Journal of clinical monitoring and computing
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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
The predictive role of carotid artery flow time for anesthesia-induced hypotension in high-risk elderly patients.
Hypotension induced by general anesthesia is associated with postoperative complications, increased mortality, and morbidity, particularly elderly patients. The aim of this study was to investigate the effectiveness of corrected carotid artery flow time (FTc) for predicting hypotension following anesthesia induction in patients over 65 years old. After faculty ethical committee approval and written informed consent, 138 patients (65 years and older, ASA physical status I-III) who scheduled for elective surgery were included in this study. In the pre-operative anesthesia unit, the carotid artery FTc value was measured by ultrasound and hemodynamic values were recorded. ⋯ The preoperative FTc value of the patients who developed hypotension was statistically lower (312.5 ms) than the patients who did not (345.0 ms) (p < 0.001). The area under the ROC curve for carotid artery FTc was 0.93 (95% CI for AUC:0.89-0.97; p < 0.001) with an optimal cut-off of value for predicting post-anesthesia hypotension 333 ms, a sensitivity of 90.4% and a specificity of 84.9%. As a result of the multiple logistic regression model, carotid artery FTc emerged as the sole independent risk factor for hypotension following anesthesia induction. Preoperative carotid artery FTc measurement is a simple, bedside, noninvasive, and reliable method for predicting anesthesia-induced hypotension in elderly patients.
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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.
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J Clin Monit Comput · Aug 2024
LetterAlgor-ethics: charting the ethical path for AI in critical care.
The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particularly in critical care, where physicians often deal with life-threating conditions requiring rapid actions and patients unable to participate in the decisional process. Moreover, development of AI-based CDSS is complex and should address different sources of bias, including data acquisition, health disparities, domain shifts during clinical use, and cognitive biases in decision-making. In this scenario algor-ethics is mandatory and emphasizes the integration of 'Human-in-the-Loop' and 'Algorithmic Stewardship' principles, and the benefits of advanced data engineering. The establishment of Clinical AI Departments (CAID) is necessary to lead AI innovation in healthcare, ensuring ethical integrity and human-centered development in this rapidly evolving field.