Evaluation of a Low-Cost Insulin Infusion Pump Prototype: In Vitro Preliminary Results
Bibliographic record
Abstract
Diabetes Mellitus (DM) is considered a worldwide epidemic, posing a major challenge for health systems around the world. According to the World Health Organization (WHO), 1 in 11 people lives with diabetes, indicating that there are around 684 million of diabetic patients in the world. According to data from the Brazilian Society of Diabetes, the estimated number of children and adolescents affected by DM type 1 (DM1) in Brazil is approximately 100 thousand, and the majority of them are individuals under 14 years old. DM1 is generally associated with extremely serious acute and chronic complications, due to improper blood glucose control. One of the therapies used for DM treatment is the insulin infusion pump (IIP), and although approximately 15% of DM1 patients have an absolute indication for its use, the number of patients with access to this type of treatment is still very low, especially in Brazil. The main limiting factor for the use of IIP in Brazil is due to the high cost of the device (around US$3,750 or R$15,000) and supplies such as syringes, batteries, cannulas and catheters (US$250.00/month or R$1,000/month), since these are imported items. These factors restrict the use of IPP by the majority of DM1 patients. Our main goal is to develop a low-cost commercial IIP whose estimated value would represent onequarter of the value of available IIP commercialized in Brazil. We are currently developing and testing (in vitro) this low-cost IIP prototype, which works using cheaper solutions, including a commercial battery and also a universal syringe. Considering that we are working with a critical medical system, the aim of this study was to perform in vitro quantitative tests to evaluate the accuracy of the low-cost IIP prototype, and based on the results, adapt our system according to the performance. Based on preliminary in vitro analysis, it was possible to conclude that the prototype presents precision, as determined by the absence of statistical differences during the tests. This gives important support for further analysis of the prototype and improvement of the system.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".