The Predictive Role of Platelet-to-Lymphocyte Ratio and Systemic Immune-Inammation Index in Young and Middle-Aged Patients with Tibial Plateau Fractures

There is suggestive evidence that the platelet-to-lymphocyte ratio (PLR) and systemic immune-inammation index (SII) are related to the severity of fracture. The purpose of this study was to investigate the role of PLR and SII in predicting fracture severity in young and middle-aged patients with tibial plateau fractures (TPFs). The retrospective cohort study involving 229 isolated TPFs was performed between January 2015 and December 2019. Medical records of hospitalized patients were extracted from the electronic case system. Three experienced orthopedic surgeons classied the imaging data according to the Schatzker classication. All the patients were divided into two groups: group1 consisted of fractures of mild to moderate severity (Schatzker types I-IV), and group2 consisted of fractures of severe severity (Schatzker types V-VI). Platelet, neutrophil, and lymphocyte values at admission were obtained. The PLR = platelet/lymphocyte counts and the SII = platelet × neutrophil/lymphocyte counts were noted. Patients in groups 1 and 2 were statistically compared in terms of PLR and SII value on hospital admission. There were differences in the PLR, + and K + levels, and neutrophil count between According were


Background
The tibial plateau is one of the main load-bearing parts of the human body which bears 5 times the human body weight [1]. The tibial plateau is easily damaged by external forces, resulting in soft-tissue damage which can impair the range of motion and stability of the knee joint [2][3][4]. Tibial plateau fracture is a complex intraarticular fracture usually caused by high energy injury. It presents a great challenge to trauma surgeons due to its complexity and the risk of various complications such as nerve and vascular injury, delayed or non-union of fractures [5]. The young and middle-aged people are the common population affected by TPFs [6,7].
Radiological classi cation systems of fractures, designed to group fractures according to injury mechanisms and fracture patterns, have been utilized to assess the severity of fracture injury [8]. The Schatzker classi cation, based on a two-dimensional representation of the fracture, is the most commonly used type of tibial plateau fracture which can classify TPFs into I-VI types [2]. The tibial plateau experiences more violent injuries, more knee instability, and a poorer prognosis with the increase in digital classi cation [9].
Recent studies have shown that some blood indicators can serve as potential biomarkers to predict the severity of tissue damage. The platelet-to-lymphocyte ratio, calculated as the absolute platelet count divided by the absolute lymphocyte count, is a predictor of diagnosis and prognosis of a variety of diseases such as hip fracture, in ammatory diseases, cancer, systemic lupus erythematosus, and cardiovascular disease [10][11][12][13]. Moreover, there is a critical balance between the pro-in ammatory and anti-in ammatory systems in a traumatic immune response [14]. Severe trauma can lead to an imbalance in the immune system, resulting in an increase in neutrophils and a decrease in lymphocytes in the circulatory system. Therefore, it is reasonable to use SII to predict the severity of trauma severity.
However, the relationship between the PLR, SII levels and the severity of TPFs has not been carefully clari ed. Therefore, this study aimed to explore the predictive role of PLR and SII in young and middleaged patients with TPFs and further elaborate their important practical role in guiding clinical work.

Study design and patients
This retrospective study was conducted in the level I electronic case system, spanning ve years (between January 2015 and December 2019). The enrolled participants were young and middle-aged adults between 18 and 60 years, the diagnosis was unilateral isolated closed TPF, and blood test and imaging records were complete. The exclusion criteria were: (a) participants with cardiovascular disease, malignancies, autoimmune disease, multiple traumas, open wounds, postoperative infections, severe neurovascular injury, and systemic in ammatory or infectious diseases, (b) participants whose time from injury to admission were > 48 hours. A total of 229 patients with isolated TPFs were included in the study.

Imaging Data And Patient Grouping
All images of the patients were taken from the hospital's Picture Archiving and Communication Systems (PACS). Patients who met the inclusion criteria had their images read independently by three experienced orthopedic surgeons. The surgeons worked independently and did not communicate with each other. The imaging data of all patients with tibial plateau fractures were classi ed according to the Schatzker classi cation system. Types I to III are fractures of the lateral tibial plateau, whereas Type IV is the isolated fracture of the medial column of the tibial plateau. Types I-IV are simple fractures that are often associated with minor injuries, whereas Type V-VI are complex fractures and are often associated with more violent injuries and a signi cant compromise of the soft tissue envelope [2]. Therefore, the patients were divided into two groups: Group 1 was mild to moderate TPFs, representing patients of Schatzker type I-IV fractures, whereas group 2 was severe TPFs, representing patients of Schatzker type V-VI fractures.

