Global Health Initiatives: International Physican-to-Physician Consultation Programs.

OBJECTIVE: The goal of this article is to provide technical and operational blueprints for two successful global telehealth programs. METHODS: We designed a physician-to-physician consultation program to provide subspecialty expertise to physicians in warn-torn Ukraine. Leveraging secure web applications, telehealth platforms, and image sharing platforms, we repeatedly iterated upon infrastructure and workflows, which in turn facilitated development of a parallel international program for Department of State (DOS) employees and families. We provide descriptive statistics and metrics of both programs' successes and failures and detail iterative improvements with workflow visuals. To measure subspecialty imaging consultation value-add, two radiologists performed a retrospective comparative review of DOS program initial versus consulted imaging reports in consensus, measuring diagnostic report agreement and rating clinical impact of identified discrepancies on a 3-point scale (mild, moderate, major). Bivariate analyses using Chi-square tests assessed for associations between diagnostic discrepancies and patient or imaging factors. P<0.05 was considered statistically significant. RESULTS: The Ukraine program (05/2022-08/2023) provided 114 patient consultations with 77 subspecialty radiology consults, >50 WhatsApp chats, and >1,000 messages exchanged, and 92% overall consult request response rate. The DOS program (11/2022-07/2023) provided 275 consultations with 70 subspecialty radiology consults and 36-38% rate of alternative diagnoses, with 20% rated as incurring moderate or major clinical impact. Bivariate analyses demonstrated no significant patient or imaging association with diagnostic disagreements (all p>0.05). DISCUSSION: Global telehealth infrastructure and multiple applications and platforms can be optimized in a workflow to provide efficient, high level clinical and imaging consultation services across the globe.

Maternal and Fetal Radiation-Induced Cancer Risk From Computed Tomography Pulmonary Angiography During Pregnancy: A Retrospective Cohort Study Across a Multihospital Integrated Health Care Network.

OBJECTIVE: Computed tomography pulmonary angiogram (CTPA) is important to evaluate suspected pulmonary embolism in pregnancy but has maternal/fetal radiation risks. The objective of this study was to estimate maternal and fetal radiation-induced cancer risk from CTPA during pregnancy. METHODS: Simulation modeling via the National Cancer Institute's Radiation Risk Assessment Tool was used to estimate excess cancer risks from 17 organ doses from CTPA during pregnancy, with doses determined by a radiation dose indexing monitoring system. Organ doses were obtained from a radiation dose indexing monitoring system. Maternal and fetal cancer risks per 100,000 were calculated for male and female fetuses and several maternal ages. RESULTS: The 534 CTPA examinations had top 3 maternal organ doses to the breast, lung, and stomach of 17.34, 15.53, and 9.43 mSv, respectively, with a mean uterine dose of 0.21 mSv. The total maternal excess risks of developing cancer per 100,000 were 181, 151, 121, 107, 94.5, 84, and 74.4, respectively, for a 20-, 25-, 30-, 35-, 40-, 45-, and 50-year-old woman undergoing CTPA, compared with baseline cancer risks of 41,408 for 20-year-old patients. The total fetal excess risks of developing cancer per 100,000 were 12.3 and 7.3 for female and male fetuses, respectively, when compared with baseline cancer risks of 41,227 and 48,291. DISCUSSION: Excess risk of developing cancer from CTPA was small relative to baseline cancer risk for pregnant patients and fetuses, decreased for pregnant patients with increasing maternal age, and was greater for female fetuses than male fetuses.

Ten-Year Trend in Advanced Imaging Utilization for Suspected Pulmonary Embolism in Pregnancy.

