Factors associated with Acinetobacter baumannii lower respiratory tract infection in the respiratory intensive care unit patients: a cross-sectional observational study

Introduction

Acinetobacter baumannii (A. baumannii) is an aerobic, Gram-negative bacillus or coccobacillus belonging to non-fermenting bacteria. It can be found in the natural environment such as water and soil, as well as hospital settings, especially on the surface of medical devices in the intensive care unit (ICU) (1). Due to its ability to survive on abiotic surfaces and strong resistance to disinfectants, A. baumannii has become a critical priority pathogen listed by the World Health Organization. This designation is attributed to its high rate of antimicrobial resistance and the high morbidity and mortality associated with infection in ICU (2). A. baumannii is also one of the core pathogens causing hospital-acquired pneumonia (HAP), ventilator-associated pneumonia (VAP) and severe pneumonia in immunocompromised hosts (3,4). Invasive mechanical ventilation, indwelling catheters, ICU admission, trauma and burn departments, prolonged hospital stay, underlying chronic diseases, immunodeficiency, antibiotic exposure, glucocorticoid use, respiratory failure, hyperlactatemia and other factors have been associated with A. baumannii infection (5-8). Animal experiments and in vitro studies have demonstrated that mice with humoral immune deficiencies exhibit increased susceptibility to A. baumannii and difficulty in controlling infections. The humoral response induced by intranasal inoculation of heat-inactivated A. baumannii protected immunodeficient mice from infection by the highly virulent LAC-4 strain (9). Peripheral blood CD4⁺ T-cell count on admission serves as an independent predictor of A. baumannii co-infection in patients with H7N9 influenza. Among routine clinical biomarkers including procalcitonin (PCT) and C-reactive protein (CRP), CD4⁺ T-cell count remains an independent predictive indicator. Immune disturbance characterized by abnormal T lymphocyte counts, impaired antigen-specific T-cell responses, and dysregulated plasma cytokines plays a pivotal role in the pathogenesis of H7N9 influenza complicated by A. baumannii superinfection (7). Impaired phagocytic activity of monocytes and granulocytes, as well as compromised T-cell function in severe coronavirus disease 2019 (COVID-19) patients, implies more severe immunosuppression (10). A marked depletion of lymphocytes has been observed in sepsis, which profoundly impairs T-cell responses to infection, as well as the humoral immune response elicited by B cells and supported by specific CD4⁺ T follicular helper (TFH) cell subsets (11). Moreover, patients with immune paralysis such as reduced lymphocyte counts, absolute T-cell counts, and naive CD4⁺ T-lymphocytes, usually have a poorer prognosis (12,13). Accordingly, host immune function may be correlated with A. baumannii LRTI and subsequent clinical outcomes.

Abnormal immune parameters may reflect either intrinsic host susceptibility or secondary alterations triggered by established infection (14). Moreover, most current studies have focused on the epidemiological and drug resistance analysis of A. baumannii infection in ICU patients. Clinical studies on the correlation between immune indicators [e.g., serum globulin (GLB), T lymphocyte subsets, B lymphocytes] and infection in the respiratory intensive care unit (RICU) patients remain limited.

This study aimed to screen immune-related factors for infection by examining differences in immune function indicators between RICU patients with A. baumannii LRTI and colonization. Furthermore, we sought to preliminarily construct an associated factor model for A. baumannii infection in RICU patients, providing evidence for clinical early warning and identification of A. baumannii LRTI in RICU. This may facilitate timely implementation of effective anti-infection and immunotherapy regimens, thereby improving the clinical prognosis of RICU patients with A. baumannii infection. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0759/rc).

Methods

Study design

This single-center retrospective cross-sectional observational study was performed among patients with A. baumannii lower respiratory tract infection (LRTI) or colonization admitted to RICU. A consecutive sampling method was adopted. The primary design aimed to enroll RICU patients with initial isolation of A. baumannii, classify them into LRTI group and colonization group, compare differences in demographic, clinical, laboratory and adaptive immune indicators, examine the factors associated with A. baumannii LRTI. The enrollment period spanned from January 1, 2023, to December 31, 2023. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Fuzhou Pulmonary (Thoracic) Hospital of Fujian Province (Fuzhou Tuberculosis Prevention and Treatment Hospital of Fujian Province) [approval No. 2025-029 (Research)-01] and individual consent for this retrospective analysis was waived.

