• Users Online: 335
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2017  |  Volume : 5  |  Issue : 2  |  Page : 73-77

Risk stratification of surgical site infection in a Tertiary Care Hospital: A prospective case-control study

1 Department of Anesthesia, Critical Care, Pain Relief and Infection Control, Bengaluru, Karnataka, India
2 Department of Microbiology, Fortis Hospitals, Bengaluru, Karnataka, India
3 Department of Infection Control Nursing, Fortis Hospitals, Bengaluru, Karnataka, India

Date of Web Publication19-Jan-2018

Correspondence Address:
Dr. Murali Chakravarthy
Department of Anesthesia, Critical Care, Pain Relief and Infection Control, Fortis Hospitals, Bannerughatta Road, Bengaluru, Karnataka
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jpsic.jpsic_24_17

Rights and Permissions

Introduction: Health care associated infections are preventable cause of morbidity and mortality in healthcare setting. Surgical site infections are no different. It is essential to identify patients who are at high risk of getting SSI and preventive measures instituted even prior to admission for surgery
Methods: This study comprising of all the SSIs that we encountered over two years and about 10 to 12 patients (per infected patient ) without infection as 'controls'. These two sets of data was used to identify the weightage of each risk factor using logistic regression.
Results: We encountered thirty infections during the years 2015 and 2016, three hundred thirty non infected cases were used as control to arrive the weightage of each factor. Using a backward stepwise multivariate logistic regression model in the whole cohort, body mass index > 30 kg/m2, duration of preoperative stay and use of preoperative antiseptic shower were found to be independent predictors for SSIs. We could predict incidence of SSI with good discrimination (area under ROC curve – 0.855 , 95% confidence intervals 0.81-0.89). Three factors appear to stand out in our study, they are BMI, preoperative stay and preoperative antiseptic shower. These factors appeared to weigh differently in each specialty.
Conclusion: The authors are now able assign scores to each of their patients depending on the type of surgery, sex of the patient, body mass index, number of preoperative days in the hospital, and whether chlorhexidine shower was given or not.

Keywords: Chlorhexidine shower, obesity, risk factors, surgical prophylaxis, surgical site infections

How to cite this article:
Chakravarthy M, Rangaswamy S, George A, Anand T, Senthilkumar P, Rose SA. Risk stratification of surgical site infection in a Tertiary Care Hospital: A prospective case-control study. J Patient Saf Infect Control 2017;5:73-7

How to cite this URL:
Chakravarthy M, Rangaswamy S, George A, Anand T, Senthilkumar P, Rose SA. Risk stratification of surgical site infection in a Tertiary Care Hospital: A prospective case-control study. J Patient Saf Infect Control [serial online] 2017 [cited 2021 Jan 17];5:73-7. Available from: https://www.jpsiconline.com/text.asp?2017/5/2/73/223694

  Introduction Top

Health-care associated infections (HCAI) have been shown to tilt the health-care economics adversely. Among the four HCAIs, surgical site infection (SSI) causes significant morbidity and mortality resulting in escalation of treatment cost.[1] Less well recognised is the cost of these complications, both in the direct costs of care and also in terms of lost economic productivity when workers are disabled as a result of an infection.[2] It is known that SSI causes cost to all concerned-healthcare institutions, health-care providers, the patients and their employers. If one could identify those at high risk of infection and take precautions to prevent the occurrence of SSI, many of the morbidity, mortality and financial implications of healthcare-associated infections could be avoided. A few risk factors for SSI have been identified; they are, the type of surgery, the duration of surgery, female sex, renal disease, diabetes, smoking and pre-operative hospitalisation.[3] If the risk factors and the degree of their contribution in the production of SSI are known, one might not only stratify the elective surgical patients, but also institute-enhanced infection prevention strategies to avoid SSI in them. This study aimed at identifying factors that were commonly associated with SSIs over a period of two calendar years in a tertiary referral corporate hospital in India.

  Methods Top

This was a prospective study of all SSIs over a period of 2 years that occurred at our institution from January 2015 to December 2016. The SSI was defined as per the centre for disease control (CDC) (https://www.cdc.gov/nhsn/pdfs/pscmanual/9pscssicurrent.pdf, released by CDC in January 2017, website accessed on 1st February 2016). All the SSIs whether superficial, deep or organ/space was taken into account.

