A318 DO IMPROVEMENTS IN METABOLIC SYNDROME POST BARIATRIC CARE ASSOCIATED WITH BETTER ORAL HEALTH?
Bibliographic record
Abstract
Obesity and diabetes may predispose to periodontal disease (PD) which is a polymicrobial inflammatory disorder destructing periodontium and promoting chronic systemic inflammation. Proposed mechanisms are increased salivary glucose level from hyperglycemia and hyposalivation, with both affecting the oral microbiome. Bariatric surgery is an effective treatment for obesity with improvements in body weight and insulin sensitivity. Bariatric care protocol also includes a very low calorie diet (VLCD) with Optifast®, used for 2–3 weeks pre-op to facilitate laparoscopic access. VLCD can also reduce weight and blood glucose. This study aims to determine the effect of the bariatric protocol (pre-bariatric VLCD and bariatric surgery) on oral inflammatory load (OIL), a surrogate marker for PD, and stimulated salivary flow rate (SFR) in obese patients. Patients were recruited from the Toronto Western Hospital. Sample collection took place at 3 time-points: pre-VLCD, post-VLCD (surgery day) and 1-month post-surgery. A 30-second mouth rinse was collected to determine neutrophils count using hemocytometer. Subjects were asked to chew on a piece of parafilm to determine salivary flow rate. Blood tests were performed to measure fasting insulin, glucose, and HbA1c. Anthropometric measurements including height, weight, and body mass index (BMI) were measured. Results are expressed as mean ± SD. Twenty patients (18 females, 2 male) were recruited of which 4 were diabetic. Mean age of the patients was 50.5 ± 8.6 years, and BMI was 46.4 ± 5.4 kg/m2. The mean VLCD duration was 16.7 ± 3.5 days. At baseline, 3 patients, assessed by OIL, were diagnosed with PD and one patient had SFR < 0.5ml/min. Overall, weight and blood tests significantly improved after VLCD except for HbA1c (BMI P <0.001, Glucose P= 0.016, insulin P= 0.013, HOMA-IR P= 0.016). Additionally, parameters significantly improved 1-month post-surgery compare to baseline (Glucose P= 0.004, insulin P= 0.008, HOMA-IR P= 0.009, HbA1c P= 0.001, BMI P <0.001). During the bariatric care protocol, the changes of oral measurements were not statistically significant (OIL P= 0.316, SFR P= 0.588). These results suggest that both VLCD and bariatric surgery improve glucose metabolism and weight. However, these preliminary results do not suggest that the bariatric care protocol has a significant impact on oral parameters. CIHR
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".