Next Article in Journal
Dissemination of OXA-48- and NDM-1-Producing Enterobacterales Isolates in an Algerian Hospital
Next Article in Special Issue
Self-Medication with Antibiotics: Prevalence, Practices and Related Factors among the Pakistani Public
Previous Article in Journal
Decreased Antibiotic Consumption Coincided with Reduction in Bacteremia Caused by Bacterial Species with Respiratory Transmission Potential during the COVID-19 Pandemic
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Antibiotics
Volume 11
Issue 6
10.3390/antibiotics11060748
antibiotics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Antibiotic Use, Incidence and Risk Factors for Orthopedic Surgical Site Infections in a Teaching Hospital in Madhya Pradesh, India

by
Kristina Skender
1,*,
Anna Machowska
1,
Vivek Singh
2,†,
Varun Goel
2,†,
Yogyata Marothi
3,
Cecilia Stålsby Lundborg
1 and
Megha Sharma
1,4
1
Department of Global Public Health, Health Systems and Policy, Karolinska Institutet, 17177 Stockholm, Sweden
2
Department of Orthopedics, Ruxmaniben Deepchand Gardi Medical College, Surasa, Ujjain 456006, India
3
Department of Microbiology, Ruxmaniben Deepchand Gardi Medical College, Surasa, Ujjain 456006, India
4
Department of Pharmacology, Ruxmaniben Deepchand Gardi Medical College, Surasa, Ujjain 456006, India
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Antibiotics 2022, 11(6), 748; https://doi.org/10.3390/antibiotics11060748
Submission received: 16 May 2022 / Revised: 29 May 2022 / Accepted: 30 May 2022 / Published: 31 May 2022
(This article belongs to the Special Issue Drugs for Superbugs: Antibiotic Discovery, Modes of Action and Mechanisms of Resistance)
Browse Figure
Review Reports Versions Notes

Abstract

:
Orthopedic surgeries contribute to the overall surgical site infection (SSI) events worldwide. In India, SSI rates vary considerably (1.6–38%); however, there is a lack of a national SSI surveillance system. This study aims to identify the SSI incidence, risk factors, antibiotic prescription and susceptibility patterns among operated orthopedic patients in a teaching hospital in India. Data for 1205 patients were collected from 2013 to 2016. SSIs were identified based on the European Centre for Disease Prevention and Control guidelines. The American Society for Anesthesiologists classification system was used to predict patients’ operative risk. Univariable and multivariable backward stepwise logistic regressions were performed. Overall, 7.6% of patients developed SSIs over three years. The most common SSIs causative microorganism was Staphylococcus aureus (7%), whose strains were resistant to penicillin (100%), erythromycin (80%), cotrimoxazole (80%), amikacin (60%) and cefoxitin (60%). Amikacin was the most prescribed antibiotic (36%). Male sex (OR 2.64; 95%CI 1.32–5.30), previous hospitalization (OR 2.15; 95%CI 1.25–3.69), antibiotic prescription during hospitalization before perioperative antibiotic prophylaxis (OR 4.19; 95%CI 2.51–7.00) and postoperative length of stay > 15 days (OR 3.30; 95%CI 1.83–5.95) were identified as significant risk factors. Additionally, preoperative shower significantly increased the SSI risk (OR 4.73; 95%CI 2.72–8.22), which is unconfirmed in the literature so far.

1. Introduction

Healthcare-associated infections (HAIs) are infections that are not present or incubating at the time of hospital admission but are acquired during a healthcare facility visit or stay [1]. HAIs contribute to adverse patient outcomes, including prolonged hospitalization, morbidity and mortality, as well as increased treatment costs posing a high financial burden at the individual and health care system level [2,3,4].
Surgical site infections (SSIs) are among the most frequently reported HAIs and may develop post-surgery due to contaminated instruments or environmental conditions of the healthcare facility [5]. In 2017, the European Centre for Disease Prevention and Control (ECDC) reported that SSIs percentage ranged from 0.5% to 10.1% across 13 European countries and varied greatly by the type of surgical procedure and between the countries [5]. In low- and middle-income countries (LMICs), the incidence rate of SSIs was much greater compared to high-income settings [2]. In India, considerable variations in SSIs rates have been reported from different geographical locations within the country and ranged from 1.6% to 38% [6,7,8].
Staphylococcus aureus has become the most common cause of SSIs in recent years, as reported by ECDC [5]. S. aureus usually originates in patients’ bacterial flora [9] and is responsible for 15–20 % of overall SSIs in hospitals [10,11]. Furthermore, S. aureus is the most common causative pathogen of orthopedic implant-associated infections, which can be particularly difficult to treat due to high levels of antibiotic resistance and limited treatment options [12].
Orthopedic surgeries contribute to the overall SSI events in hospitals across the world and remain a challenge for patients and surgeons, requiring the integration of a range of measures before, during and after surgery [13,14,15,16,17]. One of the recommended measures for the prevention of SSIs is a single administration of systemic antibiotics shortly before a surgery, i.e., perioperative antibiotic prophylaxis (PAP) [18,19]. It is estimated that 30–50% of all antimicrobial prescriptions in hospitals are PAP [10].
There are several risk factors associated with SSIs in orthopedic surgery confirmed in the literature, such as male sex, age and length of surgery [20]. According to the US National Healthcare Safety Network (NHSN), the risk index is used to assign surgical patients to one of four categories, from low to high. It is based on the presence of three major risk factors: (1) duration of the operation; (2) wound contamination class; and (3) the American Society of Anesthesiologists (ASA) physical status classification [16,21].
Knowledge of the magnitude of HAIs and SSIs is essential to reducing HAI rates and improving the effectiveness of infection prevention and control measures [22]. Furthermore, in LMICs, the follow-up of surgical patients after discharge is generally neglected and thereby contributes to underestimated SSI rates [4]. Therefore, active and targeted SSI surveillance is recommended [23]. The main goal of surveillance is to provide comprehensive evidence, expert consensus and recommendations, which are to be applied during pre-, intra- and post-operative periods to prevent and reduce the risk of SSIs—one of the objectives of the World Health Organization (WHO) global guidelines for the prevention of SSIs (2016) [24].
In India, there is a lack of a national surveillance system and guidelines on antibiotic use for common infections. Thus, there is a need to conduct recurrent SSIs surveillance at a facility level in order to understand the current situation and develop appropriate recommendations [24]. Active surveillance, audits and feedback have shown an association with the reduction in SSI rates [25]. In order to minimize the incidence rates of orthopedic SSIs, risk factors should be identified at the hospital and community level [26]. The present study aims to assess the incidence and risk factors for SSIs, as well as the profile of common causative SSI pathogens and their antibiotic susceptibility, and to analyze antibiotic use among the operated orthopedic patients in a private, tertiary care hospital in Ujjain city in central India.

2. Materials and Methods

2.1. Study Setting

The study was conducted at the department of orthopedic surgery in a teaching hospital, located in a rural area of Ujjain city in Madhya Pradesh district in central India. The teaching hospital is a private, tertiary care hospital attached to a medical college run by a non-profit charitable trust. The hospital provides free-of-charge medical services to the community and has a capacity of 750 beds, with 90 beds at the orthopedic department at the time of the study.