Study subjects

All eligible inpatients admitted to the RICU during the study period with the first positive microbiological culture of A. baumannii from respiratory specimens or peripheral blood were consecutively screened and enrolled without additional selective exclusion, reducing potential selection bias. Inclusion criteria: (I) age ≥18 years old; (II) A. baumannii isolated from respiratory specimens [qualified sputum, bronchoalveolar lavage (BAL) fluid, endotracheal aspirate (ETA), pleural effusion] or peripheral blood samples by the microbiology laboratory from January 1 to December 31, 2023; (III) complete basic clinical and laboratory data available for analysis. Exclusion criteria: (I) age <18 years old; (II) pregnant or lactating women; (III) transfer out of RICU within 24 hours without complete clinical evaluation data.

Diagnostic criteria

A. baumannii LRTI was diagnosed according to the 2016 Clinical Practice Guidelines for the Management of Adults with Hospital-Acquired and Ventilator-Associated Pneumonia by the Infectious Diseases Society of America and the American Thoracic Society, and the Chinese Guidelines for the Diagnosis and Treatment of Adult Hospital-Acquired Pneumonia and Ventilator-Associated Pneumonia (2018 Edition) by the Infection Group of the Respiratory Disease Branch of the Chinese Medical Association (15-17). Patients either admitted to the RICU or received invasive mechanical ventilation for more than 48 hours who met two or more of the following clinical diagnostic criteria for HAP or VAP were included: (I) fever (>38 ℃) or hypothermia (<36.5 ℃); (II) purulent airway secretions; (III) peripheral blood white blood cell count >10×10⁹/L or <4×10⁹/L. Additionally, all episodes of infection had to have a positive microbiological isolation in the ETA of at least 10⁵ colony-forming units (CFU) per mL, or with BAL of at least 10⁴ CFU per mL, or qualified sputum of at least 10⁴ CFU per mL, to be included in the final analysis. Patients with new or progressive pulmonary infiltration, consolidation or ground-glass opacity on chest X-ray or chest computed tomography (CT) were diagnosed with HAP or VAP; those without relevant imaging findings were diagnosed with hospital-acquired or ventilator-associated tracheobronchitis. The differentiation between infection and colonization was determined by consensus evaluation from one associate chief physician, one associate chief radiologist, and one associate chief clinical laboratory physician. All raters made comprehensive judgments based on the unified diagnostic criteria, combined with infectious biomarker results, clinical manifestations, chest imaging findings, and microbiological laboratory data. Patients meeting the above clinical diagnostic criteria were defined as the A. baumannii infection group, others were assigned to the colonization group. The primary outcome was defined as in-hospital adverse outcome, including all-cause in-hospital death or withdrawal of life-sustaining treatment owing to critical illness during hospitalization.

Data collection

All data were retrospectively extracted from hospital electronic medical record system, laboratory information system and imaging system. Collected variables included demographic characteristics, underlying diseases, pre-infection treatment and antibiotic exposure, drug resistance of A. baumannii in the first clinical sample, patient survival rate, disease severity scores within 24 hours of infection onset [Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score].The following laboratory data were collected within 24 hours of symptom onset for patients in the A. baumannii LRTI group, or within 24 hours after collection of the first A. baumannii-positive culture specimen for those in the colonization group: routine blood indices [white blood cell (WBC) count, neutrophil (NEUT) count, lymphocyte (LY) count, neutrophil-lymphocyte ratio (NLR), hemoglobin (Hb) concentration, platelet (PLT) count], inflammatory biomarkers (CRP, PCT), and other biochemical and clinical indicators [total bilirubin (TBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum total protein (TP), serum albumin (ALB), serum GLB, albumin-globulin ratio (A/G), blood urea nitrogen (BUN), creatinine (CREA), N-terminal pro-B-type natriuretic peptide (NT-proBNP), oxygenation index (PaO₂/FiO₂), arterial blood lactic acid (Lac)]. Peripheral blood CD3⁺ T lymphocytes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes, and CD19⁺ B lymphocytes count were collected for the enrolled patients within 48 hours after RICU admission.

