Neonatal hypertension: concerns within and beyond the neonatal intensive care unit

Efficacy and Safety of Mydriatic Microdrops for Retinopathy of Prematurity Screening: The MyMiROPS Randomized Clinical Trial

Importance

Commercial mydriatics administered in preterm infants during retinopathy of prematurity (ROP) screening have been associated with various cardiorespiratory and gastrointestinal adverse events.

Objective

To examine whether microdrops of a combined mixture of 1.67% phenylephrine and 0.33% tropicamide are noninferior to standard drops regarding mydriatic efficacy at 45, 90, and 120 minutes. The occurrence of systemic adverse events and systemic absorption of phenylephrine eyedrops were additional secondary outcomes.

Design, Setting, and Participants

This randomized clinical trial with a double-masked, noninferiority, crossover design included infants undergoing ROP screening at a tertiary center in Northern Greece from September 2021 to January 2023. Eligible participants were infants with gestational age below 32 weeks and/or birthweight under 1501 g, or infants beyond these thresholds referred by an attending neonatologist due to comorbidities.

Interventions

Either microdrops or standard drops of the diluted mixture were administered at a random allocation sequence with a 1-week washout period.

Main outcomes and measures

The horizontal pupil diameter at 45, 90, and 120 minutes was measured using a customized ruler in 0.5-mm increments. Mixed-effects linear regression models were developed, and the confidence interval (CI) approach was used for assessing noninferiority. The predefined noninferiority margin was -0.4 mm. Heart rate; oxygen saturation; blood pressure measurements at 45, 90, and 120 minutes; 24-hour hypertensive episodes; and 48-hour systemic adverse events were assessed. Phenylephrine concentration in peripheral blood within 3 hours postinstillation was measured using hydrophilic liquid chromatography-tandem mass spectrometry. Pooled pharmacokinetic parameters were calculated based on a developed mathematical model.

Results

A total of 83 infants were randomized (mean [SD] gestational age, 29.7 [2.0] weeks; mean [SD] birth weight, 1277 [374] g). Microdrops proved to be superior regarding mydriatic efficacy at 45 minutes (mean difference, 0.12; Bonferroni-corrected 95% CI, 0.01 to 0.23; P = .008) and noninferior at 90 minutes (Bonferroni-corrected 95% CI, -0.10 to 0.17) and 120 minutes (Bonferroni-corrected 95% CI, -0.18 to 0.14). Lower levels of oxygen saturation at 45 minutes (mean difference, 0.66; 95% CI, 0.09 to 1.24; P = .03) and 90 minutes (mean difference, 0.58; 95% CI, 0.03 to 1.14; P = .04) and higher percentage of 24-hour hypertensive episodes (median [IQR] percentage of hypertensive episodes: microdrops, 0.10% [0.02%-0.19%] vs standard drops, 0.14% [0.06%-0.40%]; P = .01) were observed after standard drops. A 1-compartment model with first-order absorption best described the pharmacokinetic data.

Conclusion and Relevance

To our knowledge, this is the first study establishing noninferiority of microdrops compared with standard drops of a diluted mydriatic mixture, showing reduced systemic adverse events after microdrops and determining the pharmacokinetic profile of phenylephrine eyedrops in preterm infants.

Trial Registration

ClinicalTrials.gov Identifier: NCT05043077.

Neonatal intermittent hypoxemia events are associated with later systemic hypertension

BACKGROUND

Approximately 5% of very premature infants delivered at less than 30 weeks' gestation have systemic hypertension. In adult human and animal models, intermittent hypoxemia events are associated with systemic hypertension. In neonates, intermittent hypoxemia events are associated with adverse outcomes, but it is unknown if they are a risk factor for hypertension. We hypothesize that early intermittent hypoxemia events in very preterm neonates are associated with systemic hypertension at 34-36 weeks' postmenstrual age.

METHODS

Secondary analysis of a single-center cohort study of 164 infants, <31 weeks' gestational age. Intermittent hypoxemia events were continuously recorded during the first 21 days of age.

RESULTS

There was a significant association between the number of intermittent hypoxemia events (per 100) and systemic hypertension (OR (95% CI) = 1.08 (1.01-1.15)), and both the number of intermittent hypoxemia events (per 100 β (95% CI) = 0.22 (0.10-0.34)) and percent of time with hypoxemia (β (95% CI) = 0.10 (0.01-0.19)) and systolic blood pressure at 34-36 weeks' postmenstrual age.

CONCLUSION

This study demonstrated a higher incidence of early intermittent hypoxemia events in preterm infants with hypertension. Decreasing intermittent hypoxemia during this critical period may reduce incidence of later vascular stress in this population.

IMPACT

Intermittent hypoxemia events are very common in premature infants and increased frequency of intermittent hypoxemia events is associated with morbidity. Intermittent hypoxemia events in adult human as well as adult and neonatal animal models are associated with systemic hypertension. This study demonstrated an association between early intermittent hypoxemia events and systemic hypertension in very preterm neonates, adding to the body of literature of possible morbidities caused by intermittent hypoxemia events. This study addresses the common, though under-recognized, issue of neonatal hypertension, and suggests increased intermittent hypoxemia events may be contributory.

