Necrotising soft tissue infections. / Nekrotiserende bløtdelsinfeksjoner.

Necrotising soft tissue infections can affect the skin, subcutaneous tissue, superficial fascia, deep fascia and musculature. The infections are severe, they spread quickly and can result in extensive tissue loss. Although rare, morbidity and mortality rates are high. Early clinical identification is crucial for the outcome, and rapid infection control through surgery and targeted antibiotic treatment is needed to save lives. Few prospective clinical trials have been conducted for the treatment of this type of infection. Specific challenges include rapid identification of the condition and the uncertain efficacy of the various treatment options. In this clinical review article, we describe clinical characteristics, diagnostics and treatment.

Streptococcus dysgalactiae Bloodstream Infections, Norway, 1999-2021.

Streptococcus dysgalactiae increasingly is recognized as a pathogen of concern for human health. However, longitudinal surveillance data describing temporal trends of S. dysgalactiae are scarce. We retrospectively identified all ß-hemolytic streptococcal bloodstream infections reported in Bergen, in western Norway, during 1999-2021. To explore S. dysgalactiae disease burden in a broader context, we mapped the incidence of all microbial species causing bloodstream infections during 2012-2021. We found S. dysgalactiae incidence rates substantially increased during the study period; by 2021, S. dysgalactiae was the fifth most common pathogen causing bloodstream infections in our region. We noted genotypic shifts and found that the rising trend was related in part to the introduction and expansion of the stG62647 emm-type. S. dysgalactiae is among the most common causes of bloodstream infections in western Norway, and increased surveillance and unambiguous species identification are needed to monitor the disease burden attributable to this pathogen.

Systemic immune activation profiles in streptococcal necrotizing soft tissue infections: A prospective multicenter study.

OBJECTIVE: Early stages with streptococcal necrotizing soft tissue infections (NSTIs) are often difficult to discern from cellulitis. Increased insight into inflammatory responses in streptococcal disease may guide correct interventions and discovery of novel diagnostic targets. METHODS: Plasma levels of 37 mediators, leucocytes and CRP from 102 patients with ß-hemolytic streptococcal NSTI derived from a prospective Scandinavian multicentre study were compared to those of 23 cases of streptococcal cellulitis. Hierarchical cluster analyses were also performed. RESULTS: Differences in mediator levels between NSTI and cellulitis cases were revealed, in particular for IL-1ß, TNFα and CXCL8 (AUC >0.90). Across streptococcal NSTI etiologies, eight biomarkers separated cases with septic shock from those without, and four mediators predicted a severe outcome. CONCLUSION: Several inflammatory mediators and wider profiles were identified as potential biomarkers of NSTI. Associations of biomarker levels to type of infection and outcomes may be utilized to improve patient care and outcomes.

Neutrophil-derived reactive agents induce a transient SpeB negative phenotype in Streptococcus pyogenes.

BACKGROUND: Streptococcus pyogenes (group A streptococci; GAS) is the main causative pathogen of monomicrobial necrotizing soft tissue infections (NSTIs). To resist immuno-clearance, GAS adapt their genetic information and/or phenotype to the surrounding environment. Hyper-virulent streptococcal pyrogenic exotoxin B (SpeB) negative variants caused by covRS mutations are enriched during infection. A key driving force for this process is the bacterial Sda1 DNase. METHODS: Bacterial infiltration, immune cell influx, tissue necrosis and inflammation in patient´s biopsies were determined using immunohistochemistry. SpeB secretion and activity by GAS post infections or challenges with reactive agents were determined via Western blot or casein agar and proteolytic activity assays, respectively. Proteome of GAS single colonies and neutrophil secretome were profiled, using mass spectrometry. RESULTS: Here, we identify another strategy resulting in SpeB-negative variants, namely reversible abrogation of SpeB secretion triggered by neutrophil effector molecules. Analysis of NSTI patient tissue biopsies revealed that tissue inflammation, neutrophil influx, and degranulation positively correlate with increasing frequency of SpeB-negative GAS clones. Using single colony proteomics, we show that GAS isolated directly from tissue express but do not secrete SpeB. Once the tissue pressure is lifted, GAS regain SpeB secreting function. Neutrophils were identified as the main immune cells responsible for the observed phenotype. Subsequent analyses identified hydrogen peroxide and hypochlorous acid as reactive agents driving this phenotypic GAS adaptation to the tissue environment. SpeB-negative GAS show improved survival within neutrophils and induce increased degranulation. CONCLUSIONS: Our findings provide new information about GAS fitness and heterogeneity in the soft tissue milieu and provide new potential targets for therapeutic intervention in NSTIs.

