Mortality risks associated with Barrett’s oesophagus: authors' reply
Bibliographic record
Abstract
Sirs, We are grateful for the comments of Cook et al. but disagree with their conclusion that ‘the overall evidence currently available suggests that Barrett’s oesophagus (BE) has little, if any, effect on the risk of other specific causes of death when compared to the population’. Their data1 suggest an increase in all-cause mortality as do others2, 3 with an overall increase in standardized mortality rate of between 15% and 46%. Most clinicians would feel this was clinically important. The situation may be more pronounced as BE predominantly affects white men of high socioeconomic status.4 Population studies can adjust only for a very limited number of confounding factors and high socioeconomic status is associated with a decrease in standardized mortality ratio (SMR). It is possible therefore that population studies evaluating BE will be biased towards the null hypothesis and that the increase in SMR may be underestimated. We hoped to address this partly, by studying a smaller geographical area, which might reduce the influence of confounding factors. We accept, however, that our study is still relatively small in size with a limited duration of follow up as we acknowledged in our discussion. We also acknowledge that in narrowing the population, our data may be less generalizable, which could explain the high SMRs we observed.5 As far as specific causes of mortality are concerned, we agree that data are conflicting but felt that it was important to publish our data so that in time, a fuller picture can emerge as to what are the individual causes that drive the increase in overall mortality. We believe that data suggest that BE patients are at an increased risk of all-cause mortality and clinicians should evaluate the whole patient and not just their Barrett’s mucosa. Declaration of personal interests: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.025 | 0.037 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".