Abstract
Previous studies show that both the frequency of surgeries and incidence of surgical site infections (SSIs) have been lower during the coronavirus disease 2019 (COVID‐19) pandemic. This study's purpose is to analyse the possible association of the COVID‐19 epidemic‐related increased health measures, such as protective equipment and products, increased hand hygiene and restrictions imposed, on the incidence of SSIs in an academic medical centre. We designed a single‐centre, retrospective cohort study and collected data on the frequency of surgeries and the incidence of SSIs, among patients who had surgeries pre‐ and post‐COVID‐19 pandemic. Besides the intervention and outcome variable, we sought information on patient gender, surgery type, body mass index (BMI), smoking, and type II diabetes mellitus. We used Wald 95% confidence interval (95% CI) and the p values of the odds ratio (OR) to report results. Of the N = 24 098 surgeries performed in this hospital, there were 269 patients who reported post‐surgical SSIs in this hospital between March 2019 and March 2021. The OR of developing a post‐surgical SSI was 0.40 (95% CI: 0.33–0.57, p < 0.05; adjusted for confounders 0.39 [95% CI: 0.30–0.52, p < 0.05]) among patients who had surgery under post‐pandemic infection control measures, as compared to patients who had surgery under pre‐pandemic usual care infection control measures. Our significant results conclude that an association may exist between the enhanced infection control measures used during the COVID‐19 pandemic and lower incidence of SSIs we observed during this period.
Keywords: cohort study, COVID‐19, hospital‐acquired infection, surgery, surgical site infection
1. INTRODUCTION
Among hospital‐acquired infections (HAIs), surgical site infections (SSIs) are the most common type of infection in low‐middle income countries and one of the most frequent in high‐income countries. 1 , 2 This is while the use of simple hand hygiene methods and personal protective equipment (PPE) has been shown to reduce the burden of these infections since the time of Semmelweis trials. 3
Following the declaration of global coronavirus disease 2019 (COVID‐19) pandemic in March 2020, the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) issued guidelines on the use PPE and products by healthcare workers during care for suspected or confirmed COVID‐19 infections. 4 The pandemic necessitated a review and updating infectious disease‐related public health protocols, including measures related to patients, medical staff and devices used. Hand hygiene, disinfection of equipment, aerosol management, as well as the use of PPE by staff are the main pillars of these developments. 5
Also, given the high infectivity and potential morbidity and mortality associated with COVID‐19, an increase in adherence of healthcare workers to safety recommendations was predictable, 6 and universal protection has become a standard of care for healthcare workers. 7 , 8 The pandemic also led to increased awareness of hygiene practices by increasing hand washing and the continued and enhanced adherence to the use of surgical masks and gloves. With increasing awareness of viral infections in the community and hospitals, these public health packages are reported to have had a positive impact on reducing classic postoperative complications such as SSIs and other HAIs. 9 , 10
Furthermore, legal limitations on elective surgeries in pandemic conditions are reported to have reduced specialized surgeries by 59% and the consequent reduction in ICU use in patients during this period is significant. 11 An exemplar study from Switzerland reports that during the first full quarantine, a set of public health measures were implemented between 16 March 2020 and 26 April 2020. As a result, all elective surgeries were restricted, and all specialist physicians and resources were reserved for critically ill patients leading to a significant decrease in both the number of surgeries and the number of hospitalizations. 12
Despite the severity of the crisis, the COVID‐19 pandemic had a positive effect on safety measures and infection control, and the extremeness of the pandemic may lead to valuable reflections, insights, and opportunities for improvement. 13 The aim of this study is to analyse the possible association of the COVID‐19 epidemic‐related increased health measures, such as PPE consumption increased hand hygiene and restrictions imposed, on the frequency of SSIs in an academic medical centre.
