MétaCan
Menu
Back to cohort
Record W1503098162 · doi:10.14740/jnr.v5i3.324

The Effect of Nocturnal Blood Pressure Changes on the Cognitive State of Patients With Parkinson’s Disease

2015· article· en· W1503098162 on OpenAlexvenueno aff
Adem Akkurt, Hüseyin Alparslan Şahin, Çetin Kürşad Akpınar, Mustafa Ceylan, İbrahim Akkurt

Bibliographic record

VenueJournal of Neurology Research · 2015
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsDipperMedicineStroop effectCognitionBlood pressureNeuropsychologyDiseaseCognitive declineNeuropsychological testInternal medicineAudiologyCardiologyAmbulatory blood pressureDementiaPsychiatry

Abstract

fetched live from OpenAlex

This article has been retracted by the authors. Background: Recent data have revealed that cognitive involvement occurs, more or less, in every stage of idiopathic Parkinson’s disease (IPD), which is definitely going to cause radical changes in this traditional understanding. The effects of blood pressure changes during the night on the cognitive states of patients with IPD are not known for sure. The purpose of this study was to research the effects of blood pressure changes during the night on cognitive state of patients with IPD. Methods: A total of 30 patients, 14 females and 16 males, were followed with a diagnosis of IPD. Cognitive functions were assessed with an extensive neuropsychological test battery. Results: The fifth stage of Stroop test, test of line direction, test of face recognition and Hooper test were significantly different in dipper group when compared with the non-dipper group. Conclusion: Not having nocturnal blood pressure decrease in IPD can be accepted as a risk factor in terms of cognitive function disorders. J Neurol Res. 2015;5(3):207-212 doi: http://dx.doi.org/10.14740/jnr324w

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.330
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Neurology ResearchSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207