Evidence map›Paper›PMID 37543896›Full record

ArticleArchives of Iranian medicine2022

Clinical and Epidemiological Aspects of Late Onset Multiple Sclerosis in East-Azerbaijan, Iran; A Population-Based Study.

Ehsan Nasiri, Amirreza Naseri, Pouya Abbasgholizadeh, Ali Fahidi, Mahnaz Talebi

Abstract read
In one paragraph

Article in Archives of Iranian medicine, 2022. 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

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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

5 authors.

Ehsan NasiriStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0002-9679-5623
Amirreza NaseriStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0001-9723-0109
Pouya AbbasgholizadehStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0003-4989-6509
Ali FahidiNeurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0001-6722-4357
Mahnaz TalebiNeurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0002-7613-3913

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLate-onset multiple sclerosis (LOMS) is defined as symptoms initiating at an age above 50. Objective: This study aims to determine the clinical and epidemiological aspects of LOMS in East-Azerbaijan province, Iran.

methodsThis population-based study recruited nearly all MS patients to the end of 2020, who were diagnosed at age≥50, by referring to the only local MS registry center. We investigated prevalence, sex, age-of-onset, first clinical presentation, family history, and gap of diagnosis. Also, we compared the disease characteristics between male and female cases.

resultsOut of 4905 total cases of MS, 217 cases (4.42%) were LOMS. The mean age of onset was 53.80±3.41 years with a maximum age of 68 years. The most common age group of the patients was 50 to 55 years (69.1%). The frequency by sex of LOMS in females (150) was greater than males (67). Positive family history was seen in 6.17%, and in 41% of the patients, the disease was diagnosed in a timely manner. Early symptoms were motor (31.3%), sensory (24.8%), optic neuritis (23%), cerebellar symptoms (13.8%), and brainstem symptoms (6.9%). The first presentation of the disease was different between male and female cases (

conclusionLOMS is not a rare condition. Increasing knowledge in the diagnosis, as well as increasing awareness of the disease in the general population, leads to early diagnosis of LOMS and prevention of consequences.

Indexed as

Multiple SclerosisAgedAge of OnsetAzerbaijanDisease ProgressionFemaleHumansIranMaleMiddle AgedElderlyEpidemiologyLate-onset multiple sclerosisLOMSMultiple sclerosis

Identifiers

PMID37543896
PMCPMC10685859

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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.