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Antidepressant’s long-term effect on cognitive performance and cardiovascular system

2022· article· en· W4294234251 on OpenAlexaboutno aff
A.H.S. Nasser

Bibliographic record

VenueCardiometry · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)AntidepressantDementiaScopusCognitionMedical prescriptionMedicinePsychiatryCognitive declinePsychologyMEDLINEInternal medicinePharmacologyDisease

Abstract

fetched live from OpenAlex

Background: The nature of antidepressants and their adverse effects should be considered when treating severe depression in individuals with psychotic symptoms. Antidepressant prescription rates have risen steadily over the last 30 years, affecting people of all ages. Aim: The goal of this study was to see if depression and antidepressant usage were linked to long-term changes in cognitive function and cardiovascular health. Methodology: Meta-analysis was performed using PRISMA guidelines along with using the SPIDER search framework using related keywords on different search engines i.e. Google scholars, PubMed, Scopus, ISI, etc. Total (n=2256) papers were obtained and assessed for eligibility. Altogether 15 studies were included using databases and other methods. The Newcastle-Ottawa Scale examined the grades provided by the data after numerous screenings. Result: A distinct link was found between antidepressants with cognitive performance and the cardiovascular system. Dementia and hypertension were prevailing long-term effects caused by frequent use of antidepressants in chronic and mild depression.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.094
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.291
Teacher spread0.277 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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