Postoperative wound infection, referred to in current studies as surgical site infection (SSI), is an infection occurring at or near the surgical incision within 30 days of an operation, or within 90 days if an implant is left in place[1,2]. Despite advances in aseptic technique, operating-room engineering and antimicrobial prophylaxis, SSI remains one of the commonest healthcare-associated infections (HAIs) worldwide. In low- and middle-income countries it is the most frequent HAI, with a pooled incidence of about 11.8 per 100 surgical patients in a systematic review and meta-analysis[3]. The World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) have both issued evidence-based guidelines for its prevention[4–7]. SSI is not merely a local complication. It prolongs hospital stay by roughly a week on average, increases the likelihood of readmission, re-operation and intensive care admission, raises the cost of care and contributes to mortality[8,9]. In a country such as India, where a large share of health expenditure is borne out of pocket, an infected wound may mean loss of wages, repeated dressings, prolonged antibiotic courses and, for many families, financial hardship. The epidemiology of wound infection has been studied for more than four decades. In the classic prospective study of 62,939 wounds by Cruse and Foord, the infection rate rose from about 1.5% in clean wounds to over 40% in dirty wounds, which established wound contamination class as the cornerstone of risk stratification[10]. Subsequent work in the NNIS system and the SENIC project showed that the risk of infection depends jointly on wound contamination, duration of operation and the patient’s intrinsic susceptibility, as measured by the ASA score[11,12]. Risk factors are conventionally grouped into patient-related factors (age, diabetes, obesity, malnutrition, anaemia, smoking), procedure-related factors (emergency surgery, duration, wound class, drains, technique) and facility-related factors (preoperative stay, skin preparation, timing of prophylaxis, operating-theatre practice). Reported SSI rates in India vary widely, from single-digit figures in studies restricted to clean and clean-contaminated surgery to well above 20% in studies that include emergency and contaminated cases[13–16]. Indian studies from tertiary teaching hospitals have identified diabetes, prolonged preoperative stay, emergency surgery, longer operative time and higher wound class as important determinants[17–19]. The bacteriological picture has also been changing: while Staphylococcus aureus was historically the dominant isolate, Gram-negative bacilli such as Escherichia coli, Klebsiella and Pseudomonas now account for a large and growing proportion of isolates, many of them multidrug resistant[19,20]. This is of concern because empirical antibiotic choices must rely on local antibiograms, as emphasised in the national treatment guidelines and the National Action Plan on Antimicrobial Resistance[21–23]. Multicentre surveillance data from Indian hospitals also point to a considerable burden of device- and procedure-associated infection[24,25]. Obstetrics and gynaecology contribute a substantial and distinct share of surgical workload. Caesarean section is among the most commonly performed major operations in the world, and its rate in India has risen steadily; the fifth National Family Health Survey (2019–21) recorded a national caesarean rate of about 21.5%, with far higher figures in the private sector and in several states[26]. SSI after caesarean delivery complicates a considerable proportion of operations, and is influenced by factors that are specific to obstetric practice such as the duration of labour, rupture of membranes and the number of vaginal examinations[27–30]. Infection after abdominal and vaginal hysterectomy is likewise an important cause of morbidity[31,32]. Obstetric and general surgical patients differ in age, nutritional status, comorbidity and contamination profile, and comparative data from the same hospital are scarce. The present study was therefore undertaken to determine the incidence and clinical profile of postoperative wound infection, to identify the bacteriological profile and antibiotic susceptibility of the causative organisms, and to analyse the risk factors for SSI in patients operated in the Departments of General Surgery and Obstetrics & Gynaecology of a tertiary care teaching hospital. The primary objectives were: • To estimate the incidence of SSI in General Surgery and Obstetrics & Gynaecology patients. • To describe the clinical profile (type, time of onset and presentation) of SSI. • To identify the causative organisms and their antibiotic susceptibility pattern. • To identify patient-related and procedure-related risk factors, and the effect of SSI on outcome.

