Autonomy of Patients With Type 2 Diabetes With an Insulin Pump Device
Bibliographic record
Abstract
BACKGROUND: Insulin pump therapy may be offered to patients with type 2 diabetes that is not controlled by multiple daily injections. Patients with type 2 diabetes may suffer from unrecognized cognitive disabilities, which may compromise the use of a pump device. METHODS: To predict patient autonomy, we evaluated 39 patients with type 2 diabetes from our database (n = 143) after continuous subcutaneous insulin infusion (CSII) initiation using (1) an autonomy questionnaire evaluating the patient's cognitive and operative capacities for CSII utilization, (2) the Montreal Cognitive Assessment (MOCA) for the detection of mild cognitive disabilities, (3) the Hospital Anxiety and Depression Scale (HADS) for the detection of anxiety and depression, and (4) the Diabetes Treatment Satisfaction Questionnaire (DTSQ). Patients were selected to constitute 3 groups matched for age, with different degrees of autonomy at discharge after the initial training program: complete (n = 13), partial (n = 13), or no autonomy (n = 13). RESULTS: The satisfaction level with the pump device was high. At the last follow-up visit, only 23% of patients did not reach complete autonomy. The autonomy score correlated fairly with the MOCA score (R = 0.771, P < .001). A receiver operating characteristic (ROC) analysis showed that at a cut-off score of 24, the MOCA identified autonomous versus dependent patients at long-term follow-up (area under the ROC curve [AUC], 0.893; sensitivity, 81%; specificity, 81%). The HADS correlated negatively with the autonomy score, and the sociocultural level also influenced autonomy with pump utilization. CONCLUSION: Patients with type 2 diabetes with partial autonomy at discharge may progress to complete autonomy. The MOCA and HADS may help predict a patient's ability to manage with a pump device.
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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 | 0.004 |
| 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 | 0.000 |
| Research integrity | 0.000 | 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".