Evidence map›Paper›PMID 36072648›Full record

ArticleBrain communications2022

Preoperative brain connectome predicts postoperative changes in processing speed in moyamoya disease.

Mengxia Gao, Charlene L M Lam, Wai M Lui, Kui Kai Lau, Tatia M C Lee

Open access · goldAbstract read
In one paragraph

Article in Brain communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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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 at 3 institutions in 2 countries.

Mengxia GaoThe State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong 999077, China.
Charlene L M LamThe State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong 999077, China.
Wai M LuiDivision of Neurosurgery, Queen Mary Hospital, Hong Kong 999077, China.
Kui Kai LauLaboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong 999077, China.
Tatia M C LeeThe State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong 999077, China.
University of Hong Kong · HKChinese University of Hong Kong · CNQueen Mary Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Moyamoya disease is a rare cerebrovascular disorder associated with cognitive dysfunction. It is usually treated by surgical revascularization, but research on the neurocognitive outcomes of revascularization surgery is controversial. Given that neurocognitive impairment could affect the daily activities of patients with moyamoya disease, early detection of postoperative neurocognitive outcomes has the potential to improve patient management. In this study, we applied a well-established connectome-based predictive modelling approach to develop machine learning models that used preoperative resting-state functional connectivity to predict postoperative changes in processing speed in patients with moyamoya disease. Twelve adult patients with moyamoya disease (age range: 23-49 years; female/male: 9/3) were recruited prior to surgery and underwent follow-up at 1 and 6 months after surgery. Twenty healthy controls (age range: 24-54 years; female/male: 14/6) were recruited and completed the behavioural test at baseline, 1-month follow-up and 6-month follow-up. Behavioural results indicated that the behavioural changes in processing speed at 1 and 6 months after surgery compared with baseline were not significant. Importantly, we showed that preoperative resting-state functional connectivity significantly predicted postoperative changes in processing speed at 1 month after surgery (negative network:

Indexed as

connectome-based predictive modellingmoyamoya diseaseneurocognitive functionsprocessing speedresting-state functional connectivity

Identifiers

PMID36072648
PMCPMC9438963
OpenAlexW4292549389

What OpenQuestion holds

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LicenceCC BY
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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.