Current approach and attitudes toward neonatal near‐miss and perinatal audits: An exploratory international survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Combined with perinatal mortality review, neonatal near-miss (NNM) audit has the potential to inform strategies to better prevent adverse perinatal outcomes. Nonetheless, there is lack of standardised definitions of NNM and limited evidence of implementation of NNM audits. AIM: To describe definitions of NNM and assess current approaches and attitudes toward perinatal mortality and morbidity audit. MATERIALS AND METHODS: Online survey from December 2021 to February 2022, with a mix of Likert scales, polar, pool, multi-choice, and open-ended questions, disseminated through national and international organisations to perinatal healthcare workers from high-income countries. RESULTS: One hundred and twenty participants came from Australia (n = 86), New Zealand (n = 18), Canada (n = 7), USA (n = 4), Netherlands (n = 2), other countries (n = 3). Neonatologists (35%), midwives (21.7%), obstetricians (12.5%), neonatal nurse practitioners (11.7%) and others (23.3%) responded. Most respondents thought the main characteristics to define NNM were birth asphyxia needing therapeutic hypothermia (68.3%), unexpected resuscitation at birth (67.5%), need for intubation/chest compression/adrenaline (65.0%) and metabolic acidosis at birth (60.0%). There were 97.5% of participants who considered NNM important for identifying cases for perinatal morbidity audits. However, only 10.0% of their institutions used a NNM definition. Overall, 98.4% of participants considered perinatal mortality and morbidity audits important to prevent adverse outcomes. CONCLUSION: Neonatal near-miss audit is viewed as a valuable tool to reduce adverse neonatal outcomes. There was reasonable consensus that NNM encompassed evidence of birth asphyxia and/or advanced neonatal resuscitation. Data from this international survey identifies a starting point for a consensus definition of NNM, which can be used for perinatal audits to identify opportunities for improvement.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it