Humidity a potential risk factor for prosthetic joint infection in a tropical Australian hospital

Armit, Drew; Vickers, Mark L.; Parr, Adam; Rosendal, Simon Van; Trott, Nick; Gunasena, Rivindi; Parkinson, Benjamin

doi:10.1111/ans.14916

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…The transition between reversible and irreversible phases of biofilm formation, coupled with phenotypic change, is the last window of opportunity for clinically reasonable preventative measures (Figure 1). microbial variability [16]. PJIs can be early (within 3 months), delayed (3-12 months), and late (>12 months).…”

Section: Key Steps Towards Pjimentioning

confidence: 99%

“…Results can depend on the location of the prosthetic joint (e.g., knee, hip, shoulder) and perhaps also on the type of PJI and related comorbidities [13][14][15]. Furthermore, the methods used to identify causative agents can vary, and the geographical location can be a source of microbial variability [16]. PJIs can be early (within 3 months), delayed (3-12 months), and late (>12 months).…”

Section: Introductionmentioning

confidence: 99%

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Prevention of Prosthetic Joint Infection: From Traditional Approaches towards Quality Improvement and Data Mining

Gallo

Nieslanikova

2020

JCM

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A projected increased use of total joint arthroplasties will naturally result in a related increase in the number of prosthetic joint infections (PJIs). Suppression of the local peri-implant immune response counters efforts to eradicate bacteria, allowing the formation of biofilms and compromising preventive measures taken in the operating room. For these reasons, the prevention of PJI should focus concurrently on the following targets: (i) identifying at-risk patients; (ii) reducing “bacterial load” perioperatively; (iii) creating an antibacterial/antibiofilm environment at the site of surgery; and (iv) stimulating the local immune response. Despite considerable recent progress made in experimental and clinical research, a large discrepancy persists between proposed and clinically implemented preventative strategies. The ultimate anti-infective strategy lies in an optimal combination of all preventative approaches into a single “clinical pack”, applied rigorously in all settings involving prosthetic joint implantation. In addition, “anti-infective” implants might be a choice in patients who have an increased risk for PJI. However, further progress in the prevention of PJI is not imaginable without a close commitment to using quality improvement tools in combination with continual data mining, reflecting the efficacy of the preventative strategy in a particular clinical setting.

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Section: Key Steps Towards Pjimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prevention of Prosthetic Joint Infection: From Traditional Approaches towards Quality Improvement and Data Mining

Gallo

Nieslanikova

2020

JCM

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“…In their study of national joint replacement registry data, Parkinson et al recently identified higher early revision rates for prosthetic joint infection (PJI) in tropical vs. subtropical Australian hospitals [9]. At their tropical Australian institution, Armit et al also suggested that relative humidity played an important role in postoperative infection rates [15]. To our knowledge, there are no prior studies that describe the epidemiology or multi-drug resistance of bacteria following orthopaedic surgery in a tropical region [13,16].…”

Section: Introductionmentioning

confidence: 99%

Bacterial Profile, Multi-Drug Resistance and Seasonality Following Lower Limb Orthopaedic Surgery in Tropical and Subtropical Australian Hospitals: An Epidemiological Cohort Study

Vickers

Ballard

Harris

et al. 2020

IJERPH

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We aimed to describe the epidemiology, multi-drug resistance and seasonal distribution of bacteria cultured within 12 months following lower limb orthopaedic surgery in tropical and subtropical Australian hospitals between 2010 and 2017. We collected data from four tropical and two subtropical hospitals. Categorical variables were examined using the Pearson Chi-squared test or Fisher’s Exact test, and continuous variables with the Student t-test or Mann–Whitney U test. A Poisson regression model was used to examine the relationship between season, weather and the incidence of Staphylococcus and nonfermentative species. We found that at tropical sites, nonfermenters (Pseudomonas aeruginosa and Acinetobacter baumannii) were more common (28.7% vs. 21.6%, p = 0.018), and patients were more likely to culture multi-drug-resistant (MDR) nonfermenters (11.4% vs. 1.3%, p = 0.009) and MDR Staphylococcus aureus (35.9% vs. 24.6%, p = 0.006). At tropical sites, patients were more likely to be younger (65.9 years vs. 72.0, p = < 0.001), male (57.7% vs. 47.8%, p = 0.005), having knee surgery (45.3% vs. 34.5%, p = 0.002) and undergoing primary procedures (85.0% vs. 73.0%, p = < 0.001). Species were similar between seasons in both tropical and subtropical hospitals. Overall, we found that following lower limb orthopaedic surgery in tropical compared with subtropical Australia, patients were more likely to culture nonfermenters and some MDR species.

