Continuous Glucose Monitor Shows Potential for Early Hypoglycemia Detection in Hospitalized Patients
Bibliographic record
Abstract
OBJECTIVE: This study shows the potential of continuous glucose monitoring (CGM) for the detection of hypoglycemia in hospitalized patients. RESEARCH DESIGN AND METHODS: A Medtronic Diabetes (Northridge, CA) CGMS iPro continuous glucose recorder was inserted into the subcutaneous tissue of a hospitalized orthopedic surgery patient with type 1 diabetes the day after a moderate hypoglycemia event. The interstitial fluid glucose concentration was recorded every 5 min. Both the patient and the hospital staff were blinded to the CGM data. Bedside capillary blood glucose measurements were performed per hospital protocol. RESULTS: The CGM recorded a repeat severe episode of hypoglycemia the next day. The hospital-defined threshold for hypoglycemia (70 mg/dL) was crossed 4.5 h prior to the patient being found unconscious by the nursing staff. CONCLUSION: Data from the CGMS iPro Recorder illustrate the potential benefit of using a real-time CGM in the hospital to detect hypoglycemia in a more timely fashion compared to infrequent point-of-care glucose meter measurements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".