FP674ORAL SYMPTOMS AND SALIVARY FUNCTION AND ASSOCIATION WITH MORTALITY IN HAEMODIALYSIS PATIENTS: A PROSPECTIVE COHORT ANALYSIS (ORAL-D SUBSTUDY)
Bibliographic record
Abstract
INTRODUCTION: Impaired oral symptoms and saliva characteristics are frequently reported in adults treated with long term hemodialysis. We evaluated the prevalence and severity of oral symptoms and salivary function and association with mortality. METHODS: We did a planned analysis in the ORAL-D study, a multinational cohort study involving a standardised oral and dental examination among 4726 haemodialysis patients. We assessed oral mucosal self-reported symptoms (thirst and xerostomia) and salivary characteristics (pH, buffer capacity, flow rate pre/post dialysis). The association with all-cause and cardiovascular mortality was estimated using a Cox proportional hazard regression model adjusted for country, age, sex, education, smoking history, prior myocardial infarction, diabetes, haemoglobin, serum albumin, serum phosphorus, time on dialysis and body mass index. RESULTS: In 4205 adults (mean age 61.6±15.6 years) who underwent an oral examination, the mean salivary pH was 7.45 (SD 1.35), with more than 60% of patients (n=1621) having high salivary buffering capacity. The mean pre-dialysis salivary flow rate was 0.83 (SD 0.74) ml/min, and slightly decreased at the end of treatment (0.76 ± 0.80 ml/min). During median follow-up of 3.5 years, salivary flow rate was associated with lower all-cause (adjusted hazard ratio (aHR) 0.85, 95% CI 0.76 to 0.95 for pre-dialysis flow rate and aHR 0.84, 95% CI 0.75 to 0.94 for post-dialysis flow rate) and cardiovascular mortality (HR 0.74, 95% CI 0.62 to 0.90 for pre-dialysis flow rate and HR 0.74, 95% CI 0.61 to 0.90 for post-dialysis flow rate). When considering the risk of mortality associated with Xerostomia Inventory items, requiring to sip a drink to swallow better was associated with all-cause and cardiovascular mortality (HR 1.26, 95% CI 1.07 to 1.48 and 1.30, 95% CI 1.02 to 1.66, respectively). Other survey items were associated with all-cause mortality, but not cardiovascular mortality (dry mouth, dry lips, wake up to drink during the night). Similarly, Thirst Inventory items (thirsty during the night and thirsty during the dialytic session) were associated with all-cause mortality. CONCLUSIONS: Oral symptoms are prevalent in haemodialysis patients. Salivary characteristics and related symptoms are associated with mortality.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".