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The association between primary ovarian insufficiency and increased multimorbidity in a large prospective cohort (Canadian Longitudinal Study on Aging)

2024· article· en· W4402014793 on OpenAlexaffabout
Abirami Kirubarajan, Nazmul Sohel, Alexandra Mayhew, Lauren E. Griffith, Parminder Raina, Alison K. Shea

Bibliographic record

VenueFertility and Sterility · 2024
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsSt. Joseph’s Healthcare HamiltonHamilton Health SciencesImpactMcMaster University
Fundersnot available
KeywordsMedicineProspective cohort studyCohortCohort studyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the prevalence of multimorbidity among individuals with primary ovarian insufficiency (POI) and early menopause compared with those with the average age of menopause. DESIGN: Prospective cohort. SUBJECTS: This prospective cohort encompassed female postmenopausal individuals from the Canadian Longitudinal Study on Aging. The Canadian Longitudinal Study on Aging collected cross-sectional data from 50,000 community-dwelling Canadians aged 45-85 years between 2010 and 2015. EXPOSURE: The primary exposure was POI (defined by onset of menopause at the age of <40 years). Comparators included average age of menopause (age, 46-55 years), early menopause (40-45 years), and late-onset menopause (56-65 years) and those who underwent hysterectomy. MAIN OUTCOME MEASURE(S): The primary outcome was multimorbidity, which was defined as two or more chronic conditions. The secondary outcomes were severe multimorbidity (defined as 3 or more chronic conditions) and frequencies of specific chronic conditions among a comprehensive list of 15 individual conditions. We assessed the association between multimorbidity and age at menopause using logistic regression and odds ratios (ORs), with confidence intervals (CIs) set at 95%. The ORs were adjusted for known predictors of multimorbidity, including age, menopausal hormone therapy, education, ethnicity, self-reported loneliness, living alone, body mass index, smoking habits, nutritional risk, social participation, and physical activity. RESULT(S): A total of 12,339 postmenopausal participants were included, of whom 374 (3.0%) experienced POI and 1,396 (11.3%) experienced early menopause. The prevalence rates of multimorbidity were 64.8% and 51.1% among those with POI and early menopause, respectively. In contrast, only 43.9% of individuals with average age of menopause (age, 46-55 years) had multimorbidity. The OR for multimorbidity in the POI population was 2.5 (95% CI, 2.0-3.1) compared with that in individuals who had the average age of menopause. This relationship was maintained after adjustment for confounders (adjusted OR [aOR], 2.0; 95% CI, 1.5-2.5). The prevalence of severe multimorbidity was also double in the POI group compared with that in the average age group (39.2% vs. 21.1%). There were significantly increased risks of ischemic heart disease (aOR, 2.8; 95% CI, 1.7-4.7), gastric ulcers (aOR, 1.6; 95% CI, 1.1-2.3), and osteoporosis (aOR, 1.6; 95% CI, 1.2-2.1) in the POI group. CONCLUSION(S): Individuals with POI and early menopause experience increased multimorbidity compared with those undergoing menopause at an average age. This trend persists even after adjusting for significant multimorbidity risk factors.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.228
Threshold uncertainty score0.458

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.051
GPT teacher head0.344
Teacher spread0.293 · 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 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

Citations11
Published2024
Admission routes2
Has abstractyes

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