ArticleNeural regeneration research2012
Neuroimaging diagnosis for cerebral infarction: An 8-year bibliometric analysis.
Article in Neural regeneration research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
- Predicting cerebral infarction in COPD patients: an individualized nomogram based on arterial oxygen saturation.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo identify global research trends in neuroimaging diagnosis for cerebral infarction using a bibliometric analysis of the Web of Science. DATA RETRIEVAL: We performed a bibliometric analysis of data retrieval for neuroimaging diagnosis for cerebral infarction containing the key words "CT, magnetic resonance imaging, MRI, transcranial Doppler, transvaginal color Doppler, digital subtraction angiography, and cerebral infarction" using the Web of Science. SELECTION CRITERIA: Inclusion criteria were: (a) peer-reviewed articles on neuroimaging diagnosis for cerebral infarction which were published and indexed in the Web of Science; (b) original research articles and reviews; and (c) publication between 2004-2011. Exclusion criteria were: (a) articles that required manual searching or telephone access; and (b) corrected papers or book chapters.
main outcome measures(1) Annual publication output; (2) distribution according to country; (3) distribution according to institution; (4) top cited publications; (5) distribution according to journals; and (6) comparison of study results on neuroimaging diagnosis for cerebral infarction.
resultsImaging has become the predominant method used in diagnosing cerebral infarction. The most frequently used clinical imaging methods were digital subtraction angiography, CT, MRI, and transcranial color Doppler examination. Digital subtraction angiography is used as the gold standard. However, it is a costly and time-consuming invasive diagnosis that requires some radiation exposure, and is poorly accepted by patients. As such, it is mostly adopted in interventional therapy in the clinic. CT is now accepted as a rapid, simple, and reliable non-invasive method for use in diagnosis of cerebrovascular disease and preoperative appraisal. Ultrasonic Doppler can be used to reflect the hardness of the vascular wall and the nature of the plaque more clearly than CT and MRI.
conclusionAt present, there is no unified standard of classification of cerebral infarction imaging. Detection of clinical super-acute cerebral infarction remains controversial due to its changes on imaging, lack of specificity, and its similarity to a space-occupying lesion. Neuroimaging diagnosis for cerebral infarction remains a highly active area of research and development.
Indexed as
Identifiers
What OpenQuestion holds
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.