“Mild’’ Hypoxic-Ischaemic Encephalopathy and Therapeutic Hypothermia: A Survey of Clinical Practice and Opinion from 35 Countries
Bibliographic record
Abstract
<b><i>Introduction:</i></b> We aimed to determine global professional opinion and practice for the use of therapeutic hypothermia (TH) for treating infants with mild hypoxic-ischaemic encephalopathy (HIE). <b><i>Methods:</i></b> A web-based survey (REDCap) was distributed via emails, social networking sites, and professional groups from October 2020 to February 2021 to neonatal clinicians in 35 countries. <b><i>Results:</i></b> A total of 484 responses were obtained from 35 countries and categorized into low/middle-income (43%, LMIC) or high-income (57%, HIC) countries. Of the 484 respondents, 53% would provide TH in mild HIE on case-to-case basis and only 25% would never cool. Clinicians from LMIC were more likely to routinely offer TH in mild HIE (25% <i>v</i> HIC 16%, <i>p</i> &#x3c; 0.05), have a unit protocol for providing TH (50% <i>v</i> HIC 26%, <i>p</i> &#x3c; 0.05), use adjunctive tools, e.g., aEEG (49% <i>v</i> HIC 32%, <i>p</i> &#x3c; 0.001), conduct an MRI post TH (48% <i>v</i> HIC 40%, <i>p</i> &#x3c; 0.05) and less likely to use neurological examinations as a HIE severity grading tool (80% <i>v</i> HIC 95%, <i>p</i> &#x3c; 0.001). The majority of respondents (91%) would support a randomized controlled trial that was sufficiently large to examine neurodevelopmental outcomes in mild HIE after TH. <b><i>Conclusions:</i></b> This is the first survey of global opinion for TH in mild HIE. The overwhelming majority of professionals would consider “cooling” an infant with mild HIE, but LMIC respondents were more likely to routinely cool infants with mild HIE and use adjunctive tools for diagnosis and follow-up. There is wide practice heterogeneity and a sufficiently large RCT designed to examine neurodevelopmental outcomes, is urgently needed and widely supported.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".