Acinetobacter baumannii (AB) is a bacterium that causes infections, particularly in immunocompromised patients. Treatment is challenging due to biofilm formation by AB strains, which hinders antibiotic effectiveness and promotes drug resistance. The aim of our study was to analyze the biofilm-producing capacity of AB isolates from various forms of infections in relation to biofilm-related genes and their drug resistance. We tested one hundred isolates for biofilm formation using the crystal violet microplate method. Drug resistance analyses were performed based on EUCAST and CLSI guidelines, and biofilm genes were detected using PCR. All tested strains were found to form biofilms, with 50% being ICU strains and 72% classified as strong biofilm producers. Among these, 87% were extensively drug-resistant (XDR) and 2% were extra-extensively drug-resistant (E-XDR). The most common gene set was bap, bfmS, csuE, and ompA, found in 57% of all isolates. Our research shows that, regardless of the form of infection, biofilm-forming strains can be expected among AB isolates. The emergence of E-XDR and XDR strains among non-ICU infections highlights the necessity for the rational use of antibiotics to stop or limit the further acquisition of drug resistance by A. baumannii. Acinetobacter baumannii (AB) is an opportunistic pathogen, dominant in Central and Southern Europe in healthcare-associated infections (HAIs). It is considered by the WHO as a critical-priority pathogen, for which there is an urgent need to search for new therapeutic solutions, primarily due to acquired resistance mechanisms [chanisms ,2. It cachanisms ,4.According to the European Antimicrobial Resistance Surveillance Network (EARS Net), the prevalence of Acinetobacter isolates resistant to at least one of the antimicrobial groups varies greatly according to country, ranging from below 1% to 98.6%. In 2021, 3 countries  reported a prevalence of less than 1%, while in 25 European countries, it was above 50%—the highest level of resistant isolates is recorded in Eastern and Southern Europe, including Poland [In Polish hospitals, especially in ICUs, the dominance of extensively drug-resistant (XDR) AB, defined as those strains that are susceptible to no more than two antimicrobial classes, has been noted for many years, and it is one of the major therapeutic problems associated with Gram-negative bacilli. The prevalence of AB isolates resistant to carbapenems in 2021 reached 82.7%, while 67% were resistant to carbapenems, fluoroquinolones, and aminoglycosides together ,6,7,8.Multidrug resistance in AB is associated with numerous mechanisms—enzymatic degradation, modification of antibiotics, reduction in membrane permeability, and increased efflux. Carbapenem resistance of AB is conferred by carbapenem-hydrolyzing class D oxacillinases (OXA): OXA-23-like, OXA-24/40-like, OXA-58-like, and intrinsic OXA-51-like. Permeability to beta-lactams, efflux pumps, and ISAba1 elements located upstream of the blaOXA-51-like gene also contributes to carbapenem resistance. Often, the production of carbapenemases coexists with overexpression of efflux pumps .The connection between biofilms and antibiotic resistance is of a considerable interest to biomedical researchers. The ability to form a biofilm, which is possessed by a large percentage of AB strains (significantly higher than in the case of other Acinetobacter species ), is conIn the hospital environment, biofilm formation promotes the long-term persistence of AB on abiotic surfaces . Under uBiofilms, as organized multicellular communities of bacteria, are surrounded by self-produced exopolysaccharide matrices. The ability to form both biofilms and genes involved in this process has been studied extensively in recent years. The formation and development of the biofilm involve many virulence factors, such as the outer membrane protein A (OmpA), biofilm-associated protein (Bap), chaperon-usher pilus (Csu), extracellular exopolysaccharide (EPS), and two-component regulatory system (BfmS/BfmR) ,17,23. CThe aim of our research was to investigate the biofilm-forming ability of AB strains recovered from bloodstream infections, pneumonia, skin and soft tissue infections, and colonizing patients in relation to the presence of biofilm-related genes and antimicrobial resistance.The studied AB strains were isolated from clinical materials collected from patients hospitalized in 2019–2021 in 7 hospitals of the Silesian Province in Southern Poland  and 2 hospitals of the Opolskie Province  and from materials collected as part of screening tests at the University Hospital in Krakow. The collection was stored in the laboratory of the Department of Microbiology at −70 °C.One hundred AB isolates were randomly selected applying the principle of one isolate from one patient, taking into account three clinical forms of infection, such as bloodstream infection (BSI), pneumonia (PNEU), skin and soft tissue infections (SSTIs), and colonization. Patients were hospitalized in ICU and non-ICU units . In this way, 25 isolates from BSI, 25 from PNEU, 25 from SSTIs, and 25 from patients without symptoms of infection (colonization) were collected.The strains were collected in accordance with the consent of the bioethics committee of the Jagiellonian University KBET 1072.6120.274.2021 and KBET 1072.6120.2.2021.