Experiments and modeling to develop a Pistia stratiotes based Floating Vegetated System (FVS) for the removal of heavy metals (Pb, Zn, Cr, Cu, Ni).

Floating Vegetated System (FVS) emerged as a green and sustainable technology, presenting a viable solution for treating heavy metals (HMs) contaminated water without disrupting the food web. Pistia stratiotes has been used in the design of FVS due to its abundance of aerenchyma tissues, which contribute to its ability to remain buoyant. FVS exhibited significant HMs removal efficiencies, with Pb top at average 84.4 %, followed by Zn (81.1 %), Cr (78.5 %), Cu (76.5 %) and Ni (73 %). Bio-concentration Factor (BCF) and Translocation Factor (TF) values evaluated the plant's adeptness in metal uptake. For plants treated with Cu, the highest post-treatment chlorophyll content of 9 ± 1 mg.ml-1 was observed while Zn induced plant shows the lowest content of 7.1 ± 0.4 mg.ml-1. Using Box-Behnken Design (BBD), the system achieved 81.48 % Pb removal under optimized conditions such as initial Pb conc. of 9.25 mg. l-1, HRT of 24.49 days and a water depth of 26.52 cm. ANOVA analysis highlighted the significant impact of all the factors such as initial HM conc., HRT and wastewater depth on FVS performance. Kinetic analysis estimated a closer observance to the zero-order model, supported by high determination coefficient (R2) values. In conclusion, the FVS, as one of the most eco-friendly technologies, demonstrates higher potential for treating polluted water bodies, offering a sustainable remedy to global metal pollution challenges. Research on FVS for HMs removal is an area of ongoing interest and there are several potential future studies that could be pursued to further understand and optimize their effectiveness such as optimization of plant species, enhancement of plant-metal interactions, effects of environmental factors, economic feasibility studies, disposal of heavy metals accumulated plant, scale-up and application in real-world settings, etc.

Recommendations for Performance Evaluation of Machine Learning in Pathology: A Concept Paper From the College of American Pathologists.

CONTEXT.­: Machine learning applications in the pathology clinical domain are emerging rapidly. As decision support systems continue to mature, laboratories will increasingly need guidance to evaluate their performance in clinical practice. Currently there are no formal guidelines to assist pathology laboratories in verification and/or validation of such systems. These recommendations are being proposed for the evaluation of machine learning systems in the clinical practice of pathology. OBJECTIVE.­: To propose recommendations for performance evaluation of in vitro diagnostic tests on patient samples that incorporate machine learning as part of the preanalytical, analytical, or postanalytical phases of the laboratory workflow. Topics described include considerations for machine learning model evaluation including risk assessment, predeployment requirements, data sourcing and curation, verification and validation, change control management, human-computer interaction, practitioner training, and competency evaluation. DATA SOURCES.­: An expert panel performed a review of the literature, Clinical and Laboratory Standards Institute guidance, and laboratory and government regulatory frameworks. CONCLUSIONS.­: Review of the literature and existing documents enabled the development of proposed recommendations. This white paper pertains to performance evaluation of machine learning systems intended to be implemented for clinical patient testing. Further studies with real-world clinical data are encouraged to support these proposed recommendations. Performance evaluation of machine learning models is critical to verification and/or validation of in vitro diagnostic tests using machine learning intended for clinical practice.

Drivers of telemedicine in primary care clinics at a large academic medical centre.

BACKGROUND: COVID-19 disrupted healthcare routines and prompted rapid telemedicine implementation. We investigated the drivers of visit modality selection (telemedicine versus in-person) in primary care clinics at an academic medical centre. METHODS: We used electronic medical record data from March 2020 to May 2022 from 13 primary care clinics (N = 21,031 new, N = 207,292 return visits), with 55% overall telemedicine use. Hierarchical logistic regression and cross-validation methods were used to estimate the variation in visit modality explained by the patient, clinician and visit factors as measured by the mean-test area under the curve (AUC). RESULTS: There was significant variation in telemedicine use across clinicians (ranging from 0-100%) for the same visit diagnosis. The strongest predictors of telemedicine were the clinician seen for new visits (mean AUC of 0.79) and the primary visit diagnosis for return visits (0.77). Models based on all patient characteristics combined accounted for relatively little variation in modality selection, 0.54 for new and 0.58 for return visits, respectively. Amongst patient characteristics, males, patients over 65 years, Asians and patient's with non-English language preferences used less telemedicine; however, those using interpreter services used significantly more telemedicine. CONCLUSION: Clinician seen and primary visit diagnoses were the best predictors of visit modality. The distinction between new and return visits and the minimal impact of patient characteristics on visit modality highlights the complexity of clinical care and warrants research approaches that go beyond linear models to uncover the emergent causal effects of specific technology features mediated by tasks, people and organisations.

