Dietary acid load significantly predicts 10-years survival in patients underwent coronary artery bypass grafting (CABG) surgery
Bibliographic record
Abstract
BACKGROUNDS: Numerous studies have revealed the role of dietary acid load as a potential risk factor for cardiovascular events and blood pressure. However, its role in predicting the mortality rate in patients underwent coronary artery bypass grafting surgery (CABG) has not been reported. In the current study we aimed to evaluate the relationship of dietary acid load and cardio-metabolic risk factors with ten year survival among patients underwent CABG. METHODS: The current prospective cohort study comprises 454 patients underwent CABG. Anthropometric, clinical and biochemical measurements were performed. Dietary acid load was calculated as either potential renal acid load (PRAL) or net endogenous acid production (NEPA) using the data obtained from a semi-quantitative food frequency questionnaire (FFQ). Survival analysis was performed using Kaplan-Meier method followed by log-rank test. The association between all-cause mortality and study parameters was performed with Cox-proportional hazard model. RESULTS: Patients in the higher PRAL and NEAP quartiles had lower BMI and lower ejection fraction rate (P <0.05). Moreover, lower hematocrit values were observed in patients of higher PRAL quartiles. Higher PRAL scores were associated with higher mortality rate and reduced survival days (adjusted hazard ratio: 1.023 (1.00-1.04; P-value = 0.01). However, there was no relationship between NEAP and survival. CONCLUSIONS: We revealed that high PRAL scores are positive predictors of 10-year mortality in patients underwent CABG. The results of our study suggest that maintaining an adequate acid-base balance can contribute to longevity by reducing the risk of mortality.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".