Evidence map›Paper›PMID 39698332›Full record

ReviewHemaSphere2024

Inflammatory pathways and anti-inflammatory therapies in sickle cell disease.

Karina Tozatto-Maio, Felipe A Rós, Ricardo Weinlich, Vanderson Rocha

Abstract readReview
In one paragraph

Review in HemaSphere, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. The Association of Serum Level of TGF-βHealth science reports · 2025
    Article
  4. 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

4 authors.

Karina Tozatto-MaioCentro de Ensino e Pesquisa Hospital Israelita Albert Einstein São Paulo Brazil.ORCID 0000-0001-9699-3462
Felipe A RósDivisão de Hematologia, Hemoterapia e Terapia Celular Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.ORCID https://orcid.org/0000-0001-7058-998X
Ricardo WeinlichCentro de Ensino e Pesquisa Hospital Israelita Albert Einstein São Paulo Brazil.ORCID https://orcid.org/0000-0001-6822-7330
Vanderson RochaDivisão de Hematologia, Hemoterapia e Terapia Celular Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo São Paulo Brazil.ORCID https://orcid.org/0000-0003-0094-619X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sickle cell disease (SCD) is a monogenic disease, resulting from a single-point mutation, that presents a complex pathophysiology and high clinical heterogeneity. Inflammation stands as a prominent characteristic of SCD. Over the past few decades, the role of different cells and molecules in the regulation of the inflammatory process has been elucidated. In conjunction with the polymerization of hemoglobin S (HbS), intravascular hemolysis, which releases free heme, HbS, and hemoglobin-related damage-associated molecular patterns, initiates multiple inflammatory pathways that are not yet fully comprehended. These complex phenomena lead to a vicious cycle that perpetuates vaso-occlusion, hemolysis, and inflammation. To date, few inflammatory biomarkers can predict disease complications; conversely, there is a plethora of therapies that reduce inflammation in SCD, although clinical outcomes vary widely. Importantly, whether the clinical heterogeneity and complications are related to the degree of inflammation is not known. This review aims to further our understanding of the roles of main immune cells, and other inflammatory factors, as potential prognostic biomarkers for predicting clinical outcomes or identifying novel treatments for SCD.

Identifiers

PMID39698332
PMCPMC11655128

What OpenQuestion holds

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Registered trials

None linked

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.