2. METHODS
2.1. Study design
In order to investigate the potential impact of the COVID‐19‐related safety and infection control measures on the incidence of SSIs in a hospital setting, we designed a single‐centre, retrospective cohort study. For this purpose, we submitted the study protocol to the Research Ethics Committee of Shahid Beheshti University of Medical Sciences (Approval ID: IR.SBMU.RETECH.REC.1400.761 dated: 17 January 2022), and sought to collect data on parameters related to the frequency of surgeries and the incidence of SSIs, among patients who had surgeries pre‐ and post‐COVID‐19 pandemic in an academic medical centre.
2.2. Setting
Shohada Tajrish Specialty Hospital is a 380‐bed (with 16 operating rooms and 10 recovery beds) tertiary care research and teaching facility affiliated with Shahid Beheshti University of Medical Sciences, in Tehran, Iran. It is the largest public sector health services facility in north Tehran, and under normal operations, it is home to specialty training fellowships. The first two cases of COVID‐19 were officially reported from Iran on 19 February 2020. Health authorities informed the hospital of the COVID‐19 epidemic on 2 March 2020.
2.3. Study population and sample
The population of this study were all patients who had surgery at the hospital between March 2019 and March 2021. The sample of this study were all patients who had a SSI reported between March 2019 and March 2021.
2.4. Variables
Besides the intervention and outcome variable, we sought information on patients' demographic variable (gender), surgery type, body mass index (BMI), smoking and type II diabetes mellitus.
2.5. Measure of the COVID‐19 infection control intervention
We considered the period between March 2019 and March 2020 as the period in which care as usual infection control measures had not been implemented. Therefore, the period between March 2020 and March 2021 is the period in which we considered COVID‐19 enhanced infection control measures to have been in place.
2.6. Measure of SSI outcome
Information on SSIs is routinely collected in this hospital as part of the infection control methods. We considered a post‐surgical infection as being registered in the hospital data set of SSIs.
2.7. Data collection
The primary investigator (HT) gathered the data from the records of patients with post‐surgical SSI and hospital administrative records.
2.8. Analysis
For the total dataset, we calculated the total number of post‐surgical SSIs, as well as the incidence risk. To create relevant subgroups, we dichotomized post‐surgical SSIs as either occurring prior to the infection control protocols of the COVID‐19 pandemic when usual care infection protocols were in place [0] or after the enhanced infection control protocols of the COVID‐19 pandemic [1] and calculated the incidence of surgeries which had and had not resulted into a post‐surgical SSI. We used MS‐Excel 2016 (Microsoft Corporation, Seattle, WA, USA) for data gathering and primary analysis.
Using the incidence of post‐surgical infections, we computed the incidence risk, the odds of post‐surgical SSI and the odds ratio of post‐surgical SSI of surgeries prior to the enhanced infection control protocols of the COVID‐19 pandemic compared to those after. For the assessment of the point estimate, the Wald 95% confidence interval (CI), and the p values of the Odds Ratio (OR), we employed the epiR package 14 in R version 4.1.3 (R Foundation for Statistical Computing, Vienna, Austria). After calculating the OR and Wald 95% CI, we tested the null hypothesis of OR = 1.
For additional analysis, as relevant confounding variables, we considered patient sex, surgery type, BMI, smoking and type II diabetes mellitus. We categorized the type of surgery into five groups (general and vascular surgery, neurosurgery, orthopaedic surgery, urology and obstetrics and gynaecology). We obtained the confounding variables for patients who had a post‐surgical infection from their patient records and used mean and standard deviation values from the Iranian population to generate sex, BMI, 15 smoking, 16 and type II diabetes mellitus 17 for patients who did not have a post‐surgical infection. We proceeded to generate logistic regression models using the binomial(link = ‘logit’) for generalized linear models (glm) in R, and exponentiation of logit coefficients to generate adjusted odds ratios (AOR) and related Wald 95% CI. The complete model we ran was:
Under our null hypothesis, there would be no significant difference in the odds of post‐surgical SSIs before the implementation of the enhanced COVID‐19 infection control measures and after the implementation of the enhanced COVID‐19 infection control measures. An OR or AOR <1 would indicate a protective association, and the entire range of the Wald 95% CI would need to be less than 1.00 to produce a significant chi‐square statistic (k = 1 degree of freedom) and p value (p < 0.05), indicating a statistically significant association.
