Relationship between preoperative red blood cell distribution width and postoperative pneumonia in elderly patients with hip fracture: a retrospective cohort study
Journal of Orthopaedic Surgery and Research volume 18, Article number: 253 (2023)
The relationship between the preoperative red blood cell distribution width and postoperative pneumonia in elderly patients with hip fractures remains unclear. This study investigated whether the preoperative red blood cell distribution width was associated with postoperative pneumonia in elderly patients with hip fractures.
Clinical data of patients with hip fractures in the Department of orthopedics of a hospital from January 2012 to December 2021 were retrospectively analyzed. A generalized additive model was used to identify both linear and nonlinear relationships between red blood cell distribution width and postoperative pneumonia. A two-piecewise linear regression model was used to calculate the saturation effect. Subgroup analyses were performed using stratified logistic regression.
This study included a total of 1444 patients. The incidence of postoperative pneumonia was 6.30% (91/1444), the mean age of the patients was 77.55 ± 8.75 years, and 73.06% of them (1055/1444) were female. After full adjustment for covariates, the preoperative red blood cell distribution width showed a nonlinear relationship with postoperative pneumonia. The two-piecewise regression model showed an inflection point at 14.3%. On the left side of the inflection point, the incidence of postoperative pneumonia increased by 61% for every 1% increase in red blood cell distribution width (OR: 1.61, 95% CI 1.13–2.31, P = 0.0089). The effect size was not statistically significant on the right side of the inflection point (OR: 0.83, 95% CI 0.61–1.12, P = 0.2171).
The relationship between preoperative red blood cell distribution width and incidence or postoperative pneumonia was nonlinear in elderly patients with hip fractures. The incidence of postoperative pneumonia was positively correlated with red blood cell distribution width when it was < 14.3%. A saturation effect was observed when the red blood cell distribution width reached 14.3%.
Hip fractures are becoming more frequent due to the increasing population of the elderly, and as a prevalent condition, its mortality and disability rates remain high . According to a retrospective study  that examined hip fractures in urban Chinese adults, the incidence of hip fractures among those aged 55 years and older was 148.75 per 100,000, with the incidence in women being higher (180.72 per 100,000) than that in men (121.86 per 100,000). The incidence of hip fractures also increases with age. For elderly patients with hip fractures, surgery is the preferred treatment option, and the choice of an intramedullary nail or hip replacement depends on the type of fracture [3,4,5]. The mortality rate for patients with hip fractures remains as high as 17–27% within 1 year after surgery and more than 40% at 5 years postoperatively, despite ongoing advancements in medical care . Pneumonia has been identified as the primary cause of postoperative death in elderly individuals with hip fractures [7, 8]. Postoperative pneumonia (POP) is a common complication of hip fracture in the elderly, with an incidence of 5.1–14.9% [9,10,11]. There are many risk factors for POP in patients with hip fractures; however, there is no shortage of contentious risk factors.
The red blood cell distribution width (RDW) is a measurement of variations in the size of red blood cells . RDW is a reliable indicator of a disease under several conditions. RDW has been found to be associated with cardiovascular disease [13, 14] (e.g., stroke, atrial fibrillation, and heart failure), malignancy , and death [16, 17]. In recent years, RDW has been found to be an independent predictor of inflammatory and infectious diseases [18,19,20]. Elevated RDW has been reported to be associated with pulmonary infections after hip fracture surgery in the elderly; however, there are variations in available reports [21, 22].
To determine whether preoperative RDW and POP were related, we conducted a retrospective cohort study with Chinese patients with hip fracture as the study population.
Participants and methods
A total of 1444 patients were included in this retrospective cohort study. We collected clinical data on elderly patients with hip fracture who were `admitted to the orthopedic department of Shenzhen Second People's Hospital between January 2012 and December 2021. The collected clinical data included general patient demographic information, preoperative laboratory test results, intraoperative data, and short-term prognostic information.