2.1 Study design, setting and period This was a hospital-based prospective observational study conducted in the Departments of General Surgery and Obstetrics & Gynaecology, in collaboration with the Department of Microbiology, of a tertiary care teaching hospital over 6 months (January 2025 to June 2025). The study was reported in accordance with the STROBE guidelines for observational studies[33]. Approval of the Institutional Ethics Committee was obtained and written informed consent was taken from all participants. 2.2 Sample size and study population Assuming an anticipated SSI rate of 13%, an absolute precision of 3.5% and a 95% confidence level, the minimum sample size was calculated as 355 using n = Z²pq/d². Allowing for loss to follow-up, 400 consecutive patients were enrolled. Adults and adolescents aged 15 years or more undergoing elective or emergency surgery under general, spinal or regional anaesthesia, who gave consent, were included. Patients with pre-existing infection at the operative site that was the indication for surgery and had been treated as a separate condition (for example, wounds already infected at presentation for secondary closure), those undergoing minor day-care procedures, those with implants, and those who declined consent or were lost to follow-up before day 30 were excluded. 2.3 Data collection A pre-tested proforma recorded demographic data, comorbidities (diabetes mellitus, anaemia, hypoalbuminaemia, obesity, tobacco use), ASA physical status[34], preoperative stay, indication and type of surgery (elective or emergency), wound class, duration of operation, use of drains, and details of antibiotic prophylaxis. Wound class was assigned as clean, clean-contaminated, contaminated or dirty according to standard CDC definitions. Antibiotic prophylaxis was classed as appropriate when a suitable agent was given within 60 minutes before incision and discontinued within 24 hours, in line with national and international recommendations[35]. Standard practice in both departments included preoperative bath, skin preparation with an antiseptic solution, surgical hand scrub and draping; the choice of skin antiseptic was left to the operating surgeon. 2.4 Follow-up and definition of SSI Wounds were inspected on alternate days during the hospital stay and on the day of discharge. After discharge, patients were reviewed in the outpatient department on days 7, 14 and 30, and telephone contact was used for those who could not attend. SSI was diagnosed and classified as superficial incisional, deep incisional or organ/space infection using the CDC/NHSN criteria. Stitch abscess without surrounding cellulitis was not counted as SSI. 2.5 Microbiological methods For every clinically suspected SSI, pus or wound discharge was collected aseptically (aspiration or two swabs) before starting or changing antibiotics, where possible. Samples were subjected to Gram stain, and aerobic culture on blood agar and MacConkey agar. Isolates were identified by standard biochemical methods. Antibiotic susceptibility was determined by the Kirby–Bauer disc diffusion method on Mueller–Hinton agar and interpreted according to CLSI M100 (32nd edition) breakpoints[36]. Methicillin resistance in S. aureus was detected by the cefoxitin disc, and ESBL production by the combined disc/double disc synergy test. Multidrug resistance (MDR) was defined as acquired non-susceptibility to at least one agent in three or more antimicrobial categories[37]. 2.6 Statistical analysis Data were entered in Microsoft Excel and analysed with SPSS version 26. Categorical variables are expressed as frequencies and percentages and compared with the chi-square test or Fisher’s exact test; continuous variables are expressed as mean ± standard deviation and compared with the unpaired t test. Unadjusted odds ratios (OR) with 95% confidence intervals (CI) were calculated for each risk factor. Variables with p <0.10 on univariate analysis were entered into a multivariate logistic regression model (backward likelihood-ratio method) to obtain adjusted odds ratios (aOR). Model fit was assessed with the Hosmer–Lemeshow test. A p value <0.05 was considered statistically significant.

3.1 Incidence and patient characteristics A total of 400 patients were enrolled, of whom 250 (62.5%) were operated in General Surgery and 150 (37.5%) in Obstetrics & Gynaecology. The mean age was 38.6 ± 14.2 years (range 16–78 years) and 252 (63.0%) were females. SSI developed in 52 patients, giving an overall incidence of 13.0% (95% CI 9.9–16.7%). The incidence was 14.4% (36/250) in General Surgery and 10.7% (16/150) in Obstetrics & Gynaecology; the difference was not statistically significant (χ² = 1.16, p = 0.28). SSI rates rose progressively with age, from 5.6% in patients under 20 years to 25.0% in those above 60 years, and the difference between males (14.9%) and females (11.9%) was not significant (p = 0.40) (Table 1). Table 1: Age and sex distribution of patients and SSI rate (N = 400) Variable Patients (n) SSI cases (n) SSI rate (%) ≤20 years 18 1 5.6 21–30 years 108 8 7.4 31–40 years 102 9 8.8 41–50 years 78 12 15.4 51–60 years 58 13 22.4 >60 years 36 9 25.0 Sex Male 148 22 14.9 Female 252 30 11.9 Total 400 52 13.0 Chi-square test for trend with age: p = 0.001; sex: p = 0.40 (not significant). 