Using a Large, Contemporary Database for Decision-Making at 22 to 25 Weeks’ Gestational Age
Bibliographic record
Abstract
As Edwards et al point out in this issue of Pediatrics, the management of infants born extremely preterm (ie, 22–25 weeks’ gestational age) presents clinicians and families with difficult and complex decisions.1 Their high-quality study of nearly 23 000 infants receiving care at more than 600 neonatal intensive care units (NICUs) from 2020 to 2022 provides contemporary data to inform shared decision-making (SDM), at a time of changing resuscitation practices. For example, the large numbers of births at 22 and 23 weeks’ gestation provides improved precision for SDM.Edwards et al1 propose that decision-making is best accomplished by SDM. SDM is defined as an approach in which clinicians and parents share the best available evidence, parents are supported to consider options, and achieve informed preferences to “select the best course of action for them.”2 This goes beyond sharing the decision with parents, but rather sharing the decision-making process. Edwards et al1 identify that “most important is improving communication and shared decision making with families.” That capable, informed parents ought to be the ultimate decision makers is particularly important in the context of medical uncertainty. Moreover, parents deal with the psychological, emotional, physical, and financial responsibility of the decision.3To use these findings in SDM, clinicians need to assess whether these data are applicable to their patients. For example, this study is based on all live births, without congenital anomalies, born at level 3 or level 4 NICUs. Hospital of birth is an important driver of outcome. Results from study NICUs, which are part of the Vermont Oxford Network, may not be generalizable to community NICUs or NICUs outside of the United States. Survival improves with intent-to-treat, which is difficult to measure4 and is not directly assessed in this study.Edwards et al1 report survival to hospital discharge as the primary outcome and time to death, survival without what they classify as “severe” neonatal complications, length of hospital stay, and technology dependence as secondary outcomes. These are important, but what other information do parents need for decision-making? Parents have reported other outcomes such as child well-being, quality of life, and functional, socioemotional, and behavioral outcomes as important.5 Because these outcomes take years to develop, having contemporary and relevant data are challenging.The terminology used to describe outcomes to parents during SDM is important. The subjective term “severe” may portray a more negative image than parents perceive.6 The use of neutral terms and factual descriptions, rather than “severe” are preferred by parents.7 Parents also want to hear a balanced perspective of the positive outcomes as well as potential challenges.8There are many factors that influence long-term outcomes, such as the social drivers of health. The ability to predict the likelihood of specific outcomes improves over time, but the inherent medical uncertainty requires approaching decision-making with humility.Parents may wish to engage in the decision-making process in different ways. Most parents want to share the decision with health care providers (HCP). Some parents understand parental decision-making authority as their duty, whereas other parents do not wish to take on this role, leaving the ultimate decision to the HCP. Any of these options ought to be acceptable.The authors of this study identify that the ultimate goal is to achieve long-term health and well-being of infants and their families. With this in mind, when communicating with parents, HCP must be aware of their own biases, and approach parents with a curiosity about what is important for the family, and hence communicate information that will assist parents in decision-making.Edwards et al1 provide useful current statistics, which may be helpful to parents in decision-making. Key considerations are discussed, such as the importance of improving communication and the SDM process, concomitantly providing the opportunity to improve clinical management.
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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 | 0.007 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".