Economic evaluation alongside the Premature Infants in Need of Transfusion randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: The Premature Infants in Need of Transfusion (PINT) Outcome Study showed no significant difference in the primary outcome of death or neurodevelopmental impairment (NDI) in extremely low birthweight (ELBW) infants. However, a post-hoc analysis expanding the definition of NDI to include borderline intellectual functioning (Mental Development Index (MDI) <85) found an improvement in outcomes in the group maintained at higher haemoglobin levels. OBJECTIVE: To determine the cost effectiveness of more frequent red blood cell transfusions (high-Hb threshold) compared with less frequent transfusions (low-Hb threshold) in ELBW infants. DESIGN/METHODS: The authors performed an economic evaluation using patient-level data collected during the PINT randomised trial. The authors measured comprehensive costs from a third-party payer's perspective over a time horizon from birth through 18-21 months corrected age. RESULTS: The average total cost in the high-Hb threshold group was CAN$149 767 compared with CAN$150 227 in the low-Hb threshold group (difference of CAN$460, p=0.96). Cost-effectiveness analysis estimated savings of CAN$6879 for every additional infant surviving without severe NDI. There was a 48% chance that the high-Hb threshold reduced costs while improving outcome and a 90% chance that it would be cost effective at a willingness-to-pay threshold of CAN$250 000 per additional survivor without severe NDI. Post-hoc analysis defining cognitive delay as MDI score <85, instead of <70, revealed savings in the high-Hb threshold group of CAN$4457 per additional survivor without NDI. Results were robust to deterministic sensitivity analyses. CONCLUSION: A high-Hb threshold for transfusion, as measured in ELBW PINT study infants through 18 months corrected gestational age, may be an economically appealing intervention. The estimates were associated with moderate statistical uncertainty that should be targeted in larger, future studies.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".