Αρχειοθήκη ιστολογίου

Αλέξανδρος Γ. Σφακιανάκης
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5
Άγιος Νικόλαος Κρήτη 72100
2841026182
6032607174

Δευτέρα 2 Νοεμβρίου 2020

Risk factors for surgical site infections using a data-driven approach

als.fakia shared this article with you from Inoreader

journal.pone.0240995.t005&size=inline

by J. M. van Niekerk, M. C. Vos, A. Stein, L. M. A. Braakman-Jansen, A. F. Voor in 't holt, J. E. W. C. van Gemert-Pijnen

Objective

The objective of this study was to identify risk factors for surgical site infection from digestive, thoracic and orthopaedic system surgeries using clinical and data-driven cut-off values. A second objective was to compare the identified risk factors in this study to risk factors identified in literature.

Summary background data

Retrospective data of 3 250 surgical procedures performed in large tertiary care hospital in The Netherlands during January 2013 to June 2014 were used.

Methods

Potential risk factors were identified using a literature scan and univariate analysis. A multivariate forward-step logistic regression model was used to identify risk factors. Standard medical cut-off values were compared with cut-offs determined from the data.

Results

For digestive, orthopaedic and thoracic system surgical procedures, the risk factors identified were preoperative temperature of ≥38°C and antibiotics used at the time of surgery. C-reactive protei n and the duration of the surgery were identified as a risk factors for digestive surgical procedures. Being an adult (age ≥18) was identified as a protective effect for thoracic surgical procedures. Data-driven cut-off values were identified for temperature, age and CRP which can explain the SSI outcome up to 19.5% better than generic cut-off values.

Conclusions

This study identified risk factors for digestive, orthopaedic and thoracic system surgical procedures and illustrated how data-driven cut-offs can add value in the process. Future studies should investigate if data-driven cut-offs can add value to explain the outcome being modelled and not solely rely on standard medical cut-off values to identify risk factors.

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