Scoring systems for early detection of sepsis on the ward. / Skåringsverktøy for tidlig oppdagelse av sepsis på sengepost.

BACKGROUND: Sepsis is one of the most common causes of death in Norwegian hospitals. The condition is often overlooked with treatment being delayed. Scoring systems to detect patients with sepsis have mostly been studied in emergency departments and more rarely on wards. The objective of this study was to investigate the ability of various clinical scoring systems to identify sepsis in patients on wards. MATERIAL AND METHOD: The ability of the scoring systems SIRS (Systemic Inflammatory Response Syndrome), qSOFA (quick Sequential Organ Failure Assessment) and NEWS2 (National Early Warning Score 2) to identify patients with sepsis was compared in a study of adult patients with clinically suspected severe infection on wards at Haukeland University Hospital in the period March-December 2019. The diagnosis of sepsis was made based on an increase in SOFA (Sequential Organ Failure Assessment) score of 2 or more in the first 24 hours after inclusion. RESULTS: 89 patients with suspected new onset of severe infection were identified. Sepsis was diagnosed in 55 of these patients. SIRS had a sensitivity of 82 % and a specificity of 6 % in diagnosing sepsis, qSOFA had a sensitivity of 20 % and a specificity of 97 %, while NEWS2 with a threshold of an aggregate score ≥ 5 and/or 3 in a single parameter had a sensitivity of 96 % and a specificity of 59 %. Oxygen saturation with a threshold of 95 % was the most sensitive measurement for sepsis. INTERPRETATION: NEWS2 was better suited than qSOFA and SIRS for early detection of sepsis on wards.

Analysis of host-pathogen gene association networks reveals patient-specific response to streptococcal and polymicrobial necrotising soft tissue infections.

BACKGROUND: Necrotising soft tissue infections (NSTIs) are rapidly progressing bacterial infections usually caused by either several pathogens in unison (polymicrobial infections) or Streptococcus pyogenes (mono-microbial infection). These infections are rare and are associated with high mortality rates. However, the underlying pathogenic mechanisms in this heterogeneous group remain elusive. METHODS: In this study, we built interactomes at both the population and individual levels consisting of host-pathogen interactions inferred from dual RNA-Seq gene transcriptomic profiles of the biopsies from NSTI patients. RESULTS: NSTI type-specific responses in the host were uncovered. The S. pyogenes mono-microbial subnetwork was enriched with host genes annotated with involved in cytokine production and regulation of response to stress. The polymicrobial network consisted of several significant associations between different species (S. pyogenes, Porphyromonas asaccharolytica and Escherichia coli) and host genes. The host genes associated with S. pyogenes in this subnetwork were characterised by cellular response to cytokines. We further found several virulence factors including hyaluronan synthase, Sic1, Isp, SagF, SagG, ScfAB-operon, Fba and genes upstream and downstream of EndoS along with bacterial housekeeping genes interacting with the human stress and immune response in various subnetworks between host and pathogen. CONCLUSIONS: At the population level, we found aetiology-dependent responses showing the potential modes of entry and immune evasion strategies employed by S. pyogenes, congruent with general cellular processes such as differentiation and proliferation. After stratifying the patients based on the subject-specific networks to study the patient-specific response, we observed different patient groups with different collagens, cytoskeleton and actin monomers in association with virulence factors, immunogenic proteins and housekeeping genes which we utilised to postulate differing modes of entry and immune evasion for different bacteria in relationship to the patients' phenotype.

MAIT Cells Are Major Contributors to the Cytokine Response in Group A Streptococcal Toxic Shock Syndrome.

