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Record W7045352960

The associations between insulin, hypoglycemia, and dementia: Combating threats to internal validity in a series of population-based cohort studies

2023· dissertation· en· W7045352960 on OpenAlexfundaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
FundersUniversity of WaterlooAlzheimer Society
KeywordsConfoundingObservational studyCohort studyEpidemiologyInternal validityDementiaCohortInverse probability weighting
DOInot available

Abstract

fetched live from OpenAlex

Although the association between type 2 diabetes and dementia is recognized, findings from the epidemiology literature on the effect of insulin and one of its side effects, hypoglycemia, are less clear. The currently available observational studies assessing these associations suffer from a wide range of methodological limitations that diminish their internal validity and lead to contradictory evidence. The aim of this thesis is to implement design and analysis techniques to combat bias and confounding in previous studies and to further extend knowledge on the risk of dementia associated with four interconnected diabetes-related exposures, each assessed in a separate study: 1) severe hypoglycemia, 2) age of severe hypoglycemia, 3) insulin use, and 4) the mediating effect of severe hypoglycemia from insulin use. \nHerein, a series of cohort studies were conducted using population-based health administrative data (1996-2018) from British Columbia, Canada housed by Population Data BC. First, we identified individuals newly diagnosed with type 2 diabetes between 01 January 1998 and 31 December 2016. Each cohort was then designed based on the research question, wherein exposure was defined accordingly. For studies 1 and 2, the exposure of interest was severe hypoglycemia compared to no hypoglycemia. For studies 3 and 4, the exposure of interest was insulin initiation compared to initiating a non-insulin class. For all cohorts, the outcome of interest was all-cause dementia. Confounding adjustment techniques including inverse probability of treatment weighting (IPTW) were used in all studies. In each study, a wide range of sensitivity analyses were conducted to ensure the robustness of results. \nFindings from study 1 confirm the previously reported higher risk of all-cause dementia with severe hypoglycemia after implementing exposure density sampling, a lag period, and IPTW (HR 1.83; 95% CI 1.31-2.57). Findings from study 2 show that the increased risk of dementia observed in study 1 is consistent whether hypoglycemia occurs in midlife (HR 2.85; 95% CI 1.72-4.72) or late life (HR 2.38; 95% CI 1.83-3.11). Conversely, findings from study 3 negate existing evidence and do not show an increased risk of dementia associated with insulin use (HR 1.14; 95% CI 0.81-1.60). Lastly, findings from study 4 indicate a potential role of severe hypoglycemia as a mediator of the association between insulin and dementia (Natural Indirect Effect HR 1.04; 95% CI 1.01-1.08). \nCollectively these studies provide further insight on the complex associations between insulin, hypoglycemia, and the risk of all-cause dementia to inform both clinicians and patients with type 2 diabetes on the need to prevent hypoglycemia. Importantly, these studies showcase the need for robust methodology when conducting observational studies for type 2 diabetes-related exposures.

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)0.490
metaresearch head score (Gemma)0.656
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.629

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4900.656
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.009
Bibliometrics0.0070.008
Science and technology studies0.0040.008
Scholarly communication0.0100.005
Open science0.0060.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.299
Teacher spread0.255 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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
Published2023
Admission routes2
Has abstractyes

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