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Abstract Occult hemorrhages after trauma can be present insidiously, and if not detected early enough can result in patient death. This study evaluated a hemorrhage model on 18 human subjects, comparing the performance of traditional vital signs to multiple off-the-shelf non-invasive biomarkers. A validated lower body negative pressure (LBNP) model was used to induce progression towards hypovolemic cardiovascular instability. Traditional vital signs included mean arterial pressure (MAP), electrocardiography (ECG), plethysmography (Pleth), and the test systems utilized electrical impedance via commercial electrical impedance tomography (EIT) and multifrequency electrical impedance spectroscopy (EIS) devices. Absolute and relative metrics were used to evaluate the performance in addition to machine learning-based modeling. Relative EIT-based metrics measured on the thorax outperformed vital sign metrics (MAP, ECG, and Pleth) achieving an area-under-the-curve (AUC) of 0.99 (CI 0.95–1.00, 100% sensitivity, 87.5% specificity) at the smallest LBNP change (0–15 mmHg). The best vital sign metric (MAP) at this LBNP change yielded an AUC of 0.6 (CI 0.38–0.79, 100% sensitivity, 25% specificity). Out-of-sample predictive performance from machine learning models were strong, especially when combining signals from multiple technologies simultaneously. EIT, alone or in machine learning-based combination, appears promising as a technology for early detection of progression toward hemodynamic instability.

Background: Brachial plexus catheter placement at the interscalene level is beneficial for shoulder analgesia but presents logistical challenges due to the superficial nature of the plexus at this level, increased patient movement in the neck, and therefore higher likelihood for catheter dislodgement. Methods: Patients requiring shoulder arthroscopy and suprascapular nerve decompression were identified. Under arthroscopic guidance, a catheter was placed percutaneously into the scalene medius muscle next to the suprascapular nerve and the upper trunk of the brachial plexus. Patients were followed postoperatively for perioperative analgesic outcomes. Results: Ten patients were identified and consented for intraoperative brachial plexus catheter placement. Patient demographics and surgical details were determined. Postoperative adjunctive pain management and pain scores were variable. Two patients required catheter replacement using ultrasound guidance in the perioperative anesthesia care unit due to poorly controlled pain. There were no incidents of catheter failure due to dislodgement. Discussion: This study presents the first description of arthroscopically-assisted brachial plexus catheter placement. This method may present an alternative to traditional ultrasound guided interscalene catheter placement. Further study is needed to determine if analgesic outcomes, block success, and dislodgement rates are improved with this method.

Telemedicine and remote monitoring are rapidly gaining momentum in health care, including in-home and postdischarge monitoring. However, remote monitoring for telemedicine teams and receiving medical centers is yet to reach emergency medical services. When transporting a critically ill patient, continuous vital sign monitoring may be helpful to enhance receiving center collaboration and change care delivery before arrival when necessary. Our primary objective was to demonstrate successful transmission and reception of real-time physiologic summary data to a hospital base station during ambulance transport using a low-energy Bluetooth wireless wearable device linked to iridium satellite communications. We completed our proof-of-concept study on 2 simulated ground ambulance transports and 1 helicopter flight in rural areas surrounding Rochester, Minnesota. Each simulated transport used Mayo Clinic–developed wearable devices paired one-to-one with a physiologic communication kit. Electrocardiographic and photoplethysmographic waveforms were processed on the wearables every 5 minutes, with vital sign data generated and transmitted to an iridium satellite and relayed to a base station network–protected computer and mobile application with real-time display of summary and location. Data and geolocation were tracked in real time with a mobile application during the simulated transport, and summary data packets were saved on Mayo Clinic servers. During the 3 simulated rural transports, all (n=7; 100%) wearables successfully captured, recorded, and transmitted raw waveform physiologic signals. All devices transmitted successfully via the iridium satellite to the base station network–protected computer and mobile application. In all, 106 (69%) of 154 transmissions were successfully processed. Our project demonstrated successful remote monitoring of physiologic vital signs during transport in rural, low–cellular signal areas. The use of live remote monitoring should be explored to understand its utility in practice and outcomes.

Objective: To identify change management (CM) strategies for implementing novel artificial intelligence and similar novel technologies in operating rooms and create a new CM model for future trials and applications inspired by the abovementioned strategies and established models. Methods: Key phases of technology implementation were defined, and strategies for transformational CM were created and applied in a recent CM experience at our institution between October 15, 2020 and October 15, 2021. We appraised existing CM models and propose the newly created model. Results: The key phases of the technology implementation were as follows: (1) team assembly; (2) committee approvals; (3) CM; and (4) system installation and go-live. Key strategies were (1) assemble team with necessary expertise; (2) anticipate potential institutional cultural and regulatory hurdles; (3) add agility to project planning and execution; (4) accommodate institutional culture and regulations; (5) early clinical partner buy-in and stakeholder engagement; and (6) consistent communication, all of which contributed to the new CM model creation. Conclusion: Key CM strategies and a new CM model addressing the unique needs and characteristics of operating room novel technology implementation were identified and created. The new model may be customized and tested for individual institution and project’s needs and characteristics.