PURPOSE: Advanced imaging is essential to diagnose pulmonary embolism (PE) in pregnancy, but there are associated maternal and fetal radiation risks. The purpose of this study was to evaluate the 10-year trend in advanced imaging utilization for the evaluation of suspected PE in pregnancy. METHODS: The authors evaluated pregnant women with advanced imaging using CT pulmonary angiography (CTPA) or lung scintigraphy (LS) for evaluation of suspected PE presenting to two tertiary hospitals from 2007 to 2016. The rate of imaging was evaluated relative to positive PE rate and local pregnancy rate. positive PE was defined as a new acute PE finding on any advanced imaging within 3 days of first advanced imaging test. Local pregnancy rates were defined per 1,000 pregnancies in the county serviced by both hospitals. Chi-square testing was used to evaluate statistical significance (P < .05) in the utilization trend of advanced imaging and relative to local pregnancy rates and evaluations positive for PE. RESULTS: A total of 707 pregnant patients were identified, of whom 92.5% (n = 654) underwent CTPA and 7.5% (n = 53) underwent LS. Regression analysis showed an average increase of 5.2 advanced imaging studies per year (P < .001), with 61 and 105 studies performed in 2007 and 2016, respectively. Additionally, there was an average increase of 0.08 (P < .001) advanced imaging studies per 1,000 local pregnancies per year, doubling from 0.7 in 2007 to 1.4 in 2016 (P < .001). Finally, there was a decrease of 0.004 (P = .009) in advanced imaging positive for PE, from 3% (2 of 61) in 2007 to 0% (0 of 100) in 2016. CONCLUSIONS: Advanced imaging utilization increased by 72% over the 10-year window, driven by higher use of CTPA. Although the detection rate of PE on advanced imaging has decreased, the utilization rate among pregnant patients doubled during this period. These results highlight the need to consider the radiation risks and costs of advanced imaging in specific patient populations.

Characteristics of Suspected COVID-19 Discharged Emergency Department Patients Who Returned During the First Wave.

INTRODUCTION: Limited information exists on patients with suspected coronavirus disease 2019 (COVID-19) who return to the emergency department (ED) during the first wave. In this study we aimed to identify predictors of ED return within 72 hours for patients with suspected COVID-19. METHODS: Incorporating data from 14 EDs within an integrated healthcare network in the New York metropolitan region from March 2-April 27, 2020, we analyzed this data on predictors for a return ED visit-including demographics, comorbidities, vital signs, and laboratory results. RESULTS: In total, 18,599 patients were included in the study. The median age was 46 years old [interquartile range 34-58]), 50.74% were female, and 49.26% were male. Overall, 532 (2.86%) returned to the ED within 72 hours, and 95.49% were admitted at the return visit. Of those tested for COVID-19, 59.24% (4704/7941) tested positive. Patients with chief complaints of "fever" or "flu" or a history of diabetes or renal disease were more likely to return at 72 hours. Risk of return increased with persistently abnormal temperature (odds ratio [OR] 2.43, 95% CI 1.8-3.2), respiratory rate (2.17, 95% CI 1.6-3.0), and chest radiograph (OR 2.54, 95% CI 2.0-3.2). Abnormally high neutrophil counts, low platelet counts, high bicarbonate values, and high aspartate aminotransferase levels were associated with a higher rate of return. Risk of return decreased when discharged on antibiotics (OR 0.12, 95% CI 0.0-0.3) or corticosteroids (OR 0.12, 95% CI 0.0-0.9). CONCLUSION: The low overall return rate of patients during the first COVID-19 wave indicates that physicians' clinical decision-making successfully identified those acceptable for discharge.

The association of clinically relevant variables with chest radiograph lung disease burden quantified in real-time by radiologists upon initial presentation in individuals hospitalized with COVID-19.

OBJECTIVES: We aimed to correlate lung disease burden on presentation chest radiographs (CXR), quantified at the time of study interpretation, with clinical presentation in patients hospitalized with coronavirus disease 2019 (COVID-19). MATERIAL AND METHODS: This retrospective cross-sectional study included 5833 consecutive adult patients, aged 18 and older, hospitalized with a diagnosis of COVID-19 with a CXR quantified in real-time while hospitalized in 1 of 12 acute care hospitals across a multihospital integrated healthcare network between March 24, 2020, and May 22, 2020. Lung disease burden was quantified in real-time by 118 radiologists on 5833 CXR at the time of exam interpretation with each lung annotated by the degree of lung opacity as clear (0%), mild (1-33%), moderate (34-66%), or severe (67-100%). CXR findings were classified as (1) clear versus disease, (2) unilateral versus bilateral, (3) symmetric versus asymmetric, or (4) not severe versus severe. Lung disease burden was characterized on initial presentation by patient demographics, co-morbidities, vital signs, and lab results with chi-square used for univariate analysis and logistic regression for multivariable analysis. RESULTS: Patients with severe lung disease were more likely to have oxygen impairment, an elevated respiratory rate, low albumin, high lactate dehydrogenase, and high ferritin compared to non-severe lung disease. A lack of opacities in COVID-19 was associated with a low estimated glomerular filtration rate, hypernatremia, and hypoglycemia. CONCLUSIONS: COVID-19 lung disease burden quantified in real-time on presentation CXR was characterized by demographics, comorbidities, emergency severity index, Charlson Comorbidity Index, vital signs, and lab results on 5833 patients. This novel approach to real-time quantified chest radiograph lung disease burden by radiologists needs further research to understand how this information can be incorporated to improve clinical care for pulmonary-related diseases.. An absence of opacities in COVID-19 may be associated with poor oral intake and a prerenal state as evidenced by the association of clear CXRs with a low eGFR, hypernatremia, and hypoglycemia.

Patient and Fetal Radiation-Induced Malignancy Risk From Imaging For Evaluation of Pulmonary Embolism in Pregnancy.

BACKGROUND: Imaging for diagnosis of suspected pulmonary embolism in pregnancy presents radiation concerns for patient and fetus. OBJECTIVES: Estimate the risks of radiation-induced breast cancer and childhood leukemia from common imaging techniques for the evaluation of suspected pulmonary embolism in pregnancy. METHODS: Breast and uterine absorbed doses for various imaging techniques were input into the National Cancer Institute Radiation Risk Assessment Tool to calculate risk of breast cancer for the patient and childhood leukemia for the fetus. Absorbed doses were obtained by synthesizing data from a recent systematic review and the International Commission on Radiological Protection. Primary outcomes were the estimated excess incidences of breast cancer and childhood leukemia per 100,000 exposures. RESULTS: Baseline incidences of breast cancer for a 30-year-old woman and childhood leukemia for a male fetus were 13,341 and 939, respectively. Excess incidences of breast cancer were 0.003 and 0.275 for a single and two-view chest radiograph, respectively, 9.53 and 20.6 for low- and full-dose computed tomography pulmonary angiography (CTPA), respectively, 0.616 and 2.54 for low- and full-dose perfusion scan, respectively, and 0.732 and 2.66 for low- and full-dose ventilation perfusion scan, respectively. Excess incidences of childhood leukemia were 0.004 and 0.007 for a single and two-view chest radiograph, respectively, 0.069 and 0.490 for low- and full-dose CTPA, respectively, 0.359 and 1.47 for low- and full-dose perfusion scan, respectively, and 0.856 and 1.97 for low- and full-dose ventilation perfusion scan, respectively. CONCLUSION: Excess cancer risks for all techniques were small relative to baseline cancer risks, with CTPA techniques carrying slightly higher risk of breast cancer for the patient and ventilation perfusion techniques a higher risk of childhood leukemia.

A radiographic, deep transfer learning framework, adapted to estimate lung opacities from chest x-rays.

Chest radiographs (CXRs) are the most widely available radiographic imaging modality used to detect respiratory diseases that result in lung opacities. CXR reports often use non-standardized language that result in subjective, qualitative, and non-reproducible opacity estimates. Our goal was to develop a robust deep transfer learning framework and adapt it to estimate the degree of lung opacity from CXRs. Following CXR data selection based on exclusion criteria, segmentation schemes were used for ROI (Region Of Interest) extraction, and all combinations of segmentation, data balancing, and classification methods were tested to pick the top performing models. Multifold cross validation was used to determine the best model from the initial selected top models, based on appropriate performance metrics, as well as a novel Macro-Averaged Heatmap Concordance Score (MA HCS). Performance of the best model is compared against that of expert physician annotators, and heatmaps were produced. Finally, model performance sensitivity analysis across patient populations of interest was performed. The proposed framework was adapted to the specific use case of estimation of degree of CXR lung opacity using ordinal multiclass classification. Acquired between March 24, 2020, and May 22, 2020, 38,365 prospectively annotated CXRs from 17,418 patients were used. We tested three neural network architectures (ResNet-50, VGG-16, and ChexNet), three segmentation schemes (no segmentation, lung segmentation, and lateral segmentation based on spine detection), and three data balancing strategies (undersampling, double-stage sampling, and synthetic minority oversampling) using 38,079 CXR images for training, and validation with 286 images as the out-of-the-box dataset that underwent expert radiologist adjudication. Based on the results of these experiments, the ResNet-50 model with undersampling and no ROI segmentation is recommended for lung opacity classification, based on optimal values for the MAE metric and HCS (Heatmap Concordance Score). The degree of agreement between the opacity scores predicted by this model with respect to the two sets of radiologist scores (OR or Original Reader and OOBTR or Out Of Box Reader) in terms of performance metrics is superior to the inter-radiologist opacity score agreement.

Utilization of a Guideline-recommended Imaging Paradigm for Pregnant Patients With Suspicion of Pulmonary Embolism.

PURPOSE: A dose reduction imaging paradigm utilizing chest x-ray (CXR) to triage between computed tomography pulmonary angiography (CTPA) and lung scintigraphy (LS) was introduced in 2001 and adopted in 2012 by the American Thoracic Society/Society of Thoracic Radiology (ATS) guideline for the evaluation of pulmonary embolism in pregnancy. We aimed to assess the utilization of this imaging paradigm preadoption and postadoption by the ATS guideline, and identify factors associated with its utilization. MATERIALS AND METHODS: This retrospective cohort study evaluated consecutive pregnant patients who received CTPA or LS for the evaluation of pulmonary embolism in pregnancy at 2 tertiary hospitals between September 2008 and March 2017, excluding 2012 for guideline release washout. Utilization of the imaging paradigm was defined per patient by the use of CXR before advanced imaging, with CTPA performed following positive CXR and LS performed following negative CXR. Multivariate analyses were performed to assess factors associated with utilization of the imaging paradigm. P <0.05 is considered significant. RESULTS: Overall, 9.8% (63/643) of studies utilized the dose reduction imaging paradigm, 13.3% (34/256) before the guidelines, and 7.5% (29/387) after. Multivariable analysis showed that the dose reduction imaging paradigm utilization was higher for inpatients (odds ratio [OR]: 4.5) and outpatients (OR: 3.1) relative to the emergency department patients, and lower for second (OR: 0.3) and third (OR: 0.2) trimester patients, without significant differences by study priority, patient age, or patient race. CONCLUSIONS: Guideline-recommended dose reduction imaging paradigm utilization was low, and decreased after guideline publication. Utilization varied by patient setting and trimester, which are potential targets for interventions to improve guideline compliance.

The patient-friendly radiology report: history, evolution, challenges and opportunities.

The past several decades have witnessed dramatic developments and improvements in the field of radiology, including technologic innovations and new imaging modalities, picture archiving and communication systems, and the rise of artificial intelligence. At the same time, an evolution has been occurring in a fundamental component of radiology practice - the radiologist's report. Initially, the radiology report was a private written communication between the radiologist and the referring physician 1,2. Today, the report is an electronic document, displayed on web portals, and visible to both physicians and the patients themselves.3 A provision in the 21st Century Cures Act, signed into law on December 13, 2016, ensures that radiology reports in the electronic health record are visible to patients without delay 4. To meet modern patient expectations and legal requirements, the structure and purpose of the radiologist report is changing. This article will provide an overview of the history of radiology reporting and the law, discuss the role of the radiologist report within the context of patient and family centered care, review current strategies and investigations in patient-friendly reporting, and summarize radiology reporting challenges and opportunities for the future.

3D Virtual Pancreatography.

We present 3D virtual pancreatography (VP), a novel visualization procedure and application for non-invasive diagnosis and classification of pancreatic lesions, the precursors of pancreatic cancer. Currently, non-invasive screening of patients is performed through visual inspection of 2D axis-aligned CT images, though the relevant features are often not clearly visible nor automatically detected. VP is an end-to-end visual diagnosis system that includes: A machine learning based automatic segmentation of the pancreatic gland and the lesions, a semi-automatic approach to extract the primary pancreatic duct, a machine learning based automatic classification of lesions into four prominent types, and specialized 3D and 2D exploratory visualizations of the pancreas, lesions and surrounding anatomy. We combine volume rendering with pancreas- and lesion-centric visualizations and measurements for effective diagnosis. We designed VP through close collaboration and feedback from expert radiologists, and evaluated it on multiple real-world CT datasets with various pancreatic lesions and case studies examined by the expert radiologists.

CT pulmonary angiography in pregnancy: Specific conversion factors to estimate effective radiation dose from dose length product: A retrospective cross-sectional study across a multi-hospital integrated healthcare network.

PURPOSE: Effective dose describes radiation-related cancer risk from CT scans and is estimated using a readily available conversion factor (k-factor), which varies by body part and study type. To purpose of this study is to determine the specific k-factor for CTPA in pregnant patients and its predictive factors. METHODS: This retrospective cross-sectional study evaluates CTPA in pregnancy across a multihospital integrated healthcare network from January 2012 to April 2017. Patient and CTPA-related data were obtained from the electronic health record and a radiation dose index monitoring system. Each patient's effective dose was determined by patient-specific Monte-Carlo simulation with Cristy phantoms and divided by patient dose-length-product to determine the k-factor. K-factor for pregnant patients was compared to the k-factor for adults of standard physique with a one-sample t-test. Bivariate and multivariable analyses were performed for patient and CT predictors of k-factor. RESULTS: A total of 534 patients were included. The mean k-factor for all patients was 0.0249 (mSv·mGy-1·cm-1), 78% greater than k-factor of 0.014 (p < 0.001) suggested for the general adult population. Multivariable analysis demonstrated lower k-factors with increasing pitch (p = 0.0002), patient size (p < 0.001), and scan length (p < 0.0001). The 120 kVp (p < 0.001) and 140 kVp (p = 0.0028) analyses showed a larger k-factor than 80 and 100 kVp studies combined. CONCLUSIONS: Specific k-factor for CTPA in pregnant patients is greater than the previously used generic chest CT k-factor and should be used to estimate the effective dose for CTPA exams in pregnancy.

External validation of the IMPROVE-DD risk assessment model for venous thromboembolism among inpatients with COVID-19.

There is a need to discriminate which COVID-19 inpatients are at higher risk for venous thromboembolism (VTE) to inform prophylaxis strategies. The IMPROVE-DD VTE risk assessment model (RAM) has previously demonstrated good discrimination in non-COVID populations. We aimed to externally validate the IMPROVE-DD VTE RAM in medical patients hospitalized with COVID-19. This retrospective cohort study evaluated the IMPROVE-DD VTE RAM in adult patients with COVID-19 admitted to one of thirteen Northwell Health hospitals in the New York metropolitan area between March 1, 2020 and April 27, 2020. VTE was defined as new-onset symptomatic deep venous thrombosis or pulmonary embolism. To assess the predictive value of the RAM, the receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Of 9407 patients who met study criteria, 274 patients developed VTE with a prevalence of 2.91%. The VTE rate was 0.41% for IMPROVE-DD score 0-1 (low risk), 1.21% for score 2-3 (moderate risk), and 5.30% for score ≥ 4 (high risk). Approximately 45.7% of patients were classified as high VTE risk, 33.3% moderate risk, and 21.0% low risk. Discrimination of low versus moderate-high VTE risk demonstrated sensitivity 0.971, specificity 0.215, PPV 0.036, and NPV 0.996. ROC AUC was 0.703. In this external validation study, the IMPROVE-DD VTE RAM demonstrated very good discrimination to identify hospitalized COVID-19 patients at low, moderate, and high VTE risk.

Risk factors and outcomes for acute-on-chronic liver failure in COVID-19: a large multi-center observational cohort study.

OBJECTIVE: Coronavirus disease 2019 [COVID-19] infection in patients with chronic liver disease [CLD] may precipitate acute-on-chronic liver failure [ACLF]. In a large multi-center cohort of COVID-19-infected patients, we aim to analyze (1) the outcomes of patients with underlying CLD [with and without cirrhosis] and (2) the development and impact of ACLF on in-hospital mortality. DESIGN: We identified 192 adults with CLD from among 10,859 patients with confirmed COVID-19 infection (admitted to any of 12 hospitals in a New York health care system between March 1, 2020 and April 27, 2020). ACLF was defined using the EASL-CLIF Consortium definition. Patient follow-up was through April 30, 2020, or until the date of discharge, transfer, or death. RESULTS: Of the 84 patients with cirrhosis, 32 [38%] developed ACLF, with respiratory failure [39%] and renal failure [26%] being the most common. Hispanic/Latino ethnicity was particularly at higher risk of in-hospital mortality [adjusted HR 4.92, 95% 1.27-19.09, p < 0.02] in cirrhosis despite having lower risk of development of ACLF [HR 0.26, 95% CI 0.08-0.89, p = 0.03]. Hypertension on admission predicted development of ACLF [HR 3.46, 95% CI 1.12-10.75, p = 0.03]. In-hospital mortality was not different between CLD patients with or without cirrhosis [p = 0.24] but was higher in those with cirrhosis who developed ACLF [adjusted HR 9.06, 95% CI 2.63-31.12, p < 0.001] with a trend for increased mortality by grade of ACLF [p = 0.002]. There was no difference in in-hospital mortality between the CLD cohort compared to matched control without CLD (log rank, p = 0.98) and between the cirrhosis cohort compared to matched control without cirrhosis (log rank, p = 0.51). CONCLUSION: Development of ACLF is the main driver of increased in-hospital mortality in hospitalized patients with COVID-19 infection and cirrhosis.

Sex-Based Differences in COVID-19 Outcomes.

Background: Smaller studies suggest lower morbidity and mortality associated with coronavirus disease 2019 (COVID-19) in women. Our aim is to assess the impact of female sex on outcomes in a large cohort of patients hospitalized with COVID-19. Materials and Methods: This is a retrospective observational cohort study of 10,630 adult patients hospitalized with a confirmed COVID-19 polymerase chain reaction between March 1, 2020 and April 27, 2020, with follow-up conducted through June 4, 2020. Logistic regression was used to examine the relationship between sex and the primary outcomes, including length of stay, admission to intensive care unit (ICU), need for mechanical ventilation, pressor requirement, and all-cause mortality as well as major adverse events and in-hospital COVID-19 treatments. Results: In the multivariable analysis, women had 27% lower odds of in-hospital mortality (odds ratio [OR] = 0.73, 95% confidence interval [CI] 0.66-0.81; p < 0.001), 24% lower odds of ICU admission (OR = 0.76, 95% CI 0.69-0.84; p < 0.001), 26% lower odds of mechanical ventilation (OR = 0.74, 95% CI 0.66-0.82; p < 0.001), and 25% lower odds of vasopressor requirement (OR = 0.75, 95% CI 0.67-0.84; p < 0.001). Women had 34% less odds of having acute cardiac injury (OR = 0.66, 95% CI 0.59-0.74; p < 0.001; n = 7,289), 16% less odds of acute kidney injury (OR = 0.84, 95% CI 0.76-0.92; p < 0.001; n = 9,840), and 27% less odds of venous thromboembolism (OR = 0.73, 95% CI 0.56-0.96; p < 0.02; c-statistic 0.85, n = 9,407). Conclusions: Female sex is associated with lower odds of in-hospital outcomes, major adverse events, and all-cause mortality. There may be protective mechanisms inherent to female sex, which explain differences in COVID-19 outcomes.

Postdischarge thromboembolic outcomes and mortality of hospitalized patients with COVID-19: the CORE-19 registry.

Thromboembolic events, including venous thromboembolism (VTE) and arterial thromboembolism (ATE), and mortality from subclinical thrombotic events occur frequently in coronavirus disease 2019 (COVID-19) inpatients. Whether the risk extends postdischarge has been controversial. Our prospective registry included consecutive patients with COVID-19 hospitalized within our multihospital system from 1 March to 31 May 2020. We captured demographics, comorbidities, laboratory parameters, medications, postdischarge thromboprophylaxis, and 90-day outcomes. Data from electronic health records, health informatics exchange, radiology database, and telephonic follow-up were merged. Primary outcome was a composite of adjudicated VTE, ATE, and all-cause mortality (ACM). Principal safety outcome was major bleeding (MB). Among 4906 patients (53.7% male), mean age was 61.7 years. Comorbidities included hypertension (38.6%), diabetes (25.1%), obesity (18.9%), and cancer history (13.1%). Postdischarge thromboprophylaxis was prescribed in 13.2%. VTE rate was 1.55%; ATE, 1.71%; ΑCM, 4.83%; and MB, 1.73%. Composite primary outcome rate was 7.13% and significantly associated with advanced age (odds ratio [OR], 3.66; 95% CI, 2.84-4.71), prior VTE (OR, 2.99; 95% CI, 2.00-4.47), intensive care unit (ICU) stay (OR, 2.22; 95% CI, 1.78-2.93), chronic kidney disease (CKD; OR, 2.10; 95% CI, 1.47-3.0), peripheral arterial disease (OR, 2.04; 95% CI, 1.10-3.80), carotid occlusive disease (OR, 2.02; 95% CI, 1.30-3.14), IMPROVE-DD VTE score ≥4 (OR, 1.51; 95% CI, 1.06-2.14), and coronary artery disease (OR, 1.50; 95% CI, 1.04-2.17). Postdischarge anticoagulation was significantly associated with reduction in primary outcome (OR, 0.54; 95% CI, 0.47-0.81). Postdischarge VTE, ATE, and ACM occurred frequently after COVID-19 hospitalization. Advanced age, cardiovascular risk factors, CKD, IMPROVE-DD VTE score ≥4, and ICU stay increased risk. Postdischarge anticoagulation reduced risk by 46%.

