Evidence map›Paper›PMID 30189858›Full record

Trial reportBMC medical imaging2018

Structural and functional brain changes in perimenopausal women who are susceptible to migraine: a study protocol of multi-modal MRI trial.

Bo Hu, Xu Wang, Jie-Bing He, Yu-Jie Dai, Jin Zhang, Ying Yu, Qian Sun, Lin-FengYan, Yu-Chuan Hu, Hai-Yan Nan and 4 more

Registry-linked trialOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in BMC medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02820974 (The Functional Magnetic Resonance Imaging Study on the Processing of Acute Pain and Cognition Among Perimenopause Women), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 38% 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.

NCT02820974 unknown statusnot on this map

The Functional Magnetic Resonance Imaging Study on the Processing of Acute Pain and Cognition Among Perimenopause Women

TypeobservationalSponsorTang-Du HospitalRan2016 to 2019Enrolled150ConditionsMenopause, Migraine
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

14 authors at 4 institutions in 2 countries.

Bo HuDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Xu WangStudent Brigade, Fourth Military Medical University (Air Force Medical University), 169 West Changle Road, Xi'an, 710032, Shaanxi Province, China.
Jie-Bing HeStudent Brigade, Fourth Military Medical University (Air Force Medical University), 169 West Changle Road, Xi'an, 710032, Shaanxi Province, China.
Yu-Jie DaiDepartment of Clinical Nutrition, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
Jin ZhangDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Ying YuDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Qian SunDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Lin-FengYanDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Yu-Chuan HuDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Hai-Yan NanDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Yang YangDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Alan D KayeDepartments of Anesthesiology and Pharmacology, Louisiana State University School of Medicine, New Orleans, Louisiana, USA.
Guang-Bin CuiDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China. cgbtd@126.com.
Wen WangDepartment of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China. wangwen@fmmu.edu.cn.ORCID 0000-0001-6473-4888
Air Force Medical University · CNTang Du Hospital · CNLouisiana State University · USXijing Hospital · CN

Funding

Key Project for Science Research and Development of Shaanxi Province No.2017SF-012Natural Science Foundation of China No.81571656
6 · The paper itself

Abstract

backgroundAs a common clinical symptom that often bothers midlife females, migraine is closely associated with perimenopause. Previous studies suggest that one of the most prominent triggers is the sudden decline of estrogen during perimenopausal period. Hormone replacement therapy (HRT) is widely used to prevent this suffering in perimenopausal women, but effective diagnostic system is lacked for quantifying the severity of the diseaase. To avoid the abuse and overuse of HRT, we propose to conduct a diagnostic trial using multimodal MRI techniques to quantify the severity of these perimenopausal migraineurs who are susceptible to the decline of estrogen.

methodsPerimenopausal women suffering from migraine will be recruited from the pain clinic of our hospital. Perimenopausal women not suffering from any kind of headache will be recruited from the local community. Clinical assessment and multi-modal MR imaging examination will be conducted. A follow up will be conducted once half year within 3 years. Pain behavior, neuropsychology scores, fMRI analysis combined with suitable statistical software will be used to reveal the potential association between these above traits and the susceptibility of migraine. DISCUSSION: Multi-modal imaging features of both healthy controls and perimenopausal women who are susceptible to estrogen decline will be acquired. Imaging features will include volumetric characteristics, white matter integrity, functional characteristics, topological properties, and perfusion properties. Clinical information, such as basic information, blood estrogen level, information of migraine, and a bunch of neurological scale will also be used for statistic assessment. This clinical trial would help to build an effective screen system for quantifying the severity of illness of those susceptible women during the perimenopausal period.

trial registrationThis study has already been registered at Clinical Trials. gov (ID: NCT02820974 ). Registration date: September 28th, 2014.

Indexed as

AdultBrainCase-Control StudiesEstrogensFemaleHumansMagnetic Resonance ImagingMiddle AgedMigraine DisordersMultimodal ImagingPain ClinicsPerimenopauseSensitivity and SpecificitySeverity of Illness IndexSoftwareEstrogensArtery spin labeling (ASL)Diffusional kurtosis imaging (DKI)Functional connectivity (FC)MigraineMulti-modalPerimenopausalVoxel-based morphology (VBM)

Identifiers

PMID30189858
PMCPMC6127929
OpenAlexW2889822997

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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.