Impact of osteoporosis on perioperative complications in patients undergoing surgical treatment for lumbar spinal stenosis: a nationwide retrospective study
Article information
Abstract
Study Design
Nationwide retrospective cohort study with propensity score matching (PSM) analysis.
Purpose
To investigate the impact of osteoporosis on perioperative complications in patients undergoing surgery for lumbar spinal stenosis (LSS).
Overview of Literature
Progressive population aging has driven an increase in surgical procedures for degenerative spinal conditions such as LSS. While previous research has examined the impact of osteoporosis on implant-related complications, its specific impact on outcomes following LSS surgeries remains unclear.
Methods
This study analyzed 60,785 patients who underwent LSS surgery between April 2020 and March 2022, utilizing data from a nationwide Diagnosis Procedure Combination database. Perioperative complications, treatment costs, blood transfusion volume, and anesthesia time were compared between osteoporotic and non-osteoporotic patients. PSM was employed to account for confounding variables. Univariate and multivariate regression analyses were employed to identify risk factors for complications.
Results
The prevalence of osteoporosis in this cohort was 10.6%. On regression analyses, age, sex, body mass index, admission activities of daily living (ADL) score (Barthel index), hospital type, spinal fusion, Charlson comorbidity index score, and osteoporosis showed a significant association with perioperative complications. Before PSM, osteoporotic patients were older, predominantly female, and had lower body mass index and admission ADL scores, higher spinal fusion rates, and more complications. After PSM, osteoporotic patients exhibited significantly higher complication rates, increased costs, greater blood transfusion requirements, and longer anesthesia durations compared to non-osteoporotic patients.
Conclusions
This nationwide analysis identified osteoporosis as an independent risk factor for perioperative complications following LSS surgery. Our findings underline the need for careful perioperative management in this population.
Introduction
The phenomenon of progressive population aging has led to a rising prevalence of age-related degenerative spinal disorders in many countries [1–4]. Lumbar spinal stenosis (LSS) is the most common spinal degenerative disease, typically managed conservatively in its early stages. However, many patients eventually require surgical intervention due to the progression of pain and/or neurological symptoms [2,5]. Concurrently, the prevalence of osteoporosis in this population is likely to increase owing to age-related deterioration of the skeletal system. Indeed, a recent meta-analysis showed that osteoporosis is a frequent complication in patients with LSS [6].
In patients undergoing spinal fusion and corrective surgeries, decreased bone density is associated with postoperative complications such as adjacent vertebral fractures and implant failure [7,8]. Consequently, optimizing bone health during the perioperative period of spinal instrumentation surgery has been increasingly emphasized in recent years [9–11]. While previous studies have primarily examined the impact of osteoporosis on implant-related complications, its impact on surgical outcomes for LSS remains unclear. Therefore, this study aimed to investigate the impact of osteoporosis on LSS surgery during the perioperative period.
Materials and Methods
Data source
This study retrospectively analyzed data from the Diagnosis Procedure Combination (DPC) database, a prospective national registry in Japan. The DPC database encompasses hospitals across all regions of Japan, accounting for 56.7% of the total beds in the country, according to a survey conducted in FY2021 [12]. The database contains comprehensive information, including patient demographics (age and sex), diagnoses, and post-admission complications recorded using both International Classification of Diseases, Tenth Revision (ICD-10) codes and Japanese text data. Given the anonymized nature of the data, the requirement for informed consent was waived. This study was approved by the Institutional Review Board of Dokkyo Medical University Saitama Medical Center (No. 23069).
Patient characteristics
Patients who underwent surgical treatment for LSS (M4806) between April 2020 and March 2022 were included in the study. Data pertaining to the following variables were analyzed: age, sex, body mass index (BMI), history of smoking, and preoperative comorbidities including osteoporosis (M81). In addition, the Charlson comorbidity index (CCI) was calculated from ICD-10 codes of comorbidities using the protocol by Quan et al. [13].
