Society of Anesthesiologists grade (ASA), anesthesia pattern, operative time, fixation type, intraoperative blood loss, and intraoperative blood transfusion. Preoperative laboratory parameters included platelet (PLT), albumin/globulin (A/G), alanine transaminase (ALT), white blood cells (WBC), red blood cell (RBC), albumin (ALB), lymphocytes (LYM), very low-density lipoprotein (VLDL), mean corpuscular volume (MCV), uric acid (UA), hemoglobin (HGB), hypersensitive C-reactive protein (HCRP), platelet distribution width (PDW), glucose (GLU), total protein (TP), and globulin (GLOB).
2.5. Statistical Analysis
Continuous variables were described as mean and standard deviation (), while categorical variables were expressed as frequency and percentage. The receiver operating characteristic (ROC) analysis was used for quantitative data such as time to surgery and operative time to determine the optimum cut-off values. The Shapiro-Wilk test was used to test continuous variables for normal distribution. According to the distribution pattern, Student’s -test or the Mann-Whitney test was performed. The Pearson chi-square test or Fisher exact test was applied to compare the categorical variables. Univariate and multivariate logistic regression analyses determine the independent risk factors. indicated statistical significance. Model fit was evaluated by the Hosmer-Lemeshow goodness-of-fit test, and acceptable fitness was accepted when was <0.05. The SPSS 26.0 software was used for data analysis, and GraphPad Prism 9 software was used for mapping.
A total of 2218 patients with femoral neck fractures were collected in the current study. There were 22 (1%) patients who developed SSI, and 2196 (99%) patients were without SSI. The rate of superficial infection was 0.7% while it was 0.3% for the deep SSI.
The ROC analysis showed the optimum cut-off value for time to surgery, and operative time was 5.5 days (considering the clinical practice, we use 6 days) and 2 hours, respectively (Table 1 and Figure 2). The univariate analysis showed that concurrent fractures (), injury mechanism (high energy) (), preoperative waiting days (), operative hours (), gender (male) (), (P =0.035), DBIL >6 μmol/L (P =0.017), and () were identified as significant risk factors for the development of SSI and to be entered into the multivariate logistic regression analysis (Table 2). The result of multivariate analysis showed gender (male vs. female) (OR, 3.521, ), preoperative waiting days (OR, 2.85, ), (OR, 2.861, ), and injury mechanism (high energy) (OR, 3.688, ) were independent risk factors (Table 3). The multivariate predictive model was adequate (Hosmer-Lemeshow test, , ).
There is still lake of some large-sample studies on the incidence and risk factors of SSI in patients with femoral neck fractures. In our study, we used a previously validated database to resolve this issue. We found the SSI rate was 1%. Univariate and multivariate analyses revealed that gender (male), preoperative waiting days, , and injury mechanism (high energy) were independent risk factors for SSI occurrence.
In this study, the incidence of SSI was 1%, remarkably lower than those (2–7%) reported in other literature [12, 15–18]. The possible reasons could be various, involving heterogeneous patient characteristics, surgical interventions, study designs, and follow-up period. Slobogean et al.  found the incidence rate of SSI was 5.1% in young femoral neck fracture patients (<60 years old). A recent prospective observational study by Ji et al. reported the rate of 3.76% . And this was probably due to the following reason that our cohort included patients at a relatively older age (66.8 vs. >60 years in Slobogean et al. ) and was a retrospective study (vs. prospective study in Ji et al. ). In addition, the bacterial culture results were used for infection diagnosis in some studies [20, 21], which might also affect the incidence of SSI.
Gender proved to be a risk factor associated with SSI in the current study, consistent with the findings of most studies [22–24]. In this study, males were 3.2-fold more susceptible than females to SSI (OR, 3.214, ), which was consistent with the finding by Zhao et al. . However, this factor was not conclusive, because some scholars found no significant correlation between gender and SSI . The possible underlying mechanism may be the higher prevalence with male population, such as tobacco and alcohol, which were well-established factors to influence the occurrence of SSI [25–29]. It was also likely that other factors that were more prevalent in males, such as higher injury mechanism in relatively younger patients, contributed to this observed risk [30–32].
