Evidence map›Paper›PMID 35399835›Full record

ArticleJournal of healthcare engineering2022

The Efficacy and Safety of Plasma Exchange in the Treatment of Thrombotic Thrombocytopenic Purpura.

Zhilan Pan, Zhimin Zhang, Yan Yang, Weihua Hao

RetractedAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Zhilan PanBlood of Internal Medicine, Shijiazhuang People's Hospital, Shijiazhuang 050000, Hebei Province, China.ORCID 0000-0001-5203-4016
Zhimin ZhangBlood of Internal Medicine, Shijiazhuang People's Hospital, Shijiazhuang 050000, Hebei Province, China.ORCID 0000-0003-1287-9908
Yan YangBlood of Internal Medicine, Shijiazhuang People's Hospital, Shijiazhuang 050000, Hebei Province, China.ORCID 0000-0002-8086-9587
Weihua HaoCardiac Intensive Care Ward (CCU), Shijiazhuang People's Hospital, Shijiazhuang 050000, Hebei Province, China.ORCID 0000-0003-3258-8008

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Thrombotic thrombocytopenic purpura (TTP) is a clinically rare thrombotic cardiovascular and microvascular disease. The purpose of this study was to observe the clinical efficacy and safety of plasma exchange in the treatment of TTP. Methods: A total of 16 TTP patients who underwent plasma exchange from January 2015 to December 2020 were selected. The clinical data of all patients were collected for retrospective analysis. The effective rate of treatment, the changes of blood cell count before and after treatment, and adverse reactions during treatment were analyzed. Results: A total of 50 plasma exchanges were performed in 16 TTP patients. After plasma exchange treatment, there were 4 invalid and 12 improved patients. The total effective rate of plasma exchange in patients with TTP was 75.0%. After treatment, platelet count (PLT) and hemoglobin (Hb) levels were significantly increased in TTP patients. Compared with before treatment, lactate dehydrogenase (LDH), indirect bilirubin (IBIL), total bilirubin (TBIL), and broken red blood cells were significantly reduced. In addition, 3 adverse reactions occurred in 50 plasmapheresis procedures, and the incidence of adverse reactions was 6.0%. Conclusion: Plasma exchange therapy has a good therapeutic effect on TTP and can significantly improve abnormal blood cell count in patients with high safety.

Indexed as

Plasma ExchangePurpura, Thrombotic ThrombocytopenicBilirubinHumansPlasmapheresisRetrospective StudiesBilirubin

Identifiers

PMID35399835
PMCPMC8989575

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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.