Hip fractures with a confirmed radiographic diagnosis (including femoral neck or intertrochanteric fractures), age ≥ 60 years, and surgical intervention were included. Old fractures (time from injury to admission > 3 weeks), pathological fractures, periprosthetic fractures, multiple fractures, or open fractures, preoperatively diagnosed pulmonary infections, combined hematological and immune system diseases (like leukemia, rheumatoid arthritis, and systemic lupus erythematosus), and incomplete data were among the exclusion criteria. The Clinical Research Ethics Committee of Shenzhen Second People's Hospital approved this study, which was conducted in compliance with the Declaration of Helsinki and medical ethics guidelines (20,210,620,213,357,012-FS01). The data were retrospective and anonymous; therefore, the requirement for informed consent was waived. See the flowchart for details (Fig. 1).
Clinical variables and outcomes
The RDW at admission served as the independent variable and the incidence of POP served as the dependent variable. Covariates included demographic data [e.g., age, sex, body mass index (BMI), classification of fracture, etc.], comorbidities [e.g., hypertension, diabetes mellitus, coronary artery disease, stroke, chronic obstructive pulmonary disease (COPD), etc.], preoperative laboratory indices (e.g., hemoglobin, leukocyte count, neutrophil count, monocyte count, albumin, globulin, blood urea nitrogen, and serum creatinine), surgery-related variables [operation duration, anesthesia methods, operation methods, American Society of Anesthesiologists (ASA) classification, intraoperative blood loss, etc.], and short-term prognostic information [e.g., length of hospital stay, intensive care unit (ICU) admission, and in-hospital death].
Definition of pneumonia
The diagnosis of pneumonia was based on the American Thoracic Society guidelines for healthcare-associated pneumonia  and Guidelines for the Diagnosis and Treatment of Adult hospital-acquired pneumonia and ventilator-associated pneumonia in China (2018 edition) : (1) newly developed cough, sputum production, or aggravation of symptoms of original respiratory disease and purulent sputum with or without chest pain after admission; (2) fever; (3) physical examination showing signs of lung consolidation and/or wet rales; (4) white blood cell count > 10 × 109/L or < 4 × 109/L; and (5) chest X-ray film showing patchy infiltrating shadow or interstitial changes. If a patient had any of the above items 1–4 plus item 5 and did not have other pulmonary diseases, such as tuberculosis, lung cancer, or pulmonary embolism, pneumonia was diagnosed. POP was used as the study outcome indicator from the first 24 h after surgery until discharge.
Continuous variables are expressed as mean ± standard deviation (normal distribution) or median (interquartile range) (skewed distribution), and categorical variables are expressed as frequencies or percentages.
One-way analysis of variance (ANOVA) (normal distribution), Kruskal–Wallis H (skewed distribution) test, and chi-square test (categorical variables) were used to determine any significant differences among the groups according to the RDW quartiles. To group the RDW in quartiles, the RDW data were ordered from smallest to largest and the ordered distribution was divided into four parts of equal size. Patients were classified into four groups according to quartiles of RDW, and baseline characteristics were compared among the groups. Second, univariate analysis with logistic regression was performed to evaluate the association between variables and POP. The results are expressed as the effect size with odds ratios (OR) and 95% confidence intervals (CI). Statistical analysis consisted of three main steps.
Step 1: Univariate and multivariate binary logistic regression models were used. We constructed three distinct models: a non-adjusted model (with unadjusted covariates), a minimally adjusted model (with adjusted sociodemographic variables only), and a fully adjusted model (with adjusted covariates, as shown in Table 1). Variance Infusion Factors > 10 were removed from the fully adjusted model. Step 2: Considering that logistic regression cannot handle the nonlinear relationship and the possibility of a nonlinear relationship between RDW and the incidence of POP cannot be ruled out, smooth curve fitting (penalized spline method) was used to address nonlinearity. We used a two-piecewise linear regression model to examine the saturation effect of RDW on the incidence of POP. The inflection point for the RDW was determined using “exploratory” analyses, which involved moving the trial inflection point along the predefined interval and picking up the one that gave the maximum model likelihood. We also performed a log-likelihood ratio test and compared the one-line linear regression model with a two-piecewise linear model. Step 3: To ensure the robustness of the data analysis, we converted RDW into a categorical variable based on quartiles for sensitivity analysis to verify the results of RDW as a continuous variable.
