Prevalence of venous thromboembolism in patients undergoing diagnostic venous ultrasound during the first SARS-CoV-2 pandemic.

Background: Venous thromboembolism appears to be associated with severe COVID-19 infection than in those without it. However, this varies considerably depending on the cohort studied. The aims of this single-centre, multi-site retrospective cross-sectional study were to assess the number of all venous scans performed in the first month of pandemic in a large university teaching hospital, to evaluate the incidence of deep venous thrombosis (DVT), and assess the predictive ability of the clinical information available on the electronic patient record in planning work-up for DVT and prioritising ultrasound scans. Patients and methods: All consecutive patients undergoing venous ultrasound for suspected acute DVT between 1st of March and 30th of April 2020 were considered. Primary outcome was the proportion of scans positive for DVT; the secondary outcomes included association of a positive SARS-CoV-2 PCR test, demographic, clinical factors, and Wells scores. Results: 819 ultrasound scans were performed on 762 patients across the Trust in March and April 2020. This number was comparable to the corresponding pre-pandemic cohort from 2019. The overall prevalence of DVT in the studied cohort was 16.1% and was higher than before the pandemic (11.5%, p=.047). Clinical symptoms consistent with COVID-19, irrespective of the SARS-CoV-2 PCR test result (positive_COVID_PCR OR 4.97, 95%CI 2.31-10.62, p<.001; negative_COVID_PCR OR 1.97, 95%CI 1.12-3.39, p=.016), a history of AF (OR 0.20, 95%CI 0.03-0.73, p=.037), and personal history of venous thromboembolism (VTE) (OR 1.95, 95%CI 1.13-3.31, p=.014), were independently associated with the diagnosis of DVT on ultrasound scan. Wells score was not associated with the incidence of DVT. Conclusions: Amongst those referred for the DVT scan, SARS-CoV-2 PCR test was associated with an increased risk of VTE and should be taken into consideration when planning DVT work-up and prioritising diagnostic imaging. We postulate that the threshold for imaging should possibly be lower.

Unquantifiably low aldosterone concentrations are prevalent in hospitalised COVID-19 patients but may not be revealed by chemiluminescent immunoassay.

Objective: Previous studies have reported conflicting findings regarding aldosterone levels in patients hospitalised with COVID-19. We therefore used the gold-standard technique of liquid chromatography-tandem mass spectrometry (LCMSMS) to address this uncertainty. Design: All patients admitted to Cambridge University Hospitals with COVID-19 between 10 March 2020 and 13 May 2021, and in whom a stored blood sample was available for analysis, were eligible for inclusion. Methods: Aldosterone was measured by LCMSMS and by immunoassay; cortisol and renin were determined by immunoassay. Results: Using LCMSMS, aldosterone was below the limit of detection (<70 pmol/L) in 74 (58.7%) patients. Importantly, this finding was discordant with results obtained using a commonly employed clinical immunoassay (Diasorin LIAISON®), which over-estimated aldosterone compared to the LCMSMS assay (intercept 14.1 (95% CI -34.4 to 54.1) + slope 3.16 (95% CI 2.09-4.15) pmol/L). The magnitude of this discrepancy did not clearly correlate with markers of kidney or liver function. Solvent extraction prior to immunoassay improved the agreement between methods (intercept -14.9 (95% CI -31.9 to -4.3) and slope 1.0 (95% CI 0.89-1.02) pmol/L) suggesting the presence of a water-soluble metabolite causing interference in the direct immunoassay. We also replicated a previous finding that blood cortisol concentrations were often increased, with increased mortality in the group with serum cortisol levels > 744 nmol/L (P = 0.005). Conclusion: When measured by LCMSMS, aldosterone was found to be profoundly low in a significant proportion of patients with COVID-19 at the time of hospital admission. This has likely not been detected previously due to high levels of interference with immunoassays in patients with COVID-19, and this merits further prospective investigation.

Factors Associated with Significant Weight Loss in Hospitalised Patients with COVID-19: A Retrospective Cohort Study in a Large Teaching Hospital.

SARS-CoV-2 infection (COVID-19) is associated with malnutrition risk in hospitalised individuals. COVID-19 and malnutrition studies in large European cohorts are limited, and post-discharge dietary characteristics are understudied. This study aimed to assess the rates of and risk factors for ≥10% weight loss in inpatients with COVID-19, and the need for post-discharge dietetic support and the General Practitioner (GP) prescription of oral nutritional supplements, during the first COVID-19 wave in a large teaching hospital in the UK. Hospitalised adult patients admitted between March and June 2020 with a confirmed COVID-19 diagnosis were included in this retrospective cohort study. Demographic, anthropometric, clinical, biochemical, and nutritional parameters associated with ≥10% weight loss and post-discharge characteristics were described. Logistic regression models were used to identify risk factors for ≥10% weight loss and post-discharge requirements for ongoing dietetic input and oral nutritional supplement prescription. From the total 288 patients analysed (40% females, 72 years median age), 19% lost ≥ 10% of their admission weight. The length of hospital stay was a significant risk factor for ≥10% weight loss in multivariable analysis (OR 1.22; 95% CI 1.08-1.38; p = 0.001). In addition, ≥10% weight loss was positively associated with higher admission weight and malnutrition screening scores, dysphagia, ICU admission, and artificial nutrition needs. The need for more than one dietetic input after discharge was associated with older age and ≥10% weight loss during admission. A large proportion of patients admitted to the hospital with COVID-19 experienced significant weight loss during admission. Longer hospital stay is a risk factor for ≥10% weight loss, independent of disease severity, reinforcing the importance of repeated malnutrition screening and timely referral to dietetics.

