Journal of clinical monitoring and computing
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J Clin Monit Comput · Aug 2024
Clinical TrialKnowledge-based, computerized, patient clinical decision support system for perioperative pain, nausea and constipation management: a clinical feasibility study.
Opioid administration is particularly challenging in the perioperative period. Computerized-based Clinical Decision Support Systems (CDSS) are a promising innovation that might improve perioperative pain control. We report the development and feasibility validation of a knowledge-based CDSS aiming at optimizing the management of perioperative pain, postoperative nausea and vomiting (PONV), and laxative medications. ⋯ The agreement level had a probability of 86.6% to exceed the 90% clinically relevant agreement threshold. The knowledge-based, patient CDSS we developed was feasible at providing recommendations for the treatment of pain, PONV and constipation in a perioperative clinical setting. Trial registration number & date The study protocol was registered in ClinicalTrial.gov before enrollment began (NCT05707247 on January 26th, 2023).
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J Clin Monit Comput · Aug 2024
EditorialTowards the automatic detection and correction of abnormal arterial pressure waveforms.
Both over and underdamping of the arterial pressure waveform are frequent during continuous invasive radial pressure monitoring. They may influence systolic blood pressure measurements and the accuracy of cardiac output monitoring with pulse wave analysis techniques. ⋯ In case of overdamping, air bubbles, kinking, and partial obstruction of the arterial catheter should be suspected and eliminated. In the case of underdamping, resonance filters may be necessary to normalize the arterial pressure waveform and ensure accurate hemodynamic measurements.
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J Clin Monit Comput · Aug 2024
Cerebral regional oxygen saturation as a predictive parameter for preoperative heart failure and delayed hemodynamic recovery in transcutaneous aortic valve implantation: a retrospective cohort study.
This study aimed to investigate the relationship of perioperative cerebral regional oxygen saturation (rSO2) with various preoperative clinical variables and hemodynamic changes during transfemoral transcatheter aortic valve implantation (TAVI) under general anesthesia. We retrospectively analyzed cerebral rSO2 values from left-hemisphere measurements obtained using near-infrared spectroscopy (O3™ regional oximetry) at five time points: pre-induction, the start of the procedure, the start of valve deployment, time of lowest cerebral rSO2 value during valve deployment, and the end of the procedure. ⋯ The patients who took longer to recover their systolic blood pressure to 90 mmHg after valve deployment with a balloon-expandable valve (group B) had lower cerebral rSO2 values during deployment compared to patients with faster recovery with balloon-expandable valve (group A) and with self-expandable valve (group C). Baseline cerebral rSO2 is associated with preoperative variables related to cardiac failure and function, and a significant decline during valve deployment may indicate a risk of prolonged hypotension during TAVI.
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J Clin Monit Comput · Aug 2024
Electronic health record data is unable to effectively characterize measurement error from pulse oximetry: a simulation study.
Large data sets from electronic health records (EHR) have been used in journal articles to demonstrate race-based imprecision in pulse oximetry (SpO2) measurements. These articles do not appear to recognize the impact of the variability of the SpO2 values with respect to time ("deviation time"). This manuscript seeks to demonstrate that due to this variability, EHR data should not be used to quantify SpO2 error. Using the MIMIC-IV Waveform dataset, SpO2 values are sampled from 198 patients admitted to an intensive care unit and used as reference samples. ⋯ Each analysis was repeated to evaluate whether the measurement errors were affected by increasing the deviation time. All error values increased linearly with respect to the logarithm of the time deviation. At 10 min, the ARMS error increased from a baseline of 2% to over 4%. EHR data cannot be reliably used to quantify SpO2 error. Caution should be used in interpreting prior manuscripts that rely on EHR data.