The practice of SSI control: At our centre, we have a strong hospital infection prevention and control (HIPAC) committee, which has laid down the process to prevent all the HCAI. The perioperative measures that are taken are

  1. Checking for methicillin-resistant Staphylococcus aureus carrier status
  2. Advising three chlorhexidine showers before surgery and intranasal mupirocin twice daily for 5 days
  3. Clipping of hair in the operative area
  4. Maintaining normothermia during transfer, hold and surgery, by adequate covering of patient
  5. Administration of surgical prophylaxis (PPX) (Cefuroxime, 1.5 g) intravenously 15–60 min before surgical incision
  6. Redosing of antibiotic if the surgery lasted longer than 4 h or if there was surgical haemorrhage >30 ml/kg
  7. Maintaining intraoperative blood sugar below 150 mg/dL
  8. Using Halstedian surgical technique to open, dissect and close body cavities
  9. Identifying patients with soaking postoperative wound and attending to them.

These processes are tracked in every patient. SSI was identified by (CDC definition) one or more of the following physical signs and symptoms: fever, swelling, redness, tenderness around the site of incision, cloudy oozing from the wound, culture of the same being positive for bacterial growth. If one or two of the said signs and symptoms were present and the surgeon operating on the patients suspects SSI, it was considered as SSI. Should the patient develop SSI while in the hospital, the HIPAC committee would be notified. Immediately, the infection control nurses (ICNs) would conduct a mini root cause analysis and present their observations in the HIPAC that is held monthly. The outpatient surgical nurse would escalate if SSI was observed in a discharged patient who came for follow-up treatment. Our ICNs make a telephone call within 1 month of discharge and go through a tool containing questions, whose answers might indicate the occurrence of SSI. As per the CDC guidelines, all surgical cases with prostheses were followed up for a year.

For every SSI (considered as test), about ten to twelve patients of similar age and same sex were identified as 'controls' in the same period, undergoing similar surgery for comparison. Pre- and intra-operative factors that were collated are shown in [Table 1]. The weightage for each factor was obtained by logistic regression. The patients were classified based on the type of surgery: cardiac, orthopedic, minimal access abdominal, obstetric and gynaecological surgeries. Multivariate regression was performed, and a risk score was developed. Receiver operative characteristics (ROC), area under the curve (AUC), standard error and confidence interval (CI) were calculated using the 'r' software.
Table 1: The parameters captured

Click here to view

  Results Top

The total number of SSIs was from January 2015 to December 2016 were 30. A total of 360 non-infected similar surgical patients were collated. [Table 2] shows the number of infections in each speciality. Apart from nine SSIs in cardiac surgery, eight in obstetric and gynaecology, twelve in minimal access abdominal surgery, there was one infection in a patient with orthopaedic trauma. We did not encounter any SSIs in neurosurgical, Orthopedic (joint replacement surgery) vascular and plastic surgeries during the study.
Table 2: The number of infections in each speciality

Click here to view

[Table 3] shows the importance of each factor in our cohort. Using a backwards step-wise multivariate logistic regression model in the whole cohort, body mass index (BMI) >30 kg/m 2, duration of pre-operative stay and use of pre-operative antiseptic shower were found to be independent predictors for SSIs. Age, female gender, presence of diabetes mellitus (DM), hypertension (HTN), hypothyroidism, intraoperative blood sugar level >180 mg/dl or blood transfusions were not significant predictors for SSI. This model was found to predict the incidence of SSI with good discrimination (area under ROC curve –0.855, 95% CIs 0.81–0.89). The risk score was found to predict the incidence of SSI with good discrimination (AUC 0.80) and calibration (Hosmer–Lemeshow test P = 0.29). The other factors associated with SSI were elevated intraoperative blood sugar, blood transfusion and pregnancy-induced HTN. Each point increase in the score was seen to increase the odds of infection by 18%. [Table 4] shows the predictive risk score of the cohort. With these information in the background, we assessed the value of these variables individually in cardiac surgery, minimal access abdominal surgery, obstetrics and gynaecological surgery [Table 5], [Table 6], [Table 7].
Table 3: The factors affecting the entire cohort