2.2. Data Collection

Data were collected from August 2013 to April 2016 by trained hospital personnel. Due to the lack of electronic surveillance system in place, data collection was performed using locally developed and validated paper forms. Forms contained information about demographic characteristics of the study population, patient history, provisional and clinical diagnoses, type of performed procedures, surgery outcomes, summary of the laboratory reports of the samples sent for antibiotic susceptibility testing and information of the potential risk factors for SSIs. Information about pre- and post-surgery antibiotic prescriptions was collected using a separate form adopted from previous studies conducted in the same setting [26,27]. Trained data collectors accompanied the orthopedic consultants who clinically identified the SSIs. Respective samples of the identified SSI patients were sent for antibiotic susceptibility testing and laboratory test reports were recorded in the forms. Patients were followed up until discharge with regular updates about antibiotic prescriptions. Data were entered into an Excel file by the trained data entry persons.

2.3. Inclusion and Exclusion Criteria

All patients admitted to the orthopedic ward who stayed at least one night were divided into operated and non-operated. In total, 1205 patients were operated and included in the analysis (Figure 1). Out of those, 1004 were operated during the present admission, and 201 were operated during the previous admission, which took place no more than 30 days before the present admission. Of all previously operated patients, 124 were also operated during the present admission tenure. Twenty-nine patients were admitted with a sign of infection and were, therefore, categorized under community-acquired infection and were not included in the SSI group. Operated patients were characterized based on the occurrence of SSIs and antibiotic use (Figure 1).

2.4. Data Management and Analysis

SSI occurrence was defined by the Centers for Disease Control and Prevention (CDC) NHSN definition with 30- or 90-day SSI surveillance period, which is determined by the NHSN operative procedure category and the tissue level of an SSI event [21]. SSI surveillance period was one year for patients with implants [28]. SSIs were classified according to NHSN into 3 categories: (i) superficial incisional, (ii) deep incisional, and (iii) organ/ space SSI [21]. Superficial incisional and deep incisional SSIs were further divided into primary and secondary. A primary superficial incision is identified in a patient that has had surgery with one or more incisions. A secondary superficial incision occurs in the secondary incision in a patient that has had an operation with more than one incision. Organ/space SSI is infection that involves any part of the body deeper than the fascial/muscle layers, that is opened or manipulated during the operative procedure [21].The ASA physical status classification system was used to assess the patient’s physiological status to predict the operative risk. According to the ASA classification: ASA I—normal healthy patient (no acute or chronic disease, non-smoker, no or minimal alcohol use); ASA II—patient with mild systemic disease; ASA III—patient with severe systemic disease; ASA IV—patient with a severe systemic disease, which is a constant threat to life.
Standard methods were followed to process the samples sent for culture and susceptibility tests [29]. The inoculated blood agar and McConkey agar plates were incubated at 37 °C for 18–24 hours. Microorganisms were identified by using standard laboratory techniques and the Clinical and Laboratory Standard Institute (CLSI) guidelines [29,30]. The types and number of colony-forming units (CFUs) of identified microorganisms were noted, and percentages of reduction in CFUs and Log10 were calculated for each sample.
The prescribed antibiotics were classified according to the WHO Anatomical Therapeutic Chemical (ATC) classification system [31]. In the study hospital, local prescribing guidelines were not present at the time of the study and consequently, high antibiotic prescribing rates were reported [27].
All information, except prescriptions, was entered into Epidata entry (version 3.1; Epidata software, Odense, Denmark), and the antibiotic prescriptions were entered in Excel. Data were analyzed using Stata 15.1 (Stata Corp., College Station, TX, USA). Continuous variables were presented as median and 25th–75th percentile, and categorical variables were presented as frequencies and percentages. Univariable logistic regression was performed to identify risk factors for SSIs. Statistically significant risk factors (p-value < 0.05) were included in multivariable backward stepwise logistic regression analysis. Pearson’s correlation coefficients were calculated for statistically significant risk factors from univariable analysis, and the coefficients that showed high correlation (≥0.5) were excluded from the multivariable analysis in order to avoid multicollinearity and increase the reliability of regression coefficients. Independent variables included in Model 1 were: male sex, ASA II and III scores, previous hospitalization, antibiotic(s) prescribed 14 days before hospital admission, perioperative antibiotic prophylaxis (PAP), antibiotic treatment during hospital stay before PAP, duration of postoperative antibiotic treatment >14 days, postoperative length of stay (LOS) > 15 days, preoperative shower, compound fracture, drain, implant. Akaike information criteria (AIC) and Bayesian information criteria (BIC) were calculated to compare the models and choose the best model.

