Journal of clinical monitoring and computing
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J Clin Monit Comput · Aug 2024
Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients.
Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring's predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. ⋯ In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76-0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.
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J Clin Monit Comput · Aug 2024
High frequency variability index in predicting postoperative pain in video/robotic-assisted thoracoscopic surgery under combined general anesthesia and peripheral nerve block: an observational study.
The high frequency variability index (HFVI)/analgesia nociception index (ANI) is purported to assess the balance between nociception and analgesia in patients under general anesthesia. This observational study investigated whether intraoperative HFVI/ANI correlates with postoperative pain in patients performed with nerve block under general anesthesia in video/robotic-assisted thoracoscopic surgery (VATS/RATS). We investigated whether maximum postoperative pain at rest and postoperative morphine consumption are associated with HFVI/ANI just before extubation, mean HFVI/ANI during anesthesia, the difference in HFVI/ANI between before and 5 min after the start of surgery, and the difference in HFVI/ANI between before and 5 min after the nerve block. ⋯ Receiver operating characteristic curve analysis revealed that moderate (NRS > 3) or severe (NRS > 7) postoperative pain could not be predicted by HFVI/ANI just before extubation. In addition, there were no associations between postoperative morphine consumption and HFVI/ANI at any time points. The present study demonstrated that it is difficult to predict the degree of postoperative pain in patients undergoing VATS/RATS under general anesthesia combined with peripheral nerve block, by using HFVI/ANI obtained at multiple time points during general anesthesia.
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J Clin Monit Comput · Aug 2024
Feasibility study of the use of a wearable vital sign patch in an intensive care unit setting.
Multiple studies and review papers have concluded that early warning systems have a positive effect on clinical outcomes, patient safety and clinical performances. Despite the substantial evidence affirming the efficacy of EWS applications, persistent barriers hinder their seamless integration into clinical practice. Notably, EWS, such as the National Early Warning Score, simplify multifaceted clinical conditions into singular numerical indices, thereby risking the oversight of critical clinical indicators and nuanced fluctuations in patients' health status. ⋯ Spearman's correlation coefficient showed a very high correlation of ρ = 0.9 8 for heart rate and a moderate correlation of ρ = 0.66 for respiratory rate. In comparison with the ventilated respiratory rate (ventilation machine) the Vivalink and ECG-based monitoring system both had a moderate correlation of ρ = 0.68 . A very high correlation was found between the heart rate measured by the Vivalink Cardiac patch and that of the ECG-based monitoring system of the hospital. Concerning respiratory rate the correlation between the data from the Vivalink Cardiac patch, the ECG-based monitoring system and the ventilation machine was found to be moderate.
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J Clin Monit Comput · Aug 2024
The impact of a lung-protective ventilation mode using transpulmonary driving pressure titrated positive end-expiratory pressure on the prognosis of patients with acute respiratory distress syndrome.
This study aimed to assess the impact of a lung-protective ventilation strategy utilizing transpulmonary driving pressure titrated positive end-expiratory pressure (PEEP) on the prognosis [mechanical ventilation duration, hospital stay, 28-day mortality rate and incidence of ventilator-associated pneumonia (VAP), survival outcome] of patients with Acute Respiratory Distress Syndrome (ARDS). ⋯ Lung-protective mechanical ventilation using transpulmonary driving pressure titrated PEEP effectively improves lung function, reduces mechanical ventilation duration and hospital stay, and enhances survival outcomes in patients with ARDS. However, further study is needed to facilitate the wider adoption of this approach.
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J Clin Monit Comput · Aug 2024
Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.
Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive arterial blood pressure monitors. This study tested whether routine non-invasive monitors could also predict intraoperative hypotension using deep learning algorithms. ⋯ A deep learning model utilizing multi-channel non-invasive monitors could predict intraoperative hypotension with high accuracy. Future prospective studies are needed to determine whether this model can assist clinicians in preventing hypotension in patients undergoing surgery with non-invasive monitoring.