Preoperative waiting time as a risk factor for SSI was a hot-discussed point, and its relation to a range of adverse outcomes has been reported [33–35]. Current clinical practice guidelines recommend surgical treatment within 24-48 hours . However, the cut-off time for preoperative waiting time applied in clinical practice varied . Chen et al.  conducted an observational study of 889 hip fracture patients and found patients with the preoperative waiting h exhibited a higher risk of complications. In another prospective study of 1941 patients with intertrochanteric fracture, time to days was reported as a significant risk factor for SSI . Our institution as a tertiary referral and orthopedic-specified hospital, received a substantial proportion of patients who were transferred from secondary hospitals, presenting with severer fractures or more complex medical conditions. Thus, a long time would be needed to adjust the patients’ preoperative physical status to improve the tolerance to operation. Furthermore, during the past ten years, the number of annual orthopedic surgeries in our hospital had increased to approximately 50,000 cases per year, which made it very tense for the operative arrangement, more during the past 3 years since COVID-19 become epidemic. Over 2/3 of patients had to be operated without the recommended early operation time frame (within 24-48 h of injury) [39–41]. The prolonged preoperative waiting time may be attributable to the physiologically unstable state of patients and insufficient staff and equipment. Thus, surgeons should be aware of the effect of preoperative waiting time on SSI and provide adequately targeted preoperative interventions and optimized operative procedures.
To our knowledge, this study was the first to identify CHE as an independent risk factor for SSI, and the relation magnitude was 2.86. The underlying pathophysiologic mechanism may be various, including but not limited to trauma per se [36, 37]. For example, Ba et al.  showed the systemic inflammatory response following trauma reduced the liver synthesis of CHE, and the greater the decrease in amplitude of CHE suggested a more severe trauma accompanied by serious soft tissue damage , which could provide a fine environment for bacterial colonization and infection. At the same time, a low CHE value could indicate malnutrition which also had detrimental effects on wound healing [5, 44–47]. Anyway, as an important indicator to evaluate the risk of SSI, CHE should be recognized and kept in mind in practice to alert the possibility of SSI.
The injury mechanism (high energy) has been verified as an independent risk factor of SSI , which was reconfirmed in the present study. First, the high-energy injuries meant the resultant more damaged skin, the fractured bone itself, and even open wounds, which allowed microbial easy to colonize and contaminate to give rise to SSI [43, 49]. Moreover, our data showed that the operative time in the high-energy group was approximately twice that of the low-energy group, which might have prolonged the exposure of wounds to the air, resulting in the increased risk of infection . Therefore, the mechanism of injury should be meticulously inquired for a comprehensive evaluation, and necessary debridement procedures should be immediately carried out, even in some cases seemingly not serious.
The present study had several strengths, including a large-sample study, adjustment for comprehensive and numerous variables covering various aspects, and ROC analysis used for detecting highly sensitive cut-off values for some continuous variables. This study was not without limitations. The retrospective design inherited the selective bias. Although a multivariate regression model was used to minimize numerous confounding variables as much as possible, unmeasured or unknown confounders remain. And our results might be less generalizable to institutions, especially in developed countries, which strictly implement the early operation (within 24-48 h) strategy.
In summary, the overall incidence of SSI for femoral neck fracture following operative treatment was 1%. Gender (male), preoperative waiting h, , and injury mechanism (high energy) were independent risk factors for the SSI after femoral neck fracture surgery. Orthopedists should take these risk factors into consideration when evaluating and stratifying the risk of SSI following surgeries of hip fracture.
Data is available from the authors upon request.
Conflicts of Interest
The authors declare that there is no conflict of interest to disclose.
ZKX participated in the study design and statistical analysis and interpreted the results, and TYX drafted the manuscript. ZKX and TYX should be considered co-first authors. LXT provided the original idea and ZYB revised the articles; TM and ZY participated in data collection.
We are grateful to the Institute of Orthopedics of the Third Hospital of Hebei Medical University for providing data.
