Unanswered questions in hypertension: prematurity and long-term trajectories, masked and white coat hypertension

Blood Pressure Estimation Based on PPG and ECG Signals Using Knowledge Distillation

OBJECTIVE

Easy access bio-signals are useful for alleviating the shortcomings and difficulties associated with cuff-based and invasive blood pressure (BP) measurement techniques. This study proposes a deep learning model, trained using knowledge distillation, based on photoplethysmographic (PPG) and electrocardiogram (ECG) signals to estimate systolic and diastolic blood pressures.

METHODS

The estimation model comprises convolutional layers followed by one bidirectional recurrent layer and attention layers. The training approach involves knowledge distillation, where a smaller model (student model) is trained by leveraging information from a larger model (teacher model).

RESULTS

The proposed multistage model was evaluated on 1205 subjects from Medical Information Mart for Intensive Care (MIMIC) III database using the Association for the Advancement of Medical Instrumentation (AAMI) and the standards of the British Hypertension Society (BHS). The results revealed that our model performance achieved grade A in estimating both systolic blood pressure (SBP) and diastolic blood pressure (DBP) and met the requirements of the AAMI standard. After training with knowledge distillation (KD), the model achieved a mean absolute error and standard deviation of 2.94 ± 5.61 mmHg for SBP and 2.02 ± 3.60 mmHg for DBP.

CONCLUSION

Our results demonstrate the benefits of the knowledge distillation training method in reducing the number of parameters and improving the predictive accuracy of the blood pressure regression model.

Pharmacogenomics-based individualized treatment of hypertension in preterm infants: A case report and review of the literature

BACKGROUND

Neonatal hypertension is a rare but potentially serious condition that requires careful monitoring and treatment. Pharmacogenomics can help guide individualized drug therapy and improve outcomes.

CASE SUMMARY

We report a case of a preterm infant with multiple complications, including bronchopulmonary dysplasia (BPD), sepsis, intracranial hemorrhage, and hypertension. The infant was treated with various drugs, including dexamethasone and amlodipine. The infant was diagnosed with neonatal hypertension based on blood pressure measurements exceeding the 95th percentile for his age and sex. The possible causes of hypertension included dexamethasone, hydrochlorothiazide, spironolactone, and BPD. The infant was treated with oral amlodipine to lower his blood pressure. A pharmacogenomic test was performed to evaluate the genetic polymorphisms of ABCB1 and CYP3A5, which are involved in the metabolism and transport of dexamethasone and amlodipine. The infant's blood pressure was well controlled after the dose of amlodipine was reduced according to the pharmacogenomic results. The infant had a stable general condition and was discharged on the 100th d after birth.

CONCLUSION

This case illustrates the importance of regular blood pressure monitoring and etiological investigation in preterm infants with hypertension. Pharmacogenomics can provide useful information for individualized drug therapy and safety in this population.