ReviewRevista de neurologia2025
[Neurology in Bohemian Lights].
Review in Revista de neurologia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionValle-Inclán's Bohemian Lights is the inaugural work of the esperpento, a literary genre that was born with the intention of offering distorted images of reality as a way of accessing it in a reflexive way. MATERIAL AND
methodsCritical reading of the editio princeps of the work to analyze its neurological content.
resultsThe character of Max Estrella, inspired by the figure of Alejandro Sawa, would not meet the criteria for encephalitis. The diagnoses of Charles Bonnet syndrome and death due to stroke are more likely. The characters at the wake discuss the differential diagnosis between death and catalepsy, and one of them suffers a non-epileptic event.
conclusionsBohemian Lights reflects different social, political and cultural aspects contemporary to the author. Health and disease are also addressed, with a preponderant role for neurology.
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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.