Outcome measures
Postoperative adverse events included surgical site infection (T793, T814), sepsis (A40, A41), pulmonary embolism (I26), respiratory complications (pneumonia [J12–J18], postprocedural respiratory disorders [J95], or respiratory failure [J96]), cardiac events (acute coronary events [I21–I24] or heart failure [I50]), stroke (cerebral infarction or hemorrhage [I60–I64]), spinal fluid leakage (G960, 961), hematoma (S064, 241, 341, T093), and meningitis (G001–003, 008–009, 039, A390, 392). The following variables were extracted from the DPC database: costs, blood transfusion volume, and anesthesia time. Anesthesia time and blood transfusion were evaluated as proxy outcomes for surgical time and blood loss, based on a previous study [14].
Statistical analyses
Logistic regression models were employed to investigate the associations between various variables and complications. Subsequently, a multivariate logistic regression analysis was conducted to identify independent predictors of the occurrence of complications. All variables assessed in the univariate analysis were considered candidate independent variables in this multivariate model.
A propensity score matching (PSM) analysis was conducted to minimize selection bias. Propensity scores for the presence or absence of osteoporosis were calculated based on the following variables: patient age and sex, BMI, smoking status, medical comorbidities, activities of daily living (ADL) scores at admission (assessed using the Barthel index [BI]), hospital type, and surgical type. The BI score is a 10-item scale used to assess ADL status, with each item having different weights. The items are scored as follows: bathing and grooming (0 or 5 points), feeding, dressing, bladder control, bowel control, using the toilet, climbing stairs (0, 5, or 10 points), and transferring from a wheelchair to a bed and walking on a flat surface (0, 5, 10, or 15 points). The total BI score is the sum of these 10 items, ranging from 0 (total dependence) to 100 (complete independence) [15]. The PSM procedure was performed using a logistic regression model, yielding a C-statistic of 0.767, indicating a good fit. One-to-one matching of osteoporosis and non-osteoporosis patients was performed based on propensity scores, with a caliper value of <0.2. After matching, costs, surgical invasiveness, and perioperative complications were compared between the two groups using a Mann-Whitney U test or chi-square test. Statistical significance was set at p<0.05. All analyses, except propensity score matching, were performed using IBM SPSS ver. 29.0 (IBM Corp., Armonk, NY, USA). Propensity score matching was performed using R ver. 4.4.0 (The R Foundation for Statistical Computing, Vienna, Austria).
Results
Patient demographics
This study included 60,785 patients who underwent surgical intervention for LSS during a 2-year period. The patient characteristics are summarized in Table 1. The mean age was 71.9 years, with a male predominance (59.0%). The mean BMI was 24.7 kg/m2, and 36.2% of patients had a history of smoking. The mean CCI score was 0.6, with 96.4% of patients (n=58,619) having a CCI score of ≤2, indicating low to medium risk. Osteoporosis was diagnosed in 6,445 patients (10.6%).
Characteristics of total patients (n=60,785)
Risk factors for perioperative complications
Univariate regression analysis revealed that older age, male sex, higher CCI score, lower ADL score at admission, treatment at non-academic hospitals, spinal fusion surgery, and presence of osteoporosis were associated with perioperative complications (Table 2). Multivariate regression analysis identified age, sex, BMI, ADL score at admission, hospital type, spinal fusion, CCI, and osteoporosis as independent risk factors for perioperative complications (Table 3).
Risk factor for perioperative complications with univariable logistic regression analysis
Risk factor for perioperative complications with multivariable logistic regression analysis
Impact of osteoporosis on perioperative complications
Next, we investigated the impact of osteoporosis on perioperative complications, medical costs, blood transfusion volume, and operative time. Before PSM, significant differences in-patient characteristics were observed between the osteoporosis and non-osteoporosis groups. Compared to the non-osteoporosis group, patients with osteoporosis were significantly older (75.7±7.6 years vs. 71.3±10.1 years, p<0.001), had a lower proportion of males (23.6% vs. 63.3%, p<0.001), lower BMI (23.6±3.7 kg/m2 vs. 24.8±3.9 kg/m2, p<0.001), and lower ADL scores at admission. Additionally, fewer patients in the osteoporosis group were smokers (1,212 [18.8%] vs. 20,798 [38.3%], p<0.001). Patients with osteoporosis had a higher proportion of fusion surgery (50.7% vs. 33.0%, p<0.001) (Table 4).