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“… 2 Studies have also shown that humidity and apparent temperature are potential important risk factors for increasing the risk of deep prosthetic joint infection in patients after Total knee arthroplasty. 10 …”

Section: Introductionmentioning

confidence: 99%

Epidemiologic Correlation and Drug Resistance Analysis of Pathogenic Bacteria in Different Open Limb Injury External Conditions

Xie

Guo

Liang

et al. 2022

Orthopaedic Surgery

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Objective To study the epidemiological correlation and drug resistance of external factors of infection caused by open injury of limbs to pathogens. Methods This experiment is a retrospective study. We took the geographical location and climate of Nanchang, Jiangxi Province, China as the background, analyzed 2017 strains of pathogens from 1589 patients with limb trauma infection in a University Affiliated Hospital from 2012 to 2017. Patients were divided into three groups according to the type of incision: I, In‐hospital infection of clean limb incision, II, In‐hospital infection with open injury, III, Community infection with open injury of the limb. Groups II and Groups III were divided into six subgroups according to the causes of trauma, including: accidents from non‐motor vehicles, machinery, cutting/piercing, pedestrian injuries, struck by/against, pedal cycles, and other injuries. We found eight common pathogens of orthopedic infection, which were mainly divided into Gram‐positive bacteria (G+, mainly including Staphylococcus ) and Gram‐negative bacteria (G‐, mainly Enterobacteriaceae ). The relationship between main pathogens and damage mechanism, apparent temperature and relative humidity was discussed in this study. SPSS v22.0 was used for statistical analysis of the data. Friedman's two‐way ANOVA was used to analyze the difference between the injury mechanism and incidence of pathogenic bacteria. Linear regression was used to determine the trend between the incidence of major pathogens and seasonal temperature and humidity. The level of significance was set as P < 0.05. Results There was no significant difference in the distribution of pathogens between Groups II and Groups III ( P >0.05). The drug resistance of Groups III was significantly higher than that of Groups II and Groups I. G+ bacteria were resistant to cephalosporin, ceftriaxone and other cephalosporins and erythromycin and other macrolides. They were sensitive to vancomycin and linezolid. G‐ were resistant to the first‐ and the second‐generation cephalosporins, including cefotetan and cefazolin, and ampicillin and other penicillins, while they were sensitive to third‐generation cephalosporins, such as ceftazidime, as well as to levofloxacin and other quinolones, meropenem, and other beta‐lactamases. The correlation between the injury mechanism and infection of pathogenic bacteria was not significant. The monthly average apparent temperature and relative humidity were correlated with the infection rate of pathogenic bacteria. Conclusion In open injury of extremities, apparent temperature and relative humidity is an important risk factor for infection by pathogenic bacteria and the drug resistance of pathogenic bacteria in out‐of‐hospital infection was lower than that of hospital infection.

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Humidity a potential risk factor for prosthetic joint infection in a tropical Australian hospital

Cited by 12 publications

References 28 publications

Prevention of Prosthetic Joint Infection: From Traditional Approaches towards Quality Improvement and Data Mining

Prevention of Prosthetic Joint Infection: From Traditional Approaches towards Quality Improvement and Data Mining

Bacterial Profile, Multi-Drug Resistance and Seasonality Following Lower Limb Orthopaedic Surgery in Tropical and Subtropical Australian Hospitals: An Epidemiological Cohort Study

Epidemiologic Correlation and Drug Resistance Analysis of Pathogenic Bacteria in Different Open Limb Injury External Conditions

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