Evidence map›Paper›PMID 21243091›Full record

ArticleBulletin of the IACFS/ME2009

CFS: A Review of Epidemiology and Natural History Studies.

Leonard A Jason, Nicole Porter, Molly Brown, Valerie Anderson, Abigail Brown, Jessica Hunnell, Athena Lerch

Open access · greenAbstract read
In one paragraph

Article in Bulletin of the IACFS/ME, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Leonard A Jason
Nicole Porter
Molly Brown
Valerie Anderson
Abigail Brown
Jessica Hunnell
Athena Lerch
DePaul University · US

Funding

Risk Factrors Associated with CFS and CF PrognosisR01AI055735 · NIAID · DE PAUL UNIVERSITY · PI JASON, LEONARD A · 2005 to 2007
$1.9M
NIAID NIH HHS R01 AI055735
6 · The paper itself

Abstract

Almost all studies with samples of patients who have chronic fatigue syndrome (CFS) have relied on referrals from physicians or health facilities. Under-served minorities, who not only tend to manifest higher levels of chronic illness, but are also less likely to seek and receive adequate medical care, have not been represented in these studies (1). This may have contributed to an under-estimation of CFS among minority groups (2). Few studies have derived their samples from socioeconomically and ethnically diverse community-based populations. A technical report issued by the Agency for Healthcare Research and Quality (3) concluded that estimating rates of recovery/improvement or relapse from CFS are not possible because there are so few natural history studies and those that are available have involved selected referral populations. This paper provides a review of epidemiologic studies of CFS followed by a discussion of diagnostic issues and risk factors for the illness. Findings from Jason et al.'s (4) epidemiologic study in a multi-ethnic, economically diverse urban area are highlighted as this research group is now examining the natural course of CFS over the past 10 years with this community-based sample. The current study will add to current epidemiologic and risk factors research by assessing the course, progression, and risk factors of CFS among a demographically diverse sample of participants who are unbiased by illness, help-seeking behaviors, or differential access to the health care system.

Identifiers

PMID21243091
PMCPMC3021257
OpenAlexW2135495229

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.