Cardiovascular
OSA severity and cardiovascular risk
Open access · cc by · source: Europe PMC
In >10,000 sleep-study patients, higher apnea–hypopnea burden predicted cardiovascular events and death over years of follow-up.
Study at a glance
- Design
- Cohort — Diagnostic polysomnography cohort linked to administrative CV outcomes
- N
- N=10149 · 10,149 of 11,596 first diagnostic sleep studies linked to admin data (88%)
- Population
- Adults undergoing diagnostic polysomnography
- Outcome
- Composite cardiovascular events and mortality
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Of 10,149 included patients, 11.5% had a composite event over median 68 months. Higher AHI related to higher hazard (e.g., HR 1.49 comparing high vs low AHI in univariate modelling).
Methodology
Adults undergoing diagnostic polysomnography were linked to administrative outcomes; investigators modelled AHI and oxygen-desaturation metrics against a composite of CV events and mortality.
Limitations
Observational sleep-lab cohorts have referral bias; CPAP claims were not clearly protective in adjusted models.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
In observational cancer and sleep cohorts, Cox models turn deprivation, education and disease severity into excess-hazard or event-rate contrasts. ONS Longitudinal Study analyses found less-deprived areas had lower excess hazard for prostate cancer (EHR 0.80) and that absolute net-survival gaps between extreme individual SES profiles were 29.6% in the most deprived areas versus 9.1% in the least; an OSA sleep-lab cohort of 10,149 patients had 11.5% composite events over a median 68 months, with higher AHI linked to higher hazard (e.g. univariate HR 1.49 for high versus low AHI).
Evidence for the claim as stated.
The same modelling family is asked to do two different jobs: describe inequalities and exposures in cohorts, versus test a randomised intervention. The SES-cancer and OSA papers cannot name a single causal mechanism or a treatment that would close the HR gap, whereas the propofol–sevoflurane trial can say the assigned anaesthetic did not shift 5-year survival under its protocol. Reading every HR as if it were that trial overclaims the observational papers and underclaims the trial's design.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
The same modelling family is asked to do two different jobs: describe inequalities and exposures in cohorts, versus test a randomised intervention. The SES-cancer and OSA papers cannot name a single causal mechanism or a treatment that would close the HR gap, whereas the propofol–sevoflurane trial can say the assigned anaesthetic did not shift 5-year survival under its protocol. Reading every HR as if it were that trial overclaims the observational papers and underclaims the trial's design.
- Supports · Individual SES and cancer survival
- Supports · Propofol vs sevoflurane and breast cancer survival
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Same topic cluster — not a recommendation engine.