3. RESULTS
Overall, N = 24 098 patients underwent surgery in this hospital between March 2019 and March 2021. The breakdown of these surgeries by specialty, other confounders, and date is displayed in Table 1.
TABLE 1.
Frequency of surgeries by date, surgery type and other confounders.
| Parameter | Pre‐pandemic: Care as usual infection control (March 2019 to March 2020) (% of column total) | Post‐pandemic: Infection control intervention (March 2020 to March 2021) (% of column total) | Total (% of column total) | Change between post‐ and pre‐ pandemic infection control (% change) |
|---|---|---|---|---|
| All surgeries | n 1 = 13 417 (100%) | n 2 = 10 681 (100%) | N = 24 098 (100%) | n 2‐n 1 = −2736 (−20.39%) |
| Frequency of surgery type | ||||
| General and vascular surgery | 4277 (31.88%) | 2999 (28.08%) | 7276 (30.19%) | −1278 (−29.88%) |
| Neurosurgery | 2248 (16.75%) | 2032 (19.02%) | 4280 (17.76%) | −216 (−9.61%) |
| Obst & Gyn surgery | 1010 (7.53%) | 624 (5.84%) | 1634 (6.78%) | −386 (−38.22%) |
| Orthopaedic surgery | 1999 (28.94%) | 2591 (22.8%) | 4590 (19.05%) | 592 (29.61%) |
| Urology surgery | 3883 (14.9%) | 2435 (24.26%) | 6318 (26.22%) | −1448 (−37.29%) |
| Frequency of patients self‐reporting smoking | ||||
| Smoke yes | 1938 (14.44%) | 1481 (13.87%) | 3419 (14.19%) | −457 (−4.01%) |
| Smoke no | 11 479 (85.56%) | 9200 (86.13%) | 20 679 (85.81%) | −2279 (−0.68%) |
| Frequency of patients with diabetes mellitus | ||||
| DM yes | 1371 (10.22%) | 1140 (10.67%) | 2511 (10.42%) | −231 (−4.45%) |
| DM no | 12 046 (89.78%) | 9541 (89.33%) | 21 587 (89.58%) | −2505 (−0.51%) |
| Patient gender frequency | ||||
| Male | 6302 (46.97%) | 5099 (47.74%) | 11 401 (47.31%) | −1203 (−1.64%) |
| Female | 7115 (53.03%) | 5582 (52.26%) | 12 697 (52.69%) | −1533 (−1.45%) |
| Patient body mass index [kg/m2] | ||||
| BMI (SD) | 26.01 (0.44) | 25.99 (0.32) | 26.00 (0.39) | −0.02 |
As Table 1 indicates the frequency of all surgeries, with the exception orthopaedic surgeries decreased resulting in an overall 20% decrease in total surgeries performed during the COVID‐19 pandemic period as compared to the pre‐pandemic period. The distributions of the frequencies of smoking patients, male and female patients, patients with diabetes mellitus, and patients' BMI were all in line with the literature‐based parameters used to generate them.
Overall, of the N = 24 098 surgeries performed in this hospital, there were 269 patients who reported post‐surgical SSIs in this hospital between March 2019 and March 2021. Table 2 summarizes these infections by date, specialty of surgery, and other confounders immediately prior to infection.
TABLE 2.