3.2 Distribution of procedures Emergency laparotomy, hernia repair and cholecystectomy were the commonest operations in General Surgery, whereas lower-segment caesarean section (LSCS) constituted 68.0% of all procedures in Obstetrics & Gynaecology. The highest SSI rates were seen after emergency laparotomy (26.1%), bowel resection/stoma closure (20.0%) and amputation/debridement procedures (20.0%), and the lowest after thyroid and other clean surgery (5.6%), elective LSCS (5.0%) and hernia repair (6.8%) (Table 2). Table 2: Distribution of surgical procedures and SSI rate Procedure Patients (n) SSI cases (n) SSI rate (%) General Surgery Emergency laparotomy 46 12 26.1 Bowel resection / stoma closure 30 6 20.0 Hernia repair 44 3 6.8 Cholecystectomy 40 3 7.5 Appendicectomy 38 5 13.2 Breast surgery 14 2 14.3 Thyroid / other clean surgery 18 1 5.6 Amputation / debridement 20 4 20.0 Subtotal – General Surgery 250 36 14.4 Obstetrics & Gynaecology Emergency LSCS 62 7 11.3 Elective LSCS 40 2 5.0 Abdominal hysterectomy 24 4 16.7 Vaginal hysterectomy 10 1 10.0 Laparotomy (ovarian / ectopic) 14 2 14.3 Subtotal – Obstetrics & Gynaecology 150 16 10.7 Grand total 400 52 13.0 General Surgery vs Obstetrics & Gynaecology: χ² = 1.16, p = 0.28. 3.3 Wound class Of the 400 operations, 96 (24.0%) were clean, 170 (42.5%) clean-contaminated, 98 (24.5%) contaminated and 36 (9.0%) dirty. The SSI rate increased steadily with the degree of contamination, from 4.2% in clean wounds to 27.8% in dirty wounds (χ² = 16.3, p = 0.001) (Table 3, Figure 1). Table 3: Wound class and SSI rate Wound class Operations (n) SSI cases (n) SSI rate (%) Clean 96 4 4.2 Clean-contaminated 170 20 11.8 Contaminated 98 18 18.4 Dirty 36 10 27.8 Total 400 52 13.0 χ² = 16.3, df = 3, p = 0.001. 3.4 Clinical profile of SSI Of the 52 infections, 34 (65.4%) were superficial incisional, 12 (23.1%) deep incisional and 6 (11.5%) organ/space infections. The mean time of onset was 8.1 ± 4.6 days after surgery; 46.2% of infections appeared between the 4th and 7th postoperative days, and 11.5% presented after the 14th day. Importantly, 16 infections (30.8%) were detected only after discharge, during post-discharge follow-up (Table 4, Figure 2). Purulent discharge was the commonest presenting feature (88.5%), followed by local pain/tenderness, erythema and induration; fever was present in 63.5% and wound dehiscence in 26.9% (Table 5). Table 4: Type, timing and mode of detection of SSI (n = 52) Characteristic Number (%) Type of SSI (CDC/NHSN) Superficial incisional 34 (65.4) Deep incisional 12 (23.1) Organ / space 6 (11.5) Postoperative day of onset ≤3 days 6 (11.5) 4–7 days 24 (46.2) 8–14 days 16 (30.8) 15–30 days 6 (11.5) Time of detection During hospital stay 36 (69.2) After discharge (follow-up) 16 (30.8) Mean day of onset 8.1 ± 4.6 days. Table 5: Presenting clinical features of SSI (n = 52; multiple features possible) Clinical feature Number (%) Purulent discharge 46 (88.5) Local pain / tenderness 48 (92.3) Erythema 50 (96.2) Induration / swelling 41 (78.8) Fever (≥38 °C) 33 (63.5) Wound dehiscence 14 (26.9) Foul-smelling discharge 19 (36.5) Spreading cellulitis 20 (38.5) 3.5 Bacteriological profile Culture was positive in 44 of 52 SSI cases (84.6%) and sterile in 8 (15.4%), most of whom had received antibiotics before sampling. Monomicrobial growth was seen in 38 cases and polymicrobial growth in 6, giving 50 isolates in all. Gram-negative bacilli accounted for 33 isolates (66.0%) and Gram-positive cocci for 17 (34.0%). The commonest isolate was Escherichia coli (28.0%), followed by Staphylococcus aureus (24.0%), Klebsiella pneumoniae (14.0%) and Pseudomonas species (12.0%) (Table 6, Figure 3). Escherichia coli predominated after lower abdominal, bowel and gynaecological surgery, whereas S. aureus predominated after clean surgery and caesarean section. Table 6: Organisms isolated from SSI (total isolates = 50) Organism Number (%) Escherichia coli 14 (28.0) Staphylococcus aureus 12 (24.0) Klebsiella pneumoniae 7 (14.0) Pseudomonas spp. 6 (12.0) Acinetobacter spp. 4 (8.0) Enterococcus spp. 3 (6.0) Proteus spp. 2 (4.0) Coagulase-negative staphylococci 2 (4.0) Total isolates 50 (100.0) Of 12 S. aureus, 5 (41.7%) were MRSA. Overall, 27 of 50 isolates (54.0%) were multidrug resistant. .6 Antibiotic susceptibility Among the 12 S. aureus isolates, all were sensitive to vancomycin and linezolid, whereas only 58.3% were methicillin-sensitive (cefoxitin) and 8.3% were penicillin-sensitive (Table 7). Among the Gram-negative isolates, susceptibility was highest to carbapenems and colistin and lowest to ampicillin, amoxicillin–clavulanate, ceftriaxone and ciprofloxacin. ESBL production was documented in 14 of 21 (66.7%) E. coli and Klebsiella isolates, and 2 of 4 Acinetobacter isolates were carbapenem resistant but sensitive to colistin. One K. pneumoniae isolate was carbapenem resistant. All Enterococcus isolates were sensitive to vancomycin and linezolid (Table 8). Table 7: Antibiotic susceptibility of Staphylococcus aureus (n = 12) Antibiotic Sensitive n (%) Resistant n (%) Penicillin 1 (8.3) 11 (91.7) Cefoxitin (methicillin-sensitive) 7 (58.3) 5 (41.7) Erythromycin 5 (41.7) 7 (58.3) Clindamycin 9 (75.0) 3 (25.0) Gentamicin 8 (66.7) 4 (33.3) Ciprofloxacin 6 (50.0) 6 (50.0) Co-trimoxazole 7 (58.3) 5 (41.7) Linezolid 12 (100.0) 0 (0.0) Vancomycin 12 (100.0) 0 (0.0) Table 8: Antibiotic susceptibility of Gram-negative isolates (sensitive, n [%]) Antibiotic E. coli (n = 14) K. pneumoniae (n = 7) Pseudomonas (n = 6) Ampicillin 2 (14.3) IR NT Amoxicillin–clavulanate 4 (28.6) 2 (28.6) NT Ceftriaxone 4 (28.6) 2 (28.6) NT Ceftazidime NT NT 3 (50.0) Ciprofloxacin 5 (35.7) 3 (42.9) 3 (50.0) Gentamicin 8 (57.1) 4 (57.1) 3 (50.0) Amikacin 11 (78.6) 5 (71.4) 4 (66.7) Piperacillin–tazobactam 9 (64.3) 4 (57.1) 4 (66.7) Meropenem 14 (100.0) 6 (85.7) 4 (66.7) Colistin 14 (100.0) 7 (100.0) 6 (100.0) IR = intrinsic resistance; NT = not tested / not applicable. 3.7 Risk factors for SSI: univariate analysis Table 9 shows the association of individual risk factors with SSI. Age above 50 years, diabetes mellitus, obesity (BMI ≥30 kg/m²), anaemia (haemoglobin <10 g/dL), hypoalbuminaemia (serum albumin <3.5 g/dL), tobacco use, ASA grade ≥III, emergency surgery, operation time >2 hours, preoperative stay >3 days, use of a drain, inappropriate antibiotic prophylaxis and contaminated/dirty wound class were all significantly associated with SSI. The strongest unadjusted associations were with operation time >2 hours (OR 5.0), emergency surgery (OR 4.6), ASA grade ≥III (OR 3.8) and hypoalbuminaemia (OR 3.7). Table 9: Univariate analysis of risk factors for SSI (N = 400) Risk factor SSI in exposed n/N (%) SSI in unexposed n/N (%) Crude OR (95% CI) p value Age >50 years 22/94 (23.4) 30/306 (9.8) 2.81 (1.53–5.16) 0.001 Diabetes mellitus 18/62 (29.0) 34/338 (10.1) 3.66 (1.90–7.03) <0.001 BMI ≥30 kg/m² 14/56 (25.0) 38/344 (11.0) 2.68 (1.34–5.36) 0.004 Anaemia (Hb <10 g/dL) 28/120 (23.3) 24/280 (8.6) 3.25 (1.79–5.89) <0.001 Albumin <3.5 g/dL 20/70 (28.6) 32/330 (9.7) 3.73 (1.98–7.02) <0.001 Tobacco use 17/88 (19.3) 35/312 (11.2) 1.89 (1.00–3.58) 0.046 ASA grade ≥III 21/74 (28.4) 31/326 (9.5) 3.77 (2.02–7.05) <0.001 Emergency surgery 38/168 (22.6) 14/232 (6.0) 4.55 (2.38–8.72) <0.001 Operation time >2 h 31/110 (28.2) 21/290 (7.2) 5.03 (2.74–9.23) <0.001 Preoperative stay >3 days 25/96 (26.0) 27/304 (8.9) 3.61 (1.98–6.60) <0.001 Drain in situ 24/120 (20.0) 28/280 (10.0) 2.25 (1.24–4.07) 0.006 Inappropriate prophylaxis 30/132 (22.7) 22/268 (8.2) 3.29 (1.81–5.97) <0.001 Contaminated / dirty wound 28/134 (20.9) 24/266 (9.0) 2.66 (1.47–4.81) 0.001 OR = odds ratio; CI = confidence interval; chi-square test. 3.8 Obstetric risk factors in caesarean section Among the 102 women who underwent LSCS, 9 (8.8%) developed SSI. The rate was 11.3% after emergency and 5.0% after elective caesarean section (p = 0.48). Prolonged rupture of membranes (>18 hours) was significantly associated with SSI (20.0% vs 4.2%; OR 5.75, p = 0.018), while five or more vaginal examinations showed a similar trend that did not reach significance (16.7% vs 4.5%; OR 4.20, p = 0.064) (Table 10). Table 10: Obstetric risk factors for SSI after caesarean section (n = 102) Factor SSI in exposed n/N (%) SSI in unexposed n/N (%) Crude OR (95% CI) p value Emergency vs elective LSCS 7/62 (11.3) 2/40 (5.0) 2.42 (0.48–12.28) 0.48 Rupture of membranes >18 h 6/30 (20.0) 3/72 (4.2) 5.75 (1.33–24.80) 0.018 ≥5 vaginal examinations 6/36 (16.7) 3/66 (4.5) 4.20 (0.98–17.95) 0.064 Fisher’s exact test. 3.9 Multivariate analysis On multivariate logistic regression (Table 11), seven factors emerged as independent predictors of SSI: operation time >2 hours, emergency surgery, diabetes mellitus, hypoalbuminaemia, inappropriate antibiotic prophylaxis, ASA grade ≥III and contaminated/dirty wound class. Age, obesity, anaemia, tobacco use, drain use and prolonged preoperative stay lost significance after adjustment. The model showed good fit (Hosmer–Lemeshow p = 0.62; Nagelkerke R² = 0.41). Table 11: Independent predictors of SSI – multivariate logistic regression Variable Adjusted OR (95% CI) p value Operation time >2 hours 3.1 (1.5–6.4) 0.002 Emergency surgery 2.9 (1.4–6.1) 0.005 Diabetes mellitus 2.7 (1.2–6.0) 0.015 Hypoalbuminaemia (<3.5 g/dL) 2.4 (1.1–5.2) 0.027 Inappropriate antibiotic prophylaxis 2.3 (1.1–4.7) 0.024 ASA grade ≥III 2.2 (1.0–4.7) 0.045 Contaminated / dirty wound class 2.1 (1.0–4.4) 0.048 Preoperative stay >3 days 2.0 (0.9–4.2) 0.080 Anaemia (Hb <10 g/dL) 1.7 (0.8–3.5) 0.150 Hosmer–Lemeshow p = 0.62. The last two variables were retained in the model but were not significant. 3.10 Outcome and burden of SSI Patients with SSI had a significantly longer postoperative hospital stay (14.8 ± 5.9 vs 6.4 ± 2.8 days; mean excess 8.4 days, p <0.001). Re-intervention in the form of secondary suturing, debridement or re-exploration was required in 36.5% of SSI patients, and 13.5% needed readmission. Mortality was 3.8% in the SSI group and 1.4% in the non-SSI group, which was not statistically significant owing to small numbers (Table 12). Table 12: Outcome in patients with and without SSI Outcome SSI (n = 52) No SSI (n = 348) p value Postoperative hospital stay (days, mean ± SD) 14.8 ± 5.9 6.4 ± 2.8 <0.001 Re-intervention (suturing / debridement / re-exploration) 19 (36.5) 9 (2.6) <0.001 Readmission within 30 days 7 (13.5) 12 (3.4) 0.006 Mortality 2 (3.8) 5 (1.4) 0.23 t test for continuous variable; Fisher’s exact test for categorical variables