Statistical analysis

IBM SPSS 19.0 statistical software was used for data analysis. Kaplan-Meier survival curves were applied to analyze the prognosis of patients in the infection group and the colonization group. The one-sample K-S goodness-of-fit test was used to verify the normal distribution of measurement data. Non-normally distributed measurement data were expressed as median (interquartile range) [M (Q1, Q3)] and compared between groups by the Mann-Whitney U test. Normally distributed measurement data were expressed as mean ± standard deviation (x¯±s) and compared between groups by the independent samples t-test. Count data were expressed as number (percentage) [n (%)] and compared between groups by the χ² test, or Fisher’s exact test when necessary. For multivariate binary logistic regression modeling: candidate associated factors were preliminarily screened by univariate analysis with a threshold of P<0.05 for preliminary inclusion. In addition, variables with confirmed clinical relevance to A. baumannii LRTI according to published literature were forced into the regression model regardless of univariate P value. All continuous immune and laboratory indicators were directly incorporated into the model in their original continuous form without categorization. Collinearity among explanatory variables was assessed by variance inflation factor (VIF). Given the limited sample size of the colonization group, variables with a VIF >2 were excluded to minimize bias arising from multicollinearity. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the accuracy of associated factors, and the Youden index was adopted to determine the optimal cut-off value. Sensitivity and specificity were calculated respectively. All statistical hypothesis tests were two-tailed, and a P value <0.05 was considered statistically significant.

Results

Comparison of clinical data between RICU patients with A. baumannii LRTI and colonization

This analysis was conducted on consecutive 99 RICU patients. Twenty-one patients were excluded due to incomplete laboratory test data. A total of 78 patients were finally enrolled in the study, including 66 males and 12 females with a male-to-female ratio of approximately 5.5:1, and the age ranged from 44 to 91 years (71.38±10.88 years).

There were 51 patients in the infection group (43 males and 8 females, male-to-female ratio with a male-to-–87 years (70.80atients in the infection group (43 maleszation group (23 males and 4 females, male-to-female ratio ≈5.6:1), aged 57–91 years (72.48atients in the infection group (43 maleszation group (23 males and 4 females, male-to-female ratio ≈5.6:1), aged 57imately 5.5:1, and the age ranged from 44 to 91 yei-Gram-positive cocci antibiotics (oxazolidinones or glycopeptides) in the infection group were significantly higher than those in the colonization group (all P<0.05). The SOFA and APACHE he infection group (43 maleszation group (23 males and 4 females, me in the colonization group (all P<0.001). The hospital stay of patients in the infection group was longer than that in the colonization group (P=0.001), with a median difference of 12 days between the two groups. The in-hospital survival rate in the infection group was significantly lower than that in the colonization group (P<0.001), with a difference of 67.1% in survival rate between the two groups. Kaplan-Meier survival curve showed that the cumulative in-hospital survival rate of patients in the infection group was significantly lower than that in the colonization group (χ²=6.091, P=0.01) (Table 1, Figures 1,2).

Figure 1 The flow chart of this study. Lac, lactic acid; RICU, respiratory intensive care unit.

Figure 2 Kaplan-Meier survival curves of RICU patients with A. baumannii LRTI and colonization. 0: colonization group; 1: infection group; 0-censored: colonization group-censored; 1-censored: infection group-censored. LRTI, lower respiratory tract infection; RICU, respiratory intensive care unit.

Comparison of laboratory examination results between RICU patients with A. baumannii LRTI and colonization

The infection-related biomarkers including WBC, NEUT, CRP and PCT in the infection group were significantly higher than those in the colonization group (all P<0.05). LY, Hb, PLT, ALB, GLB, PaO₂/FiO₂, CD3⁺ T lymphocytes, CD4⁺ T lymphocytes and CD8⁺ T lymphocytes in the infection group were significantly lower than those in the colonization group (all P<0.05). NLR, A/G and BUN in the infection group were significantly higher than those in the colonization group (all P<0.05). There were no statistically significant differences in the other laboratory examination results between the two groups (all P>0.05) (Table 2).