Streptococcal toxic shock syndrome (STSS) is a rapidly progressing, life-threatening, systemic reaction to invasive infection caused by group A streptococci (GAS). GAS superantigens are key mediators of STSS through their potent activation of T cells leading to a cytokine storm and consequently vascular leakage, shock, and multiorgan failure. Mucosal-associated invariant T (MAIT) cells recognize MR1-presented antigens derived from microbial riboflavin biosynthesis and mount protective innate-like immune responses against the microbes producing such metabolites. GAS lack de novo riboflavin synthesis, and the role of MAIT cells in STSS has therefore so far been overlooked. Here we have conducted a comprehensive analysis of human MAIT cell responses to GAS, aiming to understand the contribution of MAIT cells to the pathogenesis of STSS. We show that MAIT cells are strongly activated and represent the major T cell source of IFNγ and TNF in the early stages of response to GAS. MAIT cell activation is biphasic with a rapid TCR Vß2-specific, TNF-dominated response to superantigens and a later IL-12- and IL-18-dependent, IFNγ-dominated response to both bacterial cells and secreted factors. Depletion of MAIT cells from PBMC resulted in decreased total production of IFNγ, IL-1ß, IL-2, and TNFß. Peripheral blood MAIT cells in patients with STSS expressed elevated levels of the activation markers CD69, CD25, CD38, and HLA-DR during the acute compared with the convalescent phase. Our data demonstrate that MAIT cells are major contributors to the early cytokine response to GAS, and are therefore likely to contribute to the pathological cytokine storm underlying STSS.

Risk Factors and Predictors of Mortality in Streptococcal Necrotizing Soft-tissue Infections: A Multicenter Prospective Study.

BACKGROUND: Necrotizing soft-tissue infections (NSTI) are life-threatening conditions often caused by ß-hemolytic streptococci, group A Streptococcus (GAS) in particular. Optimal treatment is contentious. The INFECT cohort includes the largest set of prospectively enrolled streptococcal NSTI cases to date. METHODS: From the INFECT cohort of 409 adults admitted with NSTI to 5 clinical centers in Scandinavia, patients culture-positive for GAS or Streptococcus dysgalactiae (SD) were selected. Risk factors were identified by comparison with a cohort of nonnecrotizing streptococcal cellulitis. The impact of baseline factors and treatment on 90-day mortality was explored using Lasso regression. Whole-genome sequencing of bacterial isolates was used for emm typing and virulence gene profiling. RESULTS: The 126 GAS NSTI cases and 27 cases caused by SD constituted 31% and 7% of the whole NSTI cohort, respectively. When comparing to nonnecrotizing streptococcal cellulitis, streptococcal NSTI was associated to blunt trauma, absence of preexisting skin lesions, and a lower body mass index. Septic shock was significantly more frequent in GAS (65%) compared to SD (41%) and polymicrobial, nonstreptococcal NSTI (46%). Age, male sex, septic shock, and no administration of intravenous immunoglobulin (IVIG) were among factors associated with 90-day mortality. Predominant emm types were emm1, emm3, and emm28 in GAS and stG62647 in SD. CONCLUSIONS: Streptococcal NSTI was associated with several risk factors, including blunt trauma. Septic shock was more frequent in NSTI caused by GAS than in cases due to SD. Factors associated with mortality in GAS NSTI included age, septic shock, and no administration of IVIG.

Integrated Univariate, Multivariate, and Correlation-Based Network Analyses Reveal Metabolite-Specific Effects on Bacterial Growth and Biofilm Formation in Necrotizing Soft Tissue Infections.

Necrotizing soft-tissue infections (NSTIs) have multiple causes, risk factors, anatomical locations, and pathogenic mechanisms. In patients with NSTI, circulating metabolites may serve as a substrate having impact on bacterial adaptation at the site of infection. Metabolic signatures associated with NSTI may reveal the potential to be useful as diagnostic and prognostic markers and novel targets for therapy. This study used untargeted metabolomics analyses of plasma from NSTI patients (n = 34) and healthy (noninfected) controls (n = 24) to identify the metabolic signatures and connectivity patterns among metabolites associated with NSTI. Metabolite-metabolite association networks were employed to compare the metabolic profiles of NSTI patients and noninfected surgical controls. Out of 97 metabolites detected, the abundance of 33 was significantly altered in NSTI patients. Analysis of metabolite-metabolite association networks showed a more densely connected network: specifically, 20 metabolites differentially connected between NSTI and controls. A selected set of significantly altered metabolites was tested in vitro to investigate potential influence on NSTI group A streptococcal strain growth and biofilm formation. Using chemically defined media supplemented with the selected metabolites, ornithine, ribose, urea, and glucuronic acid, revealed metabolite-specific effects on both bacterial growth and biofilm formation. This study identifies for the first time an NSTI-specific metabolic signature with implications for optimized diagnostics and therapies.

Correlation Between Immunoglobulin Dose Administered and Plasma Neutralization of Streptococcal Superantigens in Patients With Necrotizing Soft Tissue Infections.