Analyses were performed using the statistical software packages R (http://www.R-project.org, The R Foundation) and EmpowerStats (http://www.empowerstats.com, X&Y Solutions, Inc, Boston, MA, USA). P values < 0.05 (two-sided) were considered statistically significant.
Baseline characteristics of participants
The baseline characteristics of the participants is shown in Table 1. We divided RDW into four groups (Q1–Q4) based on the quartile principle. The mean age of the 1444 patients was 77.55 ± 8.75 years; among them, 73.06% (1055/1444) were female and the incidence of POP was 6.30% (91/1444). Compared with the Q1–Q3 group, patients in the Q4 group had a higher mean age, longer time from fracture to surgery, and length of hospital stay; higher levels of platelet count, serum creatinine, and blood urea nitrogen; and a higher percentage of POP, femoral neck fracture, coronary artery disease, hypertension, and ASA classification ≥ 3 (P < 0.05). However, patients had a lower monocyte count, hemoglobin, albumin, and albumin–globulin ratio (AGR) (P < 0.05).
Univariate analysis showed that age, sex, comorbidity, coronary heart disease, stroke, Parkinson’s disease, white blood cell (WBC) count, neutrophil count, monocyte lymphocyte ratio (MLR), neutrophil lymphocyte ratio (NLR), hemoglobin, albumin, AGR, serum creatinine, blood urea nitrogen, ASA classification, intraoperative blood loss, ICU admission, and length of hospital stay were positively correlated with the incidence of POP (Table 2).
Results of the relationship between RDW and POP
Three models were used to evaluate the relationship between RDW and POP (Table 3). In the unadjusted model, each 1% increase in RDW was associated with a 32% increase in the incidence of POP (OR, 1.32; 95% CI 1.15–1.51, P < 0.0001). In the minimally adjusted model for age and sex, an association was also identified (OR, 1.21; 95% CI 1.05–1.41; P = 0.0076). However, in adjusted model II, we did not find a linear relationship between RDW and POP (P = 0.2354).
For sensitivity analysis, we divided RDW into four groups, and the results showed the same increasing trend in the incidence of POP in the unadjusted and minimally adjusted models (All P < 0.05), but the same trend was not found in adjusted model II (P = 0.0670).
Results of nonlinear association between RDW and POP
As shown in the smoothing spline, the RDW was found to have a nonlinear relationship with POP (Fig. 2). The two-piecewise regression model showed that the inflection point was 14.3% after adjusting for covariates (age, sex, comorbidity, coronary heart disease, stroke, Parkinson’s disease, WBC count, MLR, NLR, hemoglobin, albumin, AGR, serum creatinine, blood urea nitrogen, ASA classification, intraoperative blood loss, and ICU admission). On the left side of the inflection point, the incidence increased by 61% per 1% increase in RDW (95% CI 1.13–2.31, P = 0.0089 (Table 4). The effect size was not statistically significant on the right side of the inflection point (OR,0.83; 95% CI 0.61–1.12, P = 0.2171).
Results of subgroup analyses
We did not find any statistically significant interactions between age, sex, comorbidity, coronary heart disease, stroke, Parkinson’s disease, WBC count, NLR, MLR, hemoglobin, albumin, AGR, serum creatinine, blood urea nitrogen, ASA classification, intraoperative blood loss, and ICU admission (Table 5).
In this study, we used a generalized linear model to investigate the association between preoperative RDW and POP in elderly patients with hip fractures who were treated at the Department of Orthopedics of the Second People's Hospital of Shenzhen over a 10-year period. A nonlinear association between preoperative RDW and the incidence of postoperative pneumonia was discovered after 1444 patients' data were analyzed. To our knowledge, no previous research has mentioned this link. We found different correlations on both sides of the inflection point. On the left side of the inflection point, RDW was positively correlated with the incidence of POP (OR: 1.61, 95% CI 1.13–2.31, P = 0.0089), while on the right side of the inflection point, the effect seemed to be saturated with no statistical significance (OR, 0.83; 95% CI 0.61–1.12; P = 0.2171). Although medical technology has made great progress, there are still many problems associated with hip fractures, such as the decline in body function  and the occurrence of pneumonia.
