Evidence map›Paper›PMID 38844581›Full record

ArticleScientific reports2024

High mortality associated with inappropriate initial antibiotic therapy in hematological malignancies with Klebsiella pneumoniae bloodstream infections.

Zijun Ma, Chengcheng Lai, Jun Zhang, Yuren Han, Mengjie Xin, Jinghui Wang, Zhuanghao Wu, Yonggang Luo

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. NDM-ProducingJournal of clinical medicine · 2026
    Article
  4. Article
  5. Article
  6. Observational
  7. Multicenter Surveillance ofInfection and drug resistance · 2026
    Article
  8. Article
  9. Resistance Trends inMicroorganisms · 2025
    Article
  10. Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Zijun Ma *Department of General Practice, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Chengcheng Lai *Department of General Practice, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jun ZhangDepartment of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yuren HanDepartment of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Mengjie XinDepartment of Medical Equipment, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jinghui WangDepartment of General Practice, Luoyang Central Hospital Affiliated to Zhengzhou University, Luoyang, China.
Zhuanghao WuDepartment of Integrated Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yonggang LuoDepartment of Neurosurgical Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. luoyg_514@126.com.

Funding

Henan Province Natural Science Foundation Project 242300420384Henan Province Science and Technology Research Project 242102311040Henan Province's Medical Science and Technology Research Provincial and Ministerial Joint Construction Of Key Projects SBGJ202102081Young and Middle-aged Scientific, Technological Innovation Jie-Qing Talent Project YXKC2021042
6 · The paper itself

Abstract

Bloodstream infections caused by multidrug-resistant organisms such as Klebsiella pneumoniae are a significant challenge in managing hematological malignancies. This study aims to characterize the epidemiology of Klebsiella pneumoniae bloodstream infections specifically in patients with hematological malignancies, delineate the patterns of initial antibiotic therapy, assess the prevalence of resistant strains, identify risk factors for these resistant strains, and evaluate factors influencing patient outcomes. A retrospective analysis was conducted at a single center from January 2017 to December 2020, focusing on 182 patients with hematological malignancies who developed Klebsiella pneumoniae bloodstream infections. We compared the 30-day mortality rates between patients receiving appropriate and inappropriate antibiotic treatments, including the effectiveness of both single-drug and combination therapies. Kaplan-Meier survival analysis and multivariate logistic and Cox regression were used to identify factors influencing mortality risk. The 30-day all-cause mortality rate was 30.2% for all patients. The 30-day all-cause mortality rates were 77.2% and 8.8% in patients who received inappropriate initial treatment and appropriate initial treatment (p < 0.001). Inappropriate initial treatment significantly influenced mortality and was a key predictor of 30-day mortality, along with septic shock and previous intensive care unit (ICU) stays. Patients with carbapenem-resistant Klebsiella pneumoniae (CRKP) bloodstream infections exhibited more severe clinical symptoms compared to the CSKP group. The study demonstrates a significant association between empirical carbapenem administration and the escalating prevalence of CRKP and multidrug-resistant K. pneumoniae (MDR-KP) infections. Furthermore, the study identified inappropriate initial antibiotic therapy, septic shock, and ICU admission as independent risk factors for 30-day mortality.

Indexed as

Anti-Bacterial AgentsBacteremiaHematologic NeoplasmsKlebsiella InfectionsKlebsiella pneumoniaeAdultAgedDrug Resistance, Multiple, BacterialFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsAnti-Bacterial AgentsAntibiotic therapyBloodstream infectionCarbapenem-resistantHematological malignanciesKlebsiella pneumoniae

Identifiers

PMID38844581
PMCPMC11156844

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.