Characteristics and perioperative complications in non-osteoporosis and osteoporosis (crude analysis)
One-to-one PSM yielded 5,723 pairs (11,446 patients). After PSM, most variables were well-balanced between the osteoporosis and non-osteoporosis groups (Table 5). The osteoporosis group had a significantly higher total perioperative complication rate (5.9% vs. 5.0%, p=0.039) (Table 5). The average cost per hospitalization was significantly higher in the osteoporosis group, with a mean average difference of ¥95,515 (p<0.001). The osteoporosis group also received a higher volume of blood transfusion during hospitalization (61.2±253.4 mL vs. 51.4±234.1 mL, p<0.001). Additionally, anesthesia time was significantly higher in the osteoporosis group (251.4±151.6 minutes vs. 234.8±131.0 minutes, p<0.001) (Table 5).
Characteristics and perioperative complications in non-osteoporosis and osteoporosis (analysis after propensity score matching)
Discussion
In this study, 10.6% of patients were diagnosed with osteoporosis. However, previous studies have reported higher prevalence rates of osteoporosis in LSS patients. A prospective cohort study found that 31.8% of LSS patients had osteoporosis based on bone densitometry [16]. Furthermore, a recent meta-analysis reported an even higher prevalence of osteoporosis (34.9%) in patients with LSS aged 50 or older [6]. Thus, the frequency of osteoporosis in LSS patients observed in this study was relatively low compared to prior literature. However, a recent study conducted in Japan found that among patients aged ≥65 years who underwent spinal fusion surgery between 2018 and 2021, 15.9% received osteoporosis medications preoperatively [17]. Therefore, the prevalence rate of osteoporosis in the present study is plausible, given the inclusion of patients across all age groups and the proportion of patients actively receiving treatment for osteoporosis. Thus, preoperative osteoporosis screening is crucial, given the low treatment rates for osteoporosis. A recent guideline for osteoporosis management in spine surgery recommends bone-anabolic agents as first-line treatment for patients with osteoporosis who are scheduled for multilevel spinal reconstruction. These medications should be administered for a minimum of 2 months preoperatively and continued for at least 8 months postoperatively [10].
Univariate and multivariate regression analyses revealed an association between osteoporosis and the occurrence of perioperative complications following surgery for LSS. While osteoporosis is a known risk factor for implant-related complications in lumbar fusion surgery [18,19], the impact of osteoporosis on systemic complications is not well characterized in contemporary literature. A previous retrospective study has identified osteoporosis as a risk factor for systemic complications after surgery for LSS [19]. However, the study did not account for the confounding influence of between-group differences regarding background factors. A retrospective study using the Mariner Claims Database identified osteoporosis as a risk factor for pulmonary embolism and minor complications following single-level posterior spine instrumentation and fusion and anterior lumbar interbody fusion [20]. Although the present study did not reveal a significant association between pulmonary embolism and osteoporosis, the higher incidence of complications in the osteoporosis group indicated a consistent trend.
Compared to the non-osteoporosis group, the osteoporosis group in this study was characterized by older age, a higher proportion of females, lower BMI, and a higher frequency of fusion surgery. To account for these confounding factors, PSM was employed. Even after matching, the osteoporosis group had a higher complication rate, consistent with the multivariate regression analysis. Furthermore, patients with osteoporosis incurred higher medical costs, required more blood transfusions, and had longer anesthesia times compared to those without osteoporosis. Large cohort studies have investigated the impact of osteoporosis on thoracolumbar spine surgery, examining outcomes such as medical costs, reoperations, and readmissions [21]. An 8-year follow-up study found that osteoporotic patients had higher readmission rates, longer hospital stays, and higher medical costs compared to non-osteoporotic patients [21]. In contrast, our study focused on the impact of osteoporosis on in-patient medical costs [21]. Collectively, these findings emphasize the importance of preoperative osteoporosis screening, as its presence in patients undergoing surgery for LSS likely increases the risk of complications and higher medical costs.