Frequency of infection by date and common confounding factors (surgery type, gender, smoking, diabetes mellitus and BMI) immediately prior to infection.
| Parameter | Pre‐pandemic: Care as usual infection control (March 2019 to March 2020) (% of column total) | Post‐pandemic: Infection control intervention (March 2020 to March 2021) (% of column total) | Total (% of column total) | Change between post‐ and pre‐ pandemic infection control (% change) |
|---|---|---|---|---|
| All surgeries | n1 = 200 (100%) | n2 = 69 (100%) | N = 269 (100%) | n2‐n1 = −131 (−65.5%) |
| Frequency of surgery type | ||||
| General and vascular surgery | 58 (29%) | 2 (2.9%) | 60 (22.3%) | −56 (−96.55%) |
| Neurosurgery | 80 (40%) | 28 (40.58%) | 108 (40.15%) | −52 (−65%) |
| Obst & Gyn surgery | 9 (4.5%) | 0 (0%) | 9 (3.35%) | −9 (−100%) |
| Orthopaedic surgery | 25 (12.5%) | 25 (36.23%) | 50 (18.59%) | 0 (0%) |
| Urology surgery | 28 (14%) | 14 (20.29%) | 42 (15.61%) | −14 (−50%) |
| Frequency of patients self‐reporting smoking | ||||
| Smoke yes | 43 (21.5%) | 27 (39.13%) | 70 (26.02%) | −16 (−37.21%) |
| Smoke no | 157 (78.5%) | 42 (60.87%) | 199 (73.98%) | −115 (−73.25%) |
| Frequency of patients with diabetes mellitus | ||||
| DM yes | 31 (15.5%) | 9 (13.04%) | 40 (14.87%) | −22 (−70.97%) |
| DM no | 169 (84.5%) | 60 (86.96%) | 229 (85.13%) | −109 (−64.5%) |
| Patient gender frequency | ||||
| Male | 116 (58%) | 48 (69.57%) | 164 (60.97%) | −68 (−58.62%) |
| Female | 84 (42%) | 21 (30.43%) | 105 (39.03%) | −63 (−75%) |
| Patient body mass index (kg/m2) | ||||
| BMI (SD) | 26.27 (3.92) | 24.74 (3.59) | 25.87 (3.55) | −1.53 |
As Table 2 reveals, the overall frequency of post‐surgical SSIs dropped by 65.5% from 200 per year to 69 per year after the post‐pandemic infection control measures were introduced. This drop was not evenly distributed across all surgeries, such that in orthopaedic surgery, there was no drop in the number of infections, while in general and vascular surgery, there was a 96.55% drop as the number of infections plummeted from 58 prior to the introduction of post‐pandemic infection control measure, to two infections in the year after post‐pandemic enhanced infection control intervention was introduced.
In controlling for patient‐related confounders, based on observed data, there was a drop in post‐surgical infections across all confounders when comparing before the post‐pandemic infection control measures and after, even though the proportion of these drops was not equal. The drop in smokers infections was 37.21%, while non‐smokers infection rate drop was 73.25%. The drop in diabetic patients' infection was 70.97% and 64.5% in non‐diabetic patients', while male patients had 58.62% less infections females had 75% less infections as compared to pre‐pandemic care as usual infection control methods. The same decreasing pattern was also seen in the BMI of all patients such that on average, the BMI of patients who had a post‐surgical infection after the implementation of post‐pandemic infection control measures was 1.53 kg/m2 less.
Table 3 combines the sum frequencies from Tables 1 and 2, in order to investigate the association between exposure to the post‐pandemic enhanced infection control interventions (implemented between March 2020 and March 2021), and post‐surgical infection outcomes in the total sample of N = 24 098 patients who had surgery between March 2019 and March 2021. In calculating primary association measures, based on the figures in Table 3, the OR of developing a post‐surgical SSI was 0.40 (95% CI: 0.33–0.57, p < 0.05) among patients who had surgery under the post‐pandemic infection control measures, as compared to patients who had surgery under the pre‐pandemic usual care infection control measures.
TABLE 3.
