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Delayed versus primary closure to minimize risk of surgical-site infection for complicated appendicitis: A secondary analysis of a randomized trial using counterfactual prediction modeling

Published online by Cambridge University Press:  06 November 2023

Amarit Tansawet
Affiliation:
Department of Surgery, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
Boonying Siribumrungwong
Affiliation:
Department of Surgery, Faculty of Medicine, Thammasat University, Pathum Thani, Thailand
Suphakarn Techapongsatorn
Affiliation:
Department of Surgery, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand
Pawin Numthavaj
Affiliation:
Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
Napaphat Poprom
Affiliation:
Department of Surgery, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
Gareth J. McKay
Affiliation:
Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, United Kingdom
John Attia
Affiliation:
School of Medicine and Public Health, and Hunter Medical Research Institute, University of Newcastle, New Lambton, New South Wales, Australia
Ammarin Thakkinstian*
Affiliation:
Department of Clinical Epidemiology and Biostatistics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
*
Corresponding author: Ammarin Thakkinstian; Emails: ammarin.tha@mahidol.ac.th or ammarin.tha@mahidol.edu
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Abstract

Objective:

To evaluate the risk of surgical site infection (SSI) following complicated appendectomy in individual patients receiving delayed primary closure (DPC) versus primary closure (PC) after adjustment for individual risk factors.

Design:

Secondary analysis of randomized controlled trial (RCT) with prediction model.

Setting:

Referral centers across Thailand.

Participants:

Adult patients who underwent appendectomy via a lower-right-quadrant abdominal incision due to complicated appendicitis.

Methods:

A secondary analysis of a published RCT was performed applying a counterfactual prediction model considering interventions (PC vs DPC) and other significant predictors. A multivariable logistic regression was applied, and a likelihood-ratio test was used to select significant predictors to retain in a final model. Factual versus counterfactual SSI risks for individual patients along with individual treatment effect (iTE) were estimated.

Results:

In total, 546 patients (271 PC vs 275 DPC) were included in the analysis. The individualized prediction model consisted of allocated intervention, diabetes, type of complicated appendicitis, fecal contamination, and incision length. The iTE varied between 0.4% and 7% for PC compared to DPC; ∼38.1% of patients would have ≥2.1% lower SSI risk following PC compared to DPC. The greatest risk reduction was identified in diabetes with ruptured appendicitis, fecal contamination, and incision length of 10 cm, where SSI risks were 47.1% and 54.1% for PC and DPC, respectively.

Conclusions:

In this secondary analysis, we found that most patients benefited from early PC versus DPC. Findings may be used to inform SSI prevention strategies for patients with complicated appendicitis.

Information

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America
Figure 0

Figure 1. Flow diagram of enrollment and analysis.

Figure 1

Table 1. Patient-Related Summary Characteristics and Intraoperative Factors by Surgical Site Infection Groups

Figure 2

Table 2. Predictive Factors of Surgical Site Infection: A Multivariate Logistic Regression Model

Figure 3

Figure 2. Distribution of individual treatment effect of primary wound closure versus delayed primary wound closure.

Figure 4

Table 3. Estimation of Individualized Patient Risk of Surgical-Site Infection From Different Wound Closure Strategies: A Counterfactual Prediction Model

Supplementary material: File

Tansawet et al. supplementary material

Table S1 and Figure S1

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