Abstract

Background:

Hematopoietic stem cell transplantation (HSCT) patients are at high risk for intestinal colonization by Klebsiella pneumoniae (Kp), potentially leading to Kp-associated bloodstream infections (BSI). This study aims to determine the incidence of Kp colonization, the risk of its progression to Kp-BSI, and the associated risk factors in HSCT patients.

Methods:

Between August 2022 and December 2023, perianal swab specimens were prospectively collected from HSCT recipients. Bacterial isolates were identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS). Polymerase chain reaction (PCR) was employed to screen for prevalent antimicrobial resistance genes. The minimum inhibitory concentration (MIC) of colonizing strains to common antimicrobial agents was determined using the VITEK 2 automated system (bioMérieux, France). Risk factors associated with Kp colonization and subsequent BSI were analyzed by logistic regression.

Results:

Among 409 HSCT recipients, 112 (27.4%) demonstrated pre-transplant Kp colonization, including 14 cases of carbapenem-resistant Kp (CRKp). Subsequent Kp-BSI occurred in 14 colonized patients. The colonizing strains exhibited the highest susceptibility rates to carbapenems among all antimicrobial classes tested. Multivariate analysis identified the following independent risk factors for Kp colonization: higher Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI), fever, and use of posaconazole, acyclovir, and proton pump inhibitors (omeprazole). Colonized patients had a significantly higher risk of developing Kp-BSI within 100 days post-HSCT (P < 0.0001).

Conclusions:

Kp colonization significantly increases the risk of subsequent BSI in HSCT patients. Studies have found that rational management of non-antibacterial drugs (such as strictly evaluating the indications for proton pump inhibitors) can reduce the incidence of Kp colonization. Our data suggest that it is necessary to enhance awareness of the risks associated with bacterial colonization before transplantation.

Introduction

Hematopoietic stem cell transplantation (HSCT) is an effective treatment strategy for hematological malignancies such as leukemia and lymphoma as well as primary immunodeficiency diseases, and it is of great significance for children, adolescents, and adults (Wilson et al., 2014; Yan et al., 2024). In 2023, a total of 14,952 cases of HSCT were completed in 216 medical institutions in China, ranking first in the world (Xu et al., 2024). HSCT plays a pivotal role in prolonging the survival of patients with hematological diseases. However, approximately 30%-50% of patients have an increased non-recurrent mortality rate due to infection complications, among which bloodstream infection (BSI) plays an important role: BSI incidence following HSCT can range from 25% to 40%, and drug-resistant bacterial infections can lead to mortality rates of 20% to 35% (Gudiol and Carratala, 2014).

More and more data suggest that gut dysbiosis is a primary mechanism that predisposes HSCT recipients to serious infections. Chemotherapy/radiation used in pre-transplant conditioning, along with broad-spectrum antibiotics and immunosuppressive drugs, damage the intestinal mucosal barrier, disrupt the ecological balance, and reduce commensal microbiota (Yu et al., 2020). This imbalance in the gut microbiome allows for the opportunistic growth of harmful, multidrug-resistant pathogens, especially Enterobacteriaceae (Shono and Van Den Brink, 2018). Among these, Klebsiella pneumoniae (Kp) represents a significant threat (Taur et al., 2014; Ni et al., 2024, 2022). Kp, a highly virulent and multidrug-resistant member of the Enterobacteriaceae family, has been reported by Peled et al. to potentially undergo significant expansion and become a dominant pathogen in HSCT patients when gut microbiota diversity is severely depleted (Peled et al., 2020). These strains can translocate across the compromised intestinal epithelial barrier, triggering lethal BSIs. Moreover, due to limited therapeutic options for carbapenem-resistant Klebsiella pneumoniae (CRKp), the 30-day mortality rate in affected patients exceeded 50% (De Souza et al., 2024). Consequently, Kp colonization and infection profoundly impact the clinical outcomes of highly immunocompromised populations, including intensive care unit (ICU) patients and solid organ transplant (SOT) or HSCT recipients (Diekema et al., 2019; Zhang et al., 2024; Fan et al., 2025). CRKp colonization is notably prevalent in ICUs, with reported rates ranging from 15.2% to 49% (Qin et al., 2020). The risk of CRKp colonization is heightened by gut microbiota dysbiosis common in HSCT patients. This dysbiosis is characterized by a reduced abundance and diversity of commensal anaerobic bacteria that provide colonization resistance against pathogens. The loss of these potential antagonistic bacteria creates an ecological niche that facilitates the expansion of resistant Enterobacteriaceae like CRKp (Hu et al., 2025). In HSCT recipients specifically, rectal CRKp colonization has been established as an independent risk factor for subsequent carbapenem-resistant Enterobacterales (CRE) infections, particularly CRE-associated BSIs (Cao et al., 2022). Furthermore, Kp is frequently identified as the predominant colonizing bacterium in the pharynx of HSCT patients (Ge et al., 2022). These findings collectively underscore the multi-site colonization patterns of Kp in susceptible populations and their associated clinical risks. However, current evidence is largely limited to single-center or retrospective analyses, lacking integrated investigation into the dynamic carriage patterns of resistance genes and associated clinical risk factors.