N. Baidwan and S. Naranje, “Epidemiology and recent trends of geriatric fractures presenting to the emergency department for United States population from year 2004-2014,” Public Health, vol. 142, pp. 64–69, 2017.View at: Publisher Site | Google Scholar
Y. Zhang, Y. Su, J. Hao, and M. Punsoni, Clinical Epidemiology of Orthopedic Trauma, Georg Thieme Verlag, Stuttgart, 2012.View at: Publisher Site
B. Miller, J. Callaghan, P. Cram, M. Karam, J. Marsh, and N. Noiseux, “Changing trends in the treatment of femoral neck fractures: a review of the american board of orthopaedic surgery database,” JBJS, vol. 96, no. 17, article e149, 2014.View at: Publisher Site | Google Scholar
L. de Jong, T. Klem, T. Kuijper, and G. Roukema, “Factors affecting the rate of surgical site infection in patients after hemiarthroplasty of the hip following a fracture of the neck of the femur,” The Bone & Joint Journal, vol. 8, pp. 1088–1094, 2017.View at: Google Scholar
J. Le, Z. Dong, J. Liang et al., “Surgical site infection following traumatic orthopaedic surgeries in geriatric patients: incidence and prognostic risk factors,” International Wound Journal, vol. 17, no. 1, pp. 206–213, 2020.View at: Publisher Site | Google Scholar
X. Liu, Z. Dong, J. Li et al., “Factors affecting the incidence of surgical site infection after geriatric hip fracture surgery: a retrospective multicenter study,” Journal of Orthopaedic Surgery and Research, vol. 14, no. 1, p. 382, 2019.View at: Publisher Site | Google Scholar
F. Tian, L. Zhang, H. Zhao, C. Liang, N. Zhang, and H. Song, “An increase in the incidence of hip fractures in Tangshan, China,” Osteoporosis International, vol. 25, no. 4, pp. 1321–1325, 2014.View at: Publisher Site | Google Scholar
M. Wijeratna, J. McRoberts, and M. Porteous, “Cost of infection after surgery for intracapsular fracture of the femoral neck,” Annals of the Royal College of Surgeons of England, vol. 97, no. 4, pp. 283–286, 2015.View at: Publisher Site | Google Scholar
Q. Hu, Y. Zhao, B. Sun, W. Qi, and P. Shi, “Surgical site infection following operative treatment of open fracture: incidence and prognostic risk factors,” International Wound Journal, vol. 17, no. 3, pp. 708–715, 2020.View at: Publisher Site | Google Scholar
K. Kjørholt, N. Kristensen, D. Prieto-Alhambra, S. Johnsen, and A. Pedersen, “Increased risk of mortality after postoperative infection in hip fracture patients,” Bone, vol. 127, pp. 563–570, 2019.View at: Publisher Site | Google Scholar
T. Ma, K. Lu, L. Song et al., “Modifiable factors as current smoking, hypoalbumin, and elevated fasting blood glucose level increased the SSI risk following elderly hip fracture surgery,” Journal of Investigative Surgery, vol. 33, no. 8, pp. 750–758, 2020.View at: Publisher Site | Google Scholar
C. Pollmann, F. Dahl, J. Røtterud, J. Gjertsen, and A. Årøen, “Surgical site infection after hip fracture - mortality and risk factors: an observational cohort study of 1, 709 patients,” Acta Orthopaedica, vol. 91, no. 3, pp. 347–352, 2020.View at: Publisher Site | Google Scholar
T. Horan, R. Gaynes, W. Martone, W. Jarvis, and T. Emori, “CDC definitions of nosocomial surgical site infections, 1992: a modification of CDC definitions of surgical wound infections,” Infection Control and Hospital Epidemiology, vol. 13, no. 10, pp. 606–608, 1992.View at: Publisher Site | Google Scholar
K. Ban, J. Minei, C. Laronga et al., “American College of Surgeons and Surgical Infection Society: surgical site infection guidelines, 2016 update,” Journal of the American College of Surgeons, vol. 224, no. 1, pp. 59–74, 2017.View at: Publisher Site | Google Scholar
H. Nishikawa, M. Shirano, Y. Kasamatsu et al., “Comparative usefulness of inflammatory markers to indicate bacterial infection --analyzed according to blood culture results and related clinical factors,” Diagnostic Microbiology and Infectious Disease, vol. 84, no. 1, pp. 69–73, 2016.View at: Publisher Site | Google Scholar
O. Ojo, K. Oluwadiya, I. Ikem, L. Oginni, A. Ako-Nai, and F. Daniel, “Superficial swab cultures in open fracture management: insights from a resource-poor setting,” Journal of Wound Care, vol. 19, no. 10, pp. 432–438, 2010.View at: Publisher Site | Google Scholar
H. Deng, A. Chan, S. Ammanuel et al., “Risk factors for deep surgical site infection following thoracolumbar spinal surgery,” Journal of Neurosurgery Spine, vol. 32, no. 2, pp. 292–301, 2019.View at: Publisher Site | Google Scholar
