Survey into blood glucose control in critically ill adult patients in the Netherlands.
Bibliographic record
Abstract
BACKGROUND: To study current clinical practice in blood glucose (BG) control in adult intensive care units (ICUs) in the Netherlands. METHODS: We performed a national survey focusing on blood glucose targets, insulin administration, BG control guidelines, and opinions regarding BG control aiming for normoglycaemia (known as intensive insulin therapy, IIT). RESULTS: The completed questionnaire was returned by 88/113 (78%) of the participating centres. In 98% (86/88) of the ICUs some sort of BG control was being practised. Half of the ICUs (42/86, 48%) used tight BG targets as with IIT; 28/86 (33%) and 13/86 (15%) used more liberal targets of 4.4 to 7.0 mmol/l and 4.4 to 8.0 mmol/l, respectively. Eighty-two (93%) reported having a local guideline on BG control (or IIT). The BG threshold to start insulin was 7.0+/-1.3 mmol/l vs 7.8+/-1.3 mmol/l in ICUs that practised IIT vs ICUs that practised less tight BG control, respectively (p=0.005). In 28/86 (33%) measurement of the BG values was done according to a strict time schedule (i.e., BG values were measured on predefined time points). While respondents were fairly agreed on the benefits of IIT, opinions regarding ease of implementation and time needed to apply this strategy varied. In addition, severe hypoglycaemia was considered a serious side effect of IIT. CONCLUSION: Approximately half of the ICUs in the Netherlands reported having implemented IIT. However, the full guideline as used in the original studies on IIT was hardly ever implemented. Concerns about severe hypoglycaemia, at least in part, hampers implementation of IIT.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".