® 19606™, was used in the study as a positive control in the experiment on the production of biofilm by bacterial isolates [Isolates were identified using automated systems , depending on the hospital laboratory. In addition, the intensively producing biofilm reference strain, AB ATCCisolates .Antibiotic susceptibility was determined based on the results of an automated system, MIDITECH Analyser v.12. The results were interpreted using the clinical breakpoints defined in the latest EUCAST guidelines—v. 13.0  For cefoThe pattern of antimicrobial resistance was defined as the set of antibiotics to which at least two strains are resistant. For all strains, the multi-antibiotic-resistant (MAR) index was calculated. The MAR index is the number of antibiotics that an isolate is resistant to divided by the total number of antibiotics utilized in the study .MAR InThe Genomic Mini AX Bacteria Kit  was used to extract genomic DNA from AB isolates following the manufacturer’s protocol. The concentration and purity of the isolated DNA was assessed using a Nano Drop Lite spectrophotometer . DNA extracted from pure cultures was stored at −20 °C for further study.blaOXA-23,blaOXA-40, blaOXA-58, and blaNDM [blaOXA-23 (718 bp), blaOXA-40 (413 bp), blaNDM (517 bp), and blaOXA-58 (303 bp) genes were identified .Quantification of biofilm formation was performed as previously described by Stepanovic  with som8 CFU/mL) in saline was prepared from colonies on Tryptic Soy Agar (TSA) plates . Twenty microliters of the prepared bacterial suspension was mixed with 1980 μL of Tryptic Soy Broth (TSB)  and applied to 24-well flat-bottomed plates  yielding a titer of approximately 1.5 × 106 CFU/mL.Briefly, a bacterial suspension of approx. 0.5 MacFarland  was used as a negative control. ATCC 19606 strain was used as a positive control. After incubation, the medium with unbound cells was gently removed, then carefully rinsed three times with PBS and fixed with methanol for 30 s. The plate was dried overnight at 37 °C upside down, and then the biofilm was stained with crystal violet (1000 µL) for ~15 min at room temperature. After this time, the dye was poured off and rinsed with distilled water until the water in the wells was colorless. Again, it was dried overnight at 37 °C upside down. After the plate was completely dried, the optical density absorbance was measured at 570 nm on the surface of the biofilm formed at 225 points of each well. For each strain, two replicates were analyzed to detect the biofilm formation ability.Using the i-control software (ver. 2.0.10.0), the mean optical density (OD) and standard deviation (SD) values were calculated for each test isolate and all replicates. The cut-off point (ODc) was calculated using the following formula: ODc = mean OD of the negative control + (3 × standard deviation (SD) of the negative control). The averaged OD value of the tested isolates was reduced by the ODc value. The ODc value was calculated for each 12-well plate separately.The strains were categorized according to Stepanović  into fouGenomic DNA was extracted as described above.bap, csuE, ompA, bfmS, and espA were identified  was used to find significance between associations for the different combination of the biofilm genes and the ODs and significance between the MDR or XDR and the type of the produced biofilm. The results were considered significant at p ≤ 0.05.In statistical analyses, the determination of significant differences between the groups of isolates with low and moderate biofilm production and the group with intensive biofilm production and the clinical types of infection or colonization  was demonstrated in the cross-analysis in the Fisher–Freeman–Halton exact test with two-sided exact significance A total of 100 AB isolates were tested following the principle of 1 strain per patient, including 25 from PNEU, 25 from SSTI, 25 from BSI, and 25 from colonization. Fifty-three percent of the strains came from ICU patients, including all colonization strains from ICU, 56% from PNEU infections, and 44% from BSI infections. In contrast, only 12% of SSTIs were from ICU. The morbidity and distribution of AB in ICU and non-ICU isolates are shown in p = 0.023) and meropenem (p = 0.023) between strains from the colonization and SSTI groups and for gentamicin between the colonization and SSTI; In the BSI and PNEU groups , no significant differences were observed in the case of other antimicrobials and the other groups of strains (The highest rate of resistance was for cefoperazone/sulbactam (95%) and the lowest was for colistin (8%). Strains resistant to both carbapenems (imipenem and meropenem) were 69%, and 45% were resistant to the carbapenems, fluoroquinolones, and aminoglycosides tested. A significant difference was found for resistance to imipenem  . Among tblaOXA-40 (42%); considering the clinical form of infection, it was detected in 72% of strains from SSTI and 56% of strains from colonization. In turn, in