Evidence map›Paper›PMID 31852992›Full record

ArticleScientific reports2019

DTI Study on Brain Structure and Cognitive Function in Patients with Chronic Mountain Sickness.

Haihua Bao, Ruiyang Li, Mingli He, Dongjie Kang, Lili Zhao

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

5 authors.

Haihua BaoDepartment of Medical Imaging Center, Affiliated Hospital of Qinghai University, Xining, Qinghai, China. baohelen2@sina.com.
Ruiyang LiDepartment of Medical Imaging Center, Affiliated Hospital of Qinghai University, Xining, Qinghai, China.ORCID http://orcid.org/0000-0003-2651-6120
Mingli HeDepartment of Medical Imaging Center, Affiliated Hospital of Qinghai University, Xining, Qinghai, China.
Dongjie KangDepartment of Medical Imaging Center, Affiliated Hospital of Qinghai University, Xining, Qinghai, China.
Lili ZhaoDepartment of Medical Imaging Center, Affiliated Hospital of Qinghai University, Xining, Qinghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In chronic mountain sickness (CMS) patients, the structure of the brain, memory and cognition are often irreversibly damaged by chronic hypoxia due to red blood cell overcompensation, elevated haemoglobin and blood stasis. In this study, we aimed to evaluate this damage using diffusion tensor imaging (DTI) and to study the correlations among the fractional anisotropy (FA),the apparent diffusion coefficient (ADC) value, the severity index of CMS and the simple Mental State Examination (MMSE) score in CMS patients. A total of 17 patients with CMS and 15 healthy controls were recruited for conventional brain magnetic resonance imaging (MRI) and DTI scans, and ADC images were reconstructed along with FA and FA colour maps. The FA and ADC values of the selected regions of interest (ROIs) were measured and compared. The FA and ADC values were also compared with the haemoglobin (Hb) and MMSE scores. CMS patients are prone to intracranial ischaemia, infarction and haemorrhage. Multiple structural changes occur in the brain of CMS patients, and these changes are related to the severity of the disease and cognitive function variation. The white matter fibre bundles of CMS patients showed no obvious damage, except in the ischaemic site.

Indexed as

CognitionDiffusion Tensor ImagingAdultAltitude SicknessAnisotropyBrainCase-Control StudiesChronic DiseaseDizzinessHeadacheHumansMale

Identifiers

PMID31852992
PMCPMC6920146

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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.