3. Results

Overall, 91/1205 (7.6%) of operated patients developed SSI over three years. SSI incidence rates per year were: 15.5% (August–December 2013), 6.25% (2014), 6.45% (2015), 3.65% (January–April 2016). Significant differences were observed in distribution of potential risk factors between males and females (Supplementary Materials).
Patient-related potential SSI risk factors are presented in Table 1. Median age of all 1205 operated patients was 35 years, and the majority (70%) were male. The physiological status of the majority of SSI patients was calculated as ASA I score (69%), followed by ASA II (24%) and ASA III (7%). A total of 14% of operated patients were previously hospitalized, and 6% were prescribed antibiotic(s) within 14 days before the current admission (Table 1).
Surgery-related potential SSI risk factors are presented in Table 2. The majority of patients who developed SSI (64/91) had closed wounds. For most operated patients (35%), surgery lasted up to one hour. In total, 84% (76/91) of SSI patients had their hair removed by shaving, while 46% (16/91) had a preoperative shower. The median length of preoperative hospital stay did not significantly vary between SSI and non-SSI patients (4 vs. 5 days), whereas the median length of postoperative hospital stay was significantly longer in SSI compared to non-SSI patients (13 vs. 8 days, p < 0.001). Drains were used in 41 operated patients, out of which 8 developed SSI. Implants were used in 297 patients, out of which 49 patients developed SSI. A total of 94% operated patients (males—70%; females—30%) were prescribed antibiotics, and all SSI patients were prescribed antibiotics during their hospital stay. PAP was prescribed to 70% of all operated patients and to 46% of patients who developed SSI. Antibiotic(s) before PAP during hospital stay were prescribed to 21% of operated patients (258/1205); out of those, 43 patients developed SSI. A total of 86% of patients were prescribed a postoperative antibiotic, which was given longer than 14 days in 40% (36/91) of SSI patients (Table 2, Supplementary Materials).
Among 91 of operated patients who developed SSIs, 11 (12%) had superficial incisional primary, 2 (2%) superficial incisional secondary, 19 (21%) deep incisional primary, 3 (3%) deep incisional secondary and 53 (58%) organ/space SSI. Table 3 shows that 68 pus or wound samples were sent for culture and susceptibility testing, out of which 15 were culture positive. Two samples showed a mix of two microbial growth of S. aureus with Escherichia coli and Klebsiella spp. The most common microorganism that caused SSIs was S. aureus (5/68, 7%), followed by Gram-negative organisms: Klebsiella spp. (4/68, 6%), Pseudomonas spp. (4/68, 6%) and E. coli (2/68, 3%). All strains of S. aureus were resistant to penicillin. High resistance was also seen against erythromycin (80%), cotrimoxazole (80%) and amikacin (60%). Three out of five strains of S. aureus were resistant to cefoxitin (methicillin-resistant S. aureus, MRSA). However, Gram-negative organisms showed more than 50% susceptibility to third-generation cephalosporins (Table 3).
A total of 3030 antibiotic prescriptions were prescribed for 1205 operated orthopedic patients, out of which 11% prescriptions were given to the SSI patients and 89% to the non-SSI patients (Table 4). The most commonly prescribed antibiotic was amikacin (J01GB06, 37%), followed by a combination of ceftriaxone with a β-lactamase inhibitor (J01DD63, 24%) and cefoperazone with a β-lactamase inhibitor (J01DD62, 13%) (Table 4). Additionally, the most prescribed PAP was ceftriaxone or cefoperazone in combination with a β-lactamase inhibitor together with intravenous amikacin.
Table 5 presents the results of the univariable logistic regression analysis, which indicate that the following factors were significantly associated with the risk of developing SSIs: male sex (OR = 3.42, 95% CI = 1.79–6.49), ASA II score (OR = 2.63, 95% CI = 1.57–4.43), previous hospitalization (OR = 4.14, 95% CI = 2.57–6.66), history of antibiotic(s) 14 days before admission (OR = 4.71, 95% CI = 2.59–8.58), PAP (OR = 0.34, 95% CI = 0.21–0.53), antibiotic(s) prescribed during hospital stay before PAP (OR = 3.75, 95% CI = 2.42–5.80), duration of postoperative antibiotic treatment beyond 14 days (OR = 4.23, 95% CI = 2.32–7.69), postoperative LOS beyond 15 days (OR = 5.99, 95% CI = 2.59–13.87), preoperative shower (OR = 3.94, 95% CI = 2.49–6.24), compound fracture (OR = 4.87, 95% CI = 2.21–10.76), the presence of drain (OR = 3.21, 95% CI = 1.43–7.20) and implant (OR = 4.07, 95% CI = 2.64–6.29). Based on these risk factors, three multivariable models were built, out of which Model 3 showed the best combination of AIC and BIC. According to Model 3, the following risk factors were found to be significantly associated with SSIs: male sex (OR 2.64; 95%CI 1.32–5.30), previous hospitalization (OR 2.15; 95%CI 1.25–3.69), antibiotic treatment during hospital stay before PAP (OR 4.19; 95%CI 2.51–7.00), postoperative LOS longer than 15 days (OR 3.30; 95%CI 1.83–5.95), preoperative shower (OR 4.73; 95%CI 2.72–8.22).

4. Discussion

In this study, the incidence rate of orthopedic SSIs was 7.6% over three years. Males were 2.64 times more likely to develop SSIs compared to females (95%CI 1.32–5.30). Previously hospitalized patients had 2.15-fold higher odds (95%CI 1.25–3.69) of developing SSIs, whereas patients who received antibiotics during hospital stay before PAP had 4.19-fold higher odds of developing SSIs (95%CI 2.51–7.00). Patients who received antibiotics after surgery longer than 14 days had 4% more chance of developing SSIs (95%CI 1.00–1.09). Patients who stayed in hospital after surgery for longer than 15 days were 3.30 times more likely to develop SSIs (95%CI 1.83–5.95). Patients who showered before the operation had 4.73-fold higher odds of developing SSI (95%CI 2.72–8.22). The most prescribed PAP was third-generation cephalosporin (ceftriaxone—24% or cefoperazone—13%) in combination with β-lactamase inhibitor together with intravenous amikacin (37%). Out of 68 samples sent for culture and susceptibility testing, 22% were culture positive. The most common microorganism that caused SSIs was S. aureus (7%), and 60% of its strains were resistant to cefoxitin (MRSA).
SSI incidence of 7.6% over 3 years is in the range of overall SSI incidences reported in the EU countries (0.5–10.1%) [5]. However, in India, reported SSI rates largely vary from 1.6% to 38% [8]. A study from Madhya Pradesh in 2014 reported a lower SSI rate (2.1%) in orthopedic patients compared to our study [10]. In general, studies show that orthopedic procedures have somewhat lower SSI rates compared to other procedures in both high- and middle-income countries, as reported by studies in New Zealand (1.3%), China (2.18%) and Jordan (2.8%) [13,32,33]. A systematic review from 57 hospitals across the world reported orthopedic SSI rate of 2.7% [11]. The difference in the incidence rates can partially be attributed to higher standards and stricter policies for delivering care in high- and some middle-income countries.
In our study, S. aureus was the most common pathogen causing SSIs, responsible for 33% of the culture-positive samples. Likewise, studies from New Zealand [32] and India [10] reported S. aureus to be the main causative organism of orthopedic SSIs, responsible for 54% and 29% of the culture-positive samples, respectively. However, in a study from China, Coagulase-negative Staphylococcus was the predominant SSIs causative pathogen (42.8%) in orthopedic surgery, followed by S. aureus (11.4%) [13]. Moreover, in our study, 60% of S. aureus samples were MRSA. More than 50 % of S. aureus HAIs in Europe and the US are caused by MRSA, which is becoming increasingly challenging to treat due to antibiotic resistance and limited treatment options [11].
In orthopedic surgery, PAP is considered to be one of the most effective measures to reduce the risk of SSIs [34]. In the US and New Zealand guidelines the most widely recommended PAP for orthopedic procedures is cefazolin [32,35]. In our study, the most used PAP was third-generation cephalosporin (ceftriaxone or cefoperazone in combination with beta-lactamase inhibitor) together with intravenous amikacin. Different choices of PAP might be explained with different prevalent bacteria, susceptibility patterns and operating theatre conditions in Indian setting [34]. No orthopedic prescribing guidelines were in place in the teaching hospital at the time of the study. Given that 20% and 47% of our culture-positive bacterial isolates were resistant to ceftriaxone and amikacin, respectively, appropriate modifications to the usual choice of PAP are suggested to prevent SSIs more efficiently.
In our study, male sex was shown to be significantly associated with SSIs. This is in line with previous research which demonstrated that men, in general, are more likely to develop SSIs than women [36,37]. A German study suggested that male patients undergoing orthopedic and trauma surgeries had significantly higher SSI incidence rates than female patients [38]. This might be explained by men having higher colonization rates of S. aureus, the most prevalent SSI-causative bacteria [38].
Postoperative LOS longer than 15 days and previous hospitalization significantly increased the risk of SSIs. Previous surgery was confirmed as a risk factor by previous research [13], especially in the case of spinal surgery [39]. Postoperative LOS was also identified as a risk factor for orthopedic SSIs by a cohort study from Jordan [33]. Previous hospitalization might also be associated with increased LOS [40]. In our study, the median LOS was significantly higher in SSI patients (13 days) compared to non-SSI patients (8 days). A Swedish study showed that 42% of all adverse events in orthopedic surgery prolong the LOS for an average of 6.1 days [41]. One study from India showed that the maximum median LOS was in surgical oncology patients (31.5 days), followed by orthopedic surgery patients (14 days) [42].
Antibiotic treatment during hospital stay before PAP was significantly associated with the risk of developing SSIs. The patients who needed prolonged preoperative and postoperative antibiotic treatment were mostly the patients with implants or osteomyelitis who had come to the hospital with signs of delayed or late infection (e.g., pus, swelling or abscess) [43]. Prolonged antibiotic treatment contributes to the development of antibiotic resistance [44], which has most likely contributed to the development of SSIs [45].
Preoperative shower was found to significantly increase the risk of orthopedic SSIs. The literature on the benefit of antiseptic preoperative shower is controversial. Some studies list preoperative shower as a protective factor that reduces the incidence of SSIs, which is explained by the reduction in microbial colonization of skin [46,47]. On the other hand, certain studies found no clinically relevant benefit of preoperative chlorhexidine showers [47,48]. Contrary to these findings, the results of our study suggest that preoperative shower is a significant risk factor for SSIs. This might be due to the fact that in the teaching hospital, patients were only advised to take shower or bath before surgery, hence we do not know if patients had actually taken a shower and with what (just water, soap, chlorhexidine). Additionally, the majority of patients (86%) had a closed fracture; therefore, they might not have showered the broken limb properly or at all. Furthermore, the microbiological quality of water that people use for washing in the Ujjain district has been questioned earlier; therefore, a similar study is proposed to check the water quality in the setting [49].
Most SSIs (60%) occur after hospital discharge [50]. The time until SSI onset tends to be among the longest in orthopedic surgeries because of the risk of postponed infection associated with the implants [11]. A systematic review showed that SSIs occur, on average, 33.5 days after orthopedic surgery [11]. In our study, the follow-up was performed either 30 or 90 days after surgery, or after one year for patients with implants. Another study showed that most of operated patients (>75%) did not return to hospital for follow-up after surgery, and calling the unreturned patients was the only choice left [51]. However, follow-up was difficult when patients did not have a direct number to contact and it was not always feasible to send a text message, as most of the patients were from rural India and not educated enough to read the text messages [51]. In our study, special care was taken to avoid lost to follow-up, by noting the residential address and two separate telephone/mobile numbers in the form. Patients who failed to visit the hospital after one month of surgery were followed up by phone. As per hospital policy, free medicines, x-rays and laboratory investigations might have acted as incentives and attracted the patients to come for follow-ups. Despite all the efforts, a chance of underestimation of SSIs cannot be denied, as the postoperative follow-up was only performed in 27% of all the patients. Nevertheless, the presumption of orthopedic staff was that if patients had an infection or postoperative complications, they would have most likely come to the hospital for a follow-up.
This study had a long follow-up time, sufficient to identify patients who developed SSIs, including those with late implant infection. However, a relatively high loss to follow-up might have led to an underestimation of the SSI rate. Additionally, there is a lack of information about how preoperative shower was carried out. A relatively small sample size might have affected the multivariable analysis of potential confounders and risk factors for SSIs. However, based on the formula by Pourhoseingholi et al. [52], the minimum sample size required for the small expected prevalence of outcome <10% (7.55% in this study), the precision of 0.017 and 0.05 alpha level of significance is 928 participants; therefore, the sample size in our study exceeded the minimum number of required participants.
Based on the results of this study, appropriate modification of the current choice of PAP is advised to reduce the incidence of SSIs. Furthermore, a community-based study is recommended to complement this hospital-based study in order to identify more accurately the SSI incidence rate. Additionally, further research is needed to investigate the ways of performing preoperative shower and the reasons behind it being a risk factor, and to check the water quality in the setting.

