Acinetobacter baumannii is a Gram-negative, non-fermentative bacterium that has emerged as a significant pathogen in hospital environments due to its remarkable ability to survive on various surfaces and its intrinsic resistance to many antibiotics (Shi et al., 2024). This bacterium is one of the most problematic organisms in healthcare-associated infections (HAIs), responsible for severe infections such as ventilator-associated pneumonia (VAP), bloodstream infections (BSI), skin and soft-tissue infections, and bacteremia. These infections often result in ineffective early-stage treatment and increased mortality rates (Fu et al., 2015). A survey of nosocomial infections in tertiary general hospitals in China identified A. baumannii as the most common pathogen in HAIs (Jian et al., 2023). Reports of extensively drug-resistant A. baumannii (XDRAB) are increasing, with ventilator-associated pneumonia (VAP) and bloodstream infections (BSI) being the most common and having high mortality rates. In recent years, the probability of detecting XDRAB in ICU patients has been increasing (Fang et al., 2023; Fitzpatrick et al., 2022). This pathogen has multiple resistance mechanisms, rendering conventional antimicrobial drugs ineffective. ICU patients often have severe and complex conditions, poor baseline health, and are frequently co-infected with VAP and BSI, leading to a bloodstream infection mortality rate of 40% (Garnacho-Montero et al., 2015). Although studies on XDRAB infection exist, regional variations necessitate early detection of risk factors and effective interventions to reduce mortality, minimize complications, and improve patient prognosis. This article aims to retrospectively analyze clinical data from XDRAB-infected patients to establish a practical infection prediction model using various statistical analyses. Line graphs will be employed to convert complex regression equations into easy-to-read visuals, facilitating the assessment of XDRAB infection risk.

The aim of this study was to investigate potential risk factors for extensively drug-resistant Acinetobacter baumannii (XDRAB) infection in hospitalized patients and to develop a prediction model for such infections. XDRAB infections cause prolonged hospitalization, complications, increased patient mortality, and significant financial burden on patients’ families (Zhen et al., 2021). In our study, we used LASSO regression and multivariate logistic regression analyses to identify the most influential factors, thereby reducing confounding bias. The results indicated that ICU length of stay, hypoproteinemia, glucocorticoid use, urinary catheters, mechanical ventilation, diabetes mellitus, carbapenem use, and β-lactamase inhibitor medications were independent risk factors for XDRAB infection in hospitalized patients. Subsequently, we developed a nomogram based on these eight predictors, which has great potential for clinical application in early detection of XDRAB infection.

In our previous survey, the detection rate of XDRAB was highest in ICU wards, accounting for almost 50% of the hospital’s detection rate, making the ICU a “reservoir” of XDRAB. ICU patients often suffer from acute or critical illnesses, many with underlying diseases, rapid progression, and a high risk of disease deterioration. The risk of XDRAB infection increases under high doses of antimicrobials due to low patient mobility, prolonged bed rest, difficulty in cooperating with clinical examinations, and more invasive procedures weakening the body’s protective barriers (Wu et al., 2023). Our study showed that the risk of XDRAB infection increased significantly with ICU stay, particularly for stays longer than seven days. Therefore, early transfer from the ICU to general wards could reduce the risk of XDRAB infection for eligible patients.

We also found that patients with hypoproteinemia were more susceptible to XDRAB. Hypoproteinemia, an indicator of weakness and instability, often leads to lower immunity and poorer physical condition, particularly in ICU patients, increasing the risk of infection (Ushizawa et al., 2016). A study has shown a strong association between hypoproteinemia and death from AB infection (Zhang et al., 2020). The extensive drug resistance of XDRAB, coupled with the low immunity of patients, further elevates the risk of infection.

Prolonged and extensive use of glucocorticoids impairs immune function by reducing the immune response. This suppression of alveolar macrophages leads to increased colonization by respiratory pathogens, toxin accumulation, and a shift in favor of pathogenic bacterial growth (Hogg, 2012). Research has identified steroid use as an independent risk factor for mortality from bacteremia in patients infected with AB (Townsend et al., 2015; Ballouz et al., 2017).

The ICU environment, combined with complex patient conditions, can lead to aerosol contamination from open suctioning operations, increasing the chance of cross-infection. AB’s ability to produce biofilm enhances its colonization, allowing it to persist on artificial devices like mechanical ventilation equipment and catheters. Our study identified prolonged mechanical ventilation and urinary catheter use as independent risk factors for XDRAB infection. Mechanical ventilation compromises normal physiological function, connecting the airway to the external environment, destroying the weaker defense barrier, and allowing colonized XDRAB to enter the lower respiratory tract, leading to infection (Zilberberg et al., 2016; de Carvalho Baptista et al., 2018). Due to the drug resistance of XDRAB, the infection is difficult to control, leading to a vicious cycle, increased difficulty in weaning patients off mechanical ventilation, and even a higher risk of death (Huang et al., 2018). Indwelling urinary catheters, commonly used in clinical treatment for postoperative patients and those with incontinence or urinary retention, also facilitate AB colonization and the development of drug resistance. Meta-analyses, A recent meta-analysis identified the use of urinary catheters as one of the risk factors for XDRAB infection (Deshwal et al., 2023).