E. Remily, N. Mohamed, W. Wilkie et al., “Hip fracture trends in America between 2009 and 2016,” Geriatric Orthopaedic Surgery & Rehabilitation, vol. 11, article 215145932092958, 2020.View at: Publisher Site | Google Scholar
K. Zhao, J. Zhang, J. Li et al., “Incidence and risk factors of surgical site infection after intertrochanteric fracture surgery: a prospective cohort study,” International Wound Journal, vol. 17, no. 6, pp. 1871–1880, 2020.View at: Publisher Site | Google Scholar
G. Chan, E. Iliopoulos, A. Jain, M. Turki, and A. Trompeter, “Infection after operative fixation of tibia plateau fractures. A risk factor analysis,” Injury, vol. 50, no. 11, pp. 2089–2092, 2019.View at: Publisher Site | Google Scholar
I. Cho, M. Cho, K. Lee et al., “Effects of smoking habit change on hospitalized fractures: a retrospective cohort study in a male population,” Archives of Osteoporosis, vol. 15, no. 1, p. 29, 2020.View at: Publisher Site | Google Scholar
D. Gaalema, A. Leventhal, J. Priest, and S. Higgins, “Understanding individual differences in vulnerability to cigarette smoking is enhanced by attention to the intersection of common risk factors,” Preventive Medicine, vol. 117, pp. 38–42, 2018.View at: Publisher Site | Google Scholar
Z. Liang, K. Rong, W. Gu et al., “Surgical site infection following elective orthopaedic surgeries in geriatric patients: incidence and associated risk factors,” International Wound Journal, vol. 16, no. 3, pp. 773–780, 2019.View at: Publisher Site | Google Scholar
Y. Zhu, S. Liu, X. Zhang, W. Chen, and Y. Zhang, “Incidence and risks for surgical site infection after adult tibial plateau fractures treated by ORIF: a prospective multicentre study,” International Wound Journal, vol. 14, no. 6, pp. 982–988, 2017.View at: Publisher Site | Google Scholar
V. Groot, H. Beckerman, G. Lankhorst, and L. Bouter, “How to measure comorbidity: a critical review of available methods,” Journal of Clinical Epidemiology, vol. 57, no. 3, pp. 221–229, 2004.View at: Google Scholar
R. Clarkson, S. Mahmoud, A. Rangan, W. Eardley, and P. Baker, “The use of foot pumps compression devices in the perioperative management of ankle fractures: systematic review of the current literature,” The Foot, vol. 31, pp. 61–66, 2017.View at: Publisher Site | Google Scholar
S. R. Konda, W. D. Lack, R. B. Seymour, and M. A. Karunakar, “Mechanism of injury differentiates risk factors for mortality in geriatric trauma patients,” Journal of Orthopaedic Trauma, vol. 29, no. 7, pp. 331–336, 2015.View at: Publisher Site | Google Scholar
W. Marianne, S. Finnur, and F. Frede, “Preoperative waiting time increased the risk of periprosthetic infection in patients with femoral neck fracture,” Acta Orthopaedica, vol. 84, no. 2, pp. 124–129, 2013.View at: Publisher Site | Google Scholar
R. Smektala, S. Hahn, P. Schräder et al., “Medial hip neck fracture: influence of pre-operative delay on the quality of outcome. Results of data from the external in-hospital quality assurance within the framework of secondary data analysis,” Der Unfallchirurg, vol. 113, no. 4, pp. 287–292, 2010.View at: Google Scholar
S. Ridgeway, J. Wilson, A. Charlet, G. Kafatos, A. Pearson, and R. Coello, “Infection of the surgical site after arthroplasty of the hip,” The Journal Of Bone and Joint Surgery British Volume, vol. 87-B, no. 6, pp. 844–850, 2005.View at: Publisher Site | Google Scholar
P. Kelly-Pettersson, B. Samuelsson, O. Muren et al., “Waiting time to surgery is correlated with an increased risk of serious adverse events during hospital stay in patients with hip-fracture: a cohort study,” International Journal of Nursing Studies, vol. 69, pp. 91–97, 2017.View at: Publisher Site | Google Scholar
N. Simunovic, P. Devereaux, S. Sprague et al., “Effect of early surgery after hip fracture on mortality and complications: systematic review and meta-analysis,” CMAJ, vol. 182, no. 15, pp. 1609–1616, 2010.View at: Publisher Site | Google Scholar
X. Chen, Z. Liao, Y. Shen, B. Dong, L. Hou, and Q. Hao, “The relationship between pre-admission waiting time and the surgical outcomes after hip fracture operation in the elderly,” The Journal of Nutrition, Health & Aging, vol. 25, no. 8, pp. 951–955, 2021.View at: Publisher Site | Google Scholar
M. N. Chilov and L. M. March, “Evidence-based guidelines for fixing broken hips: an update,” The Medical Journal of Australia, vol. 179, no. 9, pp. 489–493, 2003.View at: Publisher Site | Google Scholar
S. I. G. Network, Prevention and Management of Hip Fracture in Older People: A National Clinical Guideline, Scottish Intercollegiate Guidelines Network, Edinburgh, UK, 2002.