Click here to view
Table 4: The additive risk score was developed to predict the risk of surgical site infections from the regression model

Click here to view
Table 5: The factors affecting surgical site infections in cardiac surgery (n=9)

Click here to view
Table 6: The factors affecting surgical site infections in obstetric and gynaecological surgery (n=8)

Click here to view
Table 7: The factors affecting surgical site infections in minimal access abdominal surgery (n=12)

Click here to view

In cardiac surgical patients [Table 5], the BMI >30 kg/m 2 was found to be strongly associated with SSI whereas pre-operative antiseptic shower, blood transfusions and adult patients were negatively associated. DM, HTN, hypothyroidism, duration of pre-operative stay, duration of surgery and use of antibiotic PPX before surgery did not influence SSI.

In gynaecological surgery [Table 6], increasing age, presence of pregnancy-related HTN increased the rate of SSI, while pre-operative antiseptic shower and surgical PPX reduced the risk. Blood transfusion was strongly associated with the presence of SSI. DM, BMI, hypothyroidism, duration of preoperative stay, type of surgery, duration of surgery, blood sugar levels, hypothermia, etc., were not good predictors for SSIs.

In minimal access, abdominal surgery [Table 7] SSI was present in 12 cases (9.6%). BMI >30 kg/m 2 increased the risk, whereas antibiotic PPX before surgery was protective. Age, gender, presence of diabetes, HTN or hypothyroidism, length of pre-operative stay, duration of surgery, use of pre-operative antiseptic shower, high blood sugar levels, blood transfusions, hypothermia where not significant predictors. The value of each of the risk factors in each of the speciality is shown in [Table 8].
Table 8: The weightage of each of the factors in each type of surgery

Click here to view

  Discussion Top

In this prospective observational controlled study conducted in a tertiary care corporate hospital of India, thirty SSIs were observed during two calendar years starting January 2015, ending December 2016. An additive risk score was developed to predict the risk of SSIs from the regression model. Three factors appear to stand out in our study, they are BMI (with an additive risk score of 12, indicating increased susceptibility by twelve times), pre-operative stay (with an additive risk score of 1.3, indicating an increase in susceptibility by 1.3 times) and pre-operative antiseptic shower (with a negative additive risk score of −0.1, indicating a decrease of SSI by 90% after chlorhexidine shower). Several other workers to have identified BMI as a risk factor-elevated BMI as a definite risk in laparoscopic,[4] spine and [5] cardiac surgery.[6] Our observation of having highest additive score perhaps signifies the high degree of importance one ought to give to prevent SSIs in obese patients and provide enhanced care to them. The other two factors that were identified with an increased incidence of SSIs in our study, first, increased pre-operative stay and second lack of pre-operative chlorhexidine shower. These have also been identified as risk factors for SSI by many authors too.[7],[8],[9] Chlorhexidine shower may advise for 3–5 days, because recolonisation takes place after 7 days.[10] In addition to the risk factors identified above, in this study duration of surgery and timely administration of surgical PPX were also identified as significant factors causing SSIs and similar observations have been made by other workers too.[11],[12],[13] Raja et al., have worked on a study similar to ours and developed Brompton Harefield infection score. They too identified independent predictors of SSI and put weightage which were, female gender = 2 (P< 0.0001; risk ratio [RR] 2.1), diabetes = 1 (P = 0.0098, RR 1.4) or HbA1c >7.5% = 3 (P< 0.0001; RR 3.4), BMI ≥35 = 2 (P< 0.0001; RR 2.4), left ventricular ejection fraction <45% =1 (P = 0.0255; RR 1.4) and emergency surgery = 2 (P = 0.012; RR 2.4).[14] Weights for such scores are different for each type of surgery, as could be appreciated from [Table 5], [Table 6], [Table 7]. Of all the factors studied, BMI >35 kg/m 2 appears to be the highest risk.

