Heart Transplant Donor Selection Guidelines: Review and Recommendations.

PURPOSE OF REVIEW: The rate of heart transplants, while steadily increasing, is insufficient to meet the growing list of transplant candidates. Marginal donors expand the donor pool. However, criteria used to identify donors greatly vary by institution. RECENT FINDINGS: The International Society of Heart and Lung Transplant (ISHLT) heart transplant report of 2020 reinforced the importance of donor selection criteria on heart transplant outcomes. Existing literature challenges and reinforces the report's findings. Newer methods, such as donation after circulatory death (DCD), also recontextualize existing donor selection criteria. Transplant prediction models from international databases are poor predictors of individual centers' outcome. Further study is needed to understand associations among donor risk factors, and update the methods used for donor heart selection. In this review, we examine the current literature on extended donor criteria and recommend a model for donor selection.

Vasoplegia from Continuous Flow Left Ventricular Assist Devices.

PURPOSE OF REVIEW: The contribution of continuous flow left ventricular assist devices (c-LVAD) to vasoplegic syndrome and postoperative outcomes after orthotopic heart transplant (OHT) is contested in the literature. A standardized definition of vasoplegic syndrome (VS) is needed to better recognize and manage vasoplegic shock. RECENT FINDINGS: Vasoplegic syndrome occurs after orthotopic heart transplant more frequently than after other surgeries requiring cardiopulmonary bypass. c-LVADs lead to small vessel endothelial dysfunction and desensitized adrenal receptors; however, their contribution to the development of vasoplegia is debated in clinical studies. Pulsatility may mitigate vascular dysfunction resulting from long-term continuous flow, and should be further explored in the clinical setting when considering risk factors for vasoplegic syndrome. The incidence of vasoplegic syndrome after orthotopic heart transplant is rising with the increasing use of c-LVAD bridge to therapy. Robust clinical studies are needed to advance our understanding and approach to mitigating VS after OHT.

In vitro evaluation of Capiox FX05 and RX05 oxygenators in neonatal cardiopulmonary bypass circuits with varying venous reservoir and vacuum-assisted venous drainage levels.

The purpose of this study was to evaluate the hemodynamic properties and microemboli capture associated with different vacuum-assisted venous drainage (VAVD) vacuum levels and venous reservoir levels in a neonatal cardiopulmonary bypass circuit. Trials were conducted in 2 parallel circuits to compare the performance of Capiox Baby RX05 oxygenator with separate AF02 arterial filter to Capiox FX05 oxygenator with integrated arterial filter. Arterial cannula flow rate to the patient was held at 500 mL/min and temperature maintained at 32°C, while VAVD vacuum levels (0 mm Hg, -15 mm Hg, -30 mm Hg, -45 mm Hg, -60 mm Hg) and venous reservoir levels (50 mL, 200 mL) were evaluated in both oxygenators. Hemodynamic parameters measuring flow, pressure, and total hemodynamic energy were made in real time using a custom-made data acquisition system and Labview software. Nearly 10 cc bolus of air was injected into the venous line and gaseous microemboli detected using an Emboli Detection and Classification Quantifier. Diverted blood flow via the arterial filter's purge line and mean pressures increased with increasing VAVD levels (P < 0.01). Mean pressures were lower with lower venous reservoir levels and were greater in RX05 groups compared to FX05 (P < 0.01). Microemboli detected at the preoxygenator site increased with higher VAVD vacuum levels and lower venous reservoir levels (P < 0.01). The amount of microemboli captured by the FX05 oxygenator with integrated arterial filter was greater than by the RX05 oxygenator alone, although both oxygenators were able to clear microemboli before reaching the pseudo-patient.

Racial and gender disparities in the management of acute pulmonary embolism.

OBJECTIVE: The aim of this study was to assess race and sex disparities in use and outcomes of various interventions in patient with acute pulmonary embolism (PE). METHODS: We included 129,445 patients with acute PE from the NIS from January 2016 to December 2019. Rates of inferior vena cava (IVC) filter placement, catheter-directed thrombolysis (CDT), CDT with ultrasound, systemic thrombolysis, surgical embolectomy, percutaneous thrombectomy, extracorporeal membrane oxygenation, and mechanical ventilation were compared between race and sex subgroups, along with length of hospital stay, major bleeding events, mortality, and other adverse events. Multivariate linear regression analysis was used to adjust for variables that were significantly different between race and sex, including demographic factors, comorbidities, socioeconomic factors, and hospital characteristics. RESULTS: Compared with White male patients, all subgroups had significantly higher odds of in-hospital mortality highest in Hispanic male patients (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.090-1.640; P < .01). All subgroups also had a higher odds of major bleeding events and increased length of stay. All subgroups also had lower odds of receiving CDT, lowest in Black female patients (OR, 0.740; 95% CI, 0.660-0.820; P < .001) and Hispanic female patients (0.780; 95% CI, 0.650-0.940; P < .001) compared with White male patients. There was no significant difference in the use of systemic thrombolysis among subgroups. CONCLUSIONS: Black and Hispanic patients and female patients are less likely to undergo CDT compared with White male patients, in addition to having higher odds of mortality, major bleeding, and increased length of stay after management of PE. Further efforts are needed to mitigate disparate outcomes of PE management at not only an institutional, but at a national, level to promote health care equality.

