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Record W4391468518 · doi:10.1371/journal.pone.0296662

Association of hypoglycemic events with cognitive impairment in patients with type 2 diabetes mellitus: Protocol for a dose-response meta-analysis

2024· article· en· W4391468518 on OpenAlexaboutno aff
Min Ye, A. Yuan, Qi Qi Yang, Q. Li, Fei Li

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
FundersNatural Science Foundation of Anhui ProvinceAnhui University of Chinese MedicineAnhui University
KeywordsHypoglycemiaMedicineMeta-analysisCochrane LibraryCognitionGlycemicMEDLINEObservational studyType 2 Diabetes MellitusDiabetes mellitusIncidence (geometry)Systematic reviewPsychiatryInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

INTRODUCTION: With an incidence rate as high as 46%-58%, hypoglycemia is a common complication of glycemic management among those suffering from type 2 diabetes mellitus(T2DM). According to preclinical research, hypoglycemia episodes may impair cognition by harming neurons. However, there is still controversy regarding the clinical evidence for the relationship between hypoglycemic events and the likelihood of cognitive impairment. Furthermore, little research has been done on the dose-response association between hypoglycemia incidents and the possibility of cognitive impairment. To address these knowledge gaps, the present research intends to update the comprehension of the association among hypoglycemic events and the risk of cognitive impairment and to clarify the correlation between dose and response by incorporating the most recent investigations. METHOD AND ANALYSIS: This work has developed a protocol for a systematic review and meta-analysis that will examine, via a well-organized assessment of several databases, the relationship between the incidence of hypoglycemia and the probability of cognitive impairment. Observational studies investigating the connection between hypoglycemia episodes and cognitive impairment will be included. The databases that will be searched are PubMed, Web of Science, the Chinese Biomedical Literature Database (CBM), Cochrane Library, Embase, the China National Knowledge (CNKI), Wan Fang, the Chinese Science and Technology Periodical Database (VIP), and Du Xiu. Literature from the establishment of each database to December 2023 will be included in the search. Two researchers will independently screen the studies that satisfy the requirements for both inclusion and exclusion. A third researcher will be asked to mediate any disputes. The methodological caliber of the studies included will be assessed utilizing the Newcastle-Ottawa Scale (NOS) or the Joanna Briggs Institute (JBI) critical appraisal method. With regard to GRADE, which stands for Grading of Recommendations, Assessment, Development, and Evaluation, the quality of the evidence will be evaluated. ROBIS Tool will be used to evaluate the risk of bias in the development of the systematic review. If the data is accessible, meta-analysis and dose-response curve analysis will be employed by Stata software. However, if the data does not allow for such analysis, a descriptive review will be performed. DISCUSSION AND CONCLUSION: Hypoglycemic episodes may raise the likelihood of cognitive impairment, according to earlier investigations. This study will update the relevant evidence and explore the dose-response connection between hypoglycemic episodes and cognitive impairment. The results of this review will have significant effects on decision-making by individuals with diabetes, healthcare providers, and government policy institutions. TRIAL REGISTRATION: Prospero registration number: CRD42023432352.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.075
metaresearch head score (Gemma)0.095
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.075
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.095
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0230.047
Bibliometrics0.0060.006
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0050.003
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0280.003

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 head0.073
GPT teacher head0.318
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreProtocol

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

Citations3
Published2024
Admission routes1
Has abstractyes

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