1. Introduction
Orthopedic trauma surgery often entails open reduction and internal fixation of fractured bones to restore musculoskeletal function and stability.1 One of the most frequent and dangerous complications in individuals with orthopaedic trauma is infection.1 Orthopedic surgery infections are one of the common contributors in surgical site infections.2 In spite of the advancements in surgical techniques, the issue of surgical infections continues to remain a significant concern.2
Regardless of whether trauma patients undergo open or closed reduction, they are at increased risk for infection as they undergo multiple surgical procedures, receive transfusions, often require ventilation in the intensive care unit and oftentimes become catabolic and hyperinflamed.1
Orthopaedic surgery infections not only resulted in longer hospital stay but also increased healthcare expenses, patient suffering, and morbidity.2,3,4 These patients are also at higher risk for thromboembolic events and dependency on post-hospital care.5 Most importantly, it also lead to increase in antibiotic usage and further increase the chance of antibiotic resistance. A deep understanding of the causative organisms and their antibiotic susceptibility pattern is vital for successful treatment of such infections.6
Therefore, this study was undertaken so that it may be helpful to identify the best possible initial empiric antibiotic therapy for these patients until identification of the causative pathogen, or in patients with culture-negative.
2. Methodology
This was a retrospective study based on data extracted from an electronic hospital information system (Laboratory Information System) from the period of January 2014 to December 2023 among patients presenting to the Orthopaedics department of our level 1 Trauma Center.
Obtaining the Sample and Culture: When infection was suspected based on symptoms like localized pain, swelling, fever, or pus, samples were taken. These samples were collected using sterile swabs for superficial wounds, or sterile containers for deeper fluids like aspirate or pus. The collected specimens were quickly sent to the microbiology lab, where they were cultured on 5 % blood agar and MacConkey agar and incubated at 35–37 °C for 24 h. The isolates were identified through standard techniques, including gram staining followed by MALDI-TOF system. Antimicrobial Susceptibility Testing of the isolates was tested using the VIEK-2 according to updated CLSI guidelines.
All patients with positive cultures from outpatient as well as inpatient departments were included in the study. Cultures that were contaminated or in a mixture of microorganisms (3 or >3 types) were excluded from the study.
3. Results
This study examines pathogen distribution and antimicrobial susceptibility trends among 2436 culture reports from 2014 to 2023 out of 3383 samples received which accounts for 72 % culture positivity. Rest 947 samples yielded mixed bacterial growth with >3 different types of organisms and where not processed further. The remaining 2436 were included in the study. The sample included 406 (16.6 %) females and the remainder males, with 1781 tissue samples (73 %), 168 pus swabs (7 %), and 487 (20 %)pus aspirates. Escherichia spp., particularly E. coli (20.8 %), and Klebsiella spp., mainly K. pneumoniae (18.1 %), were the most prevalent organisms. Shown in Table 1.
Table 1.
Distribution of pathogenic organisms.
| Genus | n | spp | n | spp | n | spp | n |
|---|---|---|---|---|---|---|---|
| Escherichia | 507 | E.coli | 507 | – | – | – | – |
| Klebsiella | 453 | K.pneumoniae | 442 | K.aerogenes | 11 | ||
| Pseudomonas | 355 | P.aeruginosa | 350 | P.putida | 4 | P.stutzeri | 1 |
| Acinetobacter | 362 | A.baumannii | 361 | A.lwoffii | 1 | ||
| Staphylococcus | 240 | S. aureus | 234 | S.epidermidis | 3 | S.haemolyticus | 3 |
| Enterobacter | 195 | E.cloacae | 195 | – | – | – | – |
| Proteus | 126 | P.mirabilis | 123 | P.penneri | 2 | P.hauseri | 1 |
| Enterococcus | 67 | E.faecium | 52 | E.faecalis | 15 | ||
| Citrobacter | 42 | C.freundii | 34 | C.koseri | 7 | C.amalonaticus | 1 |
| Streptococcus | 26 | S.pyogenes | 25 | S.dysgalactiae | 1 | ||
| Morganella | 19 | M.morganii | 19 | – | – | – | – |
| Providencia | 14 | P.stuartii | 12 | P.rettgeri | 2 | ||
| Serratia | 15 | S.marcescens | 15 | – | – | – | – |
| Aeromonas | 9 | A.hydrophila | 9 | – | – | – | – |
| Stenotrophomonas | 3 | S.maltophilia | 3 | – | – | – | – |
| Chryseobacterium | 1 | C.indologenes | 1 | – | – | – | – |
| Chryseomonas | 1 | C.luteola | 1 | – | – | – | – |
| Sphingomonas | 1 | S.paucimobilis | 1 | – | – | – | – |
We then divided the study group into 2 different interval types from 2014 to 2019 and 2020–2023 as shown in Table 2 to see pattern of pathogen distribution and trend. Escherichia spp were seen as predominant organism in both the group followed by Klebsiella spp, however there was decline in Acinetobacter spp causing infections from 2020 to 2023 group which were also indicated by Z-score where a positive Z score indicates an increase in the proportion in the later period relative to the earlier, while a negative score indicates a decrease. Acinetobacter spp, for example, shows a significant positive deviation, suggesting a notable decrease in its proportion in the later period compared to earlier. Staphylococcus spp also shows a significant negative deviation, indicating a substantial decrease.
