The cost implications of continuous glucose monitoring in pregnant women with type 1 diabetes in 3 Canadian provinces: a posthoc cost analysis of the CONCEPTT trial
Bibliographic record
Abstract
BACKGROUND: The Continuous Glucose Monitoring in Women with Type 1 Diabetes in Pregnancy Trial (CONCEPTT) found improved health outcomes for mothers and their infants among those randomized to self-monitoring of blood glucose (SMBG) with continuous glucose monitoring (CGM) compared with SMBG alone. In this study, we evaluated whether CGM or standard SMBG was more or less costly from the perspective of a third-party payer. METHODS: We conducted a posthoc analysis of data from the CONCEPTT trial (Mar. 25, 2013, to Mar. 22, 2016). Health care resource data from 215 pregnant women, randomized to CGM or SMBG, were collected from 31 hospitals in 7 countries. We determined resource costs posthoc based on prices from hospitals in 3 Canadian provinces (Ontario, British Columbia, Alberta). The primary outcome was the difference between groups in the mean total cost of care for mother and infant dyads, paid by each government (i.e., the third-party payer) from randomization to hospital discharge (time horizon). The secondary outcome included CGM and SMBG costs not paid by governments (e.g., glucose monitoring devices and supplies). RESULTS: The mean total cost of care was lower in the CGM group compared with the SMBG group in each province (Ontario: $13 270.25 v. $18 465.21, difference in mean total cost [DMT] -$5194.96, 95% confidence interval [CI] -$9841 to -$1395; BC: $13 480.57 v. $18 762.17, DMT -$5281.60, 95% CI -$9964 to -$1382; Alberta: $13 294.39 v. $18 674.45, DMT -$5380.06, 95% CI -$10 216 to -$1490). There was no difference in the secondary outcome. INTERPRETATION: Government health care costs are lower when CGM is paid by the patient, driven by lower costs from reduced use of the neonatal intensive care unit in the CGM group; however, when governments pay for CGM equipment, there is no overall cost difference between CGM and SMBG. Governments should consider paying for CGM, as it results in improved maternal and neonatal outcomes with no added overall cost. TRIAL REGISTRATION: ClinicalTrials.gov, no. NCT01788527.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".