Surgical-site infections following cranial surgery: is it time to reconsider our preventive measures?

Background: Identification of healthcare-associated infections (HAIs) is just a first step in the surveillance of HAIs. The other part is the analysis and interpretation of collected data, which should help to set up effective preventive measures targeted where they are needed the most. General risk factors of HAIs are mostly well known, but how do the environment and processes of each hospital affect risks of HAI? Can advanced methods of data analytics reveal hidden hospital-specific risk factors of surgical site infections (SSIs)? Methods: We analyzed data from electronic health records stored in the clinical information system of Hospital Jihlava, Czech Republic, with 650 beds and 7,500 surgeries performed annually. For each inpatient stay with a surgical procedure, we automatically observed almost 1,500 features that could lead to a higher incidence of SSIs. These features consist of patient demographic data, information from structured data (eg, patient diagnoses, departments, specific rooms, operating theaters, surgeons and other hospital staff participating in the surgery), and information extracted from clinical notes using natural language processing (eg, procedures, invasive devices, and comorbidities). We used a model based on survival analysis to reveal the risk factors that can increase the probability of SSI during the inpatient stay or outpatient care after discharge. Results: We automatically evaluated risk factors weekly for 4 months (July 2019–October 2019). We detected 16 distinct significant risk factors during this period—between 2 and 6 active risk factors each week. For example, patients visiting a specific department were up to 5 times more likely to develop an HAI than the rest of the patients (P < .001). Some of the risk factors revealed were significant only within a short time, and some of them occurred perpetually. When a feature became significant, it was considered an early warning of a problem that should be addressed by the infection prevention and control team. Trends in risk factors coefficients can also help in assessing the performance of the launched preventive measures. Conclusions: Advanced data analytics can effectively uncover hospital-specific risk factors affecting surgical site infections. Such systems can automatically deliver results that can be further explored and used as a basis for targeted preventive measures.Funding: Datlowe provided support for this study.Disclosures: Jakub Kozák reports salary from and ownership of Datlowe.

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Incidence of surgical site infections in a urology department

Acta chirurgica iugoslavica ◽

10.2298/aci1101061m ◽

2011 ◽

Vol 58 (1) ◽

pp. 61-65 ◽

Cited By ~ 1

Author(s):

Ljiljana Markovic-Denic ◽

Violeta Rakic ◽

Milovan Maksimovic ◽

Milan Djokic

Keyword(s):

Cohort Study ◽

Incidence Rate ◽

Preventive Measures ◽

Surgical Site Infections ◽

Incidence Rates ◽

Hospital Infections ◽

Asa Score ◽

One Year ◽

Definition Of ◽

Clean Contaminated

Objectives: To determine the incidence of surgical site infections (SSI) in the urology wards as well as the SSI incidence in relation to the ASA score and surgical site contamination class. Materials and methods: One-year prospective cohort study was conducted in the Urologic department, General hospital, Sabac. The patients were daily examined and their diagnoses were made according to the definition of hospital infections using concurrently the ASA score and surgical site contamination class. Results: Out of 241 operated patients, 32 patients were diagnosed with 33 SSI. The overall incidence rate of patients with SSI was 5.9% while incidence rate of SSI was 6.1%. There were not the differences in the incidence rates according to the ASA score of patients (p>0.05). The incidence of SSI was 5.0% in the clan wounds, 11.2% in the clean-contaminated, and 20.7% in the contaminated wounds (?2=8.2 DF=2 p<0.016). The patients with SSIs were hospitalized approximately 2 times longer than the patients without SSI (t=-6,28; df=239; p<0,001). Conclusion: This study suggests that it is necessary to maintain continous surveillance of surgical site infections and to implement the preventive measures, especially for clean and clean-contaminated surgery.

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Preoperative chemotherapy and corticosteroids: independent predictors of cranial surgical-site infections

Journal of Neurosurgery ◽

10.3171/2015.4.jns142719 ◽

2016 ◽

Vol 125 (1) ◽

pp. 187-195 ◽

Cited By ~ 19

Author(s):

Bryan A. Lieber ◽

Geoffrey Appelboom ◽

Blake E. Taylor ◽

Franklin D. Lowy ◽

Eliza M. Bruce ◽

...

Keyword(s):

Risk Factors ◽

Preoperative Chemotherapy ◽

Univariate Analysis ◽

Surgical Site Infections ◽

Patient Specific ◽

Improvement Program ◽

Steroid Use ◽

Cranial Surgery ◽

Duration Of Operation ◽

Wound Class

OBJECT Preoperative corticosteroids and chemotherapy are frequently prescribed for patients undergoing cranial neurosurgery but may pose a risk of postoperative infection. Postoperative surgical-site infections (SSIs) have significant morbidity and mortality, dramatically increase the length and cost of hospitalization, and are a major cause of 30-day readmission. In patients undergoing cranial neurosurgery, there is a lack of data on the role of patient-specific risk factors in the development of SSIs. The authors of this study sought to determine whether chemotherapy and prolonged steroid use before surgery increase the risk of an SSI at postoperative Day 30. METHODS Using the national prospectively collected American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database for 2006–2012, the authors calculated the rates of superficial, deep-incisional, and organ-space SSIs at postoperative Day 30 for neurosurgery patients who had undergone chemotherapy or had significant steroid use within 30 days before undergoing cranial surgery. Trauma patients, patients younger than 18 years, and patients with a preoperative infection were excluded. Univariate analysis was performed for 25 variables considered risk factors for superficial and organ-space SSIs. To identify independent predictors of SSIs, the authors then conducted a multivariate analysis in which they controlled for duration of operation, wound class, white blood cell count, and other potential confounders that were significant on the univariate analysis. RESULTS A total of 8215 patients who had undergone cranial surgery were identified. There were 158 SSIs at 30 days (frequency 1.92%), of which 52 were superficial, 27 were deep-incisional, and 79 were organ-space infections. Preoperative chemotherapy was an independent predictor of organ-space SSIs in the multivariate model (OR 5.20, 95% CI 2.33–11.62, p < 0.0001), as was corticosteroid use (OR 1.86, 95% CI 1.03–3.37, p = 0.04), but neither was a predictor of superficial or deep-incisional SSIs. Other independent predictors of organ-space SSIs were longer duration of operation (OR 1.16), wound class of ≥ 2 (clean-contaminated and further contaminated) (OR 3.17), and morbid obesity (body mass index ≥ 40 kg/m2) (OR 3.05). Among superficial SSIs, wound class of 3 (contaminated) (OR 6.89), operative duration (OR 1.13), and infratentorial surgical approach (OR 2.20) were predictors. CONCLUSIONS Preoperative chemotherapy and corticosteroid use are independent predictors of organ-space SSIs, even when data are controlled for leukopenia. This indicates that the disease process in organ-space SSIs may differ from that in superficial SSIs. In effect, this study provides one of the largest analyses of risk factors for SSIs after cranial surgery. The results suggest that, in certain circumstances, modulation of preoperative chemotherapy or steroid regimens may reduce the risk of organ-space SSIs and should be considered in the preoperative care of this population. Future studies are needed to determine optimal timing and dosing of these medications.

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