ArticleRevista da Escola de Enfermagem da U S P2025
Predictive model of surgical infection to enhance patient safety: A retrospective cohort study.
Article in Revista da Escola de Enfermagem da U S P, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07621198 (Prediction of Postoperative Complications in Major Surgery), which is not on this map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Prediction of Postoperative Complications in Major Surgery: A Prospective, Multicenter, Cohort Study in Low- and Middle-income Settings
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4 authors.
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Abstract
objectiveTo identify risk factors for surgical site infection and to establish a prediction model.
methodRetrospective cohort study with 20,778 surgeries performed between 2009 and 2019 at a university hospital in Rio de Janeiro. Clinical and operative variables were analyzed using multivariate logistic regression (p≤0.05).
resultsThe overall surgical infection rate was 7.2%. Age ≥41 years presented an odds ratio between 1.52 and 3.77 (p < 0.0001). Contaminated and infected surgeries increased the risk threefold (95% CI: 2.48-3.63). Urgent procedures (OR = 2.04; 95% CI: 1.83-2.28) and ASA III (OR=3.77) were associated with a higher risk. Each additional hour of surgery increased the risk by 34% (OR = 1.34; 95% CI: 1.30-1.38). Conventional technique had a risk 2.7 times greater than videolaparoscopy (RC = 2.72; p < 0.0001).
conclusionThe developed model allows for precise stratification of surgical site infection risk and supports preventive strategies, improving the surveillance and management of surgical risk in highly complex hospitals.
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