104 A scoring tool for predicting severity of hemodynamic instability in neonates
Bibliographic record
Abstract
Abstract Background Hemodynamic instability in neonates admitted to Neonatal Intensive Care Unit (NICU) is common and necessitates immediate treatment. The course and severity of hemodynamic instability can be varied. At present, there are no algorithms or tools available to predict episode severity. Objectives In this study we aimed to develop a scoring system (HINT) based on hemodynamic and metabolic parameters at the onset of hypotension requiring treatment and analyzed the ability of such a scoring system to predict episode related severity, morbidity, and mortality. Design/Methods This was a retrospective cohort study at a tertiary care NICU in Southwestern Ontario that included all neonates who needed inotropic support between Jan 1, 2018, to Dec 31, 2022. Data regarding physiological and metabolic parameters in the 6 hours prior to inotropic agent start were collected. Details of the episodes including number of vasoactive agents, doses, vasoactive inotropic score (VIS) and outcomes such as mortality were collected. Linear regression and receiver operating characteristic curves were used to examine the effect of the scoring system. Results 155 neonates were included in the study with a mean (SD) gestational age of 30.0 (6.2) weeks. Mean (SD) postnatal age of onset of hypotension was 6.2 (12.4) days. 78.1% of neonates were inborn and 63.9% of hypotensive episodes occurred within the first 72 hours of life (Table 1). The HINT scoring system utilized lowest blood pressure (systolic, diastolic, and mean); lowest urine output, highest heart rate, highest capillary refill time, highest base deficit, and maximum oxygen saturation index in the 6 hours prior to initiation of hypotensive agent (Table 2). The scoring system showed a positive correlation with the VIS score; for every additional point on the severity score scale, VIS increased by 2.05 (95%CI=0.28, 3.82), p=0.023 (Figure 1). The score did not emerge as a good predictor of episode related mortality (AUC=0.57), need of multiple inotrope (AUC=0.63) or days on inotropes (p=0.603). Conclusion This study designed a novel predictive tool based on physiological and metabolic derangement at onset of hypotensive episode. While higher scores on HINT were associated with higher inotropic support need (VIS) during episode, it did not show reliable accuracy to predict outcomes such as mortality which limits its clinical application. Future studies that incorporate etiology and gestational age within the score could be interesting.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".