102 Use of blood pressure trends to predict severity of hypotensive episodes in neonates
Bibliographic record
Abstract
Abstract Background Hypotension leading to circulatory insufficiency is a serious morbidity in neonates admitted to Neonatal Intensive Care Unit (NICU). Early recognition, and timely and appropriate treatment are essential to prevent adverse consequences. However, currently there are no early tools to predict episode severity to allow triaging of patients to higher level of care or intervention. Objectives This study aimed to look at trends in vital signs 6 hours prior to use of vasoactive agent and analyzed the relationship between the early trends and episode severity and outcomes. 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 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. The relationship between changes in vital signs (systolic blood pressure [SBP], diastolic blood pressure [DBP], mean blood pressure [MBP], heart rate and oxygen saturation index [OSI]) and episode severity (VIS) and mortality were examined. Repeated measures analysis of variance models was used to examine trends over time between age groups, and logistic regression models were used to examine predictors of dichotomous outcomes. Results 154 neonates were included in the study. 50.6% of cohort were <28 weeks,14.9% were 28-34 weeks and 34.4% were >34 weeks. Baseline characteristics and underlying etiology for hypotension are summarized in Table 1. On analysis of blood pressure values 6 hours prior to initiation of vasoactive agents (6-0hrs), we detected a significant declining trend over time in SBP, DBP and MBP for all neonates (Figure 1). The changes in heart rate and oxygen requirement were not significant in that 6-hour window. The logistic regression analysis showed that, for every 1-unit drop in SBP 6-0hrs, DBP 6-0hrs and MBP 6-0hrs, VIS increased by 0.30 (95%CI=0.50, 0.10), p=0.003; 0.32 (95%CI=0.56, 0.07), p=0.012; and 0.26 (95%CI=0.51, 0.01), p=0.044 respectively. Similar findings were recorded during the period of 3hours prior to initiation of vasoactive agents (3-0hrs) . Assessment of indices of oxygenation demonstrated that for every 1-unit increase in OSI 3-0hrs, VIS increased by 1.07 (95%CI=0.34, 1.80), p=0.005. Vital sign trends did not show a relationship to mortality as shown in Table 2. Conclusion This study shows that blood pressure drops significantly in the 6 hours prior to actual initiation of vasoactive medications. The rate of drop could successfully predict episode severity. Integrating the rate of hourly change in BP within routine vital monitoring algorithms could be clinically useful in managing vulnerable neonates.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".