Among the underlying diseases in this cohort, including cerebrovascular disease, cardiovascular disease, chronic pneumonia, hypertension, and diabetes, only diabetes was a risk factor for XDRAB infection. Diabetes is often accompanied by complications and disturbances in humoral immunity, such as a reduced response of complement factor 4 and cytokines after stimulation. Additionally, studies have shown that the function of polymorphonuclear cells and monocytes/macrophages (chemotaxis, phagocytosis, and killing) is impaired in diabetics. High glucose environments also enhance the virulence and adherence of certain pathogens (Geerlings and Hoepelman, 1999). Diabetic patients often face impaired blood perfusion, reducing the effectiveness of antimicrobial drugs and facilitating the growth of drug-resistant bacteria. A report from Malaysia indicated that Chinese diabetic patients are more susceptible to CRAB infections and face a higher risk of death, potentially due to genetic factors that make them more prone to severe diseases compared to other ethnic groups (Woon et al., 2021). Many diabetic patients who initially respond to antimicrobial treatment for MDRAB are found to be reinfected with drug-resistant bacteria within a month (Lin et al., 2016). Ching-Hsiang Leung’s team reported that hypoglycemia is a risk factor for increased mortality in CRAB-infected patients and emphasized the importance of glycemic control, noting that insulin therapy is a major cause of hypoglycemia (Leung and Liu, 2019). Interestingly, a recent study found AB presence in the serum of 23% of tested type 2 diabetic patients (Perera et al., 2021). There remains a need for more prospective studies in the areas of glycemic control and XDRAB infection to further validate these findings.

For ICU patients or other high-risk individuals, prophylactic use of antimicrobial drugs is common, often involving combinations of these medications. However, the irrational use of antibiotics and their inherent toxicity can disrupt the patient’s microbiota, leading to the emergence of bacterial resistance, invasion by colonizing bacteria, and replacement of sensitive bacteria with resistant strains. This also results in decreased immunity and increased risk of infection by resistant pathogens (Bassetti et al., 2018). Our study identified the prophylactic use of carbapenems (such as imipenem and meropenem) and β-lactamase inhibitors (such as piperacillin/tazobactam and cefoperazone/sulbactam) as independent risk factors for XDRAB infection. Treating AB infections is particularly challenging in distinguishing between acute infection and upper respiratory tract colonization in critically ill patients, especially those with severe immunodeficiency or other high-risk factors. Consequently, empirical treatment for AB is often initiated when the clinical diagnosis is unclear (Bartal et al., 2022).

Sensitivity thresholds for some antimicrobials against XDRAB vary between CLSI and EUCAST. Currently, the isolation rates of CRAB worldwide range from 30% to 80%, with higher rates generally observed in Asian countries (Seifert et al., 2022). Studies have shown that once resistance to carbapenems develops, resistance to many other antimicrobials often follows (Zhang et al., 2017). XDRAB resistance to carbapenems is usually associated with the horizontal gene transfer of oxacillinase (OXA) genes, particularly OXA-23 and OXA-24/40.

Piperacillin-tazobactam, often used empirically due to its pharmacodynamic efficacy when administered in high doses with extended infusions, remains effective against E. coli, K. pneumoniae, and P. aeruginosa. However, it is ineffective against A. baumannii due to high resistance rates, and frequent empirical use can select for highly resistant strains. Sulbactam, primarily a β-lactamase inhibitor, is typically combined with β-lactam antibiotics to prevent enzymatic degradation. Nevertheless, increasing resistance to cefoperazone/sulbactam in A. baumannii has been observed. Therefore, the rational use of antimicrobials, especially carbapenems and β-lactamase inhibitors, remains crucial.

Antimicrobial use is generally guided by bacterial culture and sensitivity results, but traditional identification methods are time-consuming. Emerging high-throughput sequencing technologies, such as Next-Generation Sequencing (NGS), can rapidly detect and characterize pathogens. Although NGS offers significant advantages, its high cost currently limits widespread clinical adoption (Wen et al., 2020).

Our study utilized LASSO regression analysis to screen clinical variables, effectively reducing data dimensionality and preventing multicollinearity among independent variables. This approach addresses the limitations of retrospective studies, which are often constrained by sample size and cannot include a large number of variables. As a visualization method for predictive models, nomograms have become increasingly popular in clinical research. The factors influencing XDRAB infection are complex and interrelated. The predictive model developed in this study, based on eight independent risk factors identified through regression analysis, is user-friendly and allows for quantitative risk assessment. This aids clinicians in quickly assessing the risk of XDRAB infection using existing clinical data and implementing timely isolation and treatment measures. Moreover, this study employed stringent inclusion and exclusion criteria, ensuring a sufficient sample size and relevant factors. The nomogram underwent internal and external validation, demonstrating excellent discrimination, calibration, and strong clinical utility and stability.

However, this study has certain limitations. Firstly, being a single-center study, the model’s coefficients might vary under different circumstances, introducing geographic bias and limiting generalizability. External validation with datasets from other healthcare institutions, regions, and countries is necessary. Secondly, as a retrospective study, the data were obtained from electronic medical records and laboratory systems, which could result in some data being incomplete, and some factors that we intended to include in the statistical analysis could not be included. Selection bias is also unavoidable. Future prospective studies are needed to further validate these findings.

In this study, we identified that ICU length of stay, hypoproteinemia, glucocorticoid use, urinary catheters, mechanical ventilation, diabetes mellitus, carbapenem use, and β-lactamase inhibitor use were significantly correlated with XDRAB infection. Using these eight indicators, we developed a nomogram for individualized and visualized prediction of XDRAB infection risk in hospitalized patients. This predictive model facilitates early identification and mitigation of avoidable risks, allows for timely isolation and treatment of high-risk patients, and guides clinicians in rational antibiotic use. These findings provide valuable insights for improving the prevention and control of hospital-associated infections.