Evidence map›Paper›PMID 38633475›Full record

ArticleWorld journal of critical care medicine2024

Predictive value of thrombocytopenia for bloodstream infection in patients with sepsis and septic shock.

Xia Li, Sheng Wang, Jun Ma, Su-Ge Bai, Su-Zhen Fu

Open access · diamondAbstract read
In one paragraph

Article in World journal of critical care medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Observational
  3. Thrombocytopenia in Sepsis.Life (Basel, Switzerland) · 2025
    Review
  4. Article
  5. Article
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

5 authors at 1 institution in 1 country.

Xia LiDepartment of Critical Care Medicine, Xingtai People Hospital, Xingtai 054001, Hebei Province, China. lix0518@163.com.
Sheng WangDepartment of Physiology, Hebei Collaborative Innovation Center for Cardio-cerebrovascular Disease, Hebei Medical University, Shijiazhuang 050000, Hebei Province, China.
Jun MaDepartment of Critical Care Medicine, Xingtai People Hospital, Xingtai 054001, Hebei Province, China.
Su-Ge BaiDepartment of Critical Care Medicine, Xingtai People Hospital, Xingtai 054001, Hebei Province, China.
Su-Zhen FuDepartment of Critical Care Medicine, Xingtai People Hospital, Xingtai 054001, Hebei Province, China.
Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThrombocytopenia is common in patients with sepsis and septic shock.

aimTo analyse the decrease in the number of platelets for predicting bloodstream infection in patients with sepsis and septic shock in the intensive care unit.

methodsA retrospective analysis of patients admitted with sepsis and septic shock in Xingtai People Hospital was revisited. Patient population characteristics and laboratory data were collected for analysis.

resultsThe study group consisted of 85 (39%) inpatients with bloodstream infection, and the control group consisted of 133 (61%) with negative results or contamination. The percentage decline in platelet counts (PPCs) in patients positive for pathogens [57.1 (41.3-74.6)] was distinctly higher than that in the control group [18.2 (5.1-43.1)] (

conclusionThe percentage decline in platelet counts is sensitive in predicting bloodstream infection in patients with sepsis and septic shock. However, it cannot identify gram-positive bacteraemia, gram-negative bacteraemia, and fungal infection.

Indexed as

Bloodstream infectionPlatelet countsSepsisShockThrombocytopenia

Identifiers

PMID38633475
PMCPMC11019628
OpenAlexW4392572185

What OpenQuestion holds

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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.