5-year stroke rates in nonvalvular atrial fibrillation after watchman compared to direct oral anticoagulants.

BACKGROUND: The WATCHMAN device (Boston Scientific; Marlborough, MA, USA) is noninferior to warfarin in preventing ischemic strokes while reducing bleeding risks associated with long term anticoagulation in nonvalvular atrial fibrillation (AFib). The device's performance compared to direct oral anticoagulants (DOAC) is less well known. OBJECTIVE: To compare 5-year major bleeding and ischemic stroke rates in patients with nonvalvular AFib who received a WATCHMAN device or DOAC therapy after a major bleeding event. METHODS: This retrospective, multicenter, 1:1 matched cohort study was derived from the PearlDiver Mariner database from 2010 to 2020. Patients with nonvalvular AFib on oral anticoagulation who had a major bleeding event were identified. Those who received either WATCHMAN or DOAC after resolution of the bleeding event were selected. The two groups were exactly matched 1:1 based on various comorbidities. Rates of ischemic stroke, transient ischemic attack (TIA), major bleeding, and hemorrhagic stroke were compared over 5 years. RESULTS: Each cohort consisted of 2248 patients after 1:1 matching. The mean CHADS2-VASC score was 4.81 ±â€¯1.25. At 5 years, the WATCHMAN cohort had significantly lower rates of major bleeding events [OR 0.24 (0.21, 0.27)], TIAs [OR 0.75 (0.58, 0.95)], and ischemic strokes [OR 0.72 (0.61, 0.86)]. There was no significant difference in hemorrhagic strokes [OR 1.14 (0.83, 1.58)]. CONCLUSION: Even in a high-risk population, the WATCHMAN is comparable to DOAC therapy in the primary prevention of hemorrhagic strokes and may provide benefit in the rates of bleeding events, TIAs, and ischemic strokes.

Incidence and Predictors of Acute Limb Ischemia in Patients With Acute Myocardial Infarction-Insight from National Readmission Database.

Acute limb ischemia (ALI) has been a rare complication of acute myocardial infarction (AMI), however, with the increasing use of mechanical circulatory devices it is seen more frequently. The incidence and predictors of ALI in patients with AMI in contemporary clinical practice are unknown. A retrospective review of patients with index hospitalization for AMI in the Nationwide Readmission Database from 2016 to 2019 was done. We evaluated the annual incidence of ALI and its impact on outcomes. We used multivariate logistic regression analysis to determine predictors of ALI. In 1,283,586 patients with AMI, 3,971 patients (0.31%) had ALI and 365 (0.03%) had limb amputation. The 3 major predictors of ALI were peripheral artery disease (odds ratio [OR] 11.91, 95% confidence interval [CI]: 10.78 to 13.51), intravascular microaxial left ventricular assist device (OR 4.39, 95% CI 3.86 to 5.00), and veno-arterial extracorporeal membrane oxygenation (OR 4.37, 95% CI 3.19 to 6.01). Intra-aortic balloon pump had a substantially lower predictive ability (OR 1.81, 95% CI 1.63 to 2.0, p <0.0001) than other forms of mechanical circulatory support. The mortality rate in patients with ALI was significantly higher than those without ALI (19.49% vs 4.85%, p <0.0001). Patients who developed ALI had higher rates of amputation (1.59% vs 0.02%, p <0.0001). This observational nationwide study showed that ALI is an important complication in patients with AMI and is more frequently seen in patients who have peripheral artery disease, and require a left ventricular assist device or venoarterial extracorporeal membrane oxygenation. This complication was also associated with significantly higher in-hospital mortality.

Predictors of Diffusing Capacity in Children With Sickle Cell Disease: A Longitudinal Study.

Background: Gas exchange abnormalities in Sickle Cell Disease (SCD) may represent cardiopulmonary deterioration. Identifying predictors of these abnormalities in children with SCD (C-SCD) may help us understand disease progression and develop informed management decisions. Objectives: To identify pulmonary function tests (PFT) estimates and biomarkers of disease severity that are associated with and predict abnormal diffusing capacity (DLCO) in C-SCD. Methods: We obtained PFT data from 51 C-SCD (median age:12.4 years, male: female = 29:22) (115 observations) and 22 controls (median age:11.1 years, male: female = 8:14), formulated a rank list of DLCO predictors based on machine learning algorithms (XGBoost) or linear mixed-effect models, and compared estimated DLCO to the measured values. Finally, we evaluated the association between measured or estimated DLCO and clinical outcomes, including SCD crises, pulmonary hypertension, and nocturnal desaturation. Results: Hemoglobin-adjusted DLCO (%) and several PFT indices were diminished in C-SCD compared to controls. Both statistical approaches ranked FVC (%), neutrophils (%), and FEF25-75 (%) as the top three predictors of DLCO. XGBoost had superior performance compared to the linear model. Both measured and estimated DLCO demonstrated a significant association with SCD severity: higher DLCO, estimated by XGBoost, was associated with fewer SCD crises [beta = -0.084 (95%CI: -0.13, -0.033)] and lower TRJV [beta = -0.009 (-0.017, -0.001)], but not with nocturnal desaturation (p = 0.12). Conclusions: In this cohort of C-CSD, DLCO was associated with PFT estimates representing restrictive lung disease (FVC, TLC), airflow obstruction (FEF25-75, FEV1/FVC, R5), and inflammation (neutrophilia). We used these indices to estimate DLCO, and show association with disease outcomes, underscoring the prediction models' clinical relevance.

