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Record W2756584220

A Risk Stratification Model for Adult Patients with Obstructive Sleep Apnea: Development and Evaluation

2014· dissertation· en· W2756584220 on OpenAlexfundaboutno aff
Tetyana Kendzerska

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
FundersInstitute for Clinical Evaluative Sciences
KeywordsRisk stratificationObstructive sleep apneaMedicineSleep apneaStratification (seeds)Internal medicineIntensive care medicineCardiologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Despite emerging evidence that obstructive sleep apnea (OSA) may cause cardio-metabolic disturbances independently of known risk factors, the strength and significance of this association remains unclear. This thesis is comprised of three studies assessing the long term-consequences of OSA, and specifically the prognostic value of OSA-related variables for cardiovascular (CV) events, all-cause mortality and incident diabetes. Methods: The first study is a systematic review of longitudinal studies, from 1999 to 2011. Quality was assessed using published guidelines. Studies two and three linked a clinical sleep database to Ontario health administrative databases for the period of 1991 to 2011 to examine the relationship between OSA variables and a composite CV outcome and incident diabetes. For the latter, we assembled a cohort free of diabetes at baseline, as defined by health administrative data. Cox regression models were used to investigate the association between of OSA-related predictors and outcomes of interest, controlling for potential confounders. Study one identified significant relationships between OSA and all-cause mortality and composite CV outcome in men; associations with other outcomes remain uncertain. Among OSA-related variables, only apnea-hypopnea index (AHI) was a consistent predictor. Limitations of the clinically-based studies were small numbers of events, weak definitions of outcomes, and inconsistency in polysomnographic scoring criteria over time. Study two found that 1,172 (11.5%) of 10,149 participants experienced our composite CV event over a median follow-up of 68 months. In a fully adjusted model, the following OSA-related variables were significant independent predictors: time spent with oxygen saturation (SaO2) < 90%, sleep time, awakenings, periodic leg movements, heart rate, and presence of daytime sleepiness. In study three, of 8,678 cohort participants without diabetes at baseline, 1,017 (11.7%) developed incident diabetes over a median follow-up of 67 months. In fully-adjusted models, patients with AHI > 30 had a 30% higher hazard of developing diabetes than those with AHI < 5. Among other OSA-related variables, REM-AHI, and SaO2<90%, heart rate and neck circumference were associated with incident diabetes. Conclusions: Based on these studies, we demonstrated that OSA-related predictors significantly and independently contribute to the risk for occurrence of composite CV outcome and incidence diabetes.

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)0.013
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.017
GPT teacher head0.278
Teacher spread0.262 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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