Financial toxicity among patients undergoing resectional surgery for inflammatory bowel disease in the United States
Bibliographic record
Abstract
AIM: Financial toxicity describes the financial burden and distress that patients experience due to medical treatment. Financial toxicity has yet to be characterized among patients with inflammatory bowel disease (IBD) undergoing surgical management of their disease. This study investigated the risk of financial toxicity associated with undergoing surgery for IBD. METHODS: This study used a retrospective analysis using the National Inpatient Sample from 2015 to 2019. Adult patients who underwent IBD-related surgery were identified using the International Classification of Diseases (10th Revision) diagnostic and procedure codes and stratified into privately insured and uninsured groups. The primary outcome was risk of financial toxicity, defined as hospital admission charges that constituted 40% or more of patient's post-subsistence income. Secondary outcomes included total hospital admission cost and predictors of financial toxicity. RESULTS: The analytical cohort consisted of 6412 privately insured and 3694 uninsured patients. Overall median hospital charges were $21 628 (interquartile range $14 758-$35 386). Risk of financial toxicity was 86.5% among uninsured patients and 0% among insured patients. Predictors of financial toxicity included emergency admission, being in the lowest residential income quartile and having ulcerative colitis (compared to Crohn's disease). Additional predictors were being of Black race or male sex. CONCLUSION: Financial toxicity is a serious consequence of IBD-related surgery among uninsured patients. Given the pervasive nature of this consequence, future steps to support uninsured patients receiving surgery, in particular emergency surgery, related to their IBD are needed to protect this group from financial risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".