Postoperative wound infection continues to impose a substantial burden in tertiary teaching hospitals. The overall SSI incidence of 13.0% in the present study is higher than that reported from high-income settings, but is comparable with the pooled estimates for low- and middle-income countries and falls within the broad range reported from Indian institutions. This variation reflects differences in case mix (the proportion of emergency and contaminated surgery), the intensity of post-discharge surveillance and the diagnostic criteria applied. Our rate is also likely to be higher than in studies restricted to clean and clean-contaminated surgery because a tertiary referral hospital receives a large share of delayed, emergency and contaminated cases. Studies from other developing countries have similarly reported double-digit infection rates in general surgical practice[38–40]. The SSI rate was somewhat higher in General Surgery (14.4%) than in Obstetrics & Gynaecology (10.7%), although the difference was not significant. General surgical patients were older, had more comorbidity, and underwent more bowel and emergency surgery, which entails exposure to endogenous enteric flora. In the obstetric group, the infection rate after caesarean section (8.8%) falls within the range of 3–15% commonly reported in the studies, with considerable variation depending on whether post-discharge surveillance is performed. Hysterectomy carried an infection rate of 14.7% (5 of 34), higher than in some Western series, which may reflect differences in preoperative vaginal and skin preparation, the proportion of abdominal compared with vaginal routes, and background anaemia and nutritional status among Indian women. The stepwise increase in infection from 4.2% in clean wounds to 27.8% in dirty wounds replicates the original observations of Cruse and Foord and the later NNIS analyses. Indian studies likewise show a clear gradient across wound classes, with contaminated and dirty wounds carrying several times the risk of clean wounds. The highest rates in our series followed emergency laparotomy and bowel surgery, in which spillage of enteric content, haemodynamic compromise, delayed presentation and suboptimal preoperative optimisation coexist. The finding that elective caesarean section had a lower infection rate than emergency caesarean section, although not statistically significant in our sample, is in line with large obstetric cohorts and reflects the effect of labour, ruptured membranes and intrapartum manipulation[41]. Superficial incisional infection accounted for two-thirds of cases, in agreement with most published series, and purulent discharge, pain, erythema and induration formed the usual clinical picture. The median onset was around the 7th postoperative day, which is typical of bacterial wound infection and matches the CDC description of the 30-day surveillance window. A key finding was that almost one-third of infections were diagnosed after discharge. With the current trend towards early discharge, especially after caesarean section and laparoscopic procedures, hospital-based surveillance alone grossly under-estimates the true incidence, and organised post-discharge follow-up is essential. Gram-negative bacilli constituted two-thirds of isolates, led by E. coli, while S. aureus was the commonest Gram-positive organism. This pattern, with S. aureus and E. coli as the principal pathogens and a rising share of Klebsiella and Pseudomonas, has been reported repeatedly from Indian tertiary care hospitals and also from African series. The predominance of enteric Gram-negatives in our study is explained by the large proportion of abdominal, colorectal and pelvic operations. Of greater concern was the extent of antibiotic resistance. More than 40% of S. aureus were methicillin resistant and two-thirds of the Enterobacterales were ESBL producers, with susceptibility to ceftriaxone and ciprofloxacin as low as 30–40%. Carbapenems, colistin, vancomycin and linezolid retained excellent activity, but these should be reserved for confirmed multidrug-resistant infection. The high prevalence of resistant organisms underscores the need for hospital antibiograms, an antimicrobial stewardship programme and strict infection-control practice, consistent with the national recommendations and the National Action Plan on Antimicrobial Resistance. The resistance data also highlight that empirical postoperative antibiotics selected without reference to local susceptibility patterns are likely to fail in a considerable proportion of patients. Culture-negative cases (15.4%) were largely patients who had already received antibiotics, which emphasises the value of sampling before antibiotic therapy. An operation lasting more than two hours was the strongest independent predictor in our model. Longer operations increase exposure of the wound to contamination, cause greater tissue damage and desiccation and may reduce the effective concentration of prophylactic antibiotic; systematic review evidence