Real-world utilization of guideline-directed genetic testing in inherited cardiovascular diseases.

Background: Cardiovascular disease continues to be the leading cause of death globally. Clinical practice guidelines aimed at improving disease management and positively impacting major cardiac adverse events recommend genetic testing for inherited cardiovascular conditions such as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), long QT syndrome (LQTS), hereditary amyloidosis, and familial hypercholesterolemia (FH); however, little is known about how consistently practitioners order genetic testing for these conditions in routine clinical practice. This study aimed to assess the adoption of guideline-directed genetic testing for patients diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH. Methods: This retrospective cohort study captured real-world evidence of genetic testing from ICD-9-CM and ICD-10-CM codes, procedure codes, and structured text fields of de-identified patient records in the Veradigm Health Insights Ambulatory EHR Research Database linked with insurance claims data. Data analysis was conducted using an automated electronic health record analysis engine. Patient records in the Veradigm database were sourced from more than 250,000 clinicians serving over 170 million patients in outpatient primary care and specialty practice settings in the United States and linked insurance claims data from public and private insurance providers. The primary outcome measure was evidence of genetic testing within six months of condition diagnosis. Results: Between January 1, 2017, and December 31, 2021, 224,641 patients were newly diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH and included in this study. Substantial genetic testing care gaps were identified. Only a small percentage of patients newly diagnosed with DCM (827/101,919; 0.8%), HCM (253/15,507; 1.6%), LQTS (650/56,539; 1.2%), hereditary amyloidosis (62/1,026; 6.0%), or FH (718/49,650; 1.5%) received genetic testing. Conclusions: Genetic testing is underutilized across multiple inherited cardiovascular conditions. This real-world data analysis provides insights into the delivery of genomic healthcare in the United States and suggests genetic testing guidelines are rarely followed in practice.

Clinical programs for cardiometabolic health for South Asian patients in the United States: A review of key program components.

Medical literature shows that South Asians have approximately a 2-fold higher risk of atherosclerotic cardiovascular disease (CVD) compared with other populations. Given this high prevalence, clinical programs to promote cardiovascular health have emerged in the United States that are dedicated to clinical care for South Asian individuals. In this review, we have summarized the key characteristics of clinical programs in the U.S. dedicated to preventing and managing CVD in South Asian American patients. These clinical centers have many unique components in common that are catered to South Asian patient populations including ethnicity concordance of clinical providers, intensive cardiovascular screening protocols with laboratory studies and potentially genetic testing, dieticians and nutritionists who are familiar with South Asian-style dietary patterns, health coaches to support behavior change, community outreach programs, and involvement in clinical research to learn further about risk factors, prevention, and treatment of cardiovascular disease in South Asian populations. There are still many evidence and programmatic gaps left to uncover in the prevention, diagnosis, and management of CVD in South Asian. This review provides guidance for important features, barriers, and facilitators for future cardiovascular centers to develop in the United States where they can serve South Asian populations.