BSI strains, the blaOXA-23 gene was found more often (44%). Three strains isolated from patient colonization had the blaNDM gene (BlaNDM gene was carried together with the blaOXA-23 gene. Two strains (from PNEU and colonization) had a combination of OXA-51/ISAba-I upstream. None of the isolates carried the blaOXA-58 gene. Further, 17 of the 31 strains that were carbapenem-sensitive in the phenotypic study, nevertheless, had one of the oxacillinase genes.The most frequently detected gene among all AB strains was NDM gene . The BlaQuantification of biofilm production showed that all tested isolates (n = 100) produce a biofilm: 3% were classified as weak producers of biofilm, 25% as moderate, and 72% as strong . Among tA group of strains characterized by weak and moderate biofilm production was combined for statistical analyses, due to the small number of strains in the group of weak biofilm producers (n = 3 and n = 25).p < 0.001) were found between the type of infection and the ability to form a biofilm among the isolates from the colonization group in relation to BSI and SSTI. No differences were found between isolates from different clinical forms of infection (Most of the strains strongly producing a biofilm were in the group of colonization and PNEU. Significant differences (two-sided exact significance nfection .p = 0.012) was found between the number of isolates resistant to gentamicin in the group of strong biofilm producers  and in the group of weak and moderate biofilm producers .The correlation between biofilm formation and resistance to specific antibiotics was also analyzed. All colistin-resistant strains (n = 8) were strong biofilm producers. A statistically significant difference  and groups of different biofilm producers  in different groups of origin of the strains  is shown in a radar chart . There wAB strains, regardless of the origin of the strains, were characterized by a similar distribution of XDR resistance. Among SSTI isolates, it was 68% (n = 17), BSI 76% (n = 19) and PNEU 76% (n = 19), and colonization was 80% (n = 20).All weak biofilm-producing strains (n = 3) were isolated from SSTI, while moderate biofilm-producing strains were present in all other groups, and most of them  were isolated from BSI.ompA 99%, while the least frequently detected was the epsA gene 26%.Among the tested isolates, the most frequently detected gene was bap/bfmS/csuE/ompA, observed in 57% of isolates. Among them, 66.67% (n = 38) belonged to the group of strong biofilm producers.The most common characteristic genotype was bap/bfmS/csuE/ompA/epsA, was less frequent (19%), but 78.9% (n = 15) of isolates with this set were strong producers of a biofilm. The third most common set of genes, bfmS/csuE/ompA, present in 12% of isolates, concerned 74% (n = 9) of strong biofilm producers.The set of all five tested genes, bap/bfmS/csuE/ompA, more than half of the isolates were isolates from the colonization group . The same genotype was the least frequent in the group of isolates from BSI . Moreover, the same set of genes was found among all E-XDR strains  and in 89.47% (n = 34) of XDR strains . Also, most belonged to the XDR group (75%) and were resistant to imipenem and meropenem (69%), noting that only half of the isolates were from ICU. It is alarming to note eight colistin-resistant strains that were isolated during screening tests from asymptomatic patients.In our study, the vast majority of AB strains (72%) strongly produced a biofilm and were characterized by the presence of four genes associated with biofilm formation  . Other ablaOXA-40 (42%) and blaOXA-23 (26%), which confirms our previous studies as well as other reports from Poland [BlaNDM gene was also detected in three strains from colonized patients. Slightly over 26% of carbamenem-resistant strains did not carry any of the oxacillinase genes tested; however, carbapenem-hydrolyzing class D β-lactamases (CHLD) have so many types of oxacillinase that it is possible that they have other genes not detected in our study. Resistance in AB also results from non-enzymatic mechanisms of resistance, e.g., activity of efflux pumps. One family of efflux pumps is the RND family. This efflux pump is also involved in biofilm formation and maturation. Yoon et al. [The predominant carbapenemases genes in the studied AB strains were m Poland ,39,40. Tn et al.  showed tlaOXA-40 % and blan et al.  indicateThe vast majority of studied strains tested in this publication were biofilm-producing strains, including strong producers, which accounted for 72%. In studies, where, like in ours, the association between biofilm formation and antimicrobial resistance was checked, regardless of the mechanism, a positive correlation was found much more often; strains strongly producing biofilms were characterized by higher resistance, primarily to antibiotics from the group of B-lactams and aminoglycosides, or the XDR phenotype in general ,45,46,47In our earlier research , the vasIn our current study, most of the strains were classified as strong biofilm producers. We introduced—in relation to previous experiments—a modification of the study and assessment of biofilm