Based on this gap, this study aims to elucidate the resistome characteristics of gut-colonizing Kp strains in HSCT patients and their causal relationship with BSI through molecular epidemiological investigation combined with longitudinal clinical data tracking.

Materials and methodsStudy design and population

We conducted a single-center, prospective observational case-control study at the Hematology Department of Fujian Medical University Union Hospital. The study involved active screening for Kp colonization in all patients undergoing their first HSCT between August 1, 2022, and December 31, 2023. The study included patients receiving umbilical cord blood, bone marrow, or peripheral blood stem cell transplants. The screening method involved collecting perianal swabs (once upon admission and twice weekly after entering the transplant unit).

Cases were defined as patients who had at least one perianal swab test positive for Kp prior to HSCT. Each patient was included only once, at the time of the first isolation of Kp from a perianal swab (index culture), even if multiple Kp colonizations were reported. The control group consisted of contemporaneous patients who did not develop Kp colonization. Informed consent was obtained from all participants.

Study cohort and enrollment

This study was conducted at a large first-class tertiary hospital in China, with an annual cumulative admission rate of approximately 180,000 patients. Among them, the Hematology Department of Fujian Medical University Union Hospital pioneered HSCT in 1989, making it one of the earliest medical institutions in China to perform stem cell transplantation.

Patient Inclusion Criteria: (i) Admitted to the Bone Marrow Transplantation Center of the Hematology Department; (ii) Scheduled for HSCT; (iii) Kp detected in perianal swabs during hospitalization. Exclusion Criteria: (i) Patients with incomplete medical records; (ii) Patients with missing bacterial strains; (iii) Patients with detected colonization by bacteria other than Kp.

Data sources and variables

Data were collected using standardized case report forms. Underlying diseases were documented according to the Eastern Cooperative Oncology Group (ECOG) performance status score (Jung et al., 2025). The clinical data of patients were described, including demographic characteristics, disease and treatment characteristics, transplant complications, outcomes. The following variables were assessed: sex, age at transplantation, diagnosis, donor relationship, stem cell source, conditioning intensity. Established clinical criteria were used to diagnose: Graft-versus-Host Disease (GVHD) (Glucksberg et al., 1974), engraftment syndrome in HSCT recipients (Smith et al., 2011). Chemotherapy and/or radiotherapy were defined as the administration of cytotoxic anti-neoplastic agents or ionizing radiation for curative or palliative cancer treatment. The Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI) was utilized as a tool to assess the risk of mortality following hematopoietic cell transplantation. This index summarizes weighted scores for pre-transplant individual organ dysfunctions; scores range from 0 to a theoretical maximum of 26, with higher scores indicating a greater risk of post-transplant mortality (Sorror et al., 2005). Patients were followed until either hospital discharge or in-hospital death.

Outcome definitions

Kp colonization carriers were defined as patients from whom Kp was isolated from perirectal swabs in the absence of signs and symptoms of invasive infection. Kp-BSI was defined as a BSI documented by a positive blood culture (BC) for a Kp strain (at least one sample) and clinical signs of systemic inflammatory response syndrome (SIRS) (Zarkotou et al., 2011). The BSI episode was considered as the date of index BC collection (i.e. the first BC yielding the study isolate).