Development and validation of a dynamic 48-hour in-hospital mortality risk stratification for COVID-19 in a UK teaching hospital: a retrospective cohort study.

OBJECTIVES: To develop a disease stratification model for COVID-19 that updates according to changes in a patient's condition while in hospital to facilitate patient management and resource allocation. DESIGN: In this retrospective cohort study, we adopted a landmarking approach to dynamic prediction of all-cause in-hospital mortality over the next 48 hours. We accounted for informative predictor missingness and selected predictors using penalised regression. SETTING: All data used in this study were obtained from a single UK teaching hospital. PARTICIPANTS: We developed the model using 473 consecutive patients with COVID-19 presenting to a UK hospital between 1 March 2020 and 12 September 2020; and temporally validated using data on 1119 patients presenting between 13 September 2020 and 17 March 2021. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is all-cause in-hospital mortality within 48 hours of the prediction time. We accounted for the competing risks of discharge from hospital alive and transfer to a tertiary intensive care unit for extracorporeal membrane oxygenation. RESULTS: Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, oxygen saturation/fractional inspired oxygen ratio, white cell count, presence of acidosis (pH <7.35) and interleukin-6. Internal validation achieved an area under the receiver operating characteristic (AUROC) of 0.90 (95% CI 0.87 to 0.93) and temporal validation gave an AUROC of 0.86 (95% CI 0.83 to 0.88). CONCLUSIONS: Our model incorporates both static risk factors (eg, age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient's clinical condition. On successful external validation, the model has the potential to be a powerful clinical risk assessment tool. TRIAL REGISTRATION: The study is registered as 'researchregistry5464' on the Research Registry (www.researchregistry.com).

The Prognostic and Discriminatory Utility of the Clinical Frailty Scale and Modified Frailty Index Compared to Age.

Background: There is no consensus on the optimal method for the assessment of frailty. We compared the prognostic utility of two approaches (modified Frailty Index [mFI], Clinical Frailty Scale [CFS]) in older adults (≥65 years) hospitalised with COVID-19 versus age. Methods: We used a test and validation cohort that enrolled participants hospitalised with COVID-19 between 27 February and 30 June 2020. Multivariable mixed-effects logistic modelling was undertaken, with 28-day mortality as the primary outcome. Nested models were compared between a base model, age and frailty assessments using likelihood ratio testing (LRT) and an area under the receiver operating curves (AUROC). Results: The primary cohort enrolled 998 participants from 13 centres. The median age was 80 (range:65-101), 453 (45%) were female, and 377 (37.8%) died within 28 days. The sample was replicated in a validation cohort of two additional centres (n = 672) with similar characteristics. In the primary cohort, both mFI and CFS were associated with mortality in the base models. There was improved precision when fitting CFS to the base model +mFI (LRT = 25.87, p < 0.001); however, there was no improvement when fitting mFI to the base model +CFS (LRT = 1.99, p = 0.16). AUROC suggested increased discrimination when fitting CFS compared to age (p = 0.02) and age +mFI (p = 0.03). In contrast, the mFI offered no improved discrimination in any comparison (p > 0.05). Similar findings were seen in the validation cohort. Conclusions: These observations suggest the CFS has superior prognostic value to mFI in predicting mortality following COVID-19. Our data do not support the use of the mFI as a tool to aid clinical decision-making and prognosis.

Interoperability of statistical models in pandemic preparedness: principles and reality.

We present interoperability as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of principles for future pandemic preparedness, through the joint design and deployment of adaptable systems of statistical models for disease surveillance using probabilistic reasoning. We illustrate this through case studies for inferring and characterising spatial-temporal prevalence and reproduction numbers of SARS-CoV-2 infections in England.

Clinical Features, Inpatient Trajectories and Frailty in Older Inpatients with COVID-19: A Retrospective Observational Study.

INTRODUCTION: We describe the clinical features and inpatient trajectories of older adults hospitalized with COVID-19 and explore relationships with frailty. METHODS: This retrospective observational study included older adults admitted as an emergency to a University Hospital who were diagnosed with COVID-19. Patient characteristics and hospital outcomes, primarily inpatient death or death within 14 days of discharge, were described for the whole cohort and by frailty status. Associations with mortality were further evaluated using Cox Proportional Hazards Regression (Hazard Ratio (HR), 95% Confidence Interval). RESULTS: 214 patients (94 women) were included of whom 142 (66.4%) were frail with a median Clinical Frailty Scale (CFS) score of 6. Frail compared to nonfrail patients were more likely to present with atypical symptoms including new or worsening confusion (45.1% vs. 20.8%, p < 0.001) and were more likely to die (66% vs. 16%, p = 0.001). Older age, being male, presenting with high illness acuity and high frailty were independent predictors of death and a dose-response association between frailty and mortality was observed (CFS 1-4: reference; CFS 5-6: HR 1.78, 95% CI 0.90, 3.53; CFS 7-8: HR 2.57, 95% CI 1.26, 5.24). CONCLUSIONS: Clinicians should have a low threshold for testing for COVID-19 in older and frail patients during periods of community viral transmission, and diagnosis should prompt early advanced care planning.