Abstract Women with uterine fibroids (UF), benign tumors of the myometrium, have a higher prevalence of hypertension than women without UF. The cause for this relationship is unclear. Muscle sympathetic nerve activity (MSNA) is a regulator of arterial blood pressure, and it is possible that variations in MSNA predispose women with UF to develop hypertension. The purpose of this study was to assess baseline blood pressure and MSNA and the relationships between MSNA and systemic hemodynamics in women with and without UF. We measured blood pressure (brachial intra‐arterial line), MSNA (microneurography), and systemic hemodynamics (total peripheral resistance and cardiac output) at rest in 14 healthy, normotensive, premenopausal women with UF (42 ± 2 years old) and 9 healthy, normotensive, premenopausal women without UF (41 ± 2 years old). Baseline blood pressure and MSNA did not differ between groups (p > 0.05 for both). In women with UF, there was a positive correlation between MSNA and total peripheral resistance (r = 0.75, p = 0.02), as well as a negative correlation between MSNA and cardiac output (r = −0.73, p = 0.03). In contrast, these relationships were not seen in women without UF (p > 0.05 for both relationships). These data suggest that autonomic interactions with systemic hemodynamics, and thus blood pressure regulation, are different in healthy women with UF compared to healthy women without UF.

The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to compare for the first time the discriminative ability of two machine learning (ML) algorithms based on real-time feature analysis of arterial waveforms obtained from a non-invasive continuous blood pressure system (Finometer®) signal to predict the onset of decompensated shock: the compensatory reserve index (CRI) and the compensatory reserve metric (CRM). One hundred ninety-one healthy volunteers underwent progressive simulated hemorrhage using lower body negative pressure (LBNP). The least squares means and standard deviations for each measure were assessed by LBNP level and stratified by tolerance status (high vs. low tolerance to central hypovolemia). Generalized Linear Mixed Models were used to perform repeated measures logistic regression analysis by regressing the onset of decompensated shock on CRI and CRM. Sensitivity and specificity were assessed by calculation of receiver-operating characteristic (ROC) area under the curve (AUC) for CRI and CRM. Values for CRI and CRM were not distinguishable across levels of LBNP independent of LBNP tolerance classification, with CRM ROC AUC (0.9268) being statistically similar (p = 0.134) to CRI ROC AUC (0.9164). Both CRI and CRM ML algorithms displayed discriminative ability to predict decompensated shock to include individual subjects with varying levels of tolerance to central hypovolemia. Arterial waveform feature analysis provides a highly sensitive and specific monitoring approach for the detection of ongoing hemorrhage, particularly for those patients at greatest risk for early onset of decompensated shock and requirement for implementation of life-saving interventions.

Abstract Introduction It remains unclear if naturally occurring respiratory muscle (RM) work influences leg diffusive O2 transport during exercise in heart failure patients with reduced ejection fraction (HFrEF). In this retrospective study, we hypothesized that RM unloading during submaximal exercise will lead to increases in locomotor muscle O2 diffusion capacity (DMO2) contributing to the greater leg VO2. Methods Ten HFrEF patients and 10 healthy control matched participants performed two submaximal exercise bouts (i.e., with and without RM unloading). During exercise, leg blood flow was measured via constant infusion thermodilution. Intrathoracic pressure was measured via esophageal balloon. Radial arterial and femoral venous blood gases were measured and used to calculate leg arterial and venous content (CaO2 and CvO2, respectively), VO2, O2 delivery, and DMO2. Results From CTL to RM unloading, leg VO2, O2 delivery, and DMO2 were not different in healthy participants during submaximal exercise (all, p > .15). In HFrEF, leg VO2 (CTL: 0.7 ± 0.3 vs. RM unloading: 1.0 ± 0.4 L/min, p