5. Conclusions

The SSI incidence rate of 7.6% over three years in the present study was relatively low compared to the reported incidence range for India, yet higher than the reported SSI incidences for orthopedic surgical procedures in high- and middle-income countries. The most common SSI-causative pathogen was S. aureus and the most prescribed PAP was third-generation cephalosporin in combination with intravenous amikacin. Factors that significantly increased the risk of orthopedic SSIs were male sex, previous hospitalization, antibiotic treatment during hospital stay before PAP and postoperative LOS longer than 15 days. Preoperative shower was also found to be a significant risk factor for SSIs, which is undocumented in the literature so far, to the best of our knowledge. Further studies are needed to confirm this finding and explore the possible explanations behind it. The identification of SSI incidences and risk factors in orthopedic surgery wards supports overall measures to prevent and mitigate SSIs in hospitals.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/antibiotics11060748/s1, Table S1. Orthopedic SSI incidence rates per year in the teaching hospital, Ujjain, central India. Table S2. Patient-related potential risk factors for orthopedic surgical site infection distributed by sex in the teaching hospital, Ujjain, central India. Table S3. Surgery-related potential risk factors for orthopedic surgical site infections distributed by sex in the teaching hospital, Ujjain, central India.

Author Contributions

Conceptualization, V.S., V.G., C.S.L., M.S.; methodology, M.S., K.S., A.M., C.S.L., V.S., Y.M.; software, K.S.; validation, K.S., M.S., A.M., C.S.L., V.S., Y.M.; formal analysis, K.S., M.S., A.M.; writing—original draft preparation, K.S., A.M., M.S.; writing—review and editing, K.S., M.S., A.M., C.S.L., Y.M.; visualization, K.S.; supervision, M.S.; project administration, M.S.; funding acquisition, C.S.L., M.S. All authors have read and agreed to the published version of the manuscript.

Funding

The project was funded by the Swedish Research Council (Vetenskapsrådet; K2010-396-70X-20514-04-3, 2017-01327, 2018–2021 and 2022–2025) and the Asia link (348-2006-6633). We thank the Erasmus Mundus External Cooperation Window lot 15 for providing a scholarship to M.S. for post-doctoral studies.

Institutional Review Board Statement

The study was approved by the Ethics committee of Ruxmaniben Deepchand Gardi Medical College, Ujjain, with approval letter number 311/2013.

Informed Consent Statement

There was no need for informed consent. Trained nurses recorded data using patient files. There was no direct interaction with patients, nor interference with the treatment procedure. Patient data were analyzed anonymously at a group level.

Data Availability Statement

As per the policy of the institute, the metadata of any research are not shared with the general public. This is to protect the patients’ confidentiality and hospital and hospital staff safety concerning the medical, ethical and legal issues. However, the data can be made available to the researchers who meet the criteria to access the confidential data via the Chairman of the Ethics Committee, R.D. Gardi Medical College, Agar Road, Ujjain, Madhya Pradesh, India, 456006 (email: iecrdgmc@yahoo.in), by giving all details of the article. A request can be made by quoting the ethical approval number: 311/2013.