Table- 2.
Distribution of pathogenic organisms year wise.
| Organism (Number of isolates) | 2014–2019 | 2020–2023 | Z score |
|---|---|---|---|
| Escherichia spp | 311 | 196 | 1.7 |
| Klebsiella spp | 278 | 175 | 0.95 |
| Pseudomonas spp | 227 | 128 | 0.22 |
| Acinetobacter spp | 278 | 84 | 5.3 |
| Staphylococcus spp | 133 | 107 | 3.22 |
| Enterobacter spp | 134 | 61 | 0.05 |
| Proteus spp | 86 | 40 | 0.89 |
The annual number of isolates identified from 2014 to 2023. Over this ten-year period, Escherichia coli consistently appears with significant fluctuations, peaking in 2021 with 31 % and dipping to a low of 13 % in 2019. Pseudomonas aeruginosa shows variability, with a notable increase to 19 % isolates in 2016, followed by a decrease, and then stabilizing around 14–16 % isolates in recent years. Staphylococcus aureus exhibits an irregular pattern, with no isolates reported in 2015 and 2017, but peaks in 2020 with 18 %. Klebsiella pneumoniae displays a relatively stable presence, with a notable peak of 22 % in 2018 and a consistent count of 21 % in multiple years. Acinetobacter baumannii shows a marked increase in 2016 with 22 % and another peak in 2019 with 21 %, followed by a significant decline in the subsequent years, reaching its lowest at 7 % in 2021 as shown in figure-1.
Figure:1.
Overall trend of isolates among orthopaedic patients (2014–2023).
We further focused on susceptibility patterns of most commonly offending pathogens.The analysis for Escherichia spp (E. coli) showed decrease in susceptibility rates from 2014 to 2019 to 2020–2023 for amikacin, cefoxitin, ciprofloxacin and levofloxacin with Z score of >0 and p-value <0.05 indicating statistically significant differences in susceptibility rates over a time, whereas ceftazidime, imipenem and colistin do not show significant changes, as indicated by their higher p-values. Piperacillin-tazobactam shows a moderate change with a p-value just under 0.01 as shown in Table 3.
Table- 3.
Temporal Trends in antimicrobial susceptibility among Escherichia spp. Isolates from 2014 to 2023.
| Antimicrobial agent | 2014–2019 | 2020–2023 | Z-Score | p-value |
|---|---|---|---|---|
| Number of isolates | 311 | 196 | ||
| Amikacin (%) | 197/295 (65) | 101/196 (52) | 3.39 | <0.05 |
| Cefoxitin | 29/199 (15) | 7/166 (4.2) | 3.30 | <0.05 |
| Ceftazidime | 24/216 (11) | 17/155 (11) | 0.04 | 0.96 |
| Ciprofloxacin | 49/214 (23) | 10/171 (5.8) | 4.6 | <0.05 |
| Colistin | 141/220 (64) | 92/168 (54) | 1.8 | 0.06 |
| Levofloxacin | 75/220 (34) | 19/161 (12) | 4.9 | <0.05 |
| Imipenem | 57/242 (23) | 43/180 (24) | −0.08 | 0.9 |
| Piptaz | 58/222 (26) | 27/175 (15) | 2.5 | <0.05 |
(Z-score represents the trends (Z score <0: downward trend; Z score >0:upward trend).
