Evidence map›Paper›PMID 37008802›Full record

ReviewClinical interventions in aging2023

Autoimmunity and Frontotemporal Lobar Degeneration: From Laboratory Study to Clinical Practice.

Yan Sun, Lumi Zhang, Ping Liu, Guoping Peng

Abstract readReview
In one paragraph

Review in Clinical interventions in aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Yan SunDepartment of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Lumi ZhangDepartment of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Ping LiuDepartment of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Guoping PengDepartment of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Frontotemporal lobar degeneration (FTLD) is a group of neurodegenerative diseases with heterogenous clinical, genetic, and pathological characteristics that show similar impairment of areas in the frontal and/or temporal lobes. Prime doctors' lack of awareness of this complex disease makes early identification and accurate intervention difficult. Autoimmune diseases and autoantibodies are manifestations of different levels of autoimmune reactions. This review presents research findings examining the relationship between autoimmunity and FTLD in terms of autoimmune diseases and autoantibodies with a focus on identifying potential diagnosis and treatment approaches. The findings indicate that the same or similar pathophysiological mechanisms may exist from clinical, genetic, and pathological perspectives. However, the existing evidence is not sufficient to extract substantial conclusions. On the basis of the current situation, we propose future research patterns using prospective studies on large populations and combined clinical and experimental research. Autoimmune reactions or, more generally, inflammatory reactions should receive increased attention from doctors and scientists of all disciplines.

Indexed as

Autoimmune DiseasesFrontotemporal Lobar DegenerationAutoantibodiesAutoimmunityHumansProspective Studiestau ProteinsAutoantibodiestau Proteinsautoantibodiesautoimmune disordersautoimmunitydiagnosisfrontotemporal lobar degenerationtreatment

Identifiers

PMID37008802
PMCPMC10065017

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.