Pneumonia, a common postoperative complication in elderly patients with hip fractures [9, 10, 26], causes prolonged hospitalization, increases cost and mortality, and increases the risk of readmission [27, 28], which greatly drains social resources and is a burden to patients' lives. Therefore, clinical care providers are required to take measures to reduce the incidence of POP. Numerous studies have identified risk factors for POP. Although some of these studies have identified RDW as a risk factor for POP , the fundamental relationship is still difficult to establish. Through this study, we have not only shown that preoperative RDW is a risk factor for POP but also pinpointed the inflection point, and this would give clinical healthcare practitioners a reference point on which to base future actions.
RDW was initially used to differentiate between anemia and other conditions , and a recent study demonstrated that increased RDW is a sign of an inflammatory response . Preoperative RDW was demonstrated to be a significant predictor of POP in a study on the risk factors for pneumonia following meningioma excision . Similarly, in a study of POP in patients with hip fracture , preoperative RDW was found to have a significant impact in predicting the development of pneumonia following hip fracture surgery. Additionally, another study  found that in patients undergoing coronary artery bypass grafting, the incidence of postoperative pneumonia increased from 1.5 to 4.1% in patients with RDW ≥ 12.36% compared to that of those with RDW < 11.72%, with a relative risk (RR) of 2.72 when unadjusted for variables (95% CI 1.37–5.44, P = 0.004), which remained statistically significant after multifactorial correction (RR:1.95, 95% CI 1.02–3.75, P = 0.044). Consistent with these results, our study also showed a similarly increased risk of POP in elderly patients with hip fractures with increasing RDW in the unadjusted model (OR: 1.32, 95% CI 1.15–1.51, P < 0.0001). Therefore, our study confirms that preoperative RDW is associated with POP. Clinical staffs can increase their attention to RDW for early assessment of patients at high risk of developing pneumonia.
The findings of this study demonstrated a correlation between preoperative RDW and POP incidence. Increased production of pro-inflammatory cytokines may be the cause of the inflammatory response that leads to poor maturation of peripheral blood erythrocytes and an increase in naïve erythrocytes, which in turn contributes to the increase in RDW . Previous studies  have shown that RDW is associated with the risk of postoperative inflammatory complications in patients. RDW is a valuable and sensitive marker of high levels of inflammatory activity in patients with community-acquired pneumonia . RDW is a straightforward and low-cost metric that reflects the degree of red blood cell volume heterogeneity. Because less deformable red blood cells worsen tissue oxygenation, elevated RDW may be associated with worse prognosis . However, the relationship between RDW and pneumonia remains unclear. RDW is connected to interleukin-6 (IL-6), C-reactive protein, and erythrocyte sedimentation rate, indicating that RDW levels may be a measure of inflammation, which is one of the mechanisms that has been considered [35,36,37]. Elevated RDW levels suggest that patients may develop organ dysfunction, which could have a negative impact on their outcomes [38, 39]. Chen et al.  retrospectively analyzed clinical data from elderly patients with hip fractures and found that the risk of developing POP was 5.097 times higher for patients with RDW > 14.8% than for patients with RDW < 14.8% (95% CI 2.036–12.759, P = 0.001). Another study found the same association between RDW in patients with coronavirus disease 2019 (COVID-19) and their mortality and disease severity [33, 40], with higher levels of RDW being associated with poorer outcomes in patients with COVID-19 and higher RDW in non-survivors and patients with more severe symptoms than in survivors and patients with less severe symptoms. However, Zhao et al.  found that preoperative RDW was not a risk factor for POP in a study of 1495 elderly patients (> 65 years of age) who underwent surgery for femoral intertrochanteric fractures. Considering that such a problem exists because of the inconsistent population studied, we conducted a retrospective cohort study adjusted for relevant variables and used a generalized additive model (GAM) to explore the relationship between preoperative RDW and POP, which was determined to be associated with POP by smoothed curve fitting.