Microbiological study

Bacterial isolates were obtained from perianal swabs inoculated onto Mueller-Hinton Agar (Antu Bio, China). Isolates were identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS; Bruker Daltonics). Carbapenem resistance (meropenem or imipenem) was confirmed by disk diffusion testing, defining CRE as Enterobacteriaceae resistant to either carbapenem (Castagnola et al., 2019). For CRKp isolates, carbapenemase production was assessed by modified Hodge test (Tamma and Simner, 2018). Polymerase chain reaction (PCR) and sequencing were used to detect antimicrobial resistance genes (ARGs) (Kiaei et al., 2019). Sequence results were analyzed using BLAST (http://www.ncbi.nlm.nih.gov/BLAST). The primers used for this analysis can be found in Supplementary Table 1.

Determination of minimum inhibitory concentrations

The MICs of the colonizing Klebsiella pneumoniae isolates against a panel of antimicrobial agents were determined using VITEK 2 automated system (bioMérieux, Marcy-l’Étoile, France). Briefly, pure colonies were suspended in 0.45% saline to achieve a turbidity equivalent to a 0.5 McFarland standard. The suspension was then loaded into the appropriate VITEK 2 AST-GN13 test card according to the manufacturer’s instructions. The cards were incubated and read automatically by the instrument, which reported the MIC value for each antimicrobial agent. Escherichia coli ATCC 25922 and Pseudomonas aeruginosa ATCC 27853 were used as quality control strains for each batch of testing. The interpretation of the results was based on the 2023 Clinical and Laboratory Standards Institute (CLSI 2023) guidelines.

Statistical analysis

Data were analyzed using IBM SPSS ver. 21.0 statistical software (IBM Co., Armonk, NY, USA). Frequency tables (n, %) for categorical variables and descriptive statistics (mean, median, standard deviation) for numerical variables were used. Comparisons of categorical variables were analyzed by the Chi square test. Logistic regression (Backward LR) methods (univariate, multivariate) were used to determine the risk factors for Kp colonization and BSI. Statistical significance was assigned to a P value of less than 0.05.

ResultsPatient population

During the study period (August 1, 2022, to December 31, 2023), 3,041 perianal swab specimens were collected from 416 HSCT candidates. Kp was isolated from 210 specimens (screening positivity rate: 6.9%, 210/3,041), corresponding to 119 colonized patients (colonization rate: 28.6%, 119/416). Among 119 unique patient-derived Kp isolates (excluding duplicate specimens from the same patient/timepoint), 7 strains failed revival due to improper storage. The process for screening patients is shown in Figure 1. Consequently, 112 viable isolates underwent antimicrobial susceptibility testing by disk diffusion for imipenem, meropenem, and ertapene. CRKp colonization was identified in 14 patients (3.4%, 14/409) based on phenotypic resistance.

Patients’ enrollment and exclusion of our study.

The final cohort comprised 409 HSCT recipients. Demographic and clinical characteristics included: 224 males (54.8%) and 185 females (45.2%), with a mean age of 38.8 ± 17.9 years (range: 1–76 years). The mean hospital stay was 34.6 ± 20.5 days. Predominant diagnoses were acute myeloid leukemia (26.65%), multiple myeloma (21.3%), and acute lymphoblastic leukemia (20.8%) (Table 1).

CharacteristicsKp-colonization group (n = 112)Non-colonization group (n = 297)Age, years, median(IQR)43.5 (1,76)40 (1,68)Sex, n (%)Male66 (58.9%)158 (53.2%)Female46 (41.1%)139 (46.8%)HCT-CI≥354 (48.2%)30 (10.1%)<358 (51.8%)267 (89.9%)Underlying disease, n (%)AML33 (29.5%)76 (25.6%)ALL29 (25.9%)56 (18.9%)MM25 (22.3%)62 (20.9%)LYM11 (9.8%)35 (11.8%)MDS9 (8.0%)24 (8.1%)AA1 (0.9%)25 (8.4%)Others4 (3.6%)19 (6.4%)Transplant complicationsEngraftment syndrome24 (21.4%)16 (5.4%)HLH2 (1.8%)1 (0.3%)GVHD2 (1.8%)0Donor (%)Autologous41 (36.6%)123 (41.4%)Haploidentical24 (21.4%)76 (25.6%)MSD47 (42.0%)98 (33.0%)MUD00Conditioning regimen (%)MAC95 (84.8%)265 (89.2%)RIC or NMA17 (15.2%)32 (10.8%)Graft source (%)BM7 (6.3%)39 (13.1%)UCB33 (29.5%)40 (13.5%)PB (only auto-HSCT)41 (36.6%)123 (41.4%)BM+UCB31 (27.7%)94 (31.6%)BM+PB01 (0.3%)ABO incompatibility (%)Compatible67 (59.8%)180 (60.6%)Minor mismatch12 (10.7%)24 (8.1%)Major/bidirectional mismatch17 (15.2%)38 (12.8%)half blood type matched in combined transplantation11 (9.8%)46 (15.5%)ABO-incompatible in combined transplant5 (4.5%)9 (3.0%)Donor-recipient gender match (%)Female to male11 (9.8%)17 (5.7%)Male to female14 (12.5%)34 (11.4%)Others87 (77.7%)246 (82.8%)

Clinical characteristics and transplant data of Kp-colonization group and non-colonization group.

Kp, Klebsiella pneumoniae; IQR, interquartile range; HCT-CI, hematopoietic cell transplantation–comorbidity index; AML, acute myelogenous leukemia; ALL, acute lymphoblastic leukemia; MM, multiple myeloma; LYM, lymphoma; MDS, myelodysplastic; AA, aplastic anemia; HLH, hemophagocytic lymphohistiocytosis; GVHD, graft-versus-host disease; MSD, matched sibling donor; MUD, matched unrelated donor; MAC, myeloablative conditioning; RIC, reduced intensity conditioning; NMA, non-myeloablative conditioning; BM, bone marrow; UCB, umbilical cord blood; PB, peripheral blood.

Antimicrobial susceptibility of colonizing Klebsiella pneumoniae isolates

A total of 112 unique colonizing Kp isolates were tested against 15 antimicrobial agents. The detailed MIC distribution and susceptibility profile are summarized in the Table 2. The colonizing strains exhibited the highest susceptibility rates to carbapenems (imipenem, meropenem, and ertapenem) among all antimicrobial classes tested. Amikacin also retained good potency, exhibiting a susceptibility rate of 80.36%. Among cephalosporins, susceptibility varied widely: Cefotetan demonstrated the highest activity (89.29% susceptible), followed by cefepime (66.96%) and ceftazidime (52.68%). In contrast, susceptibility to ceftriaxone and cefazolin was substantially lower (36.61% and 29.46%, respectively). This pattern is consistent with a high prevalence of ESBL-positive phenotypes (51.79%).

Antimicrobial AgentMIC Range (µg/mL)Susceptible (n)Intermediate
(n)Resistant
(n)%S (n)CephalosporinsCefazolin≤2 – ≥643307929.46Cefotetan≤4 – ≥6410011189.29Ceftriaxone≤1 – ≥644107136.61Cefepime≤1 – ≥647553266.96Ceftazidime≤1 – ≥645964752.68CarbapenemsImipenem≤1 – ≥169931088.39Meropenem≤0.5 – ≥81110199.11Ertapenem≤0.5 – ≥81090397.32MonobactamsAztreonam≤1 – ≥645315847.32AminoglycosidesGentamicin≤1 – ≥163937034.82Tobramycin≤1 – ≥1641254636.61Amikacin≤2 – ≥649002280.36FluoroquinolonesCiprofloxacin≤0.25 – ≥425206722.32Levofloxacin≤0.25 – ≥81909316.96NitrofuransNitrofurantoin≤16 – ≥51219573616.96

MIC distribution and susceptibility profile of 112 Klebsiella pneumoniae isolates.

Detection of antimicrobial resistance genes

Among 112 non-duplicate Kp isolates, extended-spectrum β-lactamase (ESBL) genes were detected as follows: SHV (85.7%, 96/112) predominated, followed by TEM (53.6%, 60/112), CTX-M-1 (50.0%, 56/112), CTX-M-10 (49.1%, 55/112), CTX-M-9 (12.5%, 14/112), and CTX-M-14 (12.5%, 14/112). No CTX-M-2 or CTX-M-8 variants were identified. Co-carriage analysis revealed 65 isolates (58.0%) harbored ≥1 CTX-M variant (CTX-M-1/9/10/14), while 50 (44.6%) carried both SHV and TEM, and 41 (36.6%) possessed all 6 ESBL genes. Quinolone resistance genes were distributed as: gyrA (96.4%, 108/112), qnrS (62.5%, 70/112), qnrB (32.1%, 36/112), and qnrA (7.1%, 8/112). qepA was undetected. Aminoglycoside resistance genes included: aac (3)-II (54.5%, 61/112), ant (3’’)-I (48.2%, 54/112), aac (6’)-Ib (46.4%, 52/112), rmtB (17.0%, 19/112), and armA (5.4%, 6/112). Carbapenemase genes were identified in 6 isolates (5.4%, 6/112): blaKPC (1.8%, 2/112) and blaNDM (3.6%, 4/112). No IMI, GIM, SME, blaIMP, blaVIM, blaOXA-181, or blaOXA-48variants were detected.

All colonizing strains carried ≥1 ESBL gene (100%), with 97.3% (109/112) harboring quinolone resistance determinants, 85.7% (96/112) aminoglycoside resistance genes, and 5.4% (6/112) carbapenemase genes. Co-occurrence of ESBL and quinolone resistance genes was observed in 93.8% (105/112), while 84.8% (95/112) carried both ESBL and aminoglycoside resistance genes.

Among the 14 CRKp isolates, carbapenemase genes were detected in 6 strains: 2 blaKPC strains and 4 blaNDM strains, with 8 strains lacking identifiable carbapenemase genes (Figure 2).

Molecular characterization of resistance genes in Kp colonization isolates as detected by PCR.

Risk factors for colonization

In this case-control analysis (112 colonized vs. 297 non-colonized HSCT recipients), multivariate analysis identified several independent risk factors significantly associated with the colonization (P < 0.05): higher HCT-CI (OR 8.557, 95% CI 4.474-16.366; P < 0.0001), posaconazole exposure (OR 3.213, 95% CI 1.796-5.749; P < 0.01), acyclovir administration (OR 3.135, 95% CI 1.530-6.425; P < 0.0001), omeprazole use (OR 2.440, 95% CI 1.280-4.651; P < 0.05), febrile episodes (OR 2.142, 95% CI 1.167-3.391; P < 0.05) (Table 3). Based on the identified risk factors, we developed a risk scoring system to predict Kp colonization in HSCT patients. Each factor was assigned weighted points based on its risk contribution, resulting in a total score ranging from 0 to 6 points (Table 4). To evaluate the predictive performance of the model and determine the optimal diagnostic threshold, we performed receiver operating characteristic (ROC) curve analysis (Figure 3A). The ROC analysis confirmed that the model possesses high discriminatory power, with an area under the curve (AUC) of 0.849.

VariablesKp colonized n (%)Non-colonized n (%)BivariateMultivariateTotal no. of patientsN=112 (27.4)N=297 (72.6)OR (95%CI)pOR (95%CI)pAge (years)41.3 ± 16.937.8 ± 18.31.011 (0.999-1.024)0.081Sex (male)66 (58.9%)158 (53.2%)0.792 (0.510-1.230)0.300HCT-CI (≥3)54 (48.2%)30 (10.1%)8.286 (4.882-14.063)0.0008.557 (4.474-16.366)0.000ECOG (3 to 5)16 (14.3%)40 (13.5%)1.071 (0.573-2.001)0.830Hospital stays (>30 days)64 (57.1%)146 (49.2%)1.379 (0.890-2.137)0.150No. of admissions (>5 times)84 (75.0%)220 (74.1%)0.952 (0.577-1.571)0.848Underlying Diseasen (%)n (%)OR (95% CI)pOR (95% CI)pAML33 (29.5%)76 (25.6%)0.485 (0.153-1.536)0.218ALL29 (25.9%)56 (18.9%)0.407 (0.126-1.307)0.131MM25 (22.3%)62 (20.9%)0.522 (0.161-1.689)0.278LYM11 (9.8%)35 (11.8%)0.670 (0.187-2.393)0.537MDS9 (8.0%)24 (8.1%)0.561 (0.150-2.107)0.392AA1 (0.9%)25 (8.4%)5.263 (0.543-50.998)0.152Others4 (3.6%)19 (6.4%)ComorbidityHypertension11 (9.8%)22 (7.4%)1.361 (0.637-2.908)0.426Diabetes mellitus7 (6.3%)18 (6.1%)1.033 (0.420-0.545)0.943Solid tumor2 (1.8%)16 (5.4%)0.319 (0.072-1.412)0.132Cardiac disease17 (15.2%)23 (7.7%)2.132 (1.092-4.162)0.0271.783 (0.731-4.347)0.204Respiratory disease28 (25.0%)53 (17.8%)1.535 (0.912-2.583)0.107