Journal of clinical monitoring and computing
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J Clin Monit Comput · Feb 2019
Observational StudyPractical impact of a decision support for goal-directed fluid therapy on protocol adherence: a clinical implementation study in patients undergoing major abdominal surgery.
The purpose of this study was to assess the effects of using a real time clinical decision-support system, "Assisted Fluid Management" (AFM), to guide goal-directed fluid therapy (GDFT) during major abdominal surgery. We compared a group of patients managed using the AFM system with a historical cohort of patients (control group) who had been managed using a manual GDFT strategy. Adherence to the protocol was defined as the relative intraoperative time spent with a stroke volume variation (SVV) < 13%. ⋯ The incidence of postoperative complications was comparable in the two groups. Implementation of a decision support system for GDFT guidance resulted in a significantly longer period during surgery with a SVV < 13% with a reduced total amount of fluid administered. Trial registration: Clinical Trials.gov (NCT03141411).
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J Clin Monit Comput · Feb 2019
Can postoperative deltoid weakness after cervical laminoplasty be prevented by using intraoperative neurophysiological monitoring?
Laminoplasty, frequently performed in patients with cervical myelopathy, is safe and provides relatively good results. However, motor palsy of the upper extremities, which occurs after decompression surgery for cervical myelopathy, often reduces muscle strength of the deltoid muscle, mainly in the C5 myotome. The aim of this study was to investigate prospectively whether postoperative deltoid weakness (DW) can be predicted by performing intraoperative neurophysiological monitoring (IONM) during cervical laminoplasty and to clarify whether it is possible to prevent palsy using IONM. ⋯ Persistent Br(E)-MsEP alerts of the deltoid muscle had a 100% sensitivity and specificity for predicting a postoperative acute deficit. IONM was unable to predict delayed-onset DW. In only 1 patient were we able to prevent postoperative DW by performing a foraminotomy.
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J Clin Monit Comput · Feb 2019
Finger and forehead photoplethysmography-derived pulse-pressure variation and the benefits of baseline correction.
To non-invasively predict fluid responsiveness, respiration-induced pulse amplitude variation (PAV) in the photoplethysmographic (PPG) signal has been proposed as an alternative to pulse pressure variation (PPV) in the arterial blood pressure (ABP) signal. However, it is still unclear how the performance of the PPG-derived PAV is site-dependent during surgery. The aim of this study is to compare finger- and forehead-PPG derived PAV in their ability to approach the value and trend of ABP-derived PPV. ⋯ By correcting for the baseline variation, improved agreements were obtained for both the finger and forehead, and the difference between these two agreements was diminished. The tracking abilities for both finger- and forehead-derived PAV still warrant improvement for wide use in clinical practice. Overall, our results show that baseline-corrected finger- and forehead-derived PAV may provide a non-invasive alternative for PPV.
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J Clin Monit Comput · Feb 2019
Observational StudyAn elevated respiratory quotient predicts complications after cardiac surgery under extracorporeal circulation: an observational pilot study.
Following cardiac surgery, hyperlactatemia due to anaerobic metabolism is associated with an increase in both morbidity and mortality. We previously found that an elevated respiratory quotient (RQ) predicts anaerobic metabolism. In the present study we aimed to demonstrate that it is also associated with poor outcome following cardiac surgery. ⋯ The AUC for RQ to predict mortality was 0.77 (IC95% [0.70-0.84]), with a threshold value of 0.76 (sensitivity 64%, specificity 100%). By comparison, the AUC for lactate levels was significantly superior (AUClact 0.89, IC95% [0.83-0.93], p = 0.02). In this study, elevated RQ appeared to be predictive of mortality after cardiac surgery with CPB.
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J Clin Monit Comput · Feb 2019
Predicting delayed cerebral ischemia after subarachnoid hemorrhage using physiological time series data.
To develop and validate a prediction model for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) using a temporal unsupervised feature engineering approach, demonstrating improved precision over standard features. 488 consecutive SAH admissions from 2006 to 2014 to a tertiary care hospital were included. Models were trained on 80%, while 20% were set aside for validation testing. Baseline information and standard grading scales were evaluated: age, sex, Hunt Hess grade, modified Fisher Scale (mFS), and Glasgow Coma Scale (GCS). ⋯ Combined baseline and physiologic features with redundant feature reduction: AUC 0.77. Current DCI prediction tools rely on admission imaging and are advantageously simple to employ. However, using an agnostic and computationally inexpensive learning approach for high-frequency physiologic time series data, we demonstrated that our models achieve higher classification accuracy.