Inhaled nitric oxide in term/late preterm neonates with hypoxic respiratory failure: estimating the financial impact of earlier use
Bibliographic record
Abstract
OBJECTIVE: We reported recently that early use of inhaled nitric oxide therapy (iNO) for term and late preterm infants with hypoxic respiratory failure (HRF) at an oxygenation index (OI) of ≥15 and <20 is associated with earlier discharge from the hospital, relative to babies treated at OI ≥25. The objective of the present analysis is to determine whether earlier use of iNO in this cohort leads to lower cost of medical care. METHODS: We used a decision-analytic model, which was developed to compare hospital resource use and costs associated with early versus standard use of iNO in HRF. The model population included infants with moderate HRF caused by primary pulmonary hypertension with an OI ≥15 and <20. A hypothetical case population of 1000 patients was assumed and probabilistic sensitivity analyses were completed where all the clinical inputs into the model were varied. Two deterministic sensitivity analyses were also completed, one surrounding the hospital cost inputs and another surrounding the cost of iNO. RESULTS: Early iNO was associated with fewer hospital days, fewer days of ventilation and fewer hours on extracorporeal membrane oxygenation (ECMO). In probabilistic sensitivity analyses, total costs per patient were $88,518 ± $7574 and $92,581 ± $9664 for early iNO and standard iNO, respectively. The probability of early iNO being cost-effective was approximately 72%, based on a willingness to pay $100,000 or less to prevent ECMO therapy and/or death. In both deterministic sensitivity analyses, early iNO was cost-saving. CONCLUSION: Our analysis shows that early use of iNO at an OI of ≥15 and <20 may be associated with shorter hospitalizations and a decreased cost of care for term/late preterm infants with HRF associated with pulmonary hypertension. Our results are based on clinical data from a single trial; future research using data from real-world practice is warranted.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".