Association of pandemic infection control measures and frequency of surgeries with post‐surgery infections.
| Time Interval | Frequency of surgeries with post‐surgery infection | Frequency of surgeries with no post‐surgery infection | Total | Risk of post‐surgery infection | Odds of post‐surgery infection | Odds ratio | Wald confidence interval | p value |
|---|---|---|---|---|---|---|---|---|
| Post‐pandemic infection control intervention (March 2020 to March 2021) | 69 | 10 612 | 10 681 | 0.00646 | 0.0065 | 0.43 | 0.33 to 0.57 | <0.001 |
| Care as usual infection control (March 2019 to March 2020) | 200 | 13 217 | 13 417 | 0.0149 | 0.0151 | |||
| Total | 269 | 23 829 | 24 098 |
The logistic regression multivariate model we generated confirmed the significant univariate association generated through Table 3. As Table 4 shows the model revealed that the AOR of developing a post‐surgical infection was 0.39 (95% CI: 0.30–0.52, p < 0.05) among patients who had surgery under the post‐pandemic infection control measures, as compared to patients who had surgery under the pre‐pandemic usual care infection control measures, after controlling for surgery type, patient gender and BMI, and patients' smoking and diabetes mellitus status.
TABLE 4.
Logistic regression of study parameters on post‐surgical infection.
| Parameter | Estimate | Std. Error | z value | Adjusted odds ratio (AOR) = e Estimate | Wald 95% confidence interval | p value Pr(>|z|) Significant values bolded |
|---|---|---|---|---|---|---|
| Infection control intervention (vs. care as usual infection control) | ||||||
| Post‐pandemic infection control intervention (surgery between March 2020 and March 2021) | −0.94 | 0.14 | −6.60 | 0.39 | 0.30–0.52 | 4.13 × 10 −11 |
| Patient factors | ||||||
| BMI kg/m2 | −0.35 | 0.08 | −4.30 | 0.71 | 0.61–0.84 | 1.74 × 10 −05 |
| Smoking (Yes vs. No) | 0.75 | 0.14 | 5.27 | 2.11 | 1.59–2.77 | 1.40 × 10 −07 |
| Diabetes (Yes vs. No) | 0.50 | 0.17 | 2.86 | 1.65 | 1.15–2.29 | 0.004 |
| Female (vs. Male) | −0.52 | 0.13 | −4.02 | 0.59 | 0.46–0.76 | 5.93 × 10 −05 |
| Surgery type factors (vs. General and vascular surgery) | ||||||
| Neurosurgery | 1.19 | 0.16 | 7.29 | 3.28 | 2.39–4.54 | 3.18 × 10 −13 |
| Obst and Gyn surgery | −0.15 | 0.37 | −0.42 | 0.86 | 0.39–1.68 | 0.68 |
| Orthopaedic surgery | 0.39 | 0.19 | 2.00 | 1.47 | 1.00–2.16 | 0.046 |
| Urology surgery | −0.24 | 0.20 | −1.19 | 0.79 | 0.53–1.17 | 0.23 |
| Model factors | ||||||
| (Intercept) | 4.50 | 2.09 | 2.15 | 89.81 | 1.02–3937.70 | 0.03 |
Note: Null deviance: 2953.4 on 24 097 degrees of freedom. Residual deviance: 2758.7 on 24 088 degrees of freedom. AIC: 2778.7. Number of Fisher Scoring iterations: 8. Bold indicates the significant p values.
