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Table_1_Association of Essential Tremor With Dementia and Affective Disorders: A Meta-Analysis.doc

2022· dataset· en· W6927263047 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInfections and bacterial resistance
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaAnxietyOdds ratioCognitionEssential tremorMEDLINEMeta-analysisDepressive symptoms

Abstract

fetched live from OpenAlex

Background<p>The dementia and affective disorders are common non-motor features in patients with essential tremor (ET). However, the relationship of ET with cognitive impairments and affective disorders remains controversial. This meta-analysis aimed to analyze the association of ET with dementia and affective disorders.</p>Methods<p>Original studies published from January 1999 to October 2019 were systematically searched from the database of Medline (OvidSP), EMBASE (OvidSP), and the Cochrane Central Register of Controlled Trials. Pooled standard mean difference (SMD, random effect model), odds ratios (ORs), relative risk (RR), and 95% CI were calculated.</p>Results<p>Compared with the Non-ET group, patients with ET had significantly lower Mini-Mental State Examination (MMSE) score (SMD, −1.16; 95% CI, −1.75 to −0.58; p = 0.0001) and had significantly higher depressive and anxiety symptoms scale score (SMD, 0.55; 95% CI, 0.22–0.87; p = 0.0009). The OR for dementia and affective disorders in individuals with ET compared with individuals without ET was 2.49 (95% CI, 2.17–2.85, p < 0.00001). While there was no significant difference in Montreal Cognitive Assessment (MoCA) score between ET and Non-ET groups (SMD, −0.52; 95% CI, −0.16 to 0.13; p = 0.23), there was a significant difference in the risk of mortality between ET and Non-ET groups (RR = 4.69, 95% CI, 2.18–10.07).</p>Conclusion<p>The non-motor symptoms should not be neglected among patients with ET. However, the causal relationship between ET and dementia, depression, and anxiety is unclear.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.203
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.2030.000

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 head0.012
GPT teacher head0.251
Teacher spread0.238 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

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