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Surgical site infections (SSIs) are a major cause of postoperative morbidity and increased healthcare costs. Negative pressure wound therapy (NPWT) and other advanced wound dressings have been widely adopted to mitigate this risk; however, evidence of their effectiveness across diverse surgical settings remains inconsistent. This systematic review aims to evaluate the effectiveness of NPWT and advanced interventions in preventing SSIs compared to conventional dressings or standard care. A systematic search was conducted across five electronic databases and registers (PubMed, Excerpta Medica database (Embase), Scopus, Web of Science, ClinicalTrials.gov) for randomized controlled trials (RCTs) published up to 2025. Studies comparing NPWT or advanced dressings to conventional care for SSI prevention in any surgical population were included. Study selection, data extraction, and risk of bias assessment using the Cochrane Risk of Bias 2 (RoB 2) tool were performed by independent reviewers. A narrative synthesis was conducted due to clinical heterogeneity. Eight RCTs were included, encompassing procedures such as emergency laparotomy, vascular surgery, cesarean section, and orthopedic trauma. The results demonstrated that the effectiveness of advanced interventions is highly context-dependent. NPWT significantly reduced SSIs in open inguinal vascular surgery, and a dialkylcarbamoyl chloride (DACC)-impregnated dressing was effective following cesarean section. In contrast, the largest RCT found no benefit of incisional NPWT after emergency laparotomy. Evidence in orthopedic trauma was mixed. The majority of included trials were assessed as having a low risk of bias. The effectiveness of NPWT and advanced wound interventions in preventing SSIs is not universal but is contingent on the specific surgical context. These technologies should be applied selectively, targeting patient populations and procedures where a clear benefit has been demonstrated, rather than being used routinely. Future research should focus on identifying predictive factors to guide the cost-effective, personalized application of these therapies.