International survey on diagnosis and management of hypotension in extremely preterm babies
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
UNLABELLED: Hypotension is a commonly diagnosed and treated complication of extremely low gestational age newborns (ELGAN), but enormous variation in diagnosis, management and clinical practice has been documented. We sought to evaluate practice regarding the management of hypotension in ELGANs and developed a web-based questionnaire addressing diagnosis, intervention thresholds and modes of treatment of hypotension in ELGANs. We received 216 completed questionnaires from respondents in 38 countries. Most responses (83 %) were from specialist units where, together, over 26,000 very low birth weight (VLBW) infants are cared for annually. The majority (73 %) defined hypotension as a mean blood pressure (BP) in mmHg less than the gestational age in weeks. Sixty percent assessed the circulation with additional methods; echocardiography was the most commonly used (74 %), with left ventricular output and fractional shortening the two most common measurements made. The majority (85 %) used volume administration as the initial intervention. Dopamine was the inotrope most commonly used initially (80 %). If the initial inotrope therapy failed, dobutamine was the most popular second-line treatment (28 %). Delayed cord clamping was used at 51 % of the centres. CONCLUSION: The definition of hypotension in ELGANs continues to follow traditional standards. Functional echocardiography is now used to assess the circulation at many centres. Volume expansion and dopamine remain the most frequently used therapies.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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