Objective: To develop and validate a phenotyping algorithm for the identification of patients with type 1 and type 2 diabetes mellitus (DM) preoperatively using routinely available clinical data from electronic health records. Patients and Methods: We used first-order logic rules (if-then-else rules) to imply the presence or absence of DM types 1 and 2. The “if” clause of each rule is a conjunction of logical and, or predicates that provides evidence toward or against the presence of DM. The rule includes International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes, outpatient prescription information, laboratory values, and positive annotation of DM in patients’ clinical notes. This study was conducted from March 2, 2015, through February 10, 2016. The performance of our rule-based approach and similar approaches proposed by other institutions was evaluated with a reference standard created by an expert reviewer and implemented for routine clinical care at an academic medical center. Results: A total of 4208 surgical patients (mean age, 52 years; males, 48%) were analyzed to develop the phenotyping algorithm. Expert review identified 685 patients (16.28% of the full cohort) as having DM. Our proposed method identified 684 patients (16.25%) as having DM. The algorithm performed well—99.70% sensitivity, 99.97% specificity—and compared favorably with previous approaches. Conclusion: Among patients undergoing surgery, determination of DM can be made with high accuracy using simple, computationally efficient rules. Knowledge of patients’ DM status before surgery may alter physicians’ care plan and reduce postsurgical complications. Nevertheless, future efforts are necessary to determine the effect of first-order logic rules on clinical processes and patient outcomes.

Objectives: Postmenopausal (PM) women have a blunted β2-adrenergic receptor-mediated responsiveness when compared to young premenopausal women in part due to a reduction in the relative contribution of nitric oxide (NO) to β2-adrenergic mediated vasodilation. Hence, we tested the contribution of NO to β2-adrenergic receptor-mediated vasodilation during terbutaline infusion. Hypothesis: We hypothesized that the contribution of NO to β2-adrenergic mediated vasodilation would be attenuated in PM women as compared to young women. Methods: Venous occlusion plethysmography was used to measure forearm blood flow (FBF) in 7 healthy young premenopausal women and 9 healthy PM women (mean age = 27 ± 1 and 60 ± 1 years, respectively). FBF was measured at baseline and during terbutaline infusion at 0.1, 0.5, 1.0, 2.0 μg/100ml tissue/min before (with saline co-infusion) and during NO synthase inhibition with L-NMMA. Forearm vascular conductance was calculated from FBF and mean arterial pressure. Results: In young women, there was a significant L-NMMA effect on forearm vascular conductance during terbutaline infusion with and without L-NMMA (1.7 ± 0.14, 3.56 ± 0.41, 7.13 ± 1.11, 7.87 ± 0.74, 10.54 ± 1.81 versus 2.08 ± 0.28, 5.54 ± 0.50, 9.32 ± 1.10, 10.77 ± 1.49, 13.29 ± 1.94 ml/100ml tissue/min/mmHg, respectively). However, there was no effect of L-NMMA in PM women during terbutaline infusion with and without L-NMMA (1.34 ± 0.26, 2.37 ± 0.32, 5.21 ± 0.99, 4.71 ± 0.99, 6.43 ± 1.37 versus 1.62 ± 0.31, 3.11 ± 0.55, 5.41 ± 1.12, 6.26 ± 1.38, 7.26 ± 1.44 ml/100ml tissue/min/mmHg, respectively). Conclusions: These data suggest that NO contributes to β2-adrenergic mediated vasodilation in young premenopausal women. In contrast, no contribution of NO to β2 mediated vasodilation was observed in PM women. These data suggest a lower β2-adrenergic responsiveness in PM women may be due to a reduced contribution of NO.

Purpose: The purpose of this study was to determine the effectiveness of a simple algorithm to mathematically predict a patients’ response to blood pressure (BP) therapy using functional genes in the 3 major organ systems involved in hypertension. Methods: Eighty-six patients with controlled hypertension completed 1 study visit consisting of a buccal swab collection, measurement of office BP, and a medical chart review for BP history. Genes in the analysis included 14 functional alleles in 11 genes. These genotypes were mathematically summed per organ system to determine whether a patient would likely respond to target therapy. Results: Patients recommended to and taking a diuretic had significantly higher rates of control (

The magnitude of decrease in BP during a vasoactive drug bolus may be associated with the calculated baroreflex sensitivity (BRS). The purpose of the present study was to evaluate whether sympathetic and/or cardiac BRS relates to the extent of change in BP and whether this was altered by sex hormones. Fifty-one young women (27 ± 1 yrs), 14 older women (58 ± 1 yrs), and 36 young men (27 ± 1 yrs) were studied. Heart rate, BP, and MSNA were monitored. Sympathetic BRS was analyzed using the slope of the MSNA-diastolic BP (DBP) relationship and cardiac BRS was analyzed using the RRI-systolic BP (SBP) relationship. Young women and men had similar mean arterial pressures (MAP, 91±1 vs. 90±1 mmHg), cardiac BRS (19±1 vs. 21±2 ms/mmHg), and sympathetic BRS (-6±1 vs. -7±1 AU/beat/mmHg), respectively. Older women had higher MAP (104±4 mmHg, p