Infection control is a collective responsibility of the team members. The key players are the pre-operative, intra- and post-operative team. The key roles of each are mentioned in [Table 9]. It is prudent that the hospital administration looks at the recommendation of the stakeholders and improves the infrastructural, technical and workforce support to reduce HCAI. A process has to be strongly placed, its use is periodically audited and suitable interventions are introduced depending on the audit findings. Process failure contributes largely to the occurrence of SSIs. It is perhaps vital to lay a standard operating procedure and follow the protocols diligently.
Table 9: Quality assurance and surgical site infection

Click here to view

  Conclusion Top

Increased duration of pre-operative stay, increased BMI and lack of pre-operative chlorhexidine shower was found to important predictors of SSI. These factors vary from one surgical speciality to other.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Anderson DJ, Pyatt DG, Weber DJ, Rutala WA, North Carolina Department of Public Health HAI Advisory Group. Statewide costs of health care-associated infections: Estimates for acute care hospitals in North Carolina. Am J Infect Control 2013;41:764-8.  Back to cited text no. 1
Fry DE. The economic costs of surgical site infection. Surg Infect (Larchmt) 2002;3 Suppl 1:S37-43.  Back to cited text no. 2
Lindsjö C, Sharma M, Mahadik VK, Sharma S, Stålsby Lundborg C, Pathak A, et al. Surgical site infections, occurrence, and risk factors, before and after an alcohol-based handrub intervention in a general surgical department in a rural hospital in Ujjain, India. Am J Infect Control 2015;43:1184-9.  Back to cited text no. 3
Kurmann A, Vorburger SA, Candinas D, Beldi G. Operation time and body mass index are significant risk factors for surgical site infection in laparoscopic sigmoid resection: A multicenter study. Surg Endosc 2011;25:3531-4.  Back to cited text no. 4
Abdallah DY, Jadaan MM, McCabe JP. Body mass index and risk of surgical site infection following spine surgery: A meta-analysis. Eur Spine J 2013;22:2800-9.  Back to cited text no. 5
Lemaignen A, Birgand G, Ghodhbane W, Alkhoder S, Lolom I, Belorgey S, et al. Sternal wound infection after cardiac surgery: Incidence and risk factors according to clinical presentation. Clin Microbiol Infect 2015;21:674.e11-8.  Back to cited text no. 6
Khan IU, Janjua MB, Hasan S, Shah S. Surgical site infection in lumbar surgeries, pre and postoperative antibiotics and length of stay: A case study. J Ayub Med Coll Abbottabad 2009;21:135-8.  Back to cited text no. 7
Chlebicki MP, Safdar N, O'Horo JC, Maki DG. Preoperative 20 chlorhexidine shower or bath for prevention of surgical site infection: 21 A meta-analysis. Am J Infect Control 2013;41:167-73.  Back to cited text no. 8
Edmiston CE Jr., Bruden B, Rucinski MC, Henen C, Graham MB, Lewis BL, et al. Reducing the risk of surgical site infections: Does chlorhexidine gluconate provide a risk reduction benefit? Am J Infect Control 2013;41:S49-55.  Back to cited text no. 9
Byrne DJ, Phillips G, Napier A, Cuschieri A. The effect of whole body disinfection on intraoperative wound contamination. J Hosp Infect 1991;18:145-8.  Back to cited text no. 10
Pop-Vicas A, Musuuza JS, Schmitz M, Al-Niaimi A, Safdar N. Incidence and risk factors for surgical site infection post-hysterectomy in a tertiary care center. Am J Infect Control 2017;45:284-7.  Back to cited text no. 11
Gaynes RP, Culver DH, Horan TC, Edwards JR, Richards C, Tolson JS, et al. Surgical site infection (SSI) rates in the United States, 1992-1998: The National Nosocomial Infections Surveillance System Basic SSI Risk Index. Clin Infect Dis 2001;33 Suppl 2:S69-77.  Back to cited text no. 12
Agodi A, Quattrocchi A, Barchitta M, Adornetto V, Cocuzza A, Latino R, et al. Risk of surgical site infection in older patients in a cohort survey: Targets for quality improvement in antibiotic prophylaxis. Int Surg 2015;100:473-9.  Back to cited text no. 13
Raja SG, Rochon M, Jarman JW. Brompton harefield infection score (BHIS): Development and validation of a stratification tool for predicting risk of surgical site infection after coronary artery bypass grafting. Int J Surg 2015;16:69-73.  Back to cited text no. 14


  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Article Tables

 Article Access Statistics
    PDF Downloaded13    
    Comments [Add]    

Recommend this journal