Analyses of plasma collected pre- and postadministration of intravenous immunoglobulin (IVIG) from patients with group A Streptococcus necrotizing soft tissue infections demonstrated a negative correlation between IVIG dose and toxin-triggered T-cell proliferation (r = -.67, P < .0001). One 25-g IVIG dose was sufficient to yield plasma-neutralizing activity against streptococcal superantigens. Clinical Trials Registration. NCT01790698 and NCT02111161.

Necrotizing Soft Tissue Infections: Case Reports, from the Clinician's Perspectives.

Necrotizing soft tissue infections (NSTI) are rapidly spreading and life-threatening infections of skin and soft tissue. Essentially there are two types of NSTI, based on the invasive microorganisms. The speed of development and associated clinical features differ markedly depending on the bacterial etiology. Early recognition, extensive surgical debridement, and appropriate antimicrobials are pivotal for successful management. In this chapter, we present three cases from the INFECT-study population. This study was an international, multicenter, prospective cohort study of adult patients with NSTI. We describe the clinical presentations, pre-, peri-, and postoperative clinical findings, microbiology, and treatment in cases of monobacillary Streptococcus pyogenes necrotizing soft tissue infections NSTI, polymicrobial infection, and an unusual presentation of pelvic monobacillary S. pyogenes infection in an immunocompromised patient.

Beta-Hemolytic Streptococci and Necrotizing Soft Tissue Infections.

ß-hemolytic streptococci are major causes of necrotizing soft tissue infections (NSTIs), Streptococcus pyogenes (group A streptococcus; GAS) in particular. NSTIs caused by Streptococcus dysgalactiae (SD) have also been reported. In the INFECT cohort of 409 NSTIs patients, more than a third of the cases were caused by GAS (31%) or SD (7%). Risk factors of streptococcal NSTIs compared to streptococcal cellulitis have previously been largely unknown. The INFECT study confirmed blunt trauma as an important risk factor. In addition, absence of pre-existing skin lesions and a lower BMI were associated with NSTIs. The study also confirmed that septic shock is more frequent in GAS cases than in other types of NSTIs. Septic shock was also among several predictors of mortality. The role of intravenous immunoglobulin (IVIG) in streptococcal NSTIs has been unclear. In the INFECT cohort, IVIG treatment was associated with increased survival. As in other studies, a significant microbial diversity was observed, but with predominance of a few emm types. Overall, the INFECT study gives a comprehensive and contemporary picture of the clinical characteristics and the microbes involved in streptococcal NSTIs. The reported severity of disease underscores the need for new efforts aimed at identifying novel diagnostic measures and improved treatment.

Microbiological Etiology of Necrotizing Soft Tissue Infections.

Necrotizing soft tissue infections (NSTIs) are severe clinical conditions requiring swift therapeutic intervention, including surgical removal of infected tissue and administration of potent antibiotics. There is wide diversity in the microbial etiologic agents, and tailoring the antibiotic treatment to the offending pathogen is essential. However, the choice of empirical therapy is frequently inadequate, underlining the need for comprehensive and contemporary knowledge on causative pathogens and relevant antimicrobial resistance patterns in NSTIs. Also, studies of the pathogenic mechanisms in different NSTIs are needed, to improve handling of patients through developing patient stratification and tailored therapies. We review the current knowledge on microbial etiology and provide detailed characterizations of the predominant pathogens.

Systems and Precision Medicine in Necrotizing Soft Tissue Infections.

Necrotizing soft tissue infections (NSTI) are multifactorial and characterized by dysfunctional, time dependent, highly varying hyper- to hypo-inflammatory host responses contributing to disease severity. Furthermore, host-pathogen interactions are diverse and difficult to identify and characterize, due to the many different disease endotypes. There is a need for both refined bedside diagnostics as well as novel targeted treatment options to improve outcome in NSTI. In order to achieve clinically relevant results and to guide preclinical and clinical research the vast amount of fragmented clinical and experimental datasets, which often include omics data at different levels (transcriptomics, proteomics, metabolomics, etc.), need to be organized, harmonized, integrated, and analyzed taking into account the Big Data nature of these datasets. In this chapter, we address these matters from a systems perspective and yet personalized approach. The chapter provides an overview on the increasingly more frequent use of Big Data and Artificial Intelligence (AI) to aggregate and generate knowledge from burgeoning clinical and biochemical information, addresses the challenges to manage this information, and summarizes current efforts to develop robust computer-aided clinical decision support systems so to tackle the serious challenges in NSTI diagnosis, stratification, and optimized tailored therapy.