Acknowledgments

The authors acknowledge the participation and support of all physicians of the orthopedic department at C. R. Gardi Hospital. The cooperation of nursing and lab staff and the patients during the study is also recognized. We extend our thanks to V. K. Mahadik, R. D. Gardi Medical College, Surasa, Ujjain, for the essential administrative support during the study.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Ducel, G.; Fabry, J.; Nicolle, L. (Eds.) Prevention of Hospital-Acquired Infections: A Practical Guide, 2nd ed.; World Health Organization: Geneva, Switzerland, 2002; Available online: https://apps.who.int/iris/handle/10665/67350 (accessed on 12 April 2021).
  2. Allegranzi, B.; Nejad, S.B.; Combescure, C.; Graafmans, W.; Attar, H.; Donaldson, L.; Pittet, D. Burden of endemic health-care-associated infection in developing countries: Systematic review and meta-analysis. Lancet 2011, 377, 228–241. [Google Scholar] [CrossRef]
  3. Badia, J.M.; Casey, A.L.; Petrosillo, N.; Hudson, P.M.; Mitchell, S.A.; Crosby, C. Impact of surgical site infection on healthcare costs and patient outcomes: A systematic review in six European countries. J. Hosp. Infect. 2017, 96, 1–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Monahan, M.; Jowett, S.; Pinkney, T.; Brocklehurst, P.; Morton, D.G.; Abdali, Z.; Roberts, T.E. Surgical site infection and costs in low- and middle-income countries: A systematic review of the economic burden. PLoS ONE 2020, 15, e0232960. [Google Scholar] [CrossRef]
  5. European Centre for Disease Prevention and Control. Healthcare-Associated Infections: Surgical Site Infections. Annual Epidemiological Report for 2017; ECDC: Stockholm, Switzerland, 2019. Available online: https://www.ecdc.europa.eu/sites/default/files/documents/AER_for_2017-SSI.pdf (accessed on 21 May 2021).
  6. Lindsjö, C.; Sharma, M.; Mahadik, V.K.; Sharma, S.; Stålsby Lundborg, C.; Pathak, A. 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, 1184–1189. [Google Scholar] [CrossRef]
  7. Kamat, U.; Ferreira, A.; Savio, R.; Motghare, D. Antimicrobial resistance among nosocomial isolates in a teaching hospital in Goa. Indian J. Community Med. 2008, 33, 89. [Google Scholar] [CrossRef] [PubMed]
  8. Mekhla, F.R.B. Determinants of superficial surgical site infections in abdominal surgeries at a Rural Teaching Hospital in Central India: A prospective study. J. Fam. Med. Prim. Care 2019, 8, 2258. [Google Scholar]
  9. Ma, N.; Cameron, A.; Tivey, D.; Grae, N.; Roberts, S.; Morris, A. Systematic review of a patient care bundle in reducing staphylococcal infections in cardiac and orthopaedic surgery. ANZ J. Surg. 2017, 87, 239–246. [Google Scholar] [CrossRef] [PubMed]
  10. Jain, R.K.; Shukla, R.; Singh, P.; Kumar, R. Epidemiology and risk factors for surgical site infections in patients requiring orthopedic surgery. Eur. J. Orthop. Surg. Traumatol. 2015, 25, 251–254. [Google Scholar] [CrossRef]
  11. Korol, E.; Johnston, K.; Waser, N.; Sifakis, F.; Jafri, H.S.; Lo, M.; Kyaw, M.H. A Systematic Review of Risk Factors Associated with Surgical Site Infections among Surgical Patients. PLoS ONE 2013, 8, e83743. [Google Scholar] [CrossRef] [Green Version]
  12. Li, B.; Webster, T.J. Bacteria antibiotic resistance: New challenges and opportunities for implant-associated orthopedic infections: BACTERIA ANTIBIOTIC RESISTANCE. J. Orthop. Res. 2017, 36, 22–32. Available online: https://onlinelibrary.wiley.com/doi/10.1002/jor.23656 (accessed on 2 May 2022). [CrossRef] [Green Version]
  13. Li, G.Q.; Guo, F.F.; Ou, Y.; Dong, G.W.; Zhou, W. Epidemiology and outcomes of surgical site infections following orthopedic surgery. Am. J. Infect. Control 2013, 41, 1268–1271. [Google Scholar] [CrossRef] [PubMed]
  14. Al-Mulhim, F.A.; Baragbah, M.A.; Sadat-Ali, M.; Alomran, A.S.; Azam, M.Q. Prevalence of Surgical Site Infection in Orthopedic Surgery: A 5-year Analysis. Int. Surg. 2014, 99, 264–268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Rajkumari, N.; Gupta, A.; Mathur, P.; Trikha, V.; Sharma, V.; Farooque, K.; Misra, M.C. Outcomes of surgical site infections in orthopedic trauma surgeries in a tertiary care centre in India. J. Postgrad. Med. 2014, 60, 254. [Google Scholar] [PubMed]
  16. Edwards, J.R.; Peterson, K.D.; Mu, Y.; Banerjee, S.; Allen-Bridson, K.; Morrell, G.; Dudeck, M.A.; Pollock, D.A.; Horan, T.C. National Healthcare Safety Network (NHSN) report: Data summary for 2006 through 2008, issued December 2009. Am. J. Infect. Control 2009, 37, 783–805. [Google Scholar] [CrossRef]
  17. Greene, L.R. Guide to the elimination of orthopedic surgery surgical site infections: An executive summary of the Association for Professionals in Infection Control and Epidemiology elimination guide. Am. J. Infect. Control 2012, 40, 384–386. [Google Scholar] [CrossRef] [PubMed]
  18. Hagel, S.; Scheuerlein, H. Perioperative Antibiotic Prophylaxis and Antimicrobial Therapy of Intra-Abdominal Infections. Viszeralmedizin 2014, 30, 310–316. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. ECDC; Public Health England; Institut de Veillle Sanitaire. Systematic Review and Evidence-Based Guidance on Perioperative Antibiotic Prophylaxis; Publications Office: Stockholm, Sweden, 2013; Available online: https://data.europa.eu/doi/10.2900/85936 (accessed on 1 January 2022).
  20. Tucci, G.; Romanini, E.; Zanoli, G.; Pavan, L.; Fantoni, M.; Venditti, M. Prevention of surgical site infections in orthopaedic surgery: A synthesis of current recommendations. Eur. Rev. Med. Pharmacol. Sci. 2019, 23, S224–S239. [Google Scholar]
  21. Centers for Disease Control and Prevention. Outpatient Procedure Component Surgical Site Infection (OPC-SSI) Surveillance; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2022. Available online: https://www.cdc.gov/nhsn/pdfs/opc/opc-ssi-protocol-current-508.pdf (accessed on 14 April 2021).
