Postoperative Complications of Cervical Spinal Fusion in Diabetic Patients: A Retrospective Study

Background

Diabetes Mellitus (DM) is a globally prevalent chronic condition that significantly impacts surgical outcomes, particularly in spine surgery. Diabetic patients face a higher risk of postoperative complications. However, over the past decade, research on the effects of different types of diabetes (Type I and Type II) on complications, mortality, length of hospital stay, and costs following cervical fusion surgery has been limited. To address this gap, a team from Nanfang Hospital of Southern Medical University in China conducted a retrospective study using the U.S. Nationwide Inpatient Sample (NIS) database to explore the specific impact of different types of diabetes on postoperative complications following cervical fusion surgery.

Source of the Study

The study was conducted by researchers including Yuan-Jing Liao, Lan-Wei Xu, and Hao Xie from Nanfang Hospital of Southern Medical University. The findings were published online on August 8, 2024, in the International Journal of Surgery. The research team analyzed data from the NIS database between 2010 and 2019 to assess the risk of postoperative complications in patients with Type I and Type II diabetes undergoing cervical fusion surgery.

Research Process and Subjects

Data Source and Study Population

The study utilized data from the NIS database, which covers inpatient data from over 1,000 hospitals in the U.S., representing approximately 20% of the nation’s hospital admissions. The study included 267,174 patients who underwent cervical fusion surgery between 2010 and 2019, of whom 224,255 had no diabetes, 670 had Type I diabetes, and 42,249 had Type II diabetes. Patients with tumors, spina bifida, infections, spinal cord injuries, or trauma, as well as those diagnosed with both Type I and Type II diabetes, were excluded.

Study Design and Analysis Methods

Propensity Score Matching (PSM) was used to balance baseline differences, and univariate and multivariate logistic regression analyses were employed to evaluate the impact of different types of diabetes on postoperative complications. The primary outcomes included postoperative complications (e.g., pneumonia, acute cerebrovascular disease, acute myocardial infarction), prolonged hospital stays, and increased hospitalization costs.

Research Findings

Comparison of Type I Diabetes and Non-Diabetic Patients

After propensity score matching, multivariate analysis revealed that patients with Type I diabetes had a significantly higher incidence of postoperative pneumonia compared to non-diabetic patients (p=0.020). Additionally, Type I diabetes patients showed higher rates of acute myocardial infarction, chest pain, and prolonged hospital stays, although these differences did not reach statistical significance in multivariate analysis.

Comparison of Type II Diabetes and Non-Diabetic Patients

Patients with Type II diabetes exhibited a higher risk of postoperative complications. Multivariate analysis showed that Type II diabetes was an independent risk factor for acute cerebrovascular disease (p=0.001), acute myocardial infarction (p=0.014), pneumonia (p=0.045), continuous trauma ventilation (p=0.016), chest pain (p<0.001), urinary tract infection (p<0.001), transfusion (p=0.005), and dysphagia (p=0.013). Furthermore, Type II diabetes patients had significantly longer hospital stays (p<0.001) and higher hospitalization costs (p=0.008).

Conclusions and Significance

Conclusions

The study found that, compared to non-diabetic patients, Type II diabetes patients faced a significantly higher risk of postoperative complications following cervical fusion surgery than Type I diabetes patients. This finding provides critical insights for preoperative risk assessment and patient management, highlighting the need for clinicians to pay special attention to the complication risks in Type II diabetes patients.

Scientific and Practical Value

This study is the first in the past decade to systematically evaluate the impact of different types of diabetes on postoperative complications following cervical fusion surgery, addressing a significant research gap. The results offer clinicians a more precise risk stratification tool, aiding in the optimization of preoperative assessments and postoperative management strategies to improve patient outcomes.

Highlights of the Study

1. Large-Scale Database Analysis: The study leveraged the NIS database, providing a large sample size and high reliability of results.
2. Propensity Score Matching: PSM was used to balance baseline differences, enhancing the accuracy of the findings.
3. Clear Risk Stratification: The study identified the high risk of complications in Type II diabetes patients, offering valuable guidance for clinical decision-making.
4. Multivariate Analysis: The use of multivariate logistic regression controlled for confounding factors, further validating the robustness of the results.

Additional Valuable Information

The study also noted that, while the relationship between diabetes and postoperative infections has been debated in previous research, this study found that neither Type I nor Type II diabetes was independently associated with postoperative infections (e.g., sepsis or wound infections). This suggests that the risk of postoperative infections may be more closely related to blood glucose control levels rather than diabetes itself. Future research could further explore the impact of preoperative and postoperative glucose management on complications.

Summary

This study, through large-scale database analysis, revealed the high risk of postoperative complications in Type II diabetes patients undergoing cervical fusion surgery, providing clinicians with an essential tool for preoperative risk assessment. The findings not only hold significant scientific value but also offer practical guidance for improving postoperative management in diabetic patients.