Among the patient confounding parameters, post‐surgical infection was associated with BMI AOR = 0.71 (95% CI: 0.61–0.84), smoking AOR = 2.11 (95% CI: 1.59–2.77), diabetes mellitus AOR = 1.65 (95% CI: 1.15–2.29) and gender AOR = 0.59 (95% CI: 0.46–0.76), and all these associations were statistically significant. However, while having neurosurgery (AOR = 3.28 [95% CI: 2.39–4.54]) or orthopaedic surgery (AOR = 1.47 [95% CI: 1.00–2.16]) significantly increased the odds of a post‐surgical infection compared to general and vascular surgery after controlling for confounders (p < 0.0001 and p < 0.05, respectively), the decrease in the odds of a post‐surgical infection after Obst and Gyn surgery (AOR = 0.86 [95% CI: 0.39–1.68]) or urological surgery (AOR = 0.79 [95% CI: 0.53–1.17]) as compared to general and vascular surgery was not statistically significant after controlling for confounders (p = 0.68 and p = 0.23, respectively).
4. DISCUSSION
Our results reveal that the odds of post‐surgical infections were significantly reduced after the implementation of the post‐pandemic infection control measures, as compared to the period when infection control measures were administered as usual care. The significant odds were found through univariate comparison of post‐surgical frequencies of infections (Table 3) and repeated after controlling for common confounders in a logistic model (Table 4).
The results we report are confirmed by several other studies. In another study from Iran, Mohammadi and colleagues report that the rate of pneumonia, UTI and SSI decreased in COVID time compared with the same period in the pre‐COVID era in 2019. However, despite decreasing the number of admissions during the COVID era (hospitalizations showed a reduction of 43.79%), the total hospital nosocomial infections they reported remained unchanged; 4.73% in the pre‐COVID period versus 4.78% during the COVID period. 10 Antonello et al. report from Brazil a 49% decrease of post C‐section SSI was detected. In their study, median SSI was 1.74 in the pre‐COVID period while it was 0.89 in the post‐COVID period. 13 In a study from Germany, Chacón‐Quesada and colleagues report that post‐neurosurgery SSI rate was 2.9% before COVID‐19 began and after COVID‐19 hygiene measures, this rate dropped to 1.4% resembling a significant reduction (p = 0.003). 18 Ishibashi et al. report from gastrointestinal surgeries performed in Japan that superficial SSI and infectious colitis occurred less frequently during the pandemic (p = 0.04 and p = 0.0002, respectively). 19 Similarly, a report from India by Mitra et al. note a 62.39% rate reduction of SSIs as well as drops in other HAIs. 20 Losurdo et al. from Italy report that in the COVID‐19 era, their rates of SSIs were lower (3.3% vs. 8.4%; p = 0.035), fewer of their patients developed a superficial SSIs (0.8% vs. 3.4%; p = 0.018), and none of their patients experienced deep SSIs (0% vs. 3.4%; p = 0.025). This is while there was no significant difference seen in comparing the previous two COVID‐19‐free years. 21 In yet another study from Italy, Cerulli Irelli and colleagues report that among neurology patients hospitalized in 2019, the incidence of overall HAIs was 31.5% (95% CI: 0.25–0.38), compared with 23.3% (95% CI: 0.15–0.32) in 2020, however, this difference was not significant (p = 0.12). Their logistic regression results, however, revealed that hospitalization during 2020 was independently associated with a lower risk of post‐surgical infections (OR: 0.34, 95% CI: 0.16–0.71) and this was significant (p = 0.004). 22 In a study focused on nosocomial Clostridioides difficile infections from Spain, Ponce‐Alonso and colleagues report that infection incidence density was nearly three times lower for the COVID‐19 period than for the non‐COVID‐19 period (incidence rate ratio, 0.31; 95% CI: 0.16–0.61) and this was significant (p = 0.000257). In all the infection incidence density was 2.68 per 10 000 patient days in the COVID‐19 era, whereas it was 8.54 per 10 000 patient days during the pre‐COVID‐19 time. 23
There are also studies that did not find significant differences between pre‐ and post‐pandemic infection rates. Baldwin and colleagues report from a hand surgery unit in the United Kingdom that the absolute risk of SSI in the ‘Pre‐COVID‐19’ group was 2.3% and 5.3% in the ‘During COVID‐19’ group. The relative risk of developing an SSI in the ‘During COVID‐19’ group was 2.34; however, with a 95% CI: 0.95–5.78 and p = 0.06, this was not significant. 24 In a study from Switzerland, a multivariate Cox regression analyses adjusting for the large case‐mix found the COVID‐19 lockdown to be unrelated to SSI (hazard ratio [HR] 1.6; 95% CI: 0.6–4.8), wound healing disorders (HR 0.7; 95% CI: 0.1–5.7) or other non‐infectious postoperative complications (HR 0.7, 95% CI: 0.3–1.5) after a median follow‐up of 7 months. 25