  22. Van Mourik, M.S.M.; van Rooden, S.M.; Abbas, M.; Aspevall, O.; Astagneau, P.; Bonten, M.J.M.; Carrara, E.; Gomila-Grange, A.; De Greeff, S.C.; Gubbels, S.; et al. PRAISE: Providing a roadmap for automated infection surveillance in Europe. Clin. Microbiol. Infect. 2021, 27, S3–S19. [Google Scholar] [CrossRef]
  23. European Centre for Disease Prevention and Control. Surveillance of Surgical Site Infections and Prevention Indicators in European Hospitals: HAI-Net SSI Protocol, Version 2.2. 2017. Available online: https://op.europa.eu/en/publication-detail/-/publication/3c8fcb38-83c2-11e7-b5c6-01aa75ed71a1/language-en (accessed on 13 April 2021).
  24. World Health Organization. Global Guidelines for the Prevention of Surgical Site Infection; World Health Organization: Geneva, Switzerland, 2016. [Google Scholar]
  25. Manivannan, B.; Gowda, D.; Bulagonda, P.; Rao, A.; Raman, S.S.; Natarajan, S.V. Surveillance, Auditing, and Feedback Can Reduce Surgical Site Infection Dramatically: Toward Zero Surgical Site Infection. Surg. Infect. 2018, 19, 313–320. [Google Scholar] [CrossRef]
  26. Sharma, M.; Damlin, A.L.; Sharma, A.; Stålsby Lundborg, C. Antibiotic prescribing in medical intensive care units—A comparison between two private sector hospitals in Central India. Infect. Dis. 2015, 47, 302–309. [Google Scholar] [CrossRef]
  27. Sharma, M.; Eriksson, B.; Marrone, G.; Dhaneria, S.; Lundborg, C.S. Antibiotic prescribing in two private sector hospitals; one teaching and one non-teaching: A cross-sectional study in Ujjain, India. BMC Infect. Dis. 2012, 12, 155. [Google Scholar] [CrossRef] [Green Version]
  28. World Health Organization. Protocol for Surgical Site Infection Surveillance with a Focus on Settings with Limited Resources. 2018. Available online: https://www.who.int/infection-prevention/tools/surgical/SSI-surveillance-protocol.pdf (accessed on 15 September 2021).
  29. Collee, J.G. Mackie & McCartney Practical Medical Microbiology; Churchill Livingstone: New York, NY, USA, 1996. [Google Scholar]
  30. Petti, C.A.; Clinical and Laboratory Standards Institute (Eds.) Interpretive Criteria for Identification of Bacteria and Fungi by DNA Target Sequencing: Approved Guideline; Clinical and Laboratory Standards Institute: Wayne, PA, USA, 2008; p. 73. [Google Scholar]
  31. World Health Organization; Collaborating Centre for Drug Statistics Methodology. ATC Classification Index with DDDs. Available online: https://www.whocc.no/use_of_atc_ddd/ (accessed on 15 April 2021).
  32. Morris, A.J.; Jackways, T.M.; Morgan, A.; Robertson, R.; McIntyre, M. Reduction in surgical site infections in the Southern Cross Hospitals network, 2004–2015: Successful outcome of a long-term surveillance and quality improvement project. N. Z. Med. J. 2018, 131, 27–39. [Google Scholar]
  33. Najjar, Y.W.; Al-Wahsh, Z.M.; Hamdan, M.; Saleh, M.Y. Risk factors of orthopedic surgical site infection in Jordan: A prospective cohort study. Int. J. Surg. Open 2018, 15, 1–6. [Google Scholar] [CrossRef]
  34. Dhammi, I.; Kumar, S.; Haq, R.U. Prophylactic antibiotics in orthopedic surgery. Indian J. Orthop. 2015, 49, 373. [Google Scholar] [CrossRef]
  35. Bratzler, D.W.; Dellinger, E.P.; Olsen, K.M.; Perl, T.M.; Auwaerter, P.G.; Bolon, M.K.; Fish, D.N.; Napolitano, L.M.; Sawyer, R.G.; Slain, D.; et al. Clinical Practice Guidelines for Antimicrobial Prophylaxis in Surgery. Surg. Infect. 2013, 14, 73–156. [Google Scholar] [CrossRef]
  36. Mazmudar, A.; Vitello, D.; Chapman, M.; Tomlinson, J.S.; Bentrem, D.J. Gender as a risk factor for adverse intraoperative and postoperative outcomes of elective pancreatectomy: Gender’s Role in Pancreatectomy Outcomes. J. Surg. Oncol. 2017, 115, 131–136. [Google Scholar] [CrossRef]
  37. Al-Qurayshi, Z.; Baker, S.M.; Garstka, M.; Ducoin, C.; Killackey, M.; Nichols, R.L.; Kandil, E. Post-Operative Infections: Trends in Distribution, Risk Factors, and Clinical and Economic Burdens. Surg. Infect. 2018, 19, 717–722. [Google Scholar] [CrossRef]
  38. Aghdassi, S.J.S.; Schröder, C.; Gastmeier, P. Gender-related risk factors for surgical site infections. Results from 10 years of surveillance in Germany. Antimicrob. Resist. Infect. Control 2019, 8, 95. [Google Scholar] [CrossRef] [Green Version]
  39. Schimmel, J.J.P.; Horsting, P.P.; de Kleuver, M.; Wonders, G.; van Limbeek, J. Risk factors for deep surgical site infections after spinal fusion. Eur. Spine J. 2010, 19, 1711–1719. [Google Scholar] [CrossRef] [Green Version]
  40. Weigelt, J.A.; Lipsky, B.A.; Tabak, Y.P.; Derby, K.G.; Kim, M.; Gupta, V. Surgical site infections: Causative pathogens and associated outcomes. Am. J. Infect. Control 2010, 38, 112–120. [Google Scholar] [CrossRef]
  41. Rutberg, H.; Borgstedt-Risberg, M.; Gustafson, P.; Unbeck, M. Adverse events in orthopedic care identified via the Global Trigger Tool in Sweden—Implications on preventable prolonged hospitalizations. Patient Saf. Surg. 2016, 10, 23. [Google Scholar] [CrossRef] [Green Version]
  42. Akshaya, D.; Sarala, K.S.; Sharmila, R. A Study of Select Determinants for Hospital Stay Among Surgical Patients in a Tertiary Care Hospital. IJMAS 2016, 2, 37–43. [Google Scholar]
  43. Ribeiro, M.; Monteiro, F.J.; Ferraz, M.P. Infection of orthopedic implants with emphasis on bacterial adhesion process and techniques used in studying bacterial-material interactions. Biomatter 2012, 2, 176–194. [Google Scholar] [CrossRef] [Green Version]
  44. Machowska, A.; Sparrentoft, J.; Dhakaita, S.K.; StålsbyLundborg, C.; Sharma, M. Perioperative antibiotic prescribing in surgery departments of two private sector hospitals in Madhya Pradesh, India. Perioper. Med. 2019, 8, 10. [Google Scholar] [CrossRef]