Our study suggests that the presence of osteoporosis is a risk factor for increased blood transfusion demand. Clinical evidence from various orthopedic surgeries supports this finding. For example, osteoporosis was identified as a risk factor for blood transfusion in total hip arthroplasty and total knee arthroplasty [22]. Furthermore, osteoporosis was found to be a risk factor for bleeding in femoral neck fractures [5]. Additionally, a retrospective study found that in patients with scoliotic spinal deformity, those with osteoporosis had a significantly higher risk of increased intraoperative blood loss [23]. Although the DPC database does not provide data on the amount of blood loss during surgery, the higher volume of blood transfusion in patients with osteoporosis suggests increased perioperative blood loss or lower tolerance for blood loss. This information can be valuable for preoperative patient counseling.
Some limitations of this study should be acknowledged. First, despite PSM, residual confounding variables such as nutritional status were not accounted for in the analysis, potentially influencing the observed outcomes. Second, retrospective analysis of large databases can be affected by coding errors, impacting data accuracy and interpretation. Nonetheless, using large sample sizes mitigates this risk. Third, the DPC database only codes patients receiving treatment, so patients classified as having osteoporosis were receiving some form of treatment for the condition. This may lead to undiagnosed or untreated osteoporosis cases in the non-osteoporosis group. Nonetheless, the study suggests that patients with osteoporosis have a high incidence of perioperative complications, even if they are receiving treatment for the condition. This indicates that the current treatment strategies for osteoporosis may not be sufficient to reduce perioperative complications. To address this, future research should investigate the causal relationship between osteoporosis and systemic complications of LSS surgery. This can be achieved by comparing three distinct groups: patients without osteoporosis, those with untreated osteoporosis, and those receiving pharmacological treatment for osteoporosis. Objective criteria, such as bone density measurements and imaging-based fracture assessment, should be used to classify these groups. Further studies should also investigate the optimal duration of osteoporosis treatment before and after spinal surgery, as well as the most effective medications. Prospective studies will also be necessary to elucidate the impact of osteoporosis on specific complications and outcomes in LSS surgery, ultimately informing evidence-based guidelines for perioperative management.
Conclusions
This large-scale retrospective analysis of a nationwide in-patient database revealed osteoporosis as an independent risk factor for perioperative complications in patients undergoing surgical treatment for LSS. The study found that patients with osteoporosis had significantly higher complication rates, greater medical costs, increased blood transfusion requirements, and longer anesthesia times compared to those without osteoporosis. These findings highlight the importance of preoperative osteoporosis screening and management in elderly patients to reduce the risk of perioperative complications.
Key Points
Osteoporosis independently increases the risk of perioperative complications in patients undergoing lumbar spinal stenosis surgery.
Osteoporotic patients incur healthcare costs, require greater blood transfusion volumes, and experience longer anesthesia durations compared to non-osteoporotic patients.
Propensity score matching and multivariate regression analyses were used to account for confounding factors, ensuring the robustness of the association between osteoporosis and surgical outcomes.
Meticulous perioperative planning and management are required in osteoporotic patients to reduce complications and improve surgical outcomes.
Notes
Conflict of Interest
No potential conflict of interest relevant to this article was reported.
Author Contributions
Conceptualization: HI. Data curation: TT, KF. Formal analysis: TT, KT. Methodology: TT, HI. Visualization: TT. Writing–original draft: TT, HI. Writing–review and editing: TT, JK, HK, T. Yanase, KF, KT, T. Yoshii, TJ. Supervision: HI. Validation: HI. Final approval of the manuscript: all authors.