Possible Predictors of Cardiorespiratory Events after Immunization in Preterm Neonates
Bibliographic record
Abstract
BACKGROUND: The influence of the first immunization on cardiorespiratory (CR) stability in very preterm infants is still a controversial subject. OBJECTIVES: To describe the changes induced by immunization on heart and respiratory rate variability (HRV-RRV) and to test a potential association between preimmunization profiles and postimmunization CR events. METHODS: Continuous 72-hour CR recordings and 2.5-hour polysomnographic recordings were performed on very preterm infants immunized after 7 weeks. The results are expressed as medians (interquartile ranges). RESULTS: Immunization was performed on 31 very preterm infants [28 weeks' gestation (26.9-29), birth weight: 965 g (795-1,105)], and was associated with an increased incidence (p < 0.01) of events lasting more than 10 s: bradycardia <80 bpm [2.2 (1.1-7) vs. 1.8 (1-4)/12 h], desaturation [17.6 (9.4-36.4) vs. 13.9 (7.7-33.8)/12 h] and associated bradycardia-desaturation [IB+D, 4.1 (1.4-7.3) vs. 2.4 (1-4.6)/12 h], with mild changes in HRV and no change in RRV. The changes in IB+D frequency were correlated with preimmunization IB+D frequency (r = 0.44, p < 0.05), HRV spectral parameter low frequency/high frequency ratio (LF/HF, r = 0.55, p < 0.01) and approximate entropy of HRV (r = -0.39, p < 0.05). CONCLUSION: The increase in CR events after the first immunization in very preterm infants was associated with: (1) sympathetic predominance in heart rate control (high LF/HF ratio), (2) abnormal oversimplification of HRV (low entropy) and (3) persistent respiratory rhythm control immaturity (high IB+D before vaccine).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".