  45. Menz, B.D.; Charani, E.; Gordon, D.L.; Leather, A.J.; Moonesinghe, S.R.; Phillips, C.J. Surgical Antibiotic Prophylaxis in an Era of Antibiotic Resistance: Common Resistant Bacteria and Wider Considerations for Practice. Infect. Drug Resist. 2021, 14, 5235–5252. [Google Scholar] [CrossRef]
  46. Forget, V.; Fauconnier, J.; Boisset, S.; Pavese, P.; Vermorel, C.; Bosson, J.L.; Saragaglia, D.; Tonetti, J.; Mallaret, M.R.; Landelle, C. Risk factors for Staphylococcus aureus surgical site infections after orthopaedic and trauma surgery in a French university hospital. Int. J. Hyg. Environ. Health 2020, 229, 113585. [Google Scholar] [CrossRef]
  47. Chlebicki, M.P.; Safdar, N.; O’Horo, J.C.; Maki, D.G. Preoperative chlorhexidine shower or bath for prevention of surgical site infection: A meta-analysis. Am. J. Infect. Control 2013, 41, 167–173. [Google Scholar] [CrossRef]
  48. Webster, J.; Osborne, S. Preoperative Bathing or Showering with Skin Antiseptics to Prevent Surgical Site Infection. In Cochrane Database of Systematic Reviews; The Cochrane Collaboration, Ed.; John Wiley & Sons, Ltd.: Chichester, UK, 2012; p. CD004985. Available online: https://doi.wiley.com/10.1002/14651858.CD004985.pub4 (accessed on 23 February 2022).
  49. Diwan, V.; Hanna, N.; Purohit, M.; Chandran, S.; Riggi, E.; Parashar, V.; Tamhankar, A.J.; Lundborg, C.S. Seasonal Variations in Water-Quality, Antibiotic Residues, Resistant Bacteria and Antibiotic Resistance Genes of Escherichia coli Isolates from Water and Sediments of the Kshipra River in Central India. Int. J. Environ. Res. Public Health 2018, 15, 1281. [Google Scholar] [CrossRef] [Green Version]
  50. Woelber, E.; Schrick, E.J.; Gessner, B.D.; Evans, H.L. Proportion of Surgical Site Infections Occurring after Hospital Discharge: A Systematic Review. Surg. Infect. 2016, 17, 510–519. [Google Scholar] [CrossRef]
  51. Pathak, A.; Sharma, S.; Sharma, M.; Mahadik, V.K.; Lundborg, C.S. Feasibility of a Mobile Phone-Based Surveillance for Surgical Site Infections in Rural India. Telemed. J. E-Health 2015, 21, 946–949. [Google Scholar] [CrossRef]
  52. Pourhoseingholi, M.A.; Vahedi, M.; Rahimzadeh, M. Sample size calculation in medical studies. Gastroenterol. Hepatol. Bed Bench 2013, 6, 14–17. [Google Scholar]
Antibiotics 11 00748 g001 550
Figure 1. Flowchart of the study population selection. SSI: surgical site infection.
Figure 1. Flowchart of the study population selection. SSI: surgical site infection.
Antibiotics 11 00748 g001
Table
Table 1. Patient-related potential risk factors for orthopedic surgical site infections in the teaching hospital, Ujjain, central India.
Table 1. Patient-related potential risk factors for orthopedic surgical site infections in the teaching hospital, Ujjain, central India.
All Operated Patients
n = 1205 (%)		SSI Patients
n = 91 (%)		Non-SSI Patients
n = 1114 (%)
Age, median (25–75th), years35 (19–50)35 (22–50)35 (18–50)
Age, years
≤18 301 (25)18 (20)283 (25)
19–60760 (63)64 (70)696 (62)
>60144 (12)9 (10)135 (12)
ASA score
ASA I1013 (84)63 (69)950 (85)
ASA II148 (12)22 (24)126 (11)
ASA III43 (4)6 (7)37 (3)
ASA IV1 (0)01 (0)
Antibiotic prescribed 14 days before hospital admission73 (6)17 (19)56 (5)
Previous hospitalization173 (14)33 (36)140 (13)
SSI = surgical site infection, ASA = American Society for Anesthesiologists.
Table
Table 2. Surgery-related potential risk factors for orthopedic surgical site infections in the teaching hospital, Ujjain, central India.
Table 2. Surgery-related potential risk factors for orthopedic surgical site infections in the teaching hospital, Ujjain, central India.
All Operated Patients
n = 1205 (%)		SSI Patients
n = 91 (%)		Non-SSI Patients
n = 1114 (%)
Type of wound a
Closed1034 (86)64 (70) 970 (87)
Compound fracture37 (3)9 (10)28 (3)
Clean3 (0)03 (0)
Contaminated23 (2)3 (3)20 (2)
Nature of surgery a
Elective1113 (92)80 (88)1033 (93)
Emergency17 (1)2 (2)15 (1)
Duration of surgery a, min
≤60425 (35)40 (44)385 (35)
61–120375 (31)22 (24)353 (32)
>120208 (17)13 (14)195 (18)
Hair removal method a
Shaving 1057 (88)76 (84)981 (88)
Clipping 2 (0) 02 (0)
Preoperative shower267 (22) 42 (46) 225 (20)
Preoperative LOS, median (25–75th), days5 (3–9)4 (2–8)5 (3–9)
Preoperative LOS a, days
1–3325 (27)24 (26)301 (27)
4–7379 (31) 28 (31)351 (32)
8–15 312 (26)16 (18)296 (27)
>1590 (7)9 (10)81 (7)
Postoperative LOS, median (25–75th), days8 (3–14)13 (4–21)8 (3–14)
Postoperative LOS a, days
1–3223 (19)7 (8)216 (19)
4–7239 (20)8 (9)231 (21)
8–15440 (37)28 (31)412 (37)
>15203 (17)33 (36)170 (15)
Oxygen support1031 (86)73 (80)958 (86)
Blood transfusion405 (34) 27 (30)378 (34)
Drain41 (3)8 (9)33 (3)
Implant297 (25)49 (54)248 (22)
Antibiotic prescription1133 (94) 91 (100) 1042 (94)
PAP840 (70)42 (46)798 (72)
Antibiotic during hospital stay before PAP258 (21)43 (47)215 (19)
Duration of antibiotic treatment before PAP, days
1–7186 (15)29 (32)157 (14)
8–1444 (4) 8 (9) 36 (3)
>1428 (2)6 (7) 22 (2)
Postoperative antibiotic1036 (86)75 (82)961 (86)
Duration of postoperative antibiotic, days
1–7440 (37)17 (19)423 (38)
8–14374 (31)24 (26)350 (31)
>14248 (21) 36 (40)212 (19)
Antibiotic duration, median (25–75th), days12 (4–16)24 (8–36)11 (4–15)
Total antibiotic duration a, days
1–7384 (32)21 (23)363 (33)
8–14319 (26) 19 (21)300 (27)
>14391 (32)50 (55)341 (31)
a For the variables where the number of patients does not correspond to the total number of patients in the group, that information for the rest of the patients is missing in the data record. SSI = surgical site infection, PAP = perioperative antibiotic prophylaxis, LOS = length of stay.
Table
Table 3. Antibiotic susceptibility patterns of the bacterial isolates in orthopedic surgical site infections in the teaching hospital, Ujjain, central India.