Distilling the knowledge from large-language model for health event prediction

Health event prediction is empowered by the rapid and wide application of electronic health records (EHR). In the Intensive Care Unit (ICU), precisely predicting the health related events in advance is essential for providing treatment and intervention to improve the patients outcomes. EHR is a kind of multi-modal data containing clinical text, time series, structured data, etc. Most health event prediction works focus on a single modality, e.g., text or tabular EHR. How to effectively learn from the multi-modal EHR for health event prediction remains a challenge. Inspired by the strong capability in text processing of large language model (LLM), we propose the framework CKLE for health event prediction by distilling the knowledge from LLM and learning from multi-modal EHR. There are two challenges of applying LLM in the health event prediction, the first one is most LLM can only handle text data rather than other modalities, e.g., structured data. The second challenge is the privacy issue of health applications requires the LLM to be locally deployed, which may be limited by the computational resource. CKLE solves the challenges of LLM scalability and portability in the healthcare domain by distilling the cross-modality knowledge from LLM into the health event predictive model. To fully take advantage of the strong power of LLM, the raw clinical text is refined and augmented with prompt learning. The embedding of clinical text are generated by LLM. To effectively distill the knowledge of LLM into the predictive model, we design a cross-modality knowledge distillation (KD) method. A specially designed training objective will be used for the KD process with the consideration of multiple modality and patient similarity. The KD loss function consists of two parts. The first one is cross-modality contrastive loss function, which models the correlation of different modalities from the same patient. The second one is patient similarity learning loss function to model the correlations between similar patients. The cross-modality knowledge distillation can distill the rich information in clinical text and the knowledge of LLM into the predictive model on structured EHR data. To demonstrate the effectiveness of CKLE, we evaluate CKLE on two health event prediction tasks in the field of cardiology, heart failure prediction and hypertension prediction. We select the 7125 patients from MIMIC-III dataset and split them into train/validation/test sets. We can achieve a maximum 4.48% improvement in accuracy compared to state-of-the-art predictive model designed for health event prediction. The results demonstrate CKLE can surpass the baseline prediction models significantly on both normal and limited label settings. We also conduct the case study on cardiology disease analysis in the heart failure and hypertension prediction. Through the feature importance calculation, we analyse the salient features related to the cardiology disease which corresponds to the medical domain knowledge. The superior performance and interpretability of CKLE pave a promising way to leverage the power and knowledge of LLM in the health event prediction in real-world clinical settings.

Pediatric Hypertension: A Condition That Matters

Systemic hypertension has been considered mainly as an adult health issue for a long time, but it is now being increasingly acknowledged as a significant problem also among pediatric patients. The frequency of pediatric hypertension has grown mostly because of increases in childhood obesity and sedentary lifestyles, but secondary forms of hypertension play a role as well. Considering that unaddressed hypertension during childhood can result in enduring cardiovascular complications, timely identification and intervention are essential. Strategies for addressing this disease encompass not only lifestyle adjustments, but also the use of medications when needed. Lifestyle modifications entail encouraging a nutritious diet, consistent physical activity, and the maintenance of a healthy weight. Moreover, educating both children and their caregivers about monitoring blood pressure at home can aid in long-term management. Thus, the aim of this review is to discuss the etiologies, classification, and principles of the treatment of hypertension in pediatric patients.

Common Clinical Scenarios of Systemic Hypertension in the NICU

Hypertension affects ∼1% to 3% of newborns in the NICU. However, the identification and management of hypertension can be challenging because of the lack of data-driven diagnostic criteria and management guidelines. In this review, we summarize the most recent approaches to diagnosis, evaluation, and treatment of hypertension in neonates and infants. We also identify common clinical conditions in neonates in whom hypertension occurs, such as renal vascular and parenchymal disease, bronchopulmonary dysplasia, and cardiac conditions, and address specific considerations for the evaluation and treatment of hypertension in those conditions. Finally, we discuss the importance of ongoing monitoring and long-term follow-up of infants diagnosed with hypertension.

Management of acute severe hypertension in youth: from the philosophical to the practical

PURPOSE OF REVIEW

Acute severe hypertension remains an uncommon but important source of morbidity and mortality in youth. However, there has been very little progress made in our understanding of how to best manage youth with acute severe hypertension to improve patient outcomes.

RECENT FINDINGS

Our understanding of what is acute severe hypertension is undergoing a philosophical change. Management of patients with acute severe hypertension is evolving towards more of a risk and outcomes-based approach.

SUMMARY

We should be intentional when we consider whether a patient has acute severe hypertension and if they are truly at an increased risk for life-threatening target organ injury. We should consider their specific risk factors to best interpret the risks and benefits of how best to treat a patient with acute severe hypertension, rather than relying on traditional approaches and conventional wisdom. We should always ask 'why' when we are pursuing a given management course. Future studies should clearly define the research questions they are investigating to best advance the field to ultimately improve patient outcomes.