Investigation of the Association of Surgical Site Infection with Socio demographic Factors and Clinical Factors

Introduction Surgical Site Infection (SSI) can be referred as the infection that occurs within about 30 days after a surgical operation and affects incision or deep tissues at the surgical site. This type of infection may be superficial or deep incisional infection or infection that includes organ or even body space (Mangramet al., 1999). SSI is one of the most common complications for the patients who undergo surgical procedures and the third most frequently occurring nosocomial infection in the hospital population. Postoperative surgical site infections are often correlated with increased morbidity, mortality, long duration of hospital stay and increased expenses for the health care of the patients (Weigeltet al., 2010). There are several advancements to control SSI which include improved operation theatre, proper ventilation, appropriate sterilization methods, use of different barriers, modern surgical technique and the availability of antimicrobial prophylaxis. But these SSIs exist as common causes of morbidity and mortality due to emergence of antimicrobial resistance of pathogenic bacteria (Mangramet al., 1999). This is partly contributed by random utilization of surgical antimicrobial prophylaxis (Al-Momanyet al., 2009). Tanzania accounted for 19.4% of patients who developed SSI post-surgery (Eriksenet al., 2003). Uganda showed the 10% prevalence of SSI and among the patients suffering from SSI, 9.4% were women who had caeserian section (Hodges and Agaba, 1997). In Ethiopia, the prevalence of SSI was found 21% according to clinical features and 38.7% depending on bacteriological features in patients who had undergone surgery in their abdomen (Kotisso and Aseffa, 1998). It was demonstrated that, in Kenya the prevalence of wound infection among female who had undergone caeserian section was 19% (Koigi-Kamauet al., 2005). In our homeland, Bangladesh, the prevalence of post-surgical wound infection has been found 6-18% (Hadi, 1991). Lots of preoperative, perioperative and postoperative predisposing factors were investigated and their association with the risk for development of SSIs was observed. Prospective inspection of the risk factors for SSIs among the sufferers in surgical wards in Iran revealed significant association of more than 60 years of age, diabetes mellitus, smoking and obesity with risk of SSIs (Arabshahi and Koohpayezade, 2006). Kaya and her colleagues displayed similar findings in addition to malnutrition, prolonged preoperative hospital stay and coexisting infections at the other site of the body being risk factors but smoking was not associated with risk of SSIs (Kaya et al., 2006).Kalmeijer and his group showedS. aureus,found in the nasal carriage,as one of the most important and significant independent risk factors for development of SSI with S. aureus(Kalmeijeret al., 2000). Many studies have reported a number of surgical procedure related factors as contributory risk factors for the development of SSIs. Kaya reported abdominal incision, whole blood transfusion, early preoperative hair removal, inappropriate antimicrobial prophylaxis, famotidine treatment and repair with mesh as independent risk factors for SSI (Kaya et al., 2006). Eriksenshowed prolonged duration of operation, sepsis of the wound, type of operation, type of incision, inappropriate antimicrobial prophylaxis and increased time lapse between shaving and operation as significantly associated with increased risk of SSI among patients who had undergone abdominal surgery (Eriksenet al., 2003). Length of preoperative hospital stay, early preoperative hair removal and compromised nutrition status were significant risk factors for SSIs in Uganda (Tiberiet al., 2010). A prospective incidence study at a district hospital in Tanzania reported American Society of Anesthesiologist (ASA) score of 2-4 and long duration of operation as risk factors significantly associated with SSI (Fehr et al., 2006). Inadequacy and inappropriate use of preoperative antimicrobials is known to be a major risk factor associated with increased incidence of SSI. However, when applied properly it can significantly prevent the occurrence of SSI. For example, a study at a rural hospital in Tanzania showed dramatically decreased rate of SSI from 21.6% to 4% after implementation of appropriate use of preoperative antimicrobial prophylaxis (Saxeret al., 2009). Hence, the present study has been conducted to find out the association of post-surgical with gender, age group, occupation, duration of hospital stay, surgery performed and comorbidities of the respondents. Methodology This cross sectional study was conducted in Khulna Medical College Hospital, Khulna, Bangladesh from June 2017 to May 2018. The data about the patient’s age, gender, occupation, surgery performed, duration of hospital stay and comorbidity was recorded with the help of standard questionnaire. The questionnaires were provided to250 patients and were requested to fill up. All these data preserved accurately and confidentially. Then the wound swabs were collected form those patients under all aseptic precaution and were kept in a sterile test tube and then were sent to the microbiology laboratory immediately. In the laboratory, the