Comparison of drug resistance to common antibiotics between RICU patients with A. baumannii LRTI and colonization

The time from hospitalization to the first positive sample culture in the infection group was longer than that in the colonization group (P<0.001), with a median difference of 6 days between the two groups. Overall, the drug resistance rates to tigecycline and meropenem were 61.3% and 69.2%, respectively. The meropenem resistance rate in the infection group was as high as 86.3%, which was significantly higher than that in the colonization group (P<0.001). There was no statistically significant difference in the tigecycline resistance rate between the two groups (P=0.20). The resistance rates of A. baumannii in the infection group to ampicillin-sulbactam, piperacillin-tazobactam, ceftazidime, cefepime, ciprofloxacin, levofloxacin and trimethoprim-sulfamethoxazole were all higher than 80%, which were significantly higher than those in the colonization group (all P<0.001). The amikacin resistance rate of A. baumannii in the infection group was 56.9%, which was higher than 37.0% in the colonization group, but the difference was not statistically significant (P=0.10). A. baumannii in both groups remained highly sensitive to colistin, with only 1 case of resistance in the colonization group and no resistance in the infection group (Tables 1,3).

Multivariate binary logistic regression analysis of associated factors with A. baumannii LRTI in RICU patients

With the infection group as the state variable (0= colonization/censored, 1= infection), indicators with statistically significant differences in Tables 1,2 were included as covariates, including risk factors related to A. baumannii LRTI such as time from hospitalization to the first sample detection, infection-related biomarkers (WBC, PCT, CRP), nutritional indicators (ALB, Hb), glucocorticoid usage rate, immune function-related indicators (serum GLB, NEUT, LY, NLR, A/G, CD3⁺ T lymphocytes, CD4⁺ T lymphocytes, CD8⁺ T lymphocytes), pre-infection antibiotic use (carbapenems, β-lactamase inhibitor combinations, quinolones, anti-Gram-positive cocci antibiotics), invasive ventilator application rate, disease severity indicators (SOFA score, APACHE II score, PaO₂/FiO₂) and PLT. Collinearity among explanatory variables was assessed by VIF. The limited number of patients in the colonization group may lead to unstable estimation of effect sizes and unreliable odds ratios (ORs), candidate variables with VIF >2 were excluded from the multivariate binary logistic regression model to eliminate collinearity interference. Final variables incorporated into the model included serum GLB, pre-infection antibiotic use (carbapenems, β-lactam/β-lactamase inhibitor combinations), NLR, A/G, Hb, and ALB. Stepwise forward conditional method was used for multivariate logistic regression analysis to calculate the OR and 95% confidence interval (CI). The final results showed that serum GLB, pre-infection use of carbapenems, and pre-infection use of β-lactamase inhibitor combinations were the factors associated with for A. baumannii LRTI in RICU patients (all P<0.05), with OR values of 0.830 (95% CI: 0.749–0.918), 8.823 (95% CI: 2.200–35.392), and 7.094 (95% CI: 1.834–27.446), respectively (Table 4).

ROC curves of associated factors with A. baumannii LRTI in RICU patients

With the infection group as the state variable, ROC curves were plotted with serum GLB, pre-infection use of carbapenems, pre-infection use of β-lactamase inhibitor combinations, combined index (serum GLB combined with pre-infection use of carbapenems or β-lactamase inhibitor combinations). ROC curve analysis demonstrated that lower serum GLB values and higher readings of the remaining biomarkers were correlated with a higher likelihood of A. baumannii LRTI. The results showed that AUC values of 0.777 (95% CI: 0.673–0.881) for GLB <27.45 g/L, 0.658 (95% CI: 0.529–0.787) for carbapenem use, and 0.694 (95% CI: 0.571–0.817) for β-lactamase inhibitor combinations, and 0.805 (95% CI: 0.708–0.902) for the combined index. The sensitivity and specificity of the combined index were 64.7% and 96.3%, respectively (Table 5 and Figure 3).

Figure 3 ROC curves of factors associated with A. baumannii LRTI in RICU patients. GLB, globulin; LRTI, lower respiratory tract infection; RICU, respiratory intensive care unit; ROC, receiver operating characteristic.

Discussion

In this cross-sectional study, factors associated with A. baumannii LRTI were examined. We have compared with patients in the RICU colonized with A. baumannii, those who developed A. baumannii LRTI had a poorer prognosis, higher resistance rates to commonly used antimicrobial agents (e.g., carbapenems), higher SOFA scores, as well as lower CD3⁺, CD4⁺, and CD8⁺ T lymphocyte levels and serum GLB levels. Specifically, reduced serum GLB levels, and prior use of carbapenems or β-lactamase inhibitor combinations before infection were identified as factors associated with A. baumannii LRTI, suggesting that humoral immune insufficiency, and pre-infection exposure to broad-spectrum antimicrobial agents were associated with a higher probability of A. baumannii LRTI in this cohort.

These findings are consistent with existing evidence regarding the high prevalence and harm of A. baumannii in ICU settings: a domestic hospital reported that A. baumannii accounted for 25% of Gram-negative bacteria causing ICU-acquired infections during the COVID-19 pandemic (18), and a single-center retrospective ICU study found it was the second most important pathogen after Pseudomonas aeruginosa in tracheostomy tube isolates (19), indicating that A. baumannii can persist in the ICU environment, colonize patients’ respiratory tracts, or adhere to invasive devices to cause LRTI. Meta-analyses have shown that the prevalence of MDR A. baumannii in ICU-acquired HAP and VAP ranges from 55% to 100%, with a mortality rate of 30% to 75% (20,21),which aligns with the findings of this study that the cumulative in-hospital survival rate of the infection group was significantly lower than that of the colonization group and that the carbapenem resistance rate of the infection group (86.3%) was much higher than that of the colonization group (37.0%, P<0.001).

The meropenem resistance rate in the infection group was as high as 86.3%, which was significantly higher than that in the colonization group (P<0.001). The pre-infection usage rates of carbapenems, β-lactamase inhibitor combinations, quinolones, and anti-Gram-positive cocci antibiotics (oxazolidinones or glycopeptides) in the infection group were significantly higher than those in the colonization group (all P<0.05). Prior exposure to broad-spectrum antimicrobials, particularly carbapenems, is associated with an increased likelihood of carbapenem resistance among A. baumannii isolates. Mechanistically, carbapenem resistance in A. baumannii commonly arises via four primary pathways: alterations in penicillin-binding proteins, loss of outer membrane porins, overexpression of efflux pumps, and especially the production of carbapenem-hydrolyzing β-lactamases; the latter is likely driven by high antibiotic usage, which induces the expression of resistance genes such as OXA-23 and TEM (22,23). In patients with risk factors, A. baumannii pathogenicity is further enhanced by multiple mechanisms, including immune evasion, intracellular persistence, and host cell interactions—encompassing bacterial adhesion to the respiratory epithelium, cellular internalization, intracellular survival and replication, which ultimately lead to host cell death and severe inflammatory responses (21). Prior exposure to broad-spectrum antibiotics and prolonged invasive mechanical ventilation are associated with disruption of the respiratory microecology. Among mechanically ventilated patients with pneumonia, lengthy ventilation courses and antimicrobial therapy reduce the diversity and richness of the respiratory microbiota, raise bacterial burdens, and consequently increase the likelihood of VAP (24-27). Patients with carbapenem-susceptible A. baumannii pneumonia demonstrate, early depletion of lower respiratory tract microbiome diversity compared with healthy individuals and patients and patients infected with carbapenem susceptible strains; moreover, respiratory microbiota undergo continuous compositional shifts alongside mechanical ventilation and antibiotic treatment (28,29). These changes, combined with mucosal barrier damage and severe lung injury, increase the likelihood of invasive infection by colonized A. baumannii. Consistent with this, existing studies have shown that previous antibiotic therapy significantly increases carbapenem-resistant A. baumannii (CRAB) colonization risk—exposure to carbapenems quadruples colonization risk even after adjusting for disease severity—and that extended-spectrum antibiotic use for more than 7 days in mechanically ventilated patients is an independent predictor of lower respiratory tract CRAB infection/colonization (1). Consistent with these published findings, our LRTI group demonstrated significantly higher pre-infection exposure to carbapenems and β-lactamase inhibitor combinations relative to the colonization group (all P<0.05). These two antimicrobial regimens were independently associated with A. baumannii LRTI in multivariate analysis (OR =8.823, 95% CI: 2.200–35.392; OR =7.094, 95% CI: 1.834–27.446, respectively), with corresponding AUC values of 0.658 (95% CI: 0.529–0.787) and 0.694 (95% CI: 0.571–0.817).

