Open AccessRisk prediction model for deep surgical site infection ( DSSI ) following open reduction and internal fixation of displaced intra‐articular calcaneal fracture
Author(s) -
Lu Kaosheng,
Ma Tianxiao,
Yang Chunyan,
Qu Qiaoge,
Liu Haibo
Publication year - 2022
Publication title -
international wound journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.867
H-Index - 63
eISSN - 1742-481X
pISSN - 1742-4801
DOI - 10.1111/iwj.13663
Subject(s) - medicine , confidence interval , internal fixation , injury severity score , demographics , univariate analysis , medical record , surgery , trauma center , retrospective cohort study , multivariate analysis , poison control , injury prevention , emergency medicine , demography , sociology
Abstract Deep surgical site infection (DSSI) is a serious complication affecting the surgical outcome of displaced intra‐articular calcaneal fracture, and a risk prediction model based on the identifiable risk factors will provide great clinical value in prevention and prompt interventions. This study retrospectively identified patients operated for calcaneal fracture between January 2014 and December 2019, with a follow‐up ≥1 year. The data were extracted from electronic medical records, with regard to demographics, comorbidities, injury, surgery and laboratory biomarkers at admission. Univariate and multivariate logistics regression analyses were used to identify the independent factors for DSSI, thereby the risk prediction model was developed. Among 900 patients included, 2.7% developed a DSSI. The multivariate analyses identified five factors independently associated with DSSI, including current smoking (OR, 2.8; 95% confidence interval [CI], 1.3‐6.4; P = .021), BMI ≥ 26.4 kg/m 2 (OR, 3.1; 95% CI, 1.6‐8.4; P = .003), ASA ≥II (OR, 1.3; 95% CI, 1.0‐5.1; P = .043), incision level of II (OR, 3.8; 95% CI, 1.3‐12.6; P = .018) and NLR ≥6.4 (OR, 3.2; 95% CI, 1.3‐7.5; P = .008). A score of 14 as the optimal cut‐off value was corresponding to sensitivity of 0.542 and specificity of 0.872 (area, 0.766; P < .001); ≥14 was associated with 8.1‐times increased risk of DSSI; a score of 7 was corresponding sensitivity of 100% and 10 corresponding to sensitivity of 0.875. The risk prediction model exhibited excellent performance in distinguishing the risk of DSSI and could be considered in practice for improvement of wound management, but its validity requires to be verified by better‐design studies.