For Klebsiella spp most agents show significant changes as indicated with Z-score and P-value except for Levofloxacin and Piperacillin-tazobactam, which did not show significant changes in susceptibility as shown in Table 4.
Table- 4.
Temporal Trends in antimicrobial susceptibility among Klebsiella spp. Isolates from 2014 to 2023.
| Antimicrobial agent | 2014–2019 | 2020–2023 | Z-Score | p-value |
|---|---|---|---|---|
| Number of isolates | 278 | 164 | -- | - |
| Amikacin (%) | 63/227 (28) | 10/164 (6) | 5.4 | <0.05 |
| Cefoxitin | 25/163 (15) | 3/136 (2) | 3.8 | <0.05 |
| Ceftazidime | 27/172 (15) | 10/135 (7) | 2.2 | <0.05 |
| Ciprofloxacin | 29/133 (21) | 9/145 (6.2) | 3.7 | <0.05 |
| Colistin | 73/174 (42) | 83/143 (58) | −20.8a | <0.05 |
| Levofloxacin | 31/181 (17) | 24/143 (16) | 0.08 | 0.9 |
| Imipenem | 46/175 (26) | 15/139 (11) | 3.4 | <0.05 |
| Piperacillin-tazobactam | 30/180 (16) | 18/142 (12) | 1 | 0.3 |
(Z-score represents the trends (Z score <0: downward trend; Z score >0:upward trend).
The negative sign indicates that the change is towards increased susceptibility.
For Acinetobacter spp colistin shows a significant negative Z-score of −4.64 with a p-value of <0.05, indicating a statistically significant increase in susceptibility from 2014 to 2019 to 2020–2023. Other agents like Cefoxitin, Ceftazidime, Ciprofloxacin, Levofloxacin, Imipenem, and Piperacillin-tazobactam do not show statistically significant changes (p-value >0.05). Amikacin also does not show a statistically significant difference in susceptibility between the two periods as shown in Table 5.
Table-5.
Temporal Trends in antimicrobial susceptibility among Acinetobacter spp. isolates from 2014 to 2023.
| Antimicrobial agent | 2014–2019 | 2020–2023 | Z-Score | p-value |
|---|---|---|---|---|
| Number of isolates | 278 | 84 | -- | - |
| Amikacin (%) | 34/264 (13) | 7/73 (9) | 0.76 | 0.4 |
| Cefoxitin | 9/188 (5) | 0/68 (0) | 1.84 | 0.06 |
| Ceftazidime | 15/196 (7.6) | 8/74 (11) | −0.83 | 0.4 |
| Ciprofloxacin | 5/53 (9) | 4/76 (5) | 0.91 | 0.3 |
| Colistin | 55/202 (27) | 42/73 (57) | −4.64 | <0.05 |
| Levofloxacin | 18/204 (9) | 10/72 (14) | −1.2 | 0.2 |
| Imipenem | 20/223 (9) | 11/72 (15) | −1.5 | 0.1 |
| Piperacillin-tazobactam | 16/207 (7) | 5/75 (6) | 0.3 | 0.7 |
(Z-score represents the trends (Z score <0: downward trend; Z score >0:upward trend).
∗The negative sign indicates that the change is towards increased susceptibility.
4. Discussion
This retrospective study from a single center examines the shifts in pathogen prevalence and distribution across various orthopedic infections over 10 years. It highlights changes in antimicrobial susceptibility, offering insights to enhance empirical treatment strategies for these infections. In this study, E. coli was the most frequently isolated organism at 20.8 %, followed by Klebsiella pneumoniae at 18.1 %. Other regions like Kerala, Chhattisgarh, and Tamil Nadu report varying prevalence's with dominant isolates such as Pseudomonas aeruginosa and Staphylococcus spp, reflecting regional microbiological as shown in Table 6.
Table 6.