Table 3. Antibiotic susceptibility patterns of the bacterial isolates in orthopedic surgical site infections in the teaching hospital, Ujjain, central India.
Antibiotics TestedGram-Positive OrganismsGram-Negative Organisms
S. aureus
(n = 5)		Pseudomonas
(n = 4)		Klebsiella
(n = 4)		E. coli
(n = 2)		Total
Penicillin5 ----
Erythromycin4 ----
Ciprofloxacin3 3115/10
Cefoxitin3 -112/6
Tetracycline2 -314/6
Cotrimoxazole4 -224/6
Vancomycin-----
Linezolid-----
Clindamycin-----
Amikacin3 3104/10
Gentamycin3 3115/10
Ampicillin--314/6
Amoxiclav--213/6
Piperacillin Tazobactam-3104/10
Cefuroxime--214/6
Cefepime-3216/10
Cefotaxime --213/6
Ceftriaxone--213/6
Ceftazidime-3216/10
Meropenem-1001/10
Aztreonam-3014/10
Susceptibility to Colistin in Gram-negative organisms was 100%.; one Klebsiella isolate was the extended-spectrum β-lactamase producer.
Table
Table 4. Antibiotic prescriptions during hospital stay at the orthopedic ward in the teaching hospital, Ujjain, central India.
Table 4. Antibiotic prescriptions during hospital stay at the orthopedic ward in the teaching hospital, Ujjain, central India.
Antibiotics Groups/Subgroups/Substances
with ATC Codes		Total Prescriptions
n = 3030 (%)		Prescriptions for SSI Patients
n = 332 (%)		Prescriptions for
Non-SSI Patients
n = 2698 (%)
Tetracyclines; J01A
Tetracyclines; J01AA025 (0) 5 (0)
β-lactams, Penicillins; J01C
Combinations of penicillins, incl. β-lactam inhibitors; J01CR02281 (9)36 (11)245 (9)
J01CR053 (0)2 (1)1 (0)
J01CR501 (0)1 (0)
Other β-lactams; J01D
Second-generation cephalosporins; J01DC023 (0)1 (0)2 (0)
J01DC101 (0) 1 (0)
Third- generation cephalosporins; J01DD0143 (1)9 (3)34 (1)
J01DD0412 (0) 12 (0)
J01DD081 (0) 1 (0)
J01DD122 (0) 2 (0)
J01DD138 (0) 8 (0)
J01DD62 380 (13)27 (8)353 (13)
J01DD63738 (24)70 (21)668 (25)
Carbapenems; J01DH511 (0) 1 (0)
Sulfonamides and Trimethoprim; J01E
Combinations of sulfonamides and trimethoprim; J01EE013 (0) 3 (0)
Macrolides, Lincosamides and Streptogramins; J01F
Lincosamides; J01FF016 (0)3 (1)3 (0)
Aminoglycosides; J01G
Other aminogylcosides; J01GB0323 (1)8 (2)15 (1)
J01GB061107 (37)96 (29)1011 (38)
Quinolones; J01M
Fluoroquinolones; J01MA011 (0) 1 (0)
J01MA0279 (3)19 (6)60 (2)
J01MA063 (0)1 (0)2 (0)
Combinations of antibacterials; J01R
Combinations of antibacterials; J01RA751 (0) 1 (0)
Other antibacterials; J01X
Imidazole derivatives; J01XD0184 (3)22 (7)62 (2)
Other antibacterials; J01XX08244 (8)37 (11)207 (8)
SSI = surgical site infection, ATC = Anatomical Therapeutic Chemical classification.
Table
Table 5. Univariable and multivariable analyses of risk factors associated with orthopedic surgical site infections.
Table 5. Univariable and multivariable analyses of risk factors associated with orthopedic surgical site infections.
Risk Factor Univariable AnalysisMultivariable Analysis
Model 1Model 2Model 3
AIC = 454, BIC = 523AIC = 482, BIC = 512AIC = 447, BIC = 487
OR95% CIp-ValueOR95% CIp-ValueOR95% CIp-ValueOR95% CIp-Value
SexFemale1
Male3.421.79–6.490.0002.571.25–5.290.0102.931.48–5.770.0022.641.32–5.300.006
Age, years≤181.00
19–601.450.84–2.480.182
>601.050.46–2.390.911
ASA scoreASA I1
ASA II2.631.57–4.430.0001.300.67–2.490.437
ASA III2.450.99–6.010.0512.080.76–5.720.156
Previous hospitalization4.142.57–6.660.0001.650.85–3.190.139 2.151.25–3.690.006
Antibiotic prescribed 14 days before hospital admission4.712.59–8.580.0001.450.61–3.420.400
PAP0.340.21–0.530.0001.110.52–2.340.789
Antibiotic treatment during hospital stay before PAP3.752.42–5.800.0003.932.33–6.630.0003.922.40–6.430.0004.192.51–7.000.000
Duration of preoperative antibiotic, days1–71
8–141.20.51–2.850.674
>141.480.55–3.960.438
Postoperative antibiotic0.750.42–1.310.311
Duration of postoperative antibiotic, days1–71
8–141.710.90–3.230.100
>144.232.32–7.690.0001.051.00–1.090.0431.051.01–1.090.0281.041.00–1.090.051
Preoperative LOS, days1–31
4–71.000.57–1.760.999
8–150.680.35–1.300.243
>151.390.62–3.120.419
Postoperative LOS, days 1–31
4–71.070.38–2.990.900
8–152.100.90–4.880.086
>155.992.59–13.870.0003.031.65–5.580.0002.951.67–5.200.0003.301.83–5.950.000
Preoperative shower3.942.49–6.240.0004.141.99–8.560.0005.493.29–9.160.0004.732.72–8.220.000
Hair removalNot done1.00
Previous night 0.650.36–1.190.161
Same day0.560.15–2.030.375
Shaving 0.590.33–1.080.087
Type of fractureClosed1
Compound 4.872.21–10.760.0001.970.73–5.350.182
Nature of surgery Elective1
Emergency1.720.39–7.660.476
Duration of surgery, min≤601.00
61–1200.600.35–1.030.064
>1200.640.34–1.230.180
Blood transfusion0.880.54–1.430.601
Oxygen support0.750.29–1.930.547
Drain3.211.43–7.200.0051.830.74–4.500.189 1.730.71–4.220.231
Implants4.072.64–6.290.0001.340.71–2.500.366
PAP = perioperative antibiotic prophylaxis, LOS = length of stay.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Skender, K.; Machowska, A.; Singh, V.; Goel, V.; Marothi, Y.; Lundborg, C.S.; Sharma, M. Antibiotic Use, Incidence and Risk Factors for Orthopedic Surgical Site Infections in a Teaching Hospital in Madhya Pradesh, India. Antibiotics 2022, 11, 748. https://doi.org/10.3390/antibiotics11060748

AMA Style

Skender K, Machowska A, Singh V, Goel V, Marothi Y, Lundborg CS, Sharma M. Antibiotic Use, Incidence and Risk Factors for Orthopedic Surgical Site Infections in a Teaching Hospital in Madhya Pradesh, India. Antibiotics. 2022; 11(6):748. https://doi.org/10.3390/antibiotics11060748

Chicago/Turabian Style

Skender, Kristina, Anna Machowska, Vivek Singh, Varun Goel, Yogyata Marothi, Cecilia Stålsby Lundborg, and Megha Sharma. 2022. "Antibiotic Use, Incidence and Risk Factors for Orthopedic Surgical Site Infections in a Teaching Hospital in Madhya Pradesh, India" Antibiotics 11, no. 6: 748. https://doi.org/10.3390/antibiotics11060748

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop