Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 56 min ago
Peer-reviewedCC BY 4.0BMC Infectious Diseases

Risk factors for Gram-negative bacterial bloodstream infections: a systematic review and meta-analysis with subgroup analyses for carbapenem-resistant organisms and Acinetobacter baumannii

  • Wang Zhang1,2
  • Mengke Ye3,2
  • Wenzeng Xu4,2
  • Xiaoting Hua3,2
  • Hua Zhou5
  • Yunsong Yu3,2
5 affiliations
  1. 1Department of Respiratory and Critical Care Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
  2. 2Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, Hangzhou, China
  3. 3Department of Infectious Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
  4. 4Department of Critical Care Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
  5. 5Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
Read full textDOICite

Abstract

Background: Gram-negative bacterial (GNB) bloodstream infections (BSIs), particularly those caused by carbapenem-resistant GNB (CR-GNB) and Acinetobacter baumannii (AB), are associated with substantial morbidity and mortality. This study aimed to provide, to our knowledge, the first comprehensive meta-analysis integrating overall GNB-BSI risk factors with both pathogen-specific and resistance-defined subgroup analyses.

Methods: A systematic literature search was conducted across PubMed, Web of Science, Embase, the Cochrane Library, and four major Chinese databases from inception to August 2025. We included observational studies evaluating risk factors for GNB-related BSIs in patients with GNB infections. Two reviewers independently performed study screening, data extraction, and quality assessment. Methodological quality was evaluated using the Newcastle–Ottawa Scale and the Agency for Healthcare Research and Quality tool. Meta-analyses were performed using R software. Pooled odds ratios (ORs) or standardized mean differences (SMDs) with 95% confidence intervals (CIs) were estimated using the Mantel-Haenszel method, applying either fixed-effects or random-effects models based on the degree of heterogeneity. Furthermore, pre-specified subgroup analyses were conducted to explore potential sources of heterogeneity.

Results: Seventy-five studies (76 articles), encompassing 26,377 patients with GNB infections, were included. The pooled incidence of BSI was 17.3%. Of the 29 evaluated risk factors, 17 were significantly associated with GNB-BSI in the overall population. Procalcitonin (SMD, 0.64; 95%CI, 0.39–0.88), C-reactive protein (SMD, 0.63; 95%CI, 0.43–0.83), carbapenem use (OR, 2.49; 95%CI, 1.92–3.23), mechanical ventilation (OR, 2.51; 95%CI, 1.74–3.61), central venous catheterization (OR, 2.67; 95%CI, 2.27–3.15), immunosuppressive status (OR, 2.20; 95%CI, 1.50–3.22), and aminoglycoside use (OR, 1.68; 95%CI, 1.31–2.15) emerged as the most consistent risk predictors of GNB-BSI. Subgroup analyses indicated that CR-GNB–BSI was specifically associated with hypoalbuminemia and indwelling urinary catheter use, whereas continuous renal replacement therapy was uniquely associated with AB-BSI.

Conclusions: As the first meta-analysis to integrate pathogen-specific and resistance-defined subgroups, this study delineates distinct risk profiles for GNB-BSI. While biomarkers of inflammation, prior carbapenem exposure, and invasive procedures represent broadly shared predictors, CR-GNB–BSI and AB-BSI exhibit additional, subtype-specific risk factors. These findings assist clinicians in the early identification of BSIs among patients with GNB infections.

Registration number: CRD420251117325.

Clinical trial number: Not applicable.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12879-026-14108-6.

Related

  1. Carbapenem resistance in pediatric Acinetobacter baumannii urinary tract infections: molecular determinants.
    Rasha Hassan Hassan, Maysaa El Sayed Zaki, Mohamed Saleh Ismail +2
    Italian journal of pediatricsPeer-reviewedCC BYFull textGeneral medicineEurope PMCPMC
  2. Cost-Effectiveness of Sulbactam-durlobactam Compared with Colistin for Treating Carbapenem-Resistant Acinetobacter baumannii Infections in Critical Care Settings in the United States
    A. Ologunowa, A. Caffrey, S. Cohen +1
    medRxivPreprintCC BYFull textInfectious diseasemedRxiv
  3. Carbapenem-resistant Acinetobacter baumannii infections in intensive care units: incidence, infection prevention and control, and antimicrobial stewardship practices in the cross-border region between Italy and France, 2019–2022
    C. Vicentini, R. Bussolino, E. Kuczewski +57
    Journal of Hospital InfectionPeer-reviewedCC BYFull text2 citedGeneral biologyEpidemiology & public healthHAL
  4. Clinical correlates of the Haemoglobin to Red Cell Distribution Width ratio in bacterial bloodstream infections and concomitant kidney dysfunction.
    John Nzobokela, David Chisompola, Jay Chibinga +3
    BMC research notesPeer-reviewedCC BY-NC-NDFull textEpidemiology & public healthEurope PMCPMC
  5. Longitudinal Multicenter Susceptibility Trends of Ceftazidime/Avibactam and Imipenem/Relebactam and Dose Optimization in Critically Ill Patients with Carbapenem-Resistant Enterobacterales Bloodstream Infections
    Wang X, Chen P, Chen T +8
    Drug Design, Development and TherapyPeer-reviewedCC BYFull textPharmacology & toxicologyDOAJ

