Report of a Quality Improvement Program for Reducing Postoperative Complications by Using a Surgical Risk Calculator in a Cohort of General Surgery Patients

The effect of interventions on the incidence of surgical site infections in acute care settings: A systematic review

AIM

Surgical site infections (SSIs) are common healthcare associated infections with serious consequences for patients and healthcare organisations. It is critical that healthcare professionals implement prevention strategies to reduce the incidence of such infections. Prevention strategies are key to reducing the incidence of SSIs. The aim of this systematic review is to describe the effect of interventions conducted in acute care settings on the incidence of SSIs (primary outcome), length of stay, intensive care unit admission, and mortality rate (secondary outcomes).

MATERIALS AND METHODS

This review is reported using the Preferred Reporting Items for Systematic review and Meta-Analysis checklist. A search was undertaken in Academic Search Complete, CINAHL, ERIC, MEDLINE, PsycARTICLES, PsycINFO and Web of Science for studies published between January 2017 and March 2022. Studies that focused on interventions within acute hospital settings in patients undergoing elective surgery with the aim of reducing the incidences of SSIs were included. Due to heterogeneity results were synthesised narratively.

RESULTS

In total, 23 studies were included. Findings show that interventions that are effective in reducing the incidences of SSIs have multiple components including care bundles, stakeholder engagement, targeted surveillance and education. Few studies were identified that evaluated the effect of SSI prevention interventions on length of stay and mortality, and none assessed intensive care admission rates.

CONCLUSIONS

The included interventions varied widely, which made it difficult to draw definitive conclusions regarding specific interventions that reduce SSI. Multicomponent interventions and care bundles showed promise in reducing the occurrence of SSIs. Further studies should focus on standardised evidence-based interventions and compliance using randomised controlled designs.

Prediction models of surgical site infection after gastrointestinal surgery: a nationwide prospective cohort study

OBJECTIVE

This study aimed to construct and validate a clinical prediction model for surgical site infection (SSI) risk 30 days after gastrointestinal surgery.

MATERIALS AND METHODS

This multicentre study involving 57 units conducted a 30-day postoperative follow-up of 17 353 patients who underwent gastrointestinal surgery at the unit from 1 March 2021 to 28 February 2022. The authors collected a series of hospitalisation data, including demographic data, preoperative preparation, intraoperative procedures and postoperative care. The main outcome variable was SSI, defined according to the Centres for Disease Control and Prevention guidelines. This study used the least absolute shrinkage and selection operator (LASSO) algorithm to screen predictive variables and construct a prediction model. The receiver operating characteristic curve, calibration and clinical decision curves were used to evaluate the prediction performance of the prediction model.

RESULTS

Overall, 17 353 patients were included in this study, and the incidence of SSI was 1.6%. The univariate analysis combined with LASSO analysis showed that 20 variables, namely, chronic liver disease, chronic kidney disease, steroid use, smoking history, C-reactive protein, blood urea nitrogen, creatinine, albumin, blood glucose, bowel preparation, surgical antibiotic prophylaxis, appendix surgery, colon surgery, approach, incision type, colostomy/ileostomy at the start of the surgery, colostomy/ileostomy at the end of the surgery, length of incision, surgical duration and blood loss were identified as predictors of SSI occurrence ( P <0.05). The area under the curve values of the model in the train and test groups were 0.7778 and 0.7868, respectively. The calibration curve and Hosmer-Lemeshow test results demonstrated that the model-predicted and actual risks were in good agreement, and the model forecast accuracy was high.

CONCLUSIONS

The risk assessment system constructed in this study has good differentiation, calibration and clinical benefits and can be used as a reference tool for predicting SSI risk in patients.

Effect of 2D vs. 3D laparoscopy on postoperative complications and operation time in a propensity-score-matched real-world data analysis

BACKGROUND

Postoperative complication rates using 3D visualization are rarely reported. The primary aim of our study is to detect a possible advantage of using 3D on postoperative complication rates in a real-world setting.

METHOD

With a sample size calculation for a medium effect size difference that 3D reduces significantly postoperative complications, data of 287 patients with 3D visualization and 832 with 2D procedure were screened. The groups underwent an exact propensity score-matching to be comparable. Comprehensive complication index (CCI) for every procedure was calculated and Operation Time was determined.

RESULTS

Including 1078 patients in the study, 213 exact propensity score-matched pairs could finally be established. Concerning overall CCI (3D: 5.70 ± 13.63 vs. 2D: 3.37 ± 9.89; p = 0.076) and operation time (3D: 103.98 ± 93.26 min vs. 2D: 88.60 ±6 9.32 min; p = 0.2569) there was no significant difference between the groups.

CONCLUSION

Our study shows no advantage of 3D over 2D laparoscopy regarding postoperative complications in a real-world setting, the second endpoint operation time, too, was not influenced by 3D overall.