However, our study did not find any correlation between BMI, smoking status, and POP. In contrast, Xiang  and Gao  demonstrated that BMI and smoking were independent risk factors for POP. There was no correlation between smoking and pneumonia due to the limitations of the retrospective study, in which the prevalence of smoking in patients was much lower than in the actual situation; moreover, our study population was predominantly female. Therefore, additional prospective studies should be conducted to determine whether smoking is an independent risk factor of POP.
This study has several advantages. It utilizes the GAM to elucidate the nonlinear relationship between RDW and POP. The use of GAM fits a smoothing spline and helps in understanding the real relationship between variables and outcomes. Rigorous statistical adjustment was performed for confounding factors owing to the retrospective nature of the study. Interaction analysis also improves the reliability of the data. Notably, the study found that when the preoperative RDW was < 14.3%, the incidence of POP increased by 61% for every 1% increase in RDW. In clinical practice, this association can be used as a predictor of POP risk. Therefore, the size of the preoperative RDW can be used to determine whether appropriate preventive measures, such as the employment of a dedicated ortho-geriatrician in an orthopedic department, allow for the optimization of patients’ clinical conditions .
This study has some limitations. The evidence for an association between exposure and outcome was weaker in this study than in previous prospective studies. In addition, this study was conducted in a population aged > 60 years; therefore, future studies should be conducted in younger and middle-aged populations to determine the correlation between preoperative RDW and POP. This was an observational study; therefore, it was inevitably subject to confounding factors. Hence, we could only adjust for measurable confounders but not for unmeasurable ones. For example, our study did not collect information on whether the patients had consumed alcohol  or previously had pneumonia; furthermore, preoperative laboratory markers (e.g., C-reactive protein and erythrocyte sedimentation rate were not collected [45, 46]). These variables are risk factors for POP, and could have affected the accuracy of our results. Therefore, prospective studies with larger sample sizes and more variables are required to validate the relationship between preoperative RDW and POP. Finally, patients with preoperative pneumonia were excluded from this study. Preoperative pneumonia has been found to be associated with the risk of postoperative adverse events in patients with hip fractures [47, 48]. Therefore, future studies on preoperative pneumonia in elderly patients with hip fracture should be conducted to determine whether RDW and preoperative pneumonia have the same trend as POP.
There was a nonlinear relationship between preoperative RDW and the incidence of POP in elderly patients with hip fractures. The incidence of POP was positively correlated with the RDW when the RDW was below 14.3%; however, no correlation was found when the RDW reached 14.3%.
Availability of data and materials
The datasets used or analyzed during the current study are available from the Corresponding author upon reasonable request.
Red blood cell distribution width
Body mass index
Intensive care unit
Chronic obstructive pulmonary disease
White blood cell
Monocytes lymphocyte ratio
Neutrophil lymphocyte ratio
American Society of Anesthesiologists
Coronavirus disease 2019
Generalized additive model
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We thank Dr. Xinglin Chen for providing guidance and for modifying the study design and content. We also thank Shenzhen Second People's Hospital for supporting this study financially.
This study was supported by the hospital-level clinical research project of Shenzhen Second People's Hospital, Project No. (20213357012).
Ethics approval and consent to participate
This was a retrospective study of patients admitted to Shenzhen Second People's Hospital. The data are retrospective and anonymous, and the requirement for informed consent was therefore waived. This study was approved by the Clinical Research Ethics Committee of Shenzhen Second People's Hospital (20210620213357012-FS01) and the protocol was registered with ClinicalTrials.gov (registration number: ChiCTR2100047560). This study was conducted in accordance with the principles of the Declaration of Helsinki.
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Zhang, D., Zhang, Y., Yang, S. et al. Relationship between preoperative red blood cell distribution width and postoperative pneumonia in elderly patients with hip fracture: a retrospective cohort study. J Orthop Surg Res 18, 253 (2023). https://doi.org/10.1186/s13018-023-03732-6