Predicting hypotension in perioperative and intensive care medicine

Blood pressure is the main determinant of organ perfusion. Hypotension is common in patients having surgery and in critically ill patients. The severity and duration of hypotension are associated with hypoperfusion and organ dysfunction. Hypotension is mostly treated reactively after low blood pressure values have already occurred. However, prediction of hypotension before it becomes clinically apparent would allow the clinician to treat hypotension pre-emptively, thereby reducing the severity and duration of hypotension. Hypotension cannowbepredictedminutes before it actually occurs from the blood pressure waveform using machine-learning algorithms that can be trained to detect subtle changes in cardiovascular dynamics preceding clinically apparent hypotension. However, analyzing the complex cardiovascular system is a challenge because cardiovascular physiology is highly interdependent, works within complicated networks, and is influenced by compensatory mechanisms. Improved hemodynamic data collection and integration will be a key to improve current models and develop new hypotension prediction models. (C) 2019 Elsevier Ltd. All rights reserved

Cardiac output estimation using pulse wave analysis-physiology, algorithms, and technologies:a narrative review

Pulse wave analysis (PWA) allows estimation of cardiac output (CO) based on continuous analysis of the arterial blood pressure (AP) waveform. We describe the physiology of the AP waveform, basic principles of PWA algorithms for CO estimation, and PWA technologies available for clinical practice. The AP waveform is a complex physiological signal that is determined by interplay of left ventricular stroke volume, systemic vascular resistance, and vascular compliance. Numerous PWA algorithms are available to estimate CO, including Windkessel models, long time interval or multi-beat analysis, pulse power analysis, or the pressure recording analytical method. Invasive, minimally-invasive, and noninvasive PWA monitoring systems can be classified according to the method they use to calibrate estimated CO values in externally calibrated systems, internally calibrated systems, and uncalibrated systems

Continuous noninvasive pulse wave analysis using finger cuff technologies for arterial blood pressure and cardiac output monitoring in perioperative and intensive care medicine:a systematic review and meta-analysis

Background: Finger cuff technologies allow continuous noninvasive arterial blood pressure (AP) and cardiac output/index (CO/CI) monitoring. Methods: We performed a meta-analysis of studies comparing finger cuff-derived AP and CO/CI measurements with invasive measurements in surgical or critically ill patients. We calculated overall random effects model-derived pooled estimates of the mean of the differences and of the percentage error (PE; CO/CI studies) with 95%-confidence intervals (95%-CI), pooled 95%-limits of agreement (95%-LOA), Cochran's Q and I2 (for heterogeneity). Results: The pooled mean of the differences (95%-CI) was 4.2 (2.8 to 5.62) mm Hg with pooled 95%-LOA of –14.0 to 22.5 mm Hg for mean AP (Q=230.4 [P<0.001], I2=91%). For mean AP, the mean of the differences between finger cuff technologies and the reference method was ≤5±8 mm Hg in 9/27 data sets (33%). The pooled mean of the differences (95%-CI) was –0.13 (–0.43 to 0.18) L min−1 with pooled 95%-LOA of –2.56 to 2.23 L min−1 for CO (Q=66.7 [P<0.001], I2=90%) and 0.07 (0.01 to 0.13) L min−1 m−2 with pooled 95%-LOA of –1.20 to 1.15 L min−1 m−2 for CI (Q=5.8 [P=0.326], I2=0%). The overall random effects model-derived pooled estimate of the PE (95%-CI) was 43 (37 to 49)% (Q=48.6 [P<0.001], I2=63%). In 4/19 data sets (21%) the PE was ≤30%, and in 10/19 data sets (53%) it was ≤45%. Conclusions: Study heterogeneity was high. Several studies showed interchangeability between AP and CO/CI measurements using finger cuff technologies and reference methods. However, the pooled results of this meta-analysis indicate that AP and CO/CI measurements using finger cuff technologies and reference methods are not interchangeable in surgical or critically ill patients. Clinical trial number: PROSPERO registration number: CRD42019119266

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p&lt;0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p&lt;0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Presentation and evaluation of the teaching concept "ENHANCE" for basic sciences in medical education.

A solid understanding of basic sciences is a prerequisite for successful completion of medical education. Therefore, it is essential to improve the quality of teaching and to ensure the applicability of basic sciences. Based on practical experiences and previous research, we developed an innovative step-by-step concept, called ENHANCE, for the implementation or revision of teaching units, especially for basic sciences. We used comparative self-assessment gains, a questionnaire to assess teaching quality as well as end-of-semester evaluations (students' satisfaction and open-ended questions) to evaluate the ENHANCE concept. It was found that ENHANCE-based teaching units were related to increased students' satisfaction, high attendance rates and that restructuring the course curriculum yielded in a positive assessment of teaching effectiveness. The revised courses were rated as the very best of all classes in several semesters. Qualitative data showed that students particularly appreciated the level of comprehension and how helpful the courses were for the understanding and preparation of the regular curriculum

Pulse Wave Analysis to Estimate Cardiac Output

Pulse wave analysis enables cardiac output to be estimated continuously and in real time. Pulse wave analysis methods can be classified into invasive, minimally invasive, and noninvasive and into externally calibrated, internally calibrated, and uncalibrated methods