pus samples were cultured on McConkey Agar medium and Blood Agar medium. These two media were used for confirmation of the bacteria. The colony morphology of the bacteria were observed. After that, the Gram Staining was carried out which is followed by several biochemical tests including – catalase test, coagulase test, motility test and oxidase test. Data were collected and analyzed statistically using the Statistical Package for Social Sciences (SPSS) database, version 16.0, submitting the data to a simple one factor Analysis of Variance (ANOVA). ANOVA was performed and mean separation was done by SPSS database (p<0.05). Results 250 patients of Khulna Medical College Hospital were considered as the respondents of this study and 195 patients showed post-surgical wound infection containing different microorganisms (Figure 1). The data the gender, age, occupation, surgery performed, duration of hospital stay and comorbidity were collected and analyzed. The results have been displayed below. Figure1: Frequency of the bacteria responsible for post-surgical wound infection. Among the microorganisms responsible for post-surgical wound infection 53 are Escherichia coli (27.18%), 90 are Pseudomonas aeruginosa(46.16%), 22 are Staphylococcus aureus(11.28%), 18 are Klebsiella spp. (9.23%) and 12 are Proteus spp. (6.15%) (Figure 1). Figure 2: Distribution of bacteria responsible for post-surgical wound infection based of the gender of the respondents. Pseudomonas aeruginosahas shown the highest frequency in both male and female. Proteus spp. has shown the lowest frequency in both male and female. However, the microorganisms responsible for post-surgical wound infection do not have any correlation with the gender of the respondents (Figure 2). Table1: Percentage of post-surgical wound infection based on the age groups of the respondents Age group (years) Frequency (Total number of patients in each group) Post-surgical Wound Infection (%) 0-9 5 2.6a 10-19 23 11.8b 20-29 34 17.4c 30-39 34 17.4c 40-49 36 18.5d 50-59 42 21.5e 60-69 17 8.7f 70-79 4 2.1g The age group ranging from 50 years to 59 years showed the highest percentage of post-surgical wound infection (21.5%). On the other hand the age group ranging from 70 years to 79 years had the lowest percentage of post-surgical wound infection (2.0%). In this study, post-surgical wound infection showed statistically significant correlation with the age groupat P<0.05 level. Different letters reveal the significant difference at P<0.05 level while same letters reveal the non-significant difference at P<0.05 level(Table 1). Table 2: Percentage of post-surgical wound infection based on the occupations of the respondents Occupation of the respondents Frequency Post-surgical wound infection (%) Businessman 22 11.3a Employee 40 20.5b Driver 21 10.8c Farmer 13 6.7d Student 31 15.8e Teacher 13 6.7d Housewife 27 13.8f Labor 21 10.8c Social Worker 7 3.6g The highest percentage of post-surgical wound infection (20.5%) was observed in case of the respondents who work as employees, whereas, the social workers presented the lowest percentage of post-surgical wound infection (3.6%).Different letters reveal the significant difference at P<0.05 level while same letters reveal the non-significant difference at P<0.05 level(Table 2). Table 3: Percentage of post-surgical wound infection based on the duration of hospital stay of the respondents Duration of Hospital Stay (days) Frequency Post-surgical wound infection (%) 0-10 51 26.2a 11-20 69 35.3b 21-30 51 26.2a 31-40 18 9.2c 41-50 6 3.1d Patients who spent 11-20 days in hospital, had the highest percentage of post-surgical wound infection (35.3%). Patients who stayed in the hospital 41-50 days displayed the lowest percentage of post-surgical wound infection (3.1%). Statistically significant correlation was found between post-surgical wound infection and the duration of hospital stay at P<0.05 level.Different letters reveal the significant difference at P<0.05 level while same letters reveal the non-significant difference at P<0.05 level(Table 3). Table 4: Percentage of post-surgical wound infection based on the surgeries performed to the respondents Surgery Performed Frequency Post-surgical Wound Infection (%) Abdominal Surgery 29 14.9a Leg Surgery 30 15.4b Hand Surgery 35 17.9c Hip Surgery 15 7.8d Scalp Cut Injury 29 14.9a Vascular Surgery 19 9.7e Back Surgery 19 9.7e Skin Surgery 19 9.7e Patients who have gone thorough hand surgery showed the highest percentage of post- surgical wound infection (17.9%) but patients with the hip surgeryshowed the lowest percentage of post-surgical wound infection(9.7%). Different letters reveal the significant difference at P<0.05 level while same letters reveal the non-significant difference at P<0.05 level (Table 4). Table 5: Percentage of post-surgical wound infection based on the comorbidities of the respondents Comorbidities Frequency Post-surgical wound infection (%) Diabetes 8 4.1a Asthma 6 3.1b Arthritis 3 1.5c Stroke 2 1.0d Ulcer 3 1.5c The diabetic patients had the highest percentage of post-surgical wound infection (4.1%). The patients with previous stroke showed the lowest percentage of post-surgical wound infection (1.0%).Different letters reveal the significant difference at P<0.05 level while same letters reveal the non-significant difference at P