intensity; namely, we read the absorbance of crystal violet on the surface of the created biofilm instead of in the solution, and, additionally, the measurement was made at 225 points. This approach allows for the classification of strains into a given group of biofilm producers with high accuracy. We showed a significant relationship in strains isolated from patients without clinical symptoms of infection and strains isolated from patients with pneumonia and between AB strong biofilm producers. Most of these patients were hospitalized in ICUs. The vast majority of strains strongly producing biofilms were XDR type, including all of them being resistant to colistin. The only antibiotic for which those isolates were more likely to produce less biofilm was gentamicin.AB survival on often-touched surfaces may have an impact on the spread of AB strains in hospital environments. It is extremely important to understand the impact of biofilm formation and antibiotic resistance on AB survival in the hospital environment. Greene et al.  indicatebap, bfmS, csuE and ompA), from which 87.2% are XDR. Other studies report a high frequency of csuE, bap, and ompA genes [epsA, which codes for extracellular exopolysaccharide, which is consistent with the reports of Thummeepak et al. and inconsistent with Zeighami et al. [ompA and bap gene products may contribute to the drug-resistant AB phenotype, especially OmpA, an outer membrane porin.The presence of genes that are mainly associated with biofilm production was confirmed in both strong and moderate biofilm producers. The strong biofilm-producing AB represents 70% of the most common set of genes  and highly biofilm-forming strains. These strains pose a serious threat to patients and a challenge for physicians in treatment ,53. In tNew strategies are also being sought to combat biofilm-forming and multidrug-resistant strains, such as new antibiotics, e.g., synthetic lipopeptides , naturalRegardless of the search for new solutions in the fight against multidrug-resistant AB, infection prevention and control are important in reducing AB infections. These include hand hygiene, environmental cleaning, provision and appropriate use of personal protective equipment, appropriate training of healthcare staff, and promotion of antimicrobial stewardship programs ,6,64. InCurrent research on biofilm-forming AB, including ours, focuses mainly on the assessment of biofilm formation and its impact on bacterial resistance and survival in the environment; however, research on agents that destroy biofilms and interact with antibiotic therapy is also needed. Therefore, in our future studies, we plan to research, among others, the influence of bacteriophages on biofilms.In this study, we did not detect the presence of efflux pumps from the RND family in the tested strains. Also, the effectiveness of cefiderocol on the tested strains was not tested. Strain genotyping was not performed. We have no information about the type of resistance to colistin  and about the association of BSIs when using catheters.


Automated surveillance methods that re-use electronic health record data are considered an attractive alternative to traditional manual surveillance. However, surveillance algorithms need to be thoroughly validated before being implemented in a clinical setting. With semi-automated surveillance patients are classified as low or high probability of having developed infection, and only high probability patients subsequently undergo manual record review. The aim of this study was to externally validate two existing semi-automated surveillance algorithms for deep SSI after colorectal surgery, developed on Spanish and Dutch data, in a Swedish setting.The algorithms were validated in 225 randomly selected surgeries from Karolinska University Hospital from the period January 1, 2015 until August 31, 2020. Both algorithms were based on (re)admission and discharge data, mortality, reoperations, radiology orders, and antibiotic prescriptions, while one additionally used microbiology cultures. SSI was based on ECDC definitions. Sensitivity, specificity, positive predictive value, negative predictive value, and workload reduction were assessed compared to manual surveillance.Both algorithms performed well, yet the algorithm not relying on microbiological culture data had highest sensitivity , which was comparable to previously published results. The latter algorithm aligned best with clinical practice and would lead to 57% records less to review.The results highlight the importance of thorough validation before implementation in other clinical settings than in which algorithms were originally developed: the algorithm excluding microbiology cultures had highest sensitivity in this new setting and has the potential to support large-scale semi-automated surveillance of SSI after colorectal surgery. Healthcare-associated infections (HAIs) pose a major burden on the healthcare system, and result in increased morbidity, mortality, prolonged hospital stay, and additional costs –3. HAIs Continuous surveillance with feedback to healthcare personnel and stakeholders is essential to allocate