Cite

BibTeXRIS
BibTeX
@article{zhang2026risk,
  title = {{Risk factors for Gram-negative bacterial bloodstream infections: a systematic review and meta-analysis with subgroup analyses for carbapenem-resistant organisms and Acinetobacter baumannii}},
  author = {Wang Zhang and Mengke Ye and Wenzeng Xu and Xiaoting Hua and Hua Zhou and Yunsong Yu},
  journal = {BMC Infectious Diseases},
  year = {2026},
  month = aug,
  doi = {10.1186/s12879-026-14108-6},
  url = {https://doi.org/10.1186/s12879-026-14108-6},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Risk factors for Gram-negative bacterial bloodstream infections: a systematic review and meta-analysis with subgroup analyses for carbapenem-resistant organisms and Acinetobacter baumannii
AU  - Wang Zhang
AU  - Mengke Ye
AU  - Wenzeng Xu
AU  - Xiaoting Hua
AU  - Hua Zhou
AU  - Yunsong Yu
PY  - 2026
DA  - 2026/08/08
JO  - BMC Infectious Diseases
DO  - 10.1186/s12879-026-14108-6
UR  - https://doi.org/10.1186/s12879-026-14108-6
AB  - Background: Gram-negative bacterial (GNB) bloodstream infections (BSIs), particularly those caused by carbapenem-resistant GNB (CR-GNB) and Acinetobacter baumannii (AB), are associated with substantial morbidity and mortality. This study aimed to provide, to our knowledge, the first comprehensive meta-analysis integrating overall GNB-BSI risk factors with both pathogen-specific and resistance-defined subgroup analyses.  Methods: A systematic literature search was conducted across PubMed, Web of Science, Embase, the Cochrane Library, and four major Chinese databases from inception to August 2025. We included observational studies evaluating risk factors for GNB-related BSIs in patients with GNB infections. Two reviewers independently performed study screening, data extraction, and quality assessment. Methodological quality was evaluated using the Newcastle–Ottawa Scale and the Agency for Healthcare Research and Quality tool. Meta-analyses were performed using R software. Pooled odds ratios (ORs) or standardized mean differences (SMDs) with 95% confidence intervals (CIs) were estimated using the Mantel-Haenszel method, applying either fixed-effects or random-effects models based on the degree of heterogeneity. Furthermore, pre-specified subgroup analyses were conducted to explore potential sources of heterogeneity.  Results: Seventy-five studies (76 articles), encompassing 26,377 patients with GNB infections, were included. The pooled incidence of BSI was 17.3%. Of the 29 evaluated risk factors, 17 were significantly associated with GNB-BSI in the overall population. Procalcitonin (SMD, 0.64; 95%CI, 0.39–0.88), C-reactive protein (SMD, 0.63; 95%CI, 0.43–0.83), carbapenem use (OR, 2.49; 95%CI, 1.92–3.23), mechanical ventilation (OR, 2.51; 95%CI, 1.74–3.61), central venous catheterization (OR, 2.67; 95%CI, 2.27–3.15), immunosuppressive status (OR, 2.20; 95%CI, 1.50–3.22), and aminoglycoside use (OR, 1.68; 95%CI, 1.31–2.15) emerged as the most consistent risk predictors of GNB-BSI. Subgroup analyses indicated that CR-GNB–BSI was specifically associated with hypoalbuminemia and indwelling urinary catheter use, whereas continuous renal replacement therapy was uniquely associated with AB-BSI.  Conclusions: As the first meta-analysis to integrate pathogen-specific and resistance-defined subgroups, this study delineates distinct risk profiles for GNB-BSI. While biomarkers of inflammation, prior carbapenem exposure, and invasive procedures represent broadly shared predictors, CR-GNB–BSI and AB-BSI exhibit additional, subtype-specific risk factors. These findings assist clinicians in the early identification of BSIs among patients with GNB infections.  Registration number: CRD420251117325.  Clinical trial number: Not applicable.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12879-026-14108-6.
SN  - 1471-2334
ER  -