Journal of clinical monitoring and computing
-
J Clin Monit Comput · Aug 2019
Randomized Controlled TrialEffects of continuous positive airway pressure in patients at high risk of obstructive sleep apnea during propofol sedation after spinal anesthesia.
In patients with obstructive sleep apnea, short-term use of a continuous positive airway pressure mask improves oxygenation, decreases the apnea-hypopnea index, and reduces hemodynamic instability. In this study, we investigated the effects of use of a continuous positive airway pressure mask in patients at high risk of obstructive sleep apnea during propofol sedation after spinal anesthesia. Forty patients who underwent propofol sedation after spinal anesthesia for transurethral bladder or prostate resection with a STOP-Bang score of 3 or more were enrolled in this study. ⋯ There were no significant differences in hemodynamic changes between the two groups. Apnea-hypopnea index was significantly reduced in the continuous positive airway pressure mask group compared to the simple facial mask group. Application of a continuous positive airway pressure mask in a patient at high risk of obstructive sleep apnea can lower the incidence of obstructive sleep apnea during sedation without a significant effect on hemodynamic stability.
-
We evaluated the accuracy and precision of a novel non-invasive monitoring device in comparison with conventional monitoring methods used in intensive care units (ICU). The study device was developed to measure blood pressure, pulse rate, respiratory rate, and oxygen saturation, continuously with a single sensor using the photoplethysmographic technique. Patients who were monitored with arterial pressure lines in the ICU were enrolled. ⋯ Percent errors for systolic, diastolic and mean blood pressures were 2.4% and 6.7% and 6.5%, respectively. Percent errors for pulse rate, respiratory rate and oxygen saturation were 3.4%, 5.6% and 1.4%, respectively. The non-invasive, continuous, multi-parameter monitoring device presented high level of agreement with the invasive arterial blood pressure monitoring, along with sufficient accuracy and precision in the measurements of pulse rate, respiratory rate, and oxygen saturation.
-
J Clin Monit Comput · Aug 2019
Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting adoption and efficacy of clinical pathway. Machine intelligence can potentially identify clinical variation and may provide useful insights to create and optimize clinical pathways. ⋯ Multiple sub-groups were easily created and analyzed. Adherence reporting tools were easy to use enabling almost real time monitoring. Machine intelligence provided useful insights to create and monitor care pathways with several advantages over traditional analytic approaches including: (1) analysis across disparate data sets, (2) unsupervised discovery, (3) speed and auto-generation of clinical pathways, (4) ease of use by team members, and (5) adherence reporting.
-
J Clin Monit Comput · Aug 2019
Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiology when analysed in detail can however be predictive of acute deterioration leading to cardiac or respiratory arrests. ⋯ A positive predictive value of 11% and negative predictive value of 98% was obtained with a prevalence of 5% by our method of prediction. While clinicians predicted 4 out of the 69 cardiac arrests (6%), the prediction system predicted 63 (91%) cardiac arrests. Prospective validation of the automated system remains.
-
J Clin Monit Comput · Aug 2019
Selection of cuffed endotracheal tube for children with congenital heart disease based on an ultrasound-based linear regression formula.
It remains to be discovered whether a formula predicting the subglottic transverse diameter measured by ultrasound (SGDformula) for the selection of an appropriate endotracheal tube (ETT) for children without congenital heart disease (CHD) is useful for children with CHD. A formula for predicting SGD was established after assessing 60 children ≤ 8 years without CHD and validated on 60 children with CHD. We selected the cuffed ETT size based on the SGD by ultrasound (SGDultra). ⋯ And the mean bias (SGDformula-ETT size and SGDultra-ETT size) was 0.21 mm (95% confidence interval, - 0.59 to 1.01 mm) and 0.00 mm (- 0.79 to 0.84 mm). For the CHD group, the ultrasound-based method yielded a 78% success rate of ETT size choice, while the formula-based method permitted an appropriate ETT size in only 32% of subjects (P < 0.001). Our analysis showed that measuring the SGDultra was more accurate in predicting the correct OD of the ETT in children with CHD undergoing cardiovascular surgery, based on the correlation and agreement with ETT OD.