Evidence map›Paper›PMID 37718527›Full record

ArticleCombinatorial chemistry & high throughput screening2024

Clinical Analysis of Bacterial Infection Characteristics in Lymphoma Patients with High-dose Chemotherapy Combined with Autologous Hematopoietic Stem Cell Transplantation-A Single-Centered Retrospective Study.

Dan-Hui Sun, Di Mei, Xiao-Qin Yao, Yi-Hui Rong, Gui-Qiang Wang

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Article in Combinatorial chemistry & high throughput screening, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

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4 · The record

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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

5 authors.

Dan-Hui SunDepartment of Infectious Diseases, Peking University International Hospital, Beijing, 102206, China.
Di MeiDepartment of Lymphoma, Peking University International Hospital, Beijing, 102206, China.
Xiao-Qin YaoDepartment of Traditional Chinese Medicine, Peking University International Hospital, Beijing, 102206, China.
Yi-Hui RongDepartment of Infectious Diseases, Peking University International Hospital, Beijing, 102206, China.
Gui-Qiang WangDepartment of Infectious Diseases, Peking University International Hospital, Beijing, 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-dose chemotherapy combined with autologous hematopoietic stem cell transplantation (HDT/AHSCT) is used to treat lymphoma. Although AHSCT has made considerable strides and become safer, HDT-AHSCT infection continues to be a leading cause of morbidity and mortality associated with transplantation.

objectiveTo characterise pathogenic bacterial infections in HDT/AHSCT-treated lymphoma patients. The prevalence of pathogenic microorganisms and the timing of foci after transplantation, along with bloodstream infection (BSI) risk factors, can help determine the need for empirical antibiotics after AHSCT.

methodsWe retrospectively analyzed 133 lymphoma patients treated by HDT/AHSCT from April 2017 to October 2021 at Peking University International Hospital, Beijing, China. We analyzed their clinical characteristics, microbiological distribution characteristics, and BSI risk factors in detail.

resultsIn order, intestinal infection (56 cases), BSI (17 cases), pulmonary (12 cases), upper respiratory tract (5 cases), and perianal (4 cases) were the most common locations of infection after HDT/AHSCT. The infection sites yielded 92 putative pathogenic pathogens, with bacteria predominating (61.96%), fungi (28.26%), viruses (5.43%), and mycoplasma (4.35%). Gram-negative bacteria (GNB) strains outnumbered gram-positive bacteria (GPB) strains (73.68%). Two strains of

conclusionHigh-dose chemotherapy combined with autologous hematopoietic stem cell transplantation (HDT/AHSCT) is used to treat lymphoma. Although AHSCT has made considerable strides and become safer, HDT-AHSCT infection continues to be a leading cause of morbidity and mortality associated with transplantation.

Indexed as

Bacterial InfectionsHematopoietic Stem Cell TransplantationLymphomaAdolescentAdultAgedAnti-Bacterial AgentsFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsTransplantation, AutologousYoung AdultAnti-Bacterial Agentsbloodstream infectionHDT/AHSCT.high-dose chemotherapyLymphomapathogensrisk factors

Identifiers

PMID37718527

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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.