Antibody Responses to Influenza A/H1N1pdm09 Virus After Pandemic and Seasonal Influenza Vaccination in Healthcare Workers: A 5-Year Follow-up Study.

Background: The 2009 influenza pandemic was caused by the A/H1N1pdm09 virus, which was subsequently included in the seasonal vaccine, up to 2016/2017, as the A/H1N1 strain. This provided a unique opportunity to investigate the antibody response to H1N1pdm09 over time. Methods: Healthcare workers (HCWs) were immunized with the AS03-adjuvanted H1N1pdm09 vaccine in 2009 (N = 250), and subsequently vaccinated with seasonal vaccines containing H1N1pdm09 for 4 seasons (repeated group), <4 seasons (occasional group), or no seasons (single group). Blood samples were collected pre and at 21 days and 3, 6, and 12 months after each vaccination, or annually (pre-season) from 2010 in the single group. The H1N1pdm09-specific antibodies were measured by the hemagglutination inhibition (HI) assay. Results: Pandemic vaccination robustly induced HI antibodies that persisted above the 50% protective threshold (HI titers ≥ 40) over 12 months post-vaccination. Previous seasonal vaccination and the duration of adverse events after the pandemic vaccination influenced the decision to vaccinate in subsequent seasons. During 2010/2011-2013/2014, antibodies were boosted after each seasonal vaccination, although no significant difference was observed between the repeated and occasional groups. In the single group without seasonal vaccination, 32% of HCWs seroconverted (≥4-fold increase in HI titers) during the 4 subsequent years, most of whom had HI titers <40 prior to seroconversion. When excluding these seroconverted HCWs, HI titers gradually declined from 12 to 60 months post-pandemic vaccination. Conclusions: Pandemic vaccination elicited durable antibodies, supporting the incorporation of adjuvant. Our findings support the current recommendation of annual influenza vaccination in HCWs. Clinical Trials Registration: NCT01003288.

Exploring the arthritogenicity of Streptococcus dysgalactiae subspecies equisimilis.

BACKGROUND: During the past decades, Streptococcus dysgalactiae subspecies equisimilis (SDSE) has been increasingly recognized as an important human pathogen. Osteoarticular infections is one of the predominant disease manifestations of SDSE, but the pathogenetic rationale for its arthritogenicity has yet to be unravelled. We aimed to explore if the rising incidence of osteoarticular infections caused by this pathogen in our region emanated from clonal expansion of strains with enhanced tropism for bone and joint tissue components or orthopaedic implants. RESULTS: Twenty-nine SDSE-isolates associated with osteoarticular infections were retrospectively identified. Their genomic content and affinity for fibronectin, collagen and stainless steel were compared to 24 temporally and geographically matched SDSE blood culture isolates obtained from patients without bone or joint infections. Despite a thorough genetic and phenotypic dissection, neither the presence or absence of any single gene, nor the binding abilities of the SDSE isolates, were predictive of clinical entity. SNP analysis revealed a heterogenous population, and a correlation between phylogenetic relationships and disease manifestation was not evident. However, we identified a strong concordance between phenotypic binding abilities and genetic variations in the pilus-region, also denoted as the FCT-region (Fibronectin binding, Collagen binding and T-antigen). This observation could be related to the ample and varied repertoire of putative adhesins residing within this region, including proteins predicted to adhere to fibronectin and collagen, as well as fibrinogen. CONCLUSIONS: SDSE strains associated with osteoarticular infections do not emanate from subpopulation characterized by distinct genetic or phenotypic traits. The genetic architecture of the pilus region was predictive of the adhesive properties of the SDSE-isolates, but its role in tissue tropism needs further investigation. To the best of our knowledge, this is the first comprehensive characterization of the genetic landscape of the SDSE pilus region.

Zoonotic necrotizing myositis caused by Streptococcus equi subsp. zooepidemicus in a farmer.