Data Collection
Patient characteristics obtained from the electronic medical records included: Demographic characteristics, lifestyle risk factors, comorbid diseases, laboratory data such as white blood cell count (× 10 9 /L, reference range 3.5-9.5), platelet counts (× 10 9 /L, reference range 100-300), lymphocyte counts (× 10 9 /L, reference range 1.1-3.2), albumin (g/L, reference range 35.0-55.0), creatinine (µmol/L, reference range 53.0-106.0) and C-reaction protein (mg/L, reference range 0.5-8) ( Table 1). The patient's venous blood was drawn by a trained nurse on admission. The PLR = platelet/lymphocyte counts, SII = platelet × neutrophil/lymphocyte counts, and the Schatzker classi cation was used to assess the severity of TPFs. The continuous data of normal distribution are expressed as mean ±SD; The continuous data of skewed distribution is categorized by reference, and categorical variables are summarized as frequency (percent)

Statistical analysis
All statistical analyses and graphics in this study were analyzed using SPSS21.0 (IBM Corp, Armonk, NY, USA). Continuous data were expressed as mean ± standard deviation (SD) and categorical variables were expressed as absolute values and percentages. Student's t-test was used for continuous variables conforming to the normal distribution, and the chi-square test was used for categorical variables to compare the differences between the two groups. Univariate analysis was used to screen the risk factors of TPFs. Factors with P 0.05 in univariate analysis were further analyzed using multivariate logistic analysis. Odds ratio (OR) and 95% con dence interval (CI) were used to measure the strength of association between risk factors and TPFs. Moreover, the ROC curve was used to calculate the cutoff points of blood PLR and SII. In the multiple logistic regression analysis, P 0.05 was considered to be signi cantly associated with TPFs and was included in the model. For all statistical tests, P 0.05 was considered statistically signi cant (Fig. 1).

Results
Over  Table 1.
Tibial plateau fracture is a very common fracture, often occurring in young people or men, and is often the result of a violent injury, such as bicycle falls or car crashes, which can lead to serious knee movement problems, therefore, age and gender were included in the multiple regression analysis. In multiple logistic regression analyses, PLR ≥ 157.9 and SII ≥ 923.9 were signi cantly associated with the severity of tibial plateau fractures ( Table 2).

