A Bayes Study of Bile Acid Constituents on Cholelithiasis and Carcinoma of the Gallbladder
Bibliographic record
Abstract
Background: Significantly high concentration of secondary bile acids and low concentration of primary acids are reported by the surgeons in patients with gallbladder carcinoma (GBC) compared to control and cholelithiasis groups. Aim: To examine the effect of primary and secondary bile acids on the development of cholelithiasis and GBC and to investigate the association, if any, among the two groups of bile acids. Methods: The study uses two groups of patients at a time selected in accordance with some pre-fixed inclusion and exclusion criteria. Informed consent was obtained from all patients. The demographic characteristics such as mean age, sex ratio and body mass index, etc. are obtained for the selected groups of patients. The study defines dichotomous responses and the four bile acid constituents, namely cholic acid (CA), chenodeoxycholic acid (CDCA), deoxycholic acid (DCA) and lithocholic acid (LCA), as the predictors. It then assumes logistic regression model to associate the binary responses with the predictors by using probability scores. Bayes analysis is developed using Markov chain Monte Carlo (MCMC) pack in R software for the posterior simulation. Results: Twenty one cholelithiasis patients and twenty patients in each of control and GBC groups are studied. It is seen that a unit decrement in the level of CA (CDCA) increases the log (odds ratio) for cholelithiasis by an amount of 0.49 (0.14) and odds ratio by almost 1.5 (1.12). Similarly, a unit increment in the level of DCA (LCA) provides the log (odds ratio) for cholelithiasis as 0.18 (1.3) and odds ratio as 1.16 (2.95). Comparing GBC with control population, it is noted that a unit decrease in the level of CA (CDCA) in the control population increases the log (odds ratio) for GBC by an amount of 1.16(0.26) and odds ratio by almost 2.63 (1.24) times. Similarly, the log(odds ratio) for GBC increases by 0.77(1.94) and the odds ratio increases by 1.9 (5.0) for the unit increment in the level of DCA(LCA). Conclusions: The study observes relatively high variations in the primary and secondary bile acids in the cholelithiasis and GBC groups as compared with the control group. It, in turn, reflects strong association among the two categories of bile acids in gallbladder diseases.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".