confirms a consistent, graded rise in SSI risk with operating time[42]. The NNIS risk index also incorporates operative duration above the 75th percentile as one of its three components. Emergency surgery carried nearly threefold adjusted odds of SSI, and the contaminated/dirty class had twofold odds. Emergency patients are less optimised, may be dehydrated, septic or anaemic, and are operated on by tired teams, often with poorly planned prophylaxis. These findings agree with several Indian studies and with African data. Diabetes was associated with a nearly threefold adjusted risk. Hyperglycaemia impairs neutrophil function, chemotaxis and collagen synthesis, and a meta-analysis has confirmed that diabetes is a significant independent risk factor across surgical specialties[43]. Hypoalbuminaemia, a marker of poor nutritional status and chronic illness, also remained significant, in keeping with the classic observation that low serum albumin predicts postoperative morbidity[44]. Given the high prevalence of undernutrition and anaemia among Indian patients, preoperative nutritional optimisation is an important opportunity. Obesity was associated with SSI on univariate analysis, in line with studies correlating adiposity with wound infection[45], but its effect was explained by other factors in the adjusted model. The univariate association of tobacco use is consistent with its effects on tissue oxygenation and wound healing[46]. Infection rates climbed with age, with the rate in those over 60 being over four times that in the youngest group, in keeping with the effects of senescence, comorbidity and reduced physiological reserve on outcome[47]. After adjustment for ASA grade, age itself was not significant, suggesting that physiological status rather than chronological age is the main determinant; ASA grade ≥III doubled the odds of infection, in line with its inclusion in the NNIS index. Inappropriate prophylaxis, that is, wrong timing, a wrong agent or prolonged postoperative continuation, emerged as one of the most important modifiable risk factors. Almost one-third of our patients did not receive prophylaxis within the recommended window, a finding that has also been documented in surveys of surgical practice in India. Prophylactic antibiotics given before skin incision significantly reduce the risk of post-caesarean infection[48] and the correct agent and timing are specified in international guidelines. The choice of agent also matters in gynaecological surgery. In women undergoing caesarean section, prolonged rupture of membranes was significantly associated with SSI, and repeated vaginal examinations tended in the same direction. Labour, membrane rupture and ascending flora are accepted risk factors for post-caesarean infection and endometritis. Our sub-group was small, so the confidence intervals are wide and these findings should be interpreted with caution. Patients with SSI stayed 8.4 days longer on average, needed re-intervention in more than a third of cases and were readmitted four times as often. These observations resemble the extra stay of about a week and the substantial extra costs described in earlier work. In a public-sector teaching hospital the additional bed-days also reduce capacity for other patients, and for the patient the indirect costs of lost wages and prolonged care are considerable. Although the difference in mortality was not significant, the trend towards higher death in the SSI group is consistent with data from larger surveillance studies. Strengths and limitations The strengths of this study are its prospective design, standard CDC/NHSN definitions, structured 30-day follow-up including post-discharge surveillance, and the inclusion of both general surgical and obstetric/gynaecological patients with microbiological correlation. Its limitations include the single-centre setting, a modest sample size that limits the power of sub-group analyses (particularly the obstetric analysis), the use of disc-diffusion testing without molecular characterisation of resistance mechanisms, the exclusion of anaerobic culture, and the possibility of under-detection of mild infections in patients who were lost to telephone follow-up. A larger multicentre study with molecular typing and cost analysis would provide stronger evidence.

Postoperative wound infection affected about one in eight patients in this tertiary care teaching hospital, with a heavy burden of Gram-negative and multidrug-resistant organisms and a significant effect on length of stay, re-intervention and readmission. Longer operative time, emergency surgery, diabetes mellitus, hypoalbuminaemia, ASA grade ≥III, contaminated or dirty wounds and inappropriate antibiotic prophylaxis were independent predictors of SSI, and in obstetric patients prolonged rupture of membranes was an additional risk factor. As many of these factors are modifiable, a structured preventive bundle, optimisation of patients before surgery, correct timing of antibiotic prophylaxis, reduction of operative time, local antibiogram-guided therapy and systematic post-discharge surveillance should be implemented in both General Surgery and Obstetrics & Gynaecology to reduce the burden of SSI.

1. Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control. 2008;36(5):309-32. 2. Mangram AJ, Horan TC, Pearson ML, Silver LC, Jarvis WR. Guideline for prevention of surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee. Infect Control Hosp Epidemiol. 1999;20(4):250-78. 3. Allegranzi B, Bagheri Nejad S, Combescure C, Graafmans W, Attar H, Donaldson L, et al. Burden of endemic health-care-associated infection in developing countries: systematic review and meta-analysis. Lancet. 2011;377(9761):228-41. 4. World Health Organization. Global guidelines for the prevention of surgical site infection. Geneva: World Health Organization; 2016. 5. Allegranzi B, Bischoff P, de Jonge S, Kubilay NZ, Zayed B, Gomes SM, et al. New WHO recommendations on preoperative measures for surgical site infection prevention: an evidence-based global perspective. Lancet Infect Dis. 2016;16(12):e276-87. 6. Allegranzi B, Zayed B, Bischoff P, Kubilay NZ, de Jonge S, de Vries F, et al. New WHO recommendations on intraoperative and postoperative measures for surgical site infection prevention: an evidence-based global perspective. Lancet Infect Dis. 2016;16(12):e288-303. 7. Berríos-Torres SI, Umscheid CA, Bratzler DW, Leas B, Stone EC, Kelz RR, et al. Centers for Disease Control and Prevention guideline for the prevention of surgical site infection, 2017. JAMA Surg. 2017;152(8):784-91. 8. Kirkland KB, Briggs JP, Trivette SL, Wilkinson WE, Sexton DJ. The impact of surgical-site infections in the 1990s: attributable mortality, excess length of hospitalization, and extra costs. Infect Control Hosp Epidemiol. 1999;20(11):725-30. 9. Plowman R, Graves N, Griffin MA, Roberts JA, Swan AV, Cookson B, et al. The rate and cost of hospital-acquired infections occurring in patients admitted to selected specialties of a district general hospital in England and the national burden imposed. J Hosp Infect. 2001;47(3):198-209. 10. Cruse PJ, Foord R. The epidemiology of wound infection: a 10-year prospective study of 62,939 wounds. Surg Clin North Am. 1980;60(1):27-40. 11. Haley RW, Culver DH, Morgan WM, White JW, Emori TG, Hooton TM. Identifying patients at high risk of surgical wound infection: a simple multivariate index of patient susceptibility and wound contamination. Am J Epidemiol. 1985;121(2):206-15. 12. Culver DH, Horan TC, Gaynes RP, Martone WJ, Jarvis WR, Emori TG, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index. National Nosocomial Infections Surveillance System. Am J Med. 1991;91(3B):152S-7S. 13. Anvikar AR, Deshmukh AB, Karyakarte RP, Damle AS, Patwardhan NS, Malik AK, et al. A one-year prospective study of 3280 surgical wounds. Indian J Med Microbiol. 1999;17(3):129-32. 14. Lilani SP, Jangale N, Chowdhary A, Daver GB. Surgical site infection in clean and clean-contaminated cases. Indian J Med Microbiol. 2005;23(4):249-52. 15. Mahesh CB, Shivakumar S, Suresh BS, Chidanand SP, Vishwanath Y. A prospective study of surgical site infections in a teaching hospital. J Clin Diagn Res. 2010;4(5):3114-9. 16. Kamat US, Fereirra AM, Kulkarni MS, Motghare DD. A prospective study of surgical site infections in a teaching hospital in Goa. Indian J Surg. 2008;70(3):120-4. 17. Suchitra JB, Lakshmidevi N. Surgical site infections: assessing risk factors, outcomes and antimicrobial sensitivity patterns. Afr J Microbiol Res. 2009;3(4):175-9. 18. Patel SM, Patel MH, Patel SD, Soni ST, Kinariwala DM, Vegad MM. Surgical site infections: incidence and risk factors in a tertiary care hospital, Western India. Natl J Community Med. 2012;3(2):193-6. 19. Mundhada AS, Tenpe S. A study of organisms causing surgical site infections and their antimicrobial susceptibility in a tertiary care government hospital. Indian J Pathol Microbiol. 2015;58(2):195-200. 20. Rao R, Sumathi S, Anuradha K, Venkatesh D, Krishna S. Bacteriology of postoperative wound infections. Int J Pharm Biomed Res. 2013;4(2):72-6. 21. Indian Council of Medical Research. Treatment guidelines for antimicrobial use in common syndromes. New Delhi: Indian Council of Medical Research, Department of Health Research, Government of India; 2017. 22. National Centre for Disease Control, Directorate General of Health Services, Ministry of Health and Family Welfare, Government of India. National treatment guidelines for antimicrobial use in infectious diseases. New Delhi: NCDC; 2016. 23. Ministry of Health and Family Welfare, Government of India. National action plan on antimicrobial resistance (NAP-AMR) 2017-2021. New Delhi: MoHFW; 2017. 