Sleep Goal Index (SGI) - A new success outcome criteria on 618 OSA patients.
Bibliographic record
Abstract
INTRODUCTION: Sleep-Goal Index (SGI) comprises of Blood Pressure, AHI (number of apnoea and hypopnea events per hour), T90 (duration of oxygen below 90% and BMI (body mass index). This study aims to demonstrate SGI as a holistic, comprehensive and practical measurement of treatment outcomes in OSA (obstructive sleep apnoea) management. MATERIALS AND METHODS: A prospective 10-center clinical trial of 618 OSA patients, who underwent nose, palate and/or tongue surgery. Pre- and post-operative data were analyzed and compared with the Sher's criteria (AHI reduction 50% and <20) and the Sleep Goal Index. RESULTS: There were 514 males and 104 females, mean age of 45.8±13.1 years. Mean snore VAS improved from 7.6±1.9 to 2.8±2.1 (p<0.001), mean Epworth score (ESS) improved from 11.5±4.8 to 5.4±3.5 (p<0.001), mean BMI decreased from 28.6±4.8 to 27.3±5.3 (p<0.001), gross weight decreased from 82.4±14.2kg to 78.1±13.3kg (p<0.001). Mean AHI decreased 37.4±25.7 to 16.4±14.6 (p<0.001), mean LSAT improved 74.5±18.4% to 85.4±7.6% (p<0.001), and mean T90 (time spent <90%) decreased from 27.7±8.9 minutes to 9.7±2.1 minutes (p<0.001). Mean SBP decreased from 130.4±19.4 to 121.1±14.6mmHg, mean DBP decreased from 84.7±13.4 to 79.5±12.3mmHg. The overall success rate (Sher's criteria) was 55.7%. Based on McNemar's test, comparing Sher's criteria and SGI (4 parameters - BP, BMI, T90, AHI), it was demonstrated that fulfilling any 2 out of 4 SGI parameters would be just as sensitive as Sher's criteria, whilst being more holistic and representative of the patients' oxidative stress. From McNemar's test, the overall duo-paired combination and permutations of these 4 SGI parameters ranged from 41.8% to 60.9%. DISCUSSION: AHI as a single parameter to measure OSA treatment success can be unreliable. The SGI is a holistic, comprehensive, easily measured and better patient appreciated measurement index reflecting true end-organ function/improvement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".