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Record W4303982527 · doi:10.36106/ijsr/9003812

EFFECT OF CHANGE IN ESTROGEN LEVELS ON COGNITIVE FUNCTIONS IN PREMENOPAUSAL, EARLY PERIMENOPAUSAL AND LATE PERIMENOPAUSAL FEMALES: A HOSPITAL BASED CROSS-SECTIONAL STUDY

2022· article· en· W4303982527 on OpenAlexaboutno aff
Swati Chaurasia, Meenakshi Gupta, Nazia Ishrat

Bibliographic record

VenueINTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH · 2022
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsEstrogenMedicineMenopauseCognitionCorrelationCross-sectional studyAffect (linguistics)Cognitive declineGynecologyPhysiologyObstetricsInternal medicinePsychologyDiseaseDementiaPsychiatry

Abstract

fetched live from OpenAlex

Background: There is an established link between the change in levels of Estrogen and its affect on mental health in middle age females. Objective: To see the correlation between serum Estrogen levels and cognitive functions in the study groups. Methods: This was a hospital based crosssectional study involving a total of 90 females who were divided into three groups of 30 females each, based on their age and menstrual history.These groups were premenopausal(31-35 years ) ,early perimenopausal( 36-40 years,),late perimenopausal (41- 45 years).The level of serum Estrogen was estimated in all the study subjects and their cognitive assessment was done using Montreal Cognitive Assessment scale(MoCA). One way ANOVA was used to asses the signicance. Results: There is a correlation between cognitive decline and serum estrogen levels in late perimenopausal age group as compared to early perimenopausal and premenopausal age group. Conclusion: There is a signicant relationship between estrogen levels and cognitive functions in middle aged females.

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)0.006
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 score0.060
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.223
GPT teacher head0.498
Teacher spread0.275 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueINTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCHSame topicMenopause: Health Impacts and TreatmentsFrench-language works237,207