Discussion
To the best of our knowledge, this is the rst study to examine the relationship between PLR, SII levels and the severity of TPFs. Our study found that patients with severe TPFs were found to have higher PLR and SII compared with patients with mild to moderate TPFs. These results demonstrate that PLR and SII, as economical, simple, and easily measured laboratory parameters, can re ect the radiographic severity of TPFs in young and middle-aged adults, and simultaneously can also be used as effective predictors of the severity of TPFs.
The tibial plateau fracture is a common intraarticular fracture in which the fracture lines usually involving the proximal end of the tibia. These fractures account for 1%-2% of all fractures and often result in knee joint mobility disorders and instability. The commonly used Schatzker classi cation, which is based on two-dimensional imaging can effectively re ect the severity of TPFs and reveal more details of TPFs. The six basic types of TPFs have been proven and generally accepted as a practical classi cation criterion. However, the more details the classi cation presents, the higher the likelihood of disagreement in an interand intra-observer basis [2], therefore, the Schatzker classi cation is easily in uenced by doctors' experience and familiarity with the Schatzker classi cation.
The PLR and SII indicators have been widely studied in recent years as immunoin ammatory indicators as they are easy to obtain and cost-effective in clinical application. The PLR has great value in predicting the severity and mortality in many diseases such as hip fracture, in ammatory diseases, malignancy, systemic lupus erythematosus, and cardiovascular disease [10][11][12]15]. Moreover, the SII has been associated with the prognosis of malignancies, post-traumatic thrombosis, and fractures following osteoporosis [16-18]. Platelets contain a large amount of soluble and cell-related immunomodulatory molecules that enhance the immune response when the body is damaged [19]. Therefore, platelets not only serve as important hemostatic cells but also bind to leukocytes and vascular cells to regulate cellular responses which play an important role in immune defense and in ammatory responses and lead to the activation of in ammation or apoptosis of cells [20,21]. Multiple studies have shown that various stress events such as tissue damage, severe trauma, and major surgery can stimulate an increase in circulating white blood cells, which are characterized by an increase in neutrophils [6]. For example, Morell et al. found a positive correlation between white blood cell count and the injury severity score [22]. Moreover, Neutrophils can promote tissue repair after injury by removing tissue debris at the site of injury and secreting growth factors or pro-angiogenic factors. Therefore, neutrophils play a similar role in immune defense as platelets and can be triggered by trauma or tissue in ammation [23,24]. In addition, Numerous stressful events can lead to lymphocyte depletion and further re ect the body's immune system's resistance and adaptability [25]. Therefore, the induction of immune defense and in ammatory responses in the body after a violent injury, such as TPFs, can lead to an increase in platelets and neutrophils and a decrease in lymphocytes, which supports the use of PLR and SII to predict the severity of TPFs.
There are a variety of factors can affect PLR and SII levels. This study tried to exclude the in uence of confounding factors. The PLR is an effective predictor of cardiovascular and rheumatic diseases as has been demonstrated in many studies [13,15]. In addition, PLR has been reported to be associated with the prognosis of many severe injuries, dementia, and malignancies in recent years [10,16,26]. For example, Wang et al. found that patients with a high PLR (≥ 189) had a higher one-year mortality rate than patients with low PLR (< 189) [10]. Mao et al. found that PLR > 193.55 in patients indicates malnutrition and more advanced cancer stage [12]. Many studies have reported SII to be closely related to fracture after osteoporosis. For example, Fang et al. found that SII ≥ 834.89 was identi ed as a signi cant risk factor for postmenopausal osteoporotic fracture [17]. Therefore, in the screening stage of TPFs cases, we tried to exclude the interference of the above confounding disease factors.
Tibial plateau fractures are usually caused by high-energy injuries and usually involve the lateral plateau, which is prone to serious knee ligament disorders and neurovascular injuries. More importantly, Bicondylar tibial plateau fractures (Schatzker types V-VI) [2] are often accompanied by severe intramedullary fractures, comminuted fractures, and extensive intramedullary hemorrhage, and may lead to greater latent blood loss [6]. However, Schatzker classi cation based on two-dimensional imaging system is still not satisfactory in displaying the above TPFs-related injuries, so PLR and SII have unique advantages in re ecting the severity of local TPFs. Moreover, there is often a concentration of body uids, loss of hemoglobin, and redistribution of red blood cells in patients with severe TPFs, which can lead to changes in HGB, and electrolyte concentration. Therefore, these indicators cannot be used to represent the severity of TPFs [27,28].
This study also has some limitations. First, the PLR and SII values were only collected at admission; their dynamic changes were not monitored over time after admission. Second, it was a single-center retrospective study with a relatively small sample size and a multi-center large sample retrospective study is needed to con rm our ndings. Third, this study failed to elaborate the detailed physiological mechanism of the elevation of PLR and SII in patients with severe TPFs, and there was a lack of clinical evidence to guide surgical treatment. Finally, some elderly patients with low-energy impairments were excluded from the study which may result in selection bias.

Conclusions
In summary, TPF is a highly prevalent intra-articular fracture that can result in extensive soft tissue injury and knee mobility impairment. Our results innovatively identi ed PLR and SII as novel serological markers of in ammation which combine the in ammatory and immune systems play an important role in predicting the severity of TPFs. Close monitoring of the changes in PLR and SII at the early stage of admission and combined with imaging examinations can help clinicians to make a more scienti c and effective judgment on the severity of TPFs. PLR and SII are likely to be a focus of future research. Availability of data and materials Flow diagram of patients included in this study Figure 2 The gure was produced by SPSS21.0 (IBM Corp, Armonk, NY, USA) (A) ROC curve analysis when the PLR cut-off point was 157.9, the sensitivity and speci city of PLR for predicting severe TPFs on admission were 60% and 86.9%, respectively, the area under curve was 0.738. (B) When the SII cutoff point was 923.9, the sensitivity and speci city of SII to predict severe TPFs at admission were 63.3% and 74.4%, respectively, the area under curve was 0.705 Figure 3