Well, I Wouldn't be Any Worse Off, Would I, Than I am Now? A Qualitative Study of Decision-Making, Hopes, and Realities of Adults With Type 1 Diabetes Undergoing Islet Cell Transplantation
Bibliographic record
Abstract
BACKGROUND: For selected individuals with type 1 diabetes, pancreatic islet transplantation (IT) prevents recurrent severe hypoglycemia and optimizes glycemia, although ongoing systemic immunosuppression is needed. Our aim was to explore candidates and recipients' expectations of transplantation, their experience of being on the waiting list, and (for recipients) the procedure and life posttransplant. METHODS: Cross-sectional qualitative research design using semistructured interviews with 16 adults (8 pretransplant, 8 posttransplant; from 4 UK centers (n = 13) and 1 Canadian center (n = 3)). Interviews were audio-recorded, transcribed, and underwent inductive thematic analysis. RESULTS: Interviewees were aged (mean ± SD) 52 ± 10 years (range, 30-64); duration of diabetes, 36 ± 9 years (range, 21-56); 12 (75%) were women. Narrative accounts centered on expectations, hopes, and realities; decision-making; waiting and uncertainty; the procedure, hospital stay, and follow-up. Expected benefits included fewer severe hypoglycemic episodes, reduced need for insulin, preventing onset/progression of complications and improved psychological well-being. These were realized for most, at least in the short term. Most interviewees described well-informed, shared decision-making with clinicians and family, and managing their expectations. Although life "on the list" could be stressful, and immunosuppressant side effects were severe, interviewees reported "no regrets." Posttransplant, interviewees experienced increased confidence, through freedom from hypoglycemia and regained glycemic control, which tempered any disappointment about continued reliance on insulin. Most viewed their transplant as a success, though several reflected upon setbacks and hidden hopes for becoming "insulin-free." CONCLUSIONS: Independently undertaken interviews demonstrated realistic and balanced expectations of IT and indicate how to optimize the process and support for future IT candidates.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".