Long-Term Follow-Up of Autonomic and Enteric Measures in Patients Undergoing Vertical Banded Gastroplasty for Morbid Obesity
Bibliographic record
Abstract
BACKGROUND: A multi-component model of autonomic and enteric factors may correlate with ultimate weight loss or gain after restrictive obesity surgery. This study aimed to determine relevant parameters to predict successful long-term weight loss. METHODS: Thirty-nine patients (four males and 35 females) with a mean age of 37.2 years were followed for over 15 years after vertical banded gastroplasty. Baseline adrenergic: postural adjustment ratio (PAR) and vasoconstriction (VC); cholinergic: electrocardiogram R-to-R interval (RRI) and enteric measure: electrogastrogram (EGG) were utilized by a discriminant function analysis to classify patients as a long-term loser or gainer. Using latest weight compared to baseline, patients were divided as 10 gainers and 29 losers. RESULTS: A discriminate model successfully predicted ultimate weight gain in 8/10 (80%) of patients who subsequently gained weight and weight loss in 24/29 (83%) of patients who lost weight for a total correct classification of 32/39 (82%). The same model with data at 3 months postoperatively predicted weight gain in 9/10 (90%) of patients and weight loss in 24/29 (83%) of patients, for a total correct classification of 34/39 (87%). CONCLUSIONS: A multi-component model at baseline and 3 months postoperative can predict long-term weight outcome from restrictive obesity surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".