We also found several reports focused on the different aspects of SSI prevention lessons, which could be learned from the COVID‐19 pandemic. Branch‐Elliman and colleagues emphasize the need for sustainability in designing SSI prevention program. 26 Fraser et al. report that the extended use of PPE (one mask per person/day) does not negatively impact the rate of 30‐day SSI and recommend mask usage even when there is a shortage. 27 This is while Losurdo and colleagues report that simple and easily viable precautions, such as wearing surgical masks and the restriction of visitors, are promising tools for the reduction of SSI risk. 21 Lowe et al. discuss the necessity of knowledge exchange to prevent the spread of SSI in low resource settings. 28 Möllers and colleagues, while reporting an outbreak of methicillin‐resistant Staphylococcus aureus (MRSA), emphasize the need for vigilance in addition to the enhanced COVID‐19 infection control protocols. 29 Sharma et al. emphasize the role of the anesthesiologist in the prevention of SSIs. 30 Reporting on a study endorsed by the Global Alliance for Infections in Surgery, Sartelli and colleagues note the importance of healthcare workers behaviours and organizational characteristics and emphasize involving patients in the implementation of prevention protocols. 31 Finally, Cerulli Irelli et al. argue that while calls for action by international agencies during the last years to improve programs for infection prevention and control worldwide have been undermined, in the midst of a health emergency of the COVID‐19 pandemic, many countries successfully rapidly planned and implemented more efficient hygiene protocols in their hospitals and it would be mistaken to waste the opportunity offered by COVID‐19 to improve infection prevention and control. 32
Out study had several limitations. While we had full access to the data of patients who had a post‐surgical SSI, and we had access to counts, surgery dates and surgery type for all patients and we did not have access to the full data of patients who did not have post‐surgical SSI infection. Therefore, the gender, smoking and diabetes prevalence data for our controls are literature‐based estimates. We managed this by using the best estimates available. However, even if we had the full data available, the nature of our study is observational, and therefore, we cannot present any claims of causality on the association between post‐COVID‐19 infection control measures and the decrease in the prevalence of post‐surgery SSIs. Furthermore, the results of our study are from one hospital within one city and one country and they may not be generalizable to similar settings in other geographies.
While our results strengthen the conclusions of several of studies we discuss, future studies could benefit from our results such that they may be able to narrow down the choice of confounders in the associative pathway between infection control measures and SSI outcomes.
5. CONCLUSION
Our significant results lead us to believe that an association may exist between the enhanced infection control measures used during the COVID‐19 pandemic and lower prevalence of SSIs we observed during this period. If these results hold valid, maintaining and sustaining the pandemic enhanced infection control measures in the post‐pandemic era may result in lowered SSI.
FUNDING INFORMATION
This research did not receive any specific grant from funding agencies in the public, commercial or not‐for‐profit sectors.
CONFLICT OF INTEREST STATEMENT
The authors have no competing interests to declare.
Teymourian H, ArianNik M, Mohit B, Massoudi N. A retrospective cohort study of the impact of COVID‐19 infection control measures on surgical site infections in an academic hospital setting. Int Wound J. 2024;21(3):e14583. doi: 10.1111/iwj.14583
DATA AVAILABILITY STATEMENT
Data openly available in a public repository that issues datasets with DOIs.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data openly available in a public repository that issues datasets with DOIs.