Journal of clinical monitoring and computing
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J Clin Monit Comput · Apr 2024
ReviewIs EIT-guided positive end-expiratory pressure titration for optimizing PEEP in ARDS the white elephant in the room? A systematic review with meta-analysis and trial sequential analysis.
Electrical Impedance Tomography (EIT) is a novel real-time lung imaging technology for personalized ventilation adjustments, indicating promising results in animals and humans. The present study aimed to assess its clinical utility for improved ventilation and oxygenation compared to traditional protocols. Comprehensive electronic database screening was done until 30th November, 2023. ⋯ Our search retrieved five controlled cohort studies and two RCTs with 515 patients and overall reduced risk of mortality [RR = 0.68; 95% CI: 0.49 to 0.95; I2 = 0%], better dynamic compliance [MD = 3.46; 95% CI: 1.59 to 5.34; I2 = 0%] with no significant difference in PaO2/FiO2 ratio [MD = 6.5; 95%CI -13.86 to 26.76; I2 = 74%]. The required information size except PaO2/FiO2 was achieved for a power of 95% based on the 50% reduction in risk of mortality, 10% improved compliance as the cumulative Z-score of the said outcomes crossed the alpha spending boundary and did not dip below the inner wedge of futility. EIT-guided individualized PEEP titration is a novel modality; further well-designed studies are needed to substantiate its utility.
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J Clin Monit Comput · Apr 2024
Effect of vertical stopcock position on start-up fluid delivery in syringe pumps used for microinfusions.
The purpose of this in vitro study was to evaluate the impact of the vertical level of the stopcock connecting the infusion line to the central venous catheter on start-up fluid delivery in microinfusions. Start-up fluid delivery was measured under standardized conditions with the syringe outlet and liquid flow sensors positioned at heart level (0 cm) and exposed to a simulated CVP of 10 mmHg at a set flow rate of 1 ml/h. Flow and intraluminal pressures were measured with the infusion line connected to the stopcock primarily placed at vertical levels of 0 cm, + 30 cm and - 30 cm or primarily placed at 0 cm and secondarily, after connecting the infusion line, displaced to + 30 cm and - 30 cm. Start-up fluid delivery 10 s after opening the stopcock placed at zero level and after opening the stopcock primarily connected at zero level and secondary displaced to vertical levels of + 30 cm and - 30 cm were similar (- 10.52 [- 13.85 to - 7.19] µL; - 8.84 [- 12.34 to - 5.33] µL and - 11.19 [- 13.71 to - 8.67] µL (p = 0.469)). ⋯ Start-up fluid delivery with the stopcock primarily placed at + 30 cm and - 30 cm resulted in large anterograde and retrograde fluid volumes of 34.39 [33.43 to 35.34] µL and - 24.90 [- 27.79 to - 22.01] µL at 10 s, respectively (p < 0.0001). Fluid delivered with the stopcock primarily placed at + 30 cm and - 30 cm resulted in 140% and 35% of calculated volume at 360 s, respectively (p < 0.0001). Syringe infusion pumps should ideally be connected to the stopcock positioned at heart level in order to minimize the amounts of anterograde and retrograde fluid volumes after opening of the stopcock.
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J Clin Monit Comput · Apr 2024
A machine learning algorithm for detecting abnormal patterns in continuous capnography and pulse oximetry monitoring.
Continuous capnography monitors patient ventilation but can be susceptible to artifact, resulting in alarm fatigue. Development of smart algorithms may facilitate accurate detection of abnormal ventilation, allowing intervention before patient deterioration. The objective of this analysis was to use machine learning (ML) to classify combined waveforms of continuous capnography and pulse oximetry as normal or abnormal. ⋯ This study presents a promising advancement in respiratory monitoring, focusing on reducing false alarms and enhancing accuracy of alarm systems. Our algorithm reliably distinguishes normal from abnormal waveforms. More research is needed to define patterns to distinguish abnormal ventilation from artifacts.
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J Clin Monit Comput · Apr 2024
Knowledge-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 · Apr 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.