C. Ji, Y. Zhu, S. Liu et al., “Incidence and risk of surgical site infection after adult femoral neck fractures treated by surgery: a retrospective case-control study,” Medicine, vol. 98, no. 11, article e14882, 2019.View at: Publisher Site | Google Scholar
M. Kalmeijer, E. van Nieuwland-Bollen, D. Bogaers-Hofman, G. de Baere, and J. A. J. W. Kluytmans, “Nasal carriage of Staphylococcus aureus: is a major risk factor for surgical-site infections in orthopedic surgery,” Infection Control and Hospital Epidemiology, vol. 21, no. 5, pp. 319–323, 2000.View at: Publisher Site | Google Scholar
O. Khan, V. Weston, and B. Scammell, “Methicillin-resistant _Staphylococcus aureus_ incidence and outcome in patients with neck of femur fractures,” The Journal of Hospital Infection, vol. 51, no. 3, pp. 185–188, 2002.View at: Publisher Site | Google Scholar
J. Merrer, L. Desbouchages, V. Serazin, J. Razafimamonjy, F. Pauthier, and M. Leneveu, “Comparison of routine prophylaxis with vancomycin or cefazolin for femoral neck fracture surgery: microbiological and clinical outcomes,” Infection Control and Hospital Epidemiology, vol. 27, no. 12, pp. 1366–1371, 2006.View at: Publisher Site | Google Scholar
G. S. S. Slobogean, T. Scott, and M. Bhandari, “Complications following young femoral neck fractures,” Injury, vol. 46, no. 3, pp. 484–491, 2015.View at: Publisher Site | Google Scholar
P. Rodriguez-Fernandez, D. Adarraga-Cansino, and P. Carpintero, “Effects of delayed hip fracture surgery on mortality and morbidity in elderly patients,” Clinical Orthopaedics and Related Research, vol. 469, no. 11, pp. 3218–3221, 2011.View at: Publisher Site | Google Scholar
L. Ba, D. Wu, A. Qian, M. Zhang, and B. Xiong, “Dynamic changes of serum cholinesterase activity after severe trauma,” Journal of Zhejiang University Science B, vol. 15, no. 12, pp. 1023–1031, 2014.View at: Publisher Site | Google Scholar
C. Bartow-McKenney, G. Hannigan, J. Horwinski et al., “The microbiota of traumatic, open fracture wounds is associated with mechanism of injury,” Wound Repair and Regeneration, vol. 26, no. 2, pp. 127–135, 2018.View at: Google Scholar
Y. Bai, X. Zhang, Y. Tian, D. Tian, and B. Zhang, “Incidence of surgical-site infection following open reduction and internal fixation of a distal femur fracture: an observational case-control study,” Medicine, vol. 98, no. 7, article e14547, 2019.View at: Publisher Site | Google Scholar
L. Santarpia, I. Grandone, F. Contaldo, and F. Pasanisi, “Butyrylcholinesterase as a prognostic marker: a review of the literature,” Journal of Cachexia, Sarcopenia and Muscle, vol. 4, no. 1, pp. 31–39, 2013.View at: Publisher Site | Google Scholar
J. Shao, H. Zhang, B. Yin, J. Li, Y. Zhu, and Y. Zhang, “Risk factors for surgical site infection following operative treatment of ankle fractures: a systematic review and meta-analysis,” International Journal of Surgery (London, England), vol. 56, pp. 124–132, 2018.View at: Publisher Site | Google Scholar
H. Ushirozako, T. Hasegawa, Y. Yamato et al., “Does preoperative prognostic nutrition index predict surgical site infection after spine surgery?” European Spine Journal, vol. 30, no. 6, pp. 1765–1773, 2021.View at: Publisher Site | Google Scholar
C. H. Renninger, G. Cochran, T. Tompane, J. Bellamy, and K. Kuhn, “Injury characteristics of low-energy Lisfranc injuries compared with high-energy injuries,” Foot and Ankle International, vol. 38, no. 9, pp. 964–969, 2017.View at: Publisher Site | Google Scholar
S. Dingemans, M. Sier, R. Peters, J. Goslings, and T. Schepers, “Two-stage treatment in patients with patients with high-energy femoral fractures does not lead to an increase in deep infectious complications: a propensity score analysis,” European Journal of Trauma and Emergency Surgery, vol. 44, no. 1, pp. 125–131, 2018.View at: Publisher Site | Google Scholar
R. Oguz, M. Diab-Elschahawi, J. Berger et al., “Airborne bacterial contamination during orthopedic surgery: a randomized controlled pilot trial,” Journal f Clinical Anesthesia, vol. 38, pp. 160–164, 2017.View at: Publisher Site | Google Scholar