Distribution of bacterial isolates in the study population.
| States from India | Common bacterial isolates (%) | ||
|---|---|---|---|
| Present study | E. coli (20.8 %) | Klebsiella pneumoniae (18.1 %) | Acinetobacter baumanni (14.8 %) |
| Pookkottu M,Kerela7 | Escherichia coli (23 %) | Pseudomonas aeruginosa (20 %) | Staphylococcus aureus (19 %) |
| Chhattisgarh, Patel et al.8 | Escherichia coli (51 %) | Staphylococcus aureus (21 %) | Klebsiella pneumoniae (12 %) |
| Tamil Nadu, Manikandan et al.9 | Pseudomonas aeruginosa (43 %) | Staphylococcus aureus (24 %) | Staphylococcus epidermidis (16 %) |
| Gujarat, Sida et al.10 | Staphylococcus aureus (26 %) | Klebsiella (23 %) | Pseudomonas aeruginosa (18 %) |
A study from Shanghai, China by Boyong Wang et all11 conducted from 2008 to 2021 also showed most common offending pathogen was Staphylococcus aureus (37.7 %). It has been reported that high incidence of infection with GNB is common in developing countries and also frequent with non-medical device associated infections.12,1 The highest percentage of resistant strains in our study was observed among Acinetobacter baumannii isolates. Similar findings have been reported by other researchers from various regions. For example, extensive multidrug resistance in Acinetobacter strains has been documented in several studies.13 Additionally, pan drug-resistant strains of Acinetobacter baumannii have been described in multiple Indian studies.8 Furthermore, some studies have indicated that carbapenem resistance in Acinetobacter baumannii isolates can reach up to 90 %.14
The excessive and inappropriate application of antibiotics has driven the global proliferation of bacterial antimicrobial resistance. This issue is exacerbated by the prevalence of mobile genetic elements carrying antimicrobial genes and the horizontal gene transfer between bacteria. Recently, it has become evident that antimicrobial resistance varies significantly worldwide, correlating with socioeconomic factors such as population density and sanitation practices. These disparities highlight the need for targeted strategies to combat resistance based on regional conditions and practices15
Monitoring and Policy Recommendation: Continuous monitoring of antibiotic resistance for 5–10 years is crucial for understanding susceptibility trends. Hospitals should implement strict antibiotic policies to curb resistance.
Study Limitations: We excluded anaerobic bacteria due to routine culture limitations and couldn't analyse.
Future Research Directions: Investigating novel antimicrobial agents and combination therapies targeting resistant gram-negative bacilli, Additionally, molecular studies to understand the mechanisms of resistance will aid in developing effective treatments and preventing the spread of resistance genes. Microbiome analysis will help in investigating the host microbiome's role in susceptibility and resistance, identifying therapeutic targets for microbiome-based interventions. And finally establishing robust surveillance systems to monitor bacterial pathogens and resistance trends enabling early threat detection and informed treatment guidelines.
Practical Implications: Strengthening antibiotic stewardship programs is crucial in promoting antibiotic use and minimizing resistance development. Interdisciplinary collaboration and patient education will enhance treatment outcomes, while advocating for policy changes will support responsible antibiotic use and comprehensive antimicrobial management strategies.
5. Conclusion
This retrospective study, highlights the evolving landscape of bacterial pathogens and their antibiotic susceptibility patterns in orthopaedic infections over a decade. The findings underscore the predominant role of gram-negative bacilli, particularly Escherichia coli and Klebsiella pneumoniae, in these infections. Given the high prevalence of resistant strains, particularly among E. coli and Klebsiella pneumoniae, there is an urgent need for judicious antibiotic use and strict adherence to hospital antibiotic policies. Based on the data from this study, Piperacillin-Tazobactam can be used because despite moderate changes in susceptibility, it remains a viable option due to its broad-spectrum activity against many gram-negative and gram-positive organisms. The choice of empirical therapy should always be tailored to the individual patient, taking into account local resistance patterns, patient history, and infection severity. This personalized approach will help optimize treatment outcomes and reduce the risk of further resistance development.
CRediT authorship contribution statement
M Nizam Ahmed: conceptualised and did original draft prepration of the manuscript. Vanlal Tluanpuii: conceptualised and did original draft prepration of the manuscript. Vivek Trikha: came with the idea and conceptulised the manuscript and did supervision and revision and editing of the manuscript. Vijay Sharma: came with the idea and conceptulised the manuscript and did supervision and revision and editing of the manuscript. Kamran Farooque: came with the idea and conceptulised the manuscript and did supervision and revision and editing of the manuscript. Purva Mathur: came with the idea and conceptulised the manuscript and did supervision and revision and editing of the manuscript. Samarth Mittal: came with the idea and conceptulised the manuscript and did supervision and revision and editing of the manuscript, All authorized finalized the draft and approved the same.
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