Iron deficiency following bariatric surgery: a retrospective cohort study
Bibliographic record
Abstract
Iron deficiency is a common consequence of bariatric surgery and frequently leads to anemia. Our study reports the incidence and predictors of iron deficiency, iron deficiency anemia (IDA), and IV iron use after bariatric surgery. We conducted a retrospective study of all adult patients who underwent bariatric surgery from January to December 2012 at the regional bariatric surgery center in Hamilton, Ontario, Canada, and were followed for at least 6 months. Time-to-event data were presented as Kaplan-Meier curves. Cox regression analysis was used to identify outcome predictors. A total of 388 patients met the inclusion criteria. Iron deficiency, IDA, and the use of IV iron were reported in 43%, 16%, and 6% of patients, respectively, with a mean follow-up of 31 months. The cumulative incidence of iron deficiency and IDA increased with longer follow-up, and there was a significant increase in IV iron use starting 3 years after surgery. Malabsorptive procedures (hazard ratio [HR], 1.92; 95% confidence interval [CI], 1.20-3.06; P = .006) and low baseline ferritin (HR, 0.96; 95% CI, 0.95-0.97; P < .001) were associated with an increased risk of iron deficiency. Young age (HR, 0.90; 95% CI, 0.82-0.99; P = .028), baseline anemia (HR, 19.6; 95% CI, 7.85-48.9; P < .001), and low baseline ferritin (HR, 0.96; 95% CI, 0.95-0.98; P < .001) were associated with an increased risk of IDA. Our results suggest that IDA is a delayed consequence of bariatric surgery and that preoperative assessment of patient risk may be possible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".