the required resources and assess the effect of interventions to prevent HAIs. Traditional HAI surveillance is often based on time-consuming and resource-intensive manual review of patient records, which is also prone to subjective interpretation and surveillance bias –7. AutomIn this study, the aim was to externally validate two existing semi-automated surveillance algorithms for deep SSI after colorectal surgery, developed based on Spanish and Dutch data , 9, in aThis retrospective study used EHR data from the Karolinska University Hospital (KUH) stored in the 2SPARE (2020 started Stockholm/Sweden Proactive Adverse Events REsearch) database. KUH is a tertiary care academic center with 1,100 beds divided between two hospitals (Huddinge and Solna), which serves the population of Region Stockholm (2.3 million inhabitants). The study was approved by the Regional Ethical Review Board in Stockholm (no. 2018/1030-31).With semi-automated surveillance patients are divided in low- and high-probability cases where low-probability cases are automatically regarded as no SSI while high-probability cases undergo manual record review to determine SSI status . Two exiOriginal classification algorithm of van Rooden et al., i.e., probability of having a deep SSI based on (re)admission and discharge data, mortality, reoperations, radiology orders, antibiotic prescriptions, and microbiology cultures ;Adapted classification algorithm according to Verberk et al., i.e., probability of having a deep SSI based on the original classification algorithm without the microbiology component .The algorithms’ performance was assessed in a validation cohort of 225 colorectal surgeries selected via simple random sampling from the 2,675 performed surgeries in the period January 1, 2015 until August 31, 2020  and Python (version 3.7), and in accordance with current regulations concerning privacy and ethics. For algorithm performance, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were assessed. The confidence interval (CI) for these estimates were calculated using the asymptotic variance with Wilson score method.Within the validation cohort the median age was 66 year (IQR 55–75), 48.9% (n = 110) were female and the median body mass index was 25.6 (IQR 22.3–29.4). Most surgeries were primary , open procedures  and related to malignancy . The surgeries had a median duration of 316 min (IQR 206–427) and in 41.8% (n = 94) of surgeries a stoma was created. In 36.5% (n = 82) of surgeries the patient had an ASA class ≥ 3 and 24.0% (n = 54) of surgeries had a contaminated or dirty-infected wound classification. Within 30-days after surgery 18.2% (n = 41) of patients developed a deep SSI and 2.2% (n = 5) of the patients died.Both semi-automated algorithms were applied to the validation cohort. Ordered radiology  and receiving antibiotic therapy for ≥ 3 consecutive days  were the most common components. In 38.7% (n = 87) of surgeries ≥ 14 days length-of-stay, readmission and/or mortality was present and in 31.1% (n = 70) a microbiological culture was taken. A reoperation  was the least common component.Of the 41 patients with a deep SSI, 34 were classified as high probability by the original algorithm  while 40 were classified as high probability by the adapted algorithm  admission and discharge dates, mortality, reoperations, radiology orders and antibiotic prescriptions, performed best and outperformed the original classification algorithm which also included microbiology culture data. Only one mild case of deep SSI was missed, which would be hard to detect using only structured data as it was assessed merely based on a free-text medical note.The original algorithm using microbiology culture data was less useful for this specific clinical setting as microbiological culture practices are not standard in suspected deep SSIs after colorectal surgery. However, this might be different in other settings and highlights the importance of thoroughly validation before implementation and pre-emptively investigating if algorithms correspond with clinical practices . It shouAlthough the original semi-automated classification algorithm was developed based on Spanish and Dutch data, and validated and adapted in the Netherlands, also within Sweden the sensitivity was high and comparable with previous results , 9. ThesStrengths of our study were the independent external validation with the extensive availability of EHR data through which the performance of epidemiological surveillance using real-world, real-time data could be mimicked. Limitations were the usage of data from only one center in Sweden, focus of algorithms on only deep SSI and that absence of active post-discharge surveillance of SSI could result in missed SSI.In conclusion, the results from this study in Sweden, in conjunction with previous studies in the Netherlands and Spain, indicate that a classification algorithm based on (re)admission and discharge dates, mortality, reoperations, radiology orders and antibiotic prescriptions, could be widely implemented for semi-automated surveillance of SSI after colorectal surgery.


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