Incidence of Venous Thromboembolism and Mortality in Patients with Initial Presentation of COVID-19.

Venous thromboembolism (VTE) has emerged as an important issue in patients with COVID-19. The purpose of this study is to identify the incidence of VTE and mortality in COVID-19 patients initially presenting to a large health system. Our retrospective study included adult patients (excluding patients presenting with obstetric/gynecologic conditions) across a multihospital health system in the New York Metropolitan Region from March 1-April 27, 2020. VTE and mortality rates within 8 h of assessment were described. In 10,871 adults with COVID-19, 118 patients (1.09%) were diagnosed with symptomatic VTE (101 pulmonary embolism, 17 deep vein thrombosis events) and 28 patients (0.26%) died during initial assessment. Among these 146 patients, 64.4% were males, 56.8% were 60 years or older, 15.1% had a BMI > 35, and 11.6% were admitted to the intensive care unit. Comorbidities included hypertension (46.6%), diabetes (24.7%), hyperlipidemia (14.4%), chronic lung disease (12.3%), coronary artery disease (11.0%), and prior VTE (7.5%). Key medications included corticosteroids (22.6%), statins (21.2%), antiplatelets (20.6%), and anticoagulants (20.6%). Highest D-Dimer was greater than six times the upper limit of normal in 51.4%. Statin and antiplatelet use were associated with decreased VTE or mortality (each p < 0.01). In COVID-19 patients who initially presented to a large multihospital health system, the overall symptomatic VTE and mortality rate was over 1.0%. Statin and antiplatelet use were associated with decreased VTE or mortality. The potential benefits of antithrombotics in high risk COVID-19 patients during the pre-hospitalization period deserves study.

Validation of the IMPROVE-DD risk assessment model for venous thromboembolism among hospitalized patients with COVID-19.

BACKGROUND: Antithrombotic guidance statements for hospitalized patients with coronavirus disease 2019 (COVID-19) suggest a universal thromboprophylactic strategy with potential to escalate doses in high-risk patients. To date, no clear approach exists to discriminate patients at high risk for venous thromboembolism (VTE). OBJECTIVES: The objective of this study is to externally validate the IMPROVE-DD risk assessment model (RAM) for VTE in a large cohort of hospitalized patients with COVID-19 within a multihospital health system. METHODS: This retrospective cohort study evaluated the IMPROVE-DD RAM on adult inpatients with COVID-19 hospitalized between March 1, 2020, and April 27, 2020. Diagnosis of VTE was defined by new acute deep venous thrombosis or pulmonary embolism by Radiology Department imaging or point-of-care ultrasound. The receiver operating characteristic (ROC) curve was plotted and area under the curve (AUC) calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using standard methods. RESULTS: A total of 9407 patients were included, with a VTE prevalence of 2.9%. The VTE rate was 0.4% for IMPROVE-DD score 0-1 (low risk), 1.3% for score 2-3 (moderate risk), and 5.3% for score ≥ 4 (high risk). Approximately 45% of the total population scored high VTE risk, while 21% scored low VTE risk. IMPROVE-DD discrimination of low versus medium/high risk showed sensitivity of 0.971, specificity of 0.218, PPV of 0.036, and NPV of 0.996. ROC AUC was 0.702. CONCLUSIONS: The IMPROVE-DD VTE RAM demonstrated very good discrimination to identify hospitalized patients with COVID-19 as low, moderate, and high VTE risk in this large external validation study with potential to individualize thromboprophylactic strategies.