24. Mehta A, Rosenthal VD, Mehta Y, Chakravarthy M, Todi SK, Sen N, et al. Device-associated nosocomial infection rates in intensive care units of seven Indian cities. Findings of the International Nosocomial Infection Control Consortium (INICC). J Hosp Infect. 2007;67(2):168-74. 25. Rosenthal VD, Maki DG, Mehta Y, Leblebicioglu H, Memish ZA, Al-Mousa HH, et al. International Nosocomial Infection Control Consortium (INICC) report, data summary of 43 countries for 2007-2012. Am J Infect Control. 2014;42(9):942-56. 26. International Institute for Population Sciences (IIPS) and ICF. National Family Health Survey (NFHS-5), 2019-21: India. Mumbai: IIPS; 2021. 27. Johnson A, Young D, Reilly J. Caesarean section surgical site infection surveillance. J Hosp Infect. 2006;64(1):30-5. 28. Olsen MA, Butler AM, Willers DM, Devkota P, Gross GA, Fraser VJ. Risk factors for surgical site infection after low transverse cesarean section. Infect Control Hosp Epidemiol. 2008;29(6):477-84. 29. Mitt P, Lang K, Peri A, Maimets M. Surgical-site infections following cesarean section in an Estonian university hospital: postdischarge surveillance and analysis of risk factors. Infect Control Hosp Epidemiol. 2005;26(5):449-54. 30. Kawakita T, Landy HJ. Surgical site infections after cesarean delivery: epidemiology, prevention and treatment. Matern Health Neonatol Perinatol. 2017;3:12. 31. Lake AG, McPencow AM, Dick-Biascoechea MA, Martin DK, Erekson EA. Surgical site infection after hysterectomy. Am J Obstet Gynecol. 2013;209(5):490.e1-9. 32. Uppal S, Harris J, Al-Niaimi A, Swenson C, Jin C, Lyons T, et al. Prophylactic antibiotic choice and risk of surgical site infection after hysterectomy. Obstet Gynecol. 2016;127(2):321-9. 33. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-7. 34. Owens WD, Felts JA, Spitznagel EL Jr. ASA physical status classifications: a study of consistency of ratings. Anesthesiology. 1978;49(4):239-43. 35. Bratzler DW, Dellinger EP, Olsen KM, Perl TM, Auwaerter PG, Bolon MK, et al. Clinical practice guidelines for antimicrobial prophylaxis in surgery. Am J Health Syst Pharm. 2013;70(3):195-283. 36. Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing. 32nd ed. CLSI supplement M100. Wayne, PA: CLSI; 2022. 37. Magiorakos AP, Srinivasan A, Carey RB, Carmeli Y, Falagas ME, Giske CG, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268-81. 38. Sangrasi AK, Leghari AA, Memon A, Talpur KA, Laghari AA, Qureshi GA. Surgical site infection rate and associated risk factors in elective general surgery at a public sector medical university in Pakistan. Int Wound J. 2008;5(1):74-8. 39. Mawalla B, Mshana SE, Chalya PL, Imirzalioglu C, Mahalu W. Predictors of surgical site infections among patients undergoing major surgery at Bugando Medical Centre in Northwestern Tanzania. BMC Surg. 2011;11:21. 40. Mulu W, Kibru G, Beyene G, Damtie M. Postoperative nosocomial infections and antimicrobial resistance pattern of bacteria isolates among patients admitted at Felege Hiwot Referral Hospital, Bahirdar, Ethiopia. Ethiop J Health Sci. 2012;22(1):7-18. 41. Conroy K, Koenig AF, Yu YH, Courtney A, Lee HJ, Norwitz ER. Infectious morbidity after cesarean delivery: 10 strategies to reduce risk. Rev Obstet Gynecol. 2012;5(2):69-77. 42. Cheng H, Chen BP, Soleas IM, Ferko NC, Cameron CG, Hinoul P. Prolonged operative duration increases risk of surgical site infections: a systematic review. Surg Infect (Larchmt). 2017;18(6):722-35. 43. Martin ET, Kaye KS, Knott C, Nguyen H, Santarossa M, Evans R, et al. Diabetes and risk of surgical site infection: a systematic review and meta-analysis. Infect Control Hosp Epidemiol. 2016;37(1):88-99. 44. Gibbs J, Cull W, Henderson W, Daley J, Hur K, Khuri SF. Preoperative serum albumin level as a predictor of operative mortality and morbidity: results from the National VA Surgical Risk Study. Arch Surg. 1999;134(1):36-42. 45. Waisbren E, Rosen H, Bader AM, Lipsitz SR, Rogers SO Jr, Eriksson E. Percent body fat and prediction of surgical site infection. J Am Coll Surg. 2010;210(4):381-9. 46. Sørensen LT. Wound healing and infection in surgery: the clinical impact of smoking and smoking cessation: a systematic review and meta-analysis. Arch Surg. 2012;147(4):373-83. 47. Kaye KS, Schmader KE, Sloane R. The effect of surgical site infection on older operative patients. J Am Geriatr Soc. 2009;57(1):46-54. 48. Smaill FM, Grivell RM. Antibiotic prophylaxis versus no prophylaxis for preventing infection after cesarean section. Cochrane Database Syst Rev. 2014;(10):CD007482. 49. Darouiche RO, Wall MJ Jr, Itani KM, Otterson MF, Webb AL, Carrick MM, et al. Chlorhexidine-alcohol versus povidone-iodine for surgical-site antisepsis. N Engl J Med. 2010;362(1):18-26.