BACKGROUND: Streptococcus equi subsp. zooepidemicus is a beta-hemolytic group C streptococcus mainly causing infections in domesticated animals. Here we describe the first case of zoonotic necrotizing myositis caused by this bacterium. CASE PRESENTATION: The patient was a 73-year-old, previously healthy farmer with two asymptomatic Shetland ponies in his stable. After close contact with the ponies while feeding them, he rapidly developed erythema of his left thigh and sepsis with multiple organ failure. The clinical course was severe and complicated, requiring repetitive surgical excision of necrotic muscle, treatment with vasopressors, mechanical ventilation and continuous venovenous hemofiltration, along with adjunctive hyperbaric oxygen therapy. The patient was discharged from hospital at day 30, without obvious sequelae. The streptococcal isolate was identified as Streptococcus equi by MALDI-ToF MS, and was later assigned subspecies identification as S. equi subsp. zooepidemicus. Multilocus sequence typing identified the strain as a novel sequence type (ST 364), closely related to types previously identified in horses and cattle. A focused proteomic analysis revealed that the ST 364 expressed putative virulence factors similar to that of Streptococcus pyogenes, including homologues of the M protein, streptodornases, interleukin 8-protease and proteins involved in the biosynthesis of streptolysin S. CONCLUSION: This case illustrates the zoonotic potential of S. equi subsp. zooepidemicus and the importance of early clinical recognition, rapid and radical surgical therapy, appropriate antibiotics and adequate supportive measures when necrotizing soft tissue infection is suspected. The expression of Streptococcus pyogenes-like putative virulence determinants in ST 364 might partially explain the fulminant clinical picture.

Early Response in Cellulitis: A Prospective Study of Dynamics and Predictors.

BACKGROUND: Skin and soft tissue infections are common reasons for medical care. Use of broad-spectrum therapy and costs have increased. Assessment of early treatment response has been given a central role both in clinical trials and everyday practice. However, there is a paucity of data on the dynamics of response, causes of early nonresponse, and how early nonresponse affects resource use and predicts outcome. METHODS: We prospectively enrolled 216 patients hospitalized with cellulitis. Clinical and biochemical response data during the first 3 days of treatment were analyzed in relation to baseline factors, antibiotic use, surgery, and outcome. Multivariable analysis included logistic lasso regression. RESULTS: Clinical or biochemical response was observed in the majority of patients the day after treatment initiation. Concordance between clinical and biochemical response was strongest at days 2 and 3. Female sex, cardiovascular disease, higher body mass index, shorter duration of symptoms, and cellulitis other than typical erysipelas were predictors of nonresponse at day 3. In contrast, baseline factors were not predictive of clinical failure assessed posttreatment. Among cases with antibiotic treatment escalation by day 2, 90% (37/41) had nonresponse at day 1, but only 5% (2/40) had inappropriate initial therapy. Nonresponse at day 3 was a predictor of treatment duration >14 days, but not of clinical failure. CONCLUSIONS: Nonpharmacological factors had a major impact on early response dynamics. Delayed response was rarely related to inappropriate therapy but strongly predictive of early treatment escalation, suggesting that broadening antibiotic treatment may often be premature.

Temporal trends of ß-haemolytic streptococcal osteoarticular infections in western Norway.

BACKGROUND: Beta-haemolytic streptococci are important contributors to the global burden of osteoarticular infections (OAI). Knowledge on the disease traits specific for streptococcal OAI, however, remains scarce. We wished to explore temporal trends of OAI caused by Group A Streptococci (GAS), Group B Streptococci (GBS) and Group C and G Streptococci (GCGS), and furthermore, to describe the associated host and pathogen characteristics. METHODS: All cases of microbiologically verified ß-haemolytic streptococcal OAI in Health Region Bergen, Norway, in the period 1999-2013 were retrospectively identified. Clinical data were extracted from medical records. Microbial isolates were submitted to antibiotic susceptibility testing and molecular typing. RESULTS: A total of 24 GAS, 45 GBS and 42 GCGS acute OAI were identified. The cumulative incidence of GCGS OAI, but not GAS or GBS OAI, increased significantly from the first to the last 5-year period (IRR 5.7, p = 0.0003), with the annual incidence peaking at 1.9/100 000 in 2013. GAS OAI generally produced the most acute and severe clinical presentation, whereas GBS and GCGS predominantly affected the elderly, and were significantly associated with the presence of host risk factors of systemic and focal origin, respectively. CONCLUSIONS: We found a significantly increasing incidence of GCGS OAI, likely related to the presence of host susceptibility factors, including prosthetic material and pre-existing joint disease. With an increasing application of therapeutic and diagnostic bone and joint procedures, the rising trend of OAI caused by GCGS is likely to continue. Sustained epidemiological attentiveness to GCGS seems warranted.