CT colonography's role in the COVID-19 pandemic: a safe(r), socially distanced total colon examination.

PURPOSE: To describe the favorable procedural profile of CT colonography (CTC) during the COVID-19 pandemic. CONCLUSION: Postponement of cancer screening due to COVID-19 has resulted in a backlog of individuals needing to undergo structural examination of the colon. The experience during the initial COVID-19 surge with urgent evaluation of the colon for transplant patients prior to transplant suggests that CTC can be done in a lower risk manner as compared to other structural examinations. The procedural profile of CTC is advantageous during this pandemic as maintaining social distancing and preserving healthcare supplies including PPE are of paramount importance. CTC is an important option to utilize in the screening armamentarium to allow effective screening of average risk asymptomatic individuals in the COVID-19 era.

Abdominal pelvic CT findings compared between COVID-19 positive and COVID-19 negative patients in the emergency department setting.

PURPOSE: Manifestations of COVID-19 are primarily respiratory based, however, gastrointestinal symptoms are now recognized as an important component of the disease. The purpose of this study is to evaluate differences in abdominal pelvic CT findings in the emergency department by COVID-19 test result. METHODS: This retrospective study identified patients tested by PCR for COVID-19 infection who underwent abdominal pelvic CT scan in the ED across an academic health system from March 15 to April 15, 2020. Radiology reports were reviewed for the presence of ground glass opacity in the lungs and acute abdominal pathology. A subset of patients with acute abdominal pathology were identified with inflammatory pathology in organs with high ACE2 receptor expression including bowel, pancreas, urinary bladder, and kidney. CT findings for COVID positive versus negative patients were compared with Chi-square test. RESULTS: 597 patients tested by PCR for COVID-19 infection underwent abdominal pelvic CT scan, 44% were COVID-19 positive. COVID-19 positive patients demonstrated significantly more ground glass opacity at the lung bases, 65.1%, (222/341) versus 12.4% (33/266), p < 0.001), and significantly less acute abdominal findings, 23.8% (81/341) versus 45.5% (121/266), p ≤ 0.001). When abdominal pathology was present, COVID-19 positive patients had higher rate of inflammatory pathology 58% (47/81) versus 29.8% (36/121). CONCLUSIONS: In patients undergoing abdominopelvic CT from the ED, COVID-19 positive patients are more likely to have ground glass opacities at the lung bases and less likely to have acute abdominal pathology compared with COVID-19 negative patients. Further, COVID-19 positive patients are more likely to have inflammation of organs with high expression of ACE2 receptors than other types of acute abdominal pathology.

3D-GLCM CNN: A 3-Dimensional Gray-Level Co-Occurrence Matrix-Based CNN Model for Polyp Classification via CT Colonography.

Accurately classifying colorectal polyps, or differentiating malignant from benign ones, has a significant clinical impact on early detection and identifying optimal treatment of colorectal cancer. Convolution neural network (CNN) has shown great potential in recognizing different objects (e.g. human faces) from multiple slice (or color) images, a task similar to the polyp differentiation, given a large learning database. This study explores the potential of CNN learning from multiple slice (or feature) images to differentiate malignant from benign polyps from a relatively small database with pathological ground truth, including 32 malignant and 31 benign polyps represented by volumetric computed tomographic (CT) images. The feature image in this investigation is the gray-level co-occurrence matrix (GLCM). For each volumetric polyp, there are 13 GLCMs, computed from each of the 13 directions through the polyp volume. For comparison purpose, the CNN learning is also applied to the multi-slice CT images of the volumetric polyps. The comparison study is further extended to include Random Forest (RF) classification of the Haralick texture features (derived from the GLCMs). From the relatively small database, this study achieved scores of 0.91/0.93 (two-fold/leave-one-out evaluations) AUC (area under curve of the receiver operating characteristics) by using the CNN on the GLCMs, while the RF reached 0.84/0.86 AUC on the Haralick features and the CNN rendered 0.79/0.80 AUC on the multiple-slice CT images. The presented CNN learning from the GLCMs can relieve the challenge associated with relatively small database, improve the classification performance over the CNN on the raw CT images and the RF on the Haralick features, and have the potential to perform the clinical task of differentiating malignant from benign polyps with pathological ground truth.