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Surgical Site Infection After Hysterectomy: A Meta-Analysis Of Risk Factors In Cancer Patients

Surgical Site Infection After Hysterectomy: A Meta-Analysis Of Risk Factors In Cancer Patients

Endometrial cancer (EC) continues to pose a significant threat as the third leading cause of gynecological malignancy resulting in female mortality. In the year 2020 alone, there were 417,367 newly reported cases of endometrial cancer, contributing to the alarming statistic of over 97,370 recorded deaths. 

This represents a substantial impact, constituting nearly 4% of all female cancer-related fatalities on an annual basis. The prevalence and severity of endometrial cancer highlight the pressing need for continued research, early detection, and effective interventions to address this critical health concern.

Surgical Site Infections (SSIs) emerge as frequent complications within the realm of surgical procedures, comprising a substantial 38% of postoperative morbidity and mortality. The repercussions of SSIs extend beyond the immediate health implications, imposing significant financial burdens in both low-income and high-income countries alike. 

The toll on healthcare resources is undeniable, with considerable costs associated with managing the aftermath of these infections. Furthermore, SSIs play a pivotal role in postoperative scenarios, contributing significantly to hospital readmissions, especially after procedures like hysterectomy. Addressing the challenges posed by SSIs is imperative not only for patient well-being but also for optimizing healthcare expenditure and outcomes in diverse economic settings. 

Surgery continues to stand as the primary therapeutic approach for endometrial cancer (EC). Past investigations have delved into anticipated factors linked to Surgical Site Infections (SSI) following hysterectomy in EC patients. These factors include obesity, diabetes mellitus, surgical approach, operative time, and the American Society of Anesthesiologists (ASA) score. 

However, substantial variations in research outcomes persist, with different studies showing diverse correlation coefficients. Notably, Shi et al. found no significant associations between body mass index (BMI), diabetes, and the risk of SSI in EC, contradicting findings from other studies. 

As of now, a comprehensive meta-analysis of the risk factors for SSI in EC patients is lacking. Consequently, this analysis aims to scrutinize significant risk factors, providing robust evidence to support clinical prevention and intervention strategies for SSI in EC patients post-hysterectomy.


This meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

The study’s inclusion criteria encompassed all types of observational studies (such as case–control, cross-sectional, prospective, and retrospective cohort studies) involving patients diagnosed with endometrial cancer (EC) or carcinoma based on histological results from an endometrial biopsy. Exclusions were made for records that did not report on risk factors related to surgical site or wound infection after hysterectomy for EC, duplicates, publications not in English or Chinese, and review articles or conference abstracts.

Two researchers independently conducted literature screening, quality assessment of the included studies, and data extraction, cross-checking their findings. Authors were contacted for clarification or missing information as needed. The screening process involved a thorough examination of titles, abstracts, and full texts to determine inclusion. Extracted details included publication information, study type, subject size (SSI/non-SSI), and clinical features.

The Newcastle–Ottawa Scale (NOS) was employed to assess the quality of selected literature during the initial screening. This scale, aligned with Cochrane non-randomized studies methods, evaluates studies based on the selection of study groups, comparability of study groups, and assessment of exposures and outcomes. The scale awards stars for high-quality characteristics within each criterion, with a maximum of four stars for selection, two stars for comparability, and three stars for assessment. The quality assessment was independently carried out by two investigators, with any discrepancies resolved through discussion or arbitration by a third author if needed.

Statistical Analysis

All statistical analyses were executed using ReviewManager Software (RevMan 5.4.1). In cases where two or more studies reported the same risk factor, combined odds ratio (OR) estimates with corresponding 95% confidence intervals (CIs) were assessed. If the OR was not specified, for discontinuous outcomes, it was derived from the original data. 

Results were presented descriptively if data synthesis was not possible or if risk factors were identified in only one study. The presence of heterogeneity among studies was evaluated using χ2 and I2 tests. Heterogeneity across the studies was examined with the Q-test (test level α=0.1) and measured by I2 statistics, with I2 values categorized as low (25% to 50%), moderate (50% to 75%), and high (≥75%) heterogeneity. A fixed-effects model was employed when no statistically significant heterogeneity was observed among the studies (p≥0.10 and I2<50%). In cases of significant heterogeneity, further analysis was conducted to identify the source, and a random-effects model was applied.


In the initial electronic search, a total of 81 pertinent records were retrieved, comprising 21 from PubMed, 13 from Web of Science, 40 from Embase, and 7 from ScienceDirect. After eliminating duplicates and screening titles and/or abstracts, 59 studies were included. From these, some studies were excluded based on reasons such as incomplete data (n=2), being in poster format (n=1), and existing as conference abstracts (n=1) upon a comprehensive assessment of the full text (n=10). Eventually, six studies were chosen for the ultimate analysis.

A total of 11 factors were documented across the six studies incorporated in the meta-analysis. The analysis focused on six risk factors (laparotomy, postoperative blood sugar≥10 mmol/L, FIGO stage-III or IV, diabetes mellitus, durations of drainage≥7d, BMI), among which three showed statistical significance (laparotomy, postoperative blood sugar≥10 mmol/L, FIGO stage-III or IV). The remaining factors (chemotherapy, postoperative serum albumin <30 g/L, ASA score, preoperative hematocrit <36%, operative time >164 min) were mentioned in only one study each and were consequently not amalgamated in the meta-analysis. 

Final Thoughts 

This meta-analysis investigated the risk factors for Surgical Site Infections (SSI) following hysterectomy in patients with endometrial cancer (EC). Six studies, encompassing 3647 samples, were included in the analysis. The results identified laparotomy, postoperative blood sugar≥10 mmol/L, and FIGO stage-III or IV as correlated risk factors for SSI after hysterectomy in EC patients, showing low or moderate heterogeneity between results. Among the variables analyzed, postoperative blood sugar presented the highest Odds Ratio (OR) for SSI. No significant associations were observed between diabetes, durations of drainage≥7d, BMI, and SSI.

The analysis supported targeted prevention and intervention for SSI in EC patients, emphasizing the importance of minimizing laparotomy and managing postoperative blood sugar levels. Laparotomy was associated with a 2.66 times higher risk of SSI compared to minimally invasive surgery (MIS), highlighting MIS as the preferred surgical approach due to superior in-hospital outcomes and fewer complications.

Patients with postoperative blood sugar≥10 mmol/L faced a 4.38 times higher risk of SSI, emphasizing the significance of glycemic control after surgery. Obesity (BMI≥30 kg/cm2) was identified as an independent risk factor for SSI in EC patients, with high BMI linked to weakened immune responses and increased bacterial proliferation. Addressing modifiable factors, especially obesity and hyperglycemia, is crucial for preventing SSI in EC patients.

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