Knowledge, Perceptions, and Preferred Information Sources Related to COVID-19 Among Healthcare Workers: Results of a Cross Sectional Survey.

PURPOSE: To compare COVID-19 related knowledge, perceptions, and preferred information sources between healthcare workers and non-healthcare workers. DESIGN: Cross-sectional survey. SETTING: Web-based. SUBJECTS: Convenience sample of Pennsylvanian adults. MEASURES: Primary outcomes were binary responses to 15 COVID-19 knowledge questions weighted by a Likert scale assessing response confidence. ANALYSIS: Generalized linear mixed-effects models to assess comparisons between clinical decision makers (CDM), non-clinical decision makers working in healthcare (non-CDM) and non-healthcare workers (non-HCW). RESULTS: CDMs (n = 91) had higher overall knowledge than non-CDMs (n = 854; OR 1.81 [1.51, 2.17], p < .05). Overall knowledge scores were not significantly different between non-CDMs (n = 854) and non-HCW (n = 4,966; OR 1.03 [0.97, 1.09], p > .05). CONCLUSION: The findings suggest a need for improved education about COVID-19 for healthcare workers who are not clinical decision makers, as they play key roles in patient perceptions and compliance with preventive medicine during primary care visits.

Contact lens-based lysozyme detection in tear using a mobile sensor.

We report a method for sensing analytes in tear-fluid using commercial contact lenses (CLs) as sample collectors for subsequent analysis with a cost-effective and field-portable reader. In this study we quantify lysozyme, the most prevalent protein in tear fluid, non-specifically bound to CLs worn by human participants. Our mobile reader uses time-lapse imaging to capture an increasing fluorescent signal in a standard well-plate, the rate-of-change of which is used to indirectly infer lysozyme concentration through the use of a standard curve. We empirically determined the best-suited CL material for our sampling procedure and assay, and subsequently monitored the lysozyme levels of nine healthy human participants over a two-week period. Of these participants who were regular CL wearers (6 out of 9), we observed an increase in lysozyme levels from 6.89 ± 2.02 µg mL-1 to 10.72 ± 3.22 µg mL-1 (mean ± SD) when inducing an instance of digital eye-strain by asking them to play a game on their mobile-phones during the CL wear-duration. We also observed a lower mean lysozyme concentration (2.43 ± 1.66 µg mL-1) in a patient cohort with dry eye disease (DED) as compared to the average monitoring level of healthy (no DED) human participants (6.89 ± 2.02 µg mL-1). Taken together, this study demonstrates tear-fluid analysis with simple and non-invasive sampling steps along with a rapid, easy-to-use, and cost-effective measurement system, ultimately indicating physiological differences in human participants. We believe this method could be used in future tear-fluid studies, even supporting multiplexed detection of a panel of tear biomarkers toward improved diagnostics and prognostics as well as personalized mobile-health applications.

Computational Sensing Using Low-Cost and Mobile Plasmonic Readers Designed by Machine Learning.

Plasmonic sensors have been used for a wide range of biological and chemical sensing applications. Emerging nanofabrication techniques have enabled these sensors to be cost-effectively mass manufactured onto various types of substrates. To accompany these advances, major improvements in sensor read-out devices must also be achieved to fully realize the broad impact of plasmonic nanosensors. Here, we propose a machine learning framework which can be used to design low-cost and mobile multispectral plasmonic readers that do not use traditionally employed bulky and expensive stabilized light sources or high-resolution spectrometers. By training a feature selection model over a large set of fabricated plasmonic nanosensors, we select the optimal set of illumination light-emitting diodes needed to create a minimum-error refractive index prediction model, which statistically takes into account the varied spectral responses and fabrication-induced variability of a given sensor design. This computational sensing approach was experimentally validated using a modular mobile plasmonic reader. We tested different plasmonic sensors with hexagonal and square periodicity nanohole arrays and revealed that the optimal illumination bands differ from those that are "intuitively" selected based on the spectral features of the sensor, e.g., transmission peaks or valleys. This framework provides a universal tool for the plasmonics community to design low-cost and mobile multispectral readers, helping the translation of nanosensing technologies to various emerging applications such as wearable sensing, personalized medicine, and point-of-care diagnostics. Beyond plasmonics, other types of sensors that operate based on spectral changes can broadly benefit from this approach, including e.g., aptamer-enabled nanoparticle assays and graphene-based sensors, among others.