The prominent peripheral immunosuppressive phenotype, among LRTI patients (higher glucocorticoid exposure: 80.4% vs. 33.3%, P<0.001; significantly reduced total lymphocytes,CD3⁺, CD4⁺ and CD8⁺ T cells, all P<0.05) aligns with established, critical illness immunopathology. Serum GLB primarily derives from plasma cell-secreted immunoglobulins under regulated CD4⁺ TFH-assisted B-cell activation. Critically ill patients frequently develop sepsis-associated immune paralysis within 48–72 h of acute insult, crippling both innate macrophage clearance and adaptive T/B cell-mediated antimicrobial immunity (11,30,31). Reduced circulating CD4⁺ subsets disrupt downstream humoral maturation and reduce systemic immunoglobulin concentrations, which epidemiologically correlates with elevated opportunistic infection susceptibility and unfavorable sepsis outcomes (4,32). Again, two-way causal pathways exist: systemic inflammation from verified LRTI itself drives lymphocyte apoptosis and transient globulin deficiency, which in turn may further aggravate bacterial proliferation.

Accumulating evidence from animal and in vitro studies indicated that humoral immunity was critical for host defense against A. baumannii and constraining disease progression (9). In terms of serum GLB, multivariate analysis yielded an adjusted OR value of 0.830 (95% CI: 0.749–0.918) for A. baumannii LRTI. The optimal cut-off value was determined as 27.45 g/L via the Youden index, with a sensitivity of 70.6%, specificity of 77.8%, and an AUC of 0.777 (95% CI: 0.673–0.881). Serum GLB has been validated as a biomarker for risk stratification across multiple clinical scenarios; prior orthopedic research has assessed its diagnostic performance for periprosthetic joint infection and consistently verified its discriminative capacity (33,34). One cohort reported an AUC of 0.887 for serum GLB in identifying periprosthetic joint infection (33), while another study documented an AUC of 0.880, a sensitivity of 91.07% and a specificity of 72.64% at a cut-off of 29.5 g/L (34). Consistent with these external data, serum GLB may reflect the status of host humoral immunity. Low serum GLB is correlated with higher prevalence of opportunistic bacterial infection. The observed depletion of humoral immune markers among patients with LRTI may reflect an association with the transition from asymptomatic respiratory colonization to clinical LRTI.

A combined model incorporating serum GLB <27.45 g/L and pre-infection exposure to carbapenems or β-lactamase inhibitor combinations generated an AUC of 0.805 (95% CI: 0.708–0.902), with a sensitivity of 64.7% and a specificity of 96.3%. Of note, this combined panel exhibited significantly higher AUC, specificity and positive predictive value compared with each individual indicator alone.

Study limitations

Despite these findings, this study has several limitations. First, owing to the cross-sectional design of this investigation, temporal sequence and causal links cannot be established: all exposure biomarkers were measured concurrently within matched 24 h sampling windows. This simultaneous measurement cannot distinguish whether immune abnormalities predate infection (host susceptibility factors) or arise as secondary inflammatory consequences of established LRTI; these statistical correlations merely reflect coexisting associations rather than definitive causal relationships between impaired humoral immunity, broad-spectrum antibiotic exposure and active A. baumannii LRTI. Abnormal immune-inflammatory factors were associated with the presence of A. baumannii LRTI, although the temporal and causal direction of these associations cannot be determined in a cross-sectional design. Second, the total number of non-event (colonization) cases was relatively small, which may increase the risk of model overfitting and unstable parameter estimation in multivariate logistic regression. Third, this composite panel effectively distinguishes patients with A. baumannii LRTI from colonized counterparts within our single-center cohort; however, given the single-institution design and limited overall sample size alongside relatively few colonization cases, external generalizability is restricted. Local hospital-specific antimicrobial stewardship protocols, institutional A. baumannii endemic resistance profiles and regional patient demographic characteristics limit direct extrapolation of these cut-off values and association magnitudes to other geographically distinct ICUs. Finally, the specific immune mechanism by which serum GLB influences A. baumannii LRTI in RICU patients requires further exploration through basic research.

Conclusions

In conclusion, our findings indicate that impaired humoral immune status (reflected by decreased serum GLB), together with prior exposure to extended-spectrum antimicrobials including carbapenems and β-lactamase inhibitor combinations, are associated with A. baumannii LRTI among RICU patients.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0759/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0759/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0759/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0759/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Fuzhou Pulmonary (Thoracic) Hospital of Fujian Province (Fuzhou Tuberculosis Prevention and Treatment Hospital of Fujian Province) [approval No. 2025-029 (Research)-01] and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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