Sociodemographic disparities in the use of cardiovascular ambulatory care and telemedicine during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic accelerated adoption of telemedicine in cardiology clinics. Early in the pandemic, there were sociodemographic disparities in telemedicine use. It is unknown if these disparities persisted and whether they were associated with changes in the population of patients accessing care. METHODS: We examined all adult cardiology visits at an academic and an affiliated community practice in Northern California from March 2019 to February 2020 (pre-COVID) and March 2020 to February 2021 (COVID). We compared patient sociodemographic characteristics between these periods. We used logistic regression to assess the association of patient/visit characteristics with visit modality (in-person vs telemedicine and video- vs phone-based telemedicine) during the COVID period. RESULTS: There were 54,948 pre-COVID and 58,940 COVID visits. Telemedicine use increased from <1% to 70.7% of visits (49.7% video, 21.0% phone) during the COVID period. Patient sociodemographic characteristics were similar during both periods. In adjusted analyses, visits for patients from some sociodemographic groups were less likely to be delivered by telemedicine, and when delivered by telemedicine, were less likely to be delivered by video versus phone. The observed disparities in the use of video-based telemedicine were greatest for patients aged ≥80 years (vs age <60, OR 0.24, 95% CI 0.21, 0.28), Black patients (vs non-Hispanic White, OR 0.64, 95% CI 0.56, 0.74), patients with limited English proficiency (vs English proficient, OR 0.52, 95% CI 0.46-0.59), and those on Medicaid (vs privately insured, OR 0.47, 95% CI 0.41-0.54). CONCLUSIONS: During the first year of the pandemic, the sociodemographic characteristics of patients receiving cardiovascular care remained stable, but the modality of care diverged across groups. There were differences in the use of telemedicine vs in-person care and most notably in the use of video- vs phone-based telemedicine. Future studies should examine barriers and outcomes in digital healthcare access across diverse patient groups.

Sociodemographic determinants of oral anticoagulant prescription in patients with atrial fibrillations: findings from the PINNACLE registry using machine learning.

Background: Current risk scores that are solely based on clinical factors have shown modest predictive ability for understanding of factors associated with gaps in real-world prescription of oral anticoagulation (OAC) in patients with atrial fibrillation (AF). Objective: In this study, we sought to identify the role of social and geographic determinants, beyond clinical factors associated with variation in OAC prescriptions using a large national registry of ambulatory patients with AF. Methods: Between January 2017 and June 2018, we identified patients with AF from the American College of Cardiology PINNACLE (Practice Innovation and Clinical Excellence) Registry. We examined associations between patient and site-of-care factors and prescription of OAC across U.S. counties. Several machine learning (ML) methods were used to identify factors associated with OAC prescription. Results: Among 864,339 patients with AF, 586,560 (68%) were prescribed OAC. County OAC prescription rates ranged from 26.8% to 93%, with higher OAC use in the Western United States. Supervised ML analysis in predicting likelihood of OAC prescriptions and identified a rank order of patient features associated with OAC prescription. In the ML models, in addition to clinical factors, medication use (aspirin, antihypertensives, antiarrhythmic agents, lipid modifying agents), and age, household income, clinic size, and U.S. region were among the most important predictors of an OAC prescription. Conclusion: In a contemporary, national cohort of patients with AF underuse of OAC remains high, with notable geographic variation. Our results demonstrated the role of several important demographic and socioeconomic factors in underutilization of OAC in patients with AF.

Pathologist-performed ultrasound-guided fine needle aspiration biopsies of extrathyroidal sites: An observational study.

BACKGROUND: Pathologist-performed ultrasound-guided fine needle aspiration (USFNA) biopsies have become an increasingly important component of the interventional cytopathologist's toolbox. However, its application varies between institutions, and there is limited literature describing its performance characteristics when utilized in extrathyroidal sites. Here we review our institutional experience within our pathologist-run FNA clinic. METHODS: A retrospective review was conducted of pathologist-performed USFNAs of extrathyroidal sites over a 9-year period. Data collected included lesion site, size, patient age, patient gender, diagnostic category, and corresponding results from surgical resection when available. The diagnosis on surgical resection was considered the gold standard for determining discordance rates. RESULTS: A total of 143 pathologist-performed USFNAs of extrathyroidal lesions were performed from October 2011 to October 2020. These encompassed a wide range of sites, with most biopsies from the head and neck. The mean recorded size was 2.2 cm, with a range of 0.6-6 cm. Larger lesions (over 2 cm) were more likely to be noted in challenging locations, demonstrate difficult features, or be cystic. Most (n = 133) biopsies were sufficient for diagnosis, with a non-diagnostic rate of 7% (n = 10). Accuracy when compared to subsequent surgical resection was high, with sensitivity of 89%, specificity of 93%, positive predictive value of 94%, and negative predictive value of 87%. CONCLUSION: Our experience supports that pathologist-performed USFNA of extrathyroidal lesions-even those with challenging features-can result in excellent diagnostic yield and accuracy. The addition of USFNA to the interventional cytopathologists' repertoire can be a valuable tool to enhance patient care.

Drivers of variation in telemedicine use during the COVID-19 pandemic: The experience of a large academic cardiovascular practice.

BACKGROUND: COVID-19 spurred rapid adoption and expansion of telemedicine. We investigated the factors driving visit modality (telemedicine vs. in-person) for outpatient visits at a large cardiovascular center. METHODS: We used electronic health record data from March 2020 to February 2021 from four cardiology subspecialties (general cardiology, electrophysiology, heart failure, and interventional cardiology) at a large academic health system in Northern California. There were 21,912 new and return visits with 69% delivered by telemedicine. We used hierarchical logistic regression and cross-validation methods to estimate the variation in visit modality explained by patient, clinician, and visit factors as measured by the mean area under the curve. RESULTS: Across all subspecialties, the clinician seen was the strongest predictor of telemedicine usage, while primary visit diagnosis was the next most predictive. In general cardiology, the model based on clinician seen had a mean area under the curve of 0.83, the model based on the primary diagnosis had a mean area under the curve of 0.69, and the model based on all patient characteristics combined had a mean area under the curve of 0.56. There was significant variation in telemedicine use across clinicians within each subspecialty, even for visits with the same primary visit diagnosis. CONCLUSION: Individual clinician practice patterns had the largest influence on visit modality across subspecialties in a large cardiovascular medicine practice, while primary diagnosis was less predictive, and patient characteristics even less so. Cardiovascular clinics should reduce variability in visit modality selection through standardized processes that integrate clinical factors and patient preference.

Pandemic-proof recruitment and engagement in a fully decentralized trial in atrial fibrillation patients (DeTAP).

The Coronavirus Disease 2019 (COVID-19) pandemic curtailed clinical trial activity. Decentralized clinical trials (DCTs) can expand trial access and reduce exposure risk but their feasibility remains uncertain. We evaluated DCT feasibility for atrial fibrillation (AF) patients on oral anticoagulation (OAC). DeTAP (Decentralized Trial in Afib Patients, NCT04471623) was a 6-month, single-arm, 100% virtual study of 100 AF patients on OAC aged >55 years, recruited traditionally and through social media. Participants enrolled and participated virtually using a mobile application and remote blood pressure (BP) and six-lead electrocardiogram (ECG) sensors. Four engagement-based primary endpoints included changes in pre- versus end-of-study OAC adherence (OACA), and % completion of televisits, surveys, and ECG and BP measurements. Secondary endpoints included survey-based nuisance bleeding and patient feedback. 100 subjects (mean age 70 years, 44% women, 90% White) were recruited in 28 days (traditional: 6 pts; social media: 94 pts in 12 days with >300 waitlisted). Study engagement was high: 91% televisits, 85% surveys, and 99% ECG and 99% BP measurement completion. OACA was unchanged at 6 months (baseline: 97 ± 9%, 6 months: 96 ± 15%, p = 0.39). In patients with low baseline OACA (<90%), there was significant 6-month improvement (85 ± 16% to 96 ± 6%, p < 0.01). 86% of respondents (69/80) expressed willingness to continue in a longer trial. The DeTAP study demonstrated rapid recruitment, high engagement, and physiologic reporting via the integration of digital technologies and dedicated study coordination. These findings may inform DCT designs for future cardiovascular trials.

Pathologist-performed ultrasound-guided fine-needle aspirations of the thyroid: A single institution observational study.

BACKGROUND: Ultrasound-guided fine-needle aspiration biopsies (USFNAs) are increasingly performed by pathologists. This study was designed to assess the diagnostic yield and characterization of thyroid nodules biopsied at a teaching hospital setting in which both attending physicians and trainees are involved in the performance of USFNAs. METHODS: A retrospective study of pathologist-performed USFNAs of thyroid cases was performed over a period of 9 years at a tertiary medical center. Data collected included patient characteristics and The Bethesda System diagnostic categories. RESULTS: Over the study period, 1531 USFNAs of thyroid nodules were performed in the pathology-based clinic, with 1209 lesions in females and 322 in males. Ninety-three percent of samples were sufficient for diagnosis (n = 1420). The majority of nodules biopsied were benign (65.4%, n = 1002). Overall, 3.1% of nodules biopsied were diagnostic of malignancy (n = 47). The number of USFNAs over the years showed a rapid increase initially, with a coronavirus disease 2019-related decrease in 2020. CONCLUSIONS: The authors report their experience with thyroid USFNA over nearly a decade. The most common diagnosis was benign and the second most common was Bethesda category III. Lesions that were diagnostic of malignancy were relatively uncommon. Over the study period, the results showed that at a large tertiary care center in which USFNAs were performed by trainees as well as attending physicians, the diagnostic yield was good with a majority of thyroid nodules biopsied associated with a definitive diagnosis.

Changes in telemedicine use and ambulatory visit volumes at a multispecialty cardiovascular center during the COVID-19 pandemic.

Early in the COVID-19 pandemic, cardiology clinics rapidly implemented telemedicine to maintain access to care. Little is known about subsequent trends in telemedicine use and visit volumes across cardiology subspecialties. We conducted a retrospective cohort study including all patients with ambulatory visits at a multispecialty cardiovascular center in Northern California from March 2019 to February 2020 (pre-COVID) and March 2020 to February 2021 (COVID). Telemedicine use increased from 3.5% of visits (1200/33,976) during the pre-COVID period to 63.0% (21,251/33,706) during the COVID period. Visit volumes were below pre-COVID levels from March to May 2020 but exceeded pre-COVID levels after June 2020, including when local COVID-19 cases peaked. Telemedicine use was above 75% of visits in all cardiology subspecialties in April 2020 and stabilized at rates ranging from over 95% in electrophysiology to under 25% in heart transplant and vascular medicine. From June 2020 to February 2021, subspecialties delivering a greater percentage of visits through telemedicine experienced larger increases in new patient visits (r = 0.81, p = 0.029). Telemedicine can be used to deliver a significant proportion of outpatient cardiovascular care though utilization varies across subspecialties. Higher rates of telemedicine adoption may increase access to care in cardiology clinics.

Waste Stabilization Pond (WSP) for wastewater treatment: A review on factors, modelling and cost analysis.

Waste stabilization pond (WSP) is natural technology which can be installed in centralized or semi-centralized sewerage systems for treatment of domestic and industrial wastewater, septage and sludge, etc. WSPs are highly efficient, simple to construct, low cost and easy to operate. It can be used as secondary or tertiary treatment unit in a treatment plant either individually or in a coupling manner. The algal-bacterial symbiosis in WSP makes it completely natural treatment process for which it becomes economic as compared to other treatment technologies in terms of its maintenance cost and energy requirement. Effluent from WSP can also be used for agricultural purpose, gardening, watering road, vehicle wash, etc. Advance technologies are being integrated for better design and efficiency of WSP, but the main challenges are the separation and removal of algal species which lead to deterioration of the water if stays long. Research is necessary to maximize algal growth yield, selection of beneficial strain and optimizing harvesting methods. This review focuses on the treatment mechanism in the pond, affecting factors, types of ponds, design equation, cost analysis.

COVID-19 is associated with higher risk of venous thrombosis, but not arterial thrombosis, compared with influenza: Insights from a large US cohort.

INTRODUCTION: Infection with SARS-CoV-2 is typically compared with influenza to contextualize its health risks. SARS-CoV-2 has been linked with coagulation disturbances including arterial thrombosis, leading to considerable interest in antithrombotic therapy for Coronavirus Disease 2019 (COVID-19). However, the independent thromboembolic risk of SARS-CoV-2 infection compared with influenza remains incompletely understood. We evaluated the adjusted risks of thromboembolic events after a diagnosis of COVID-19 compared with influenza in a large retrospective cohort. METHODS: We used a US-based electronic health record (EHR) dataset linked with insurance claims to identify adults diagnosed with COVID-19 between April 1, 2020 and October 31, 2020. We identified influenza patients diagnosed between October 1, 2018 and April 31, 2019. Primary outcomes [venous composite of pulmonary embolism (PE) and acute deep vein thrombosis (DVT); arterial composite of ischemic stroke and myocardial infarction (MI)] and secondary outcomes were assessed 90 days post-diagnosis. Propensity scores (PS) were calculated using demographic, clinical, and medication variables. PS-adjusted hazard ratios (HRs) were calculated using Cox proportional hazards regression. RESULTS: There were 417,975 COVID-19 patients (median age 57y, 61% women), and 345,934 influenza patients (median age 47y, 66% women). Compared with influenza, patients with COVID-19 had higher venous thromboembolic risk (HR 1.53, 95% CI 1.38-1.70), but not arterial thromboembolic risk (HR 1.02, 95% CI 0.95-1.10). Secondary analyses demonstrated similar risk for ischemic stroke (HR 1.11, 95% CI 0.98-1.25) and MI (HR 0.93, 95% CI 0.85-1.03) and higher risk for DVT (HR 1.36, 95% CI 1.19-1.56) and PE (HR 1.82, 95% CI 1.57-2.10) in patients with COVID-19. CONCLUSION: In a large retrospective US cohort, COVID-19 was independently associated with higher 90-day risk for venous thrombosis, but not arterial thrombosis, as compared with influenza. These findings may inform crucial knowledge gaps regarding the specific thromboembolic risks of COVID-19.

Performance of repeat cytology with reflex ThyroSeq genomic classifier for indeterminant thyroid cytology.

BACKGROUND: The American Thyroid Association recommends either repeat fine-needle aspiration biopsy (FNAB) or molecular testing (eg, ThyroSeq) of Bethesda category III (atypia of undetermined significance/follicular lesion of undetermined significance [AUS/FLUS]) nodules to provide further risk stratification. How a testing algorithm that uses ancillary molecular tests performs as a reflex test for repeat sampling of indeterminant nodules remains unclear. METHODS: Thyroid FNABs performed over a 24-month period that received a diagnosis of AUS/FLUS and underwent subsequent FNAB were analyzed. RESULTS: In total, 187 patients were identified who received an FNAB diagnosis of AUS/FLUS and had repeat sampling. Of these patients, 64% received a subsequent indeterminant diagnosis on repeat biopsy: 7 (3.7%) repeat biopsies were diagnosed as nondiagnostic/unsatisfactory, 104 (55.6%) were diagnosed as AUS/FLUS, and 8 (4.3%) were diagnosed as follicular neoplasm/suspicious for follicular neoplasm. Of the repeat biopsied nodules, 63% underwent subsequent testing with ThyroSeq version 3. The diagnostic performance was calculated using only surgically confirmed nodules (sensitivity, 100%; specificity, 30%; positive predictive value, 41%; negative predictive value, 100%) and by assigning nonresected nodules with negative ThyroSeq or benign cytology results as benign (sensitivity, 100%; specificity, 88%; positive predictive value, 41%; negative predictive value, 100%). CONCLUSIONS: In the majority of patients, repeat FNAB for AUS/FLUS did not preclude subsequent molecular ancillary testing because of the high rate of indeterminant results on repeat biopsy. The diagnostic performance of the testing algorithm reported here was very similar to other reports using either repeat biopsy or molecular testing alone. Ultimately, the algorithm of performing molecular testing on repeat indeterminant nodules increased the number of biopsies performed and lengthened the time to definitive risk stratification without a disproportionate decrease in the use of molecular testing or an appreciable improvement in diagnostic performance.

Application of the Quadruple Aim to evaluate the operational impact of a telemedicine program.

BACKGROUND: In response to the COVID-19 pandemic, telemedicine utilization has increased dramatically, yet most institutions lack a standardized approach to determine how much to invest in these programs. METHODS: We used the Quadruple Aim to evaluate the operational impact of CardioClick, a program replacing in-person follow-up visits with video visits in a preventive cardiology clinic. We examined data for 134 patients enrolled in CardioClick with 181 video follow-up visits and 276 patients enrolled in the clinic's traditional prevention program with 694 in-person follow-up visits. RESULTS: Patients in CardioClick and the cohort receiving in-person care were similar in terms of age (43 vs 45 years), gender balance (74% vs 79% male), and baseline clinical characteristics. Video follow-up visits were shorter than in-person visits in terms of clinician time (median 22 vs 30 min) and total clinic time (median 22 vs 68 min). Video visits were more likely to end on time than in-person visits (71 vs 11%, p < .001). Physicians more often completed video visit documentation on the day of the visit (56 vs 42%, p = .002). CONCLUSIONS: Implementation of video follow-up visits in a preventive cardiology clinic was associated with operational improvements in the areas of efficiency, patient experience, and clinician experience. These benefits in three domains of the Quadruple Aim justify expanded use of telemedicine at our institution. IMPLICATIONS: The Quadruple Aim provides a framework to evaluate telemedicine programs recently implemented in many health systems. LEVEL OF EVIDENCE: Level III (retrospective comparative study).

COVID-19 is associated with higher risk of venous thrombosis, but not arterial thrombosis, compared with influenza: Insights from a large US cohort.

INTRODUCTION: Infection with SARS-CoV-2 is typically compared with influenza to contextualize its health risks. SARS-CoV-2 has been linked with coagulation disturbances including arterial thrombosis, leading to considerable interest in antithrombotic therapy for Coronavirus Disease 2019 (COVID-19). However, the independent thromboembolic risk of SARS-CoV-2 infection compared with influenza remains incompletely understood. We evaluated the adjusted risks of thromboembolic events after a diagnosis of COVID-19 compared with influenza in a large retrospective cohort. METHODS: We used a US-based electronic health record (EHR) dataset linked with insurance claims to identify adults diagnosed with COVID-19 between April 1, 2020 and October 31, 2020. We identified influenza patients diagnosed between October 1, 2018 and April 31, 2019. Primary outcomes [venous composite of pulmonary embolism (PE) and acute deep vein thrombosis (DVT); arterial composite of ischemic stroke and myocardial infarction (MI)] and secondary outcomes were assessed 90 days post-diagnosis. Propensity scores (PS) were calculated using demographic, clinical, and medication variables. PS-adjusted hazard ratios (HRs) were calculated using Cox proportional hazards regression. RESULTS: There were 417,975 COVID-19 patients (median age 57y, 61% women), and 345,934 influenza patients (median age 47y, 66% women). Compared with influenza, patients with COVID-19 had higher venous thromboembolic risk (HR 1.53, 95% CI 1.38-1.70), but not arterial thromboembolic risk (HR 1.02, 95% CI 0.95-1.10). Secondary analyses demonstrated similar risk for ischemic stroke (HR 1.11, 95% CI 0.98-1.25) and MI (HR 0.93, 95% CI 0.85-1.03) and higher risk for DVT (HR 1.36, 95% CI 1.19-1.56) and PE (HR 1.82, 95% CI 1.57-2.10) in patients with COVID-19. CONCLUSION: In a large retrospective US cohort, COVID-19 was independently associated with higher 90-day risk for venous thrombosis, but not arterial thrombosis, as compared with influenza. These findings may inform crucial knowledge gaps regarding the specific thromboembolic risks of COVID-19.

Initial Outcomes of CardioClick, a Telehealth Program for Preventive Cardiac Care: Observational Study.

BACKGROUND: Telehealth use has increased in specialty clinics, but there is limited evidence on the outcomes of telehealth in primary cardiovascular disease (CVD) prevention. OBJECTIVE: The objective of this study was to evaluate the initial outcomes of CardioClick, a telehealth primary CVD prevention program. METHODS: In 2017, the Stanford South Asian Translational Heart Initiative (a preventive cardiology clinic focused on high-risk South Asian patients) introduced CardioClick, which is a clinical pathway replacing in-person follow-up visits with video visits. We assessed patient engagement and changes in CVD risk factors in CardioClick patients and in a historical in-person cohort from the same clinic. RESULTS: In this study, 118 CardioClick patients and 441 patients who received in-person care were included. CardioClick patients were more likely to complete the clinic's CVD prevention program (76/118, 64.4% vs 173/441, 39.2%, respectively; P<.001) and they did so in lesser time (mean, 250 days vs 307 days, respectively; P<.001) than the patients in the historical in-person cohort. Patients who completed the CardioClick program achieved reductions in CVD risk factors, including blood pressure, lipid concentrations, and BMI, which matched or exceeded those observed in the historical in-person cohort. CONCLUSIONS: Telehealth can be used to deliver care effectively in a preventive cardiology clinic setting and may result in increased patient engagement. Further studies on telehealth outcomes are needed to determine the optimal role of virtual care models across diverse preventive medicine clinics.

Integrating the Health-care Enterprise Pathology and Laboratory Medicine Guideline for Digital Pathology Interoperability.

Integrating the health-care enterprise (IHE) is an international initiative to promote the use of standards to achieve interoperability among health information technology systems. The Pathology and Laboratory Medicine domain within IHE has brought together subject matter experts, electronic health record vendors, and digital imaging vendors, to initiate development of a series of digital pathology interoperability guidelines, called "integration profiles" within IHE. This effort begins with documentation of common use cases, followed by identification of available data and technology standards best utilized to achieve those use cases. An integration profile that describes the information flow and technology interactions is then published for trial use. Real world testing occurs in "connectathon" events, in which multiple vendors attempt to connect their products following the interoperability guidance parameters set forth in the profile. This paper describes the overarching set of integration profiles, one of which has been published, to support key digital pathology use cases.

Real-World Diagnosis and Treatment of Diabetic Kidney Disease.

INTRODUCTION: People with type 2 diabetes mellitus (T2DM) and diabetic kidney disease (DKD) have increased morbidity and mortality risk. Angiotensin-converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARB) are recommended to slow kidney function decline in DKD. This representative, real-world data analysis of patients with T2DM was performed to detect onset of DKD and determine methods and timing of DKD diagnosis and time to initiation of ACEi/ARB therapy. METHODS: Patients diagnosed with T2DM before January 1, 2016 who developed DKD between January 1, 2017 and June 30, 2019 were identified from a longitudinal ambulatory electronic health record (EHR) dataset (Veradigm Inc). Each record was analyzed using the CLinical INTelligence engine (CLINT™, HealthPals, Inc.) to identify delays and gaps in diagnosing DKD. DKD was diagnosed through two reduced estimated glomerular filtration rate (eGFR; < 60 mL/min/1.73 m2) measurements at least 90 days apart, a single elevated urine albumin-to-creatinine ratio (UACR; > 30 mg/g) measurement, or ICD-9/10 diagnosis codes for DKD and/or albuminuria. Time to diagnose (TTD), time to treat (TTT), and diagnosis to treatment time were assessed. RESULTS: Of 6,499,409 patients with T2DM before January 2016, 245,978 developed DKD between January 1, 2017 and June 30, 2019. In this DKD cohort, ca. 50% were first identified through EHR diagnosis and ca. 50% by UACR or eGFR lab-based diagnosis. In patients who had UACR/eGFR assessed, more than 90% exhibited DKD-level results on the first diagnostic test. Average TTD after eGFR labs was 2 years; average TTT with ACEi/ARB was 6-9 months after DKD lab evidence. The majority of patients who developed DKD received ACEi/ARB therapy 6-7 months after diagnosis. CONCLUSION: In a contemporary, large national cohort of patients with T2DM, progression to DKD was common but likely underrepresented. The low rate of DKD-screening labs, along with sizable delays in diagnosis of DKD and initiation of ACEi/ARB therapy, indicates that many patients who progress to DKD are not being properly treated.

Diabetic kidney disease is kidney disease that occurs in patients with type 2 diabetes and is associated with greater risk of death and other adverse cardiovascular and kidney outcomes. Unfortunately, diabetic kidney disease is underdiagnosed because of lack of awareness and its early asymptomatic presentation. Early detection and treatment of diabetic kidney disease with medicines such as angiotensin-converting enzyme inhibitors (also known as ACE inhibitors) or angiotensin II receptor blockers (also known as ARBs) is important for the prevention of disease progression and the development of other serious conditions. This real-world analysis evaluated electronic health record data from more than 6 million patients with diabetes to detect the onset of diabetic kidney disease and to determine timing of treatment and gaps in medical care. Results from the study show that there are often significant delays in the diagnosis of diabetic kidney disease, even when laboratory evidence is available. Furthermore, many patients are not undergoing regular renal function testing, thus missing the opportunity for diagnosis (and subsequent treatment) of earlier onset, less severe disease. After diagnosis, patients with diabetic kidney disease experience significant delay until they receive appropriate treatment with an ACE inhibitor or ARB. The low rate of kidney function screening coupled with delays in diagnosis and treatment initiation suggest that many patients who progress to diabetic kidney disease are not being properly treated. The results from this study highlight the need to improve diagnostic and treatment protocols to address these significant gaps in care.