Evidence map›Paper›PMID 39901114›Full record

ArticleBMC infectious diseases2025

Predictive value of serum procalcitonin level for the diagnosis of bloodstream infections in hematological patients.

Qi Sun, Qingsong Lin, Yanxia Lv, Zhiying Tian, Qiushuang Yan, Yaqing Yu, Xue Fu, Hongjing Yao, Fujun Sun, Yonghui Xia and 2 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Guideline
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Observational
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

12 authors.

Qi Sun *State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Qingsong Lin *State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yanxia LvState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Zhiying TianState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Qiushuang YanState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yaqing YuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Xue FuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Hongjing YaoState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Fujun SunState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Yonghui XiaState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
Guoqing ZhuState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China. zhuguoqing@ihcams.ac.cn.
Sizhou FengState Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China. doctor_szhfeng@163.com.

Funding

CAMS Innovation Fund for Medical Sciences 2021-I2M-1-039
6 · The paper itself

Abstract

objectivesProcalcitonin (PCT) is a critical diagnostic biomarker for bacterial infections in patients. Numerous studies have shown that PCT have high sensitivity and specificity for diagnosing bloodstream infection. However, the cut-off value of PCT for the diagnosis of bloodstream infections in patients with hematolgic diseases is still unclear and unreliable.

methodsWe conducted a retrospective study involving 2299 cases with hematological diseases and who had been performed blood culture and PCT test within 24 h.

resultsFor patients with hematological diseases, the serum PCT was slightly elevated in the BSI group. We found that most hematological patients with bloodstream infection were in the stage of severe neutropenia. The main infected strains were Escherichia coli (n = 84, 21%), Klebsiella pneumoniae (n = 61, 15.25%) and Pseudomonas aeruginosa (n = 65, 16.25%), and the increasing trend of PCT level was more obvious in patients infected with Gram-negative bacteria. ROC analysis results showed that the area under the receiver operating characteristic curve for distinguishing bacterial infection from non-bacterial infection was 0.554 (95%CI: 0.522-0.585) with the diagnostic threshold of BSI (PCT > 0.5ng/mL).

conclusionsIn our study, low PCT levels were found in patients with hematological diseases, and a better cut-off value may be necessary to determine infection in hematology patients.

Indexed as

BacteremiaHematologic DiseasesProcalcitoninAdolescentAdultAgedAged, 80 and overBiomarkersFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesROC CurveSensitivity and SpecificityBiomarkersProcalcitoninBloodstream infection (BSI)Cut-off levelHematology patientsProcalcitonin (PCT)

Identifiers

PMID39901114
PMCPMC11792228

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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.