Profiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression

With a rising incidence of COVID-19-associated morbidity and mortality worldwide, it is critical to elucidate the innate and adaptive immune responses that drive disease severity. We performed longitudinal immune profiling of peripheral blood mononuclear cells from 45 patients and healthy donors. We observed a dynamic immune landscape of innate and adaptive immune cells in disease progression and absolute changes of lymphocyte and myeloid cells in severe versus mild cases or healthy controls. Intubation and death were coupled with selected natural killer cell KIR receptor usage and IgM+ B cells and associated with profound CD4 and CD8 T-cell exhaustion. Pseudo-temporal reconstruction of the hierarchy of disease progression revealed dynamic time changes in the global population recapitulating individual patients and the development of an eight-marker classifier of disease severity. Estimating the effect of clinical progression on the immune response and early assessment of disease progression risks may allow implementation of tailored therapies.

A method to automate the discharge summary hospital course for neurology patients

OBJECTIVE

Generation of automated clinical notes has been posited as a strategy to mitigate physician burnout. In particular, an automated narrative summary of a patient's hospital stay could supplement the hospital course section of the discharge summary that inpatient physicians document in electronic health record (EHR) systems. In the current study, we developed and evaluated an automated method for summarizing the hospital course section using encoder-decoder sequence-to-sequence transformer models.

MATERIALS AND METHODS

We fine-tuned BERT and BART models and optimized for factuality through constraining beam search, which we trained and tested using EHR data from patients admitted to the neurology unit of an academic medical center.

RESULTS

The approach demonstrated good ROUGE scores with an R-2 of 13.76. In a blind evaluation, 2 board-certified physicians rated 62% of the automated summaries as meeting the standard of care, which suggests the method may be useful clinically.

DISCUSSION AND CONCLUSION

To our knowledge, this study is among the first to demonstrate an automated method for generating a discharge summary hospital course that approaches a quality level of what a physician would write.

Multivariate analysis of CT imaging, laboratory, and demographical features for prediction of acute kidney injury in COVID-19 patients: a Bi-centric analysis

PURPOSE

To develop and externally validate a multivariate prediction model for the prediction of acute kidney injury (AKI) in COVID-19, based on baseline renal perfusion from contrast-enhanced CT together with clinical and laboratory parameters.

METHODS

In this retrospective IRB-approved study, we identified COVID-19 patients who had a standard-of-care contrast-enhanced abdominal CT scan within 5 days of their COVID-19 diagnosis at our institution (training set; n = 45, mean age 65 years, M/F 23/22) and at a second institution (validation set; n = 41, mean age 61 years, M/F 22/19). The CT renal perfusion parameter, cortex-to-aorta enhancement index (CAEI), was measured in both sets. A multivariate logistic regression model for predicting AKI was constructed from the training set with stepwise feature selection with CAEI together with demographical and baseline laboratory/clinical data used as input variables. Model performance in the training and validation set was evaluated with ROC analysis.

RESULTS

AKI developed in 16 patients (35.6%) of the training set and in 6 patients (14.6%) of the validation set. Baseline CAEI was significantly lower in the patients that ultimately developed AKI (P = 0.003). Logistic regression identified a model combining baseline CAEI, blood urea nitrogen, and gender as most significant predictor of AKI. This model showed excellent diagnostic performance for prediction of AKI in the training set (AUC = 0.89, P < 0.001) and good performance in the validation set (AUC 0.78, P = 0.030).

CONCLUSION

Our results show diminished renal perfusion preceding AKI and a promising role of CAEI, combined with laboratory and demographic markers, for prediction of AKI in COVID-19.

Sex-Related Differences in Clinical Presentation and Risk Factors for Mortality in Patients Hospitalized With Coronavirus Disease 2019 in New York City

We evaluated sex-related differences in symptoms and risk factors for mortality in 4798 patients hospitalized with coronavirus disease 2019 in New York City. When adjusted for age and comorbidities, being male was an independent predictor of death with mortality significantly higher than females, even with low severe acute respiratory syndrome coronavirus 2 viral load at admission.

Using electronic health records for population health sciences: a case study to evaluate the associations between changes in left ventricular ejection fraction and the built environment

OBJECTIVE

Electronic health record (EHR) data linked with address-based metrics using geographic information systems (GIS) are emerging data sources in population health studies. This study examined this approach through a case study on the associations between changes in ejection fraction (EF) and the built environment among heart failure (HF) patients.

MATERIALS AND METHODS

We identified 1287 HF patients with at least 2 left ventricular EF measurements that are minimally 1 year apart. EHR data were obtained at an academic medical center in New York for patients who visited between 2012 and 2017. Longitudinal clinical information was linked with address-based built environment metrics related to transportation, air quality, land use, and accessibility by GIS. The primary outcome is the increase in the severity of EF categories. Statistical analyses were performed using mixed-effects models, including a subgroup analysis of patients who initially had normal EF measurements.

RESULTS

Previously reported effects from the built environment among HF patients were identified. Increased daily nitrogen dioxide concentration was associated with the outcome while controlling for known HF risk factors including sex, comorbidities, and medication usage. In the subgroup analysis, the outcome was significantly associated with decreased distance to subway stops and increased distance to parks.

CONCLUSIONS

Population health studies using EHR data may drive efficient hypothesis generation and enable novel information technology-based interventions. The availability of more precise outcome measurements and home locations, and frequent collection of individual-level social determinants of health may further drive the use of EHR data in population health studies.

Protocol for Health Risk Information Technology-Assisted Genetic Evaluation (HeRITAGE): a randomised controlled trial of digital genetic cancer risk assessment in a diverse underserved gynaecology clinic

INTRODUCTION

In the USA, up to 95% of individuals harbouring cancer-predisposing germline pathogenic variants have not been identified despite recommendations for screening at the primary care level.

METHODS AND ANALYSIS

Our primary objective is to use a two-arm, single-institution randomised controlled trial to compare the proportion of eligible patients that are recommended genetic testing for hereditary cancer syndromes using a digital tool versus clinician interview for genetic cancer risk assessment in an urban academic gynaecology clinic. New gynaecology patients will be consented and randomised 1:1 to either the intervention arm, in which a digital tool is used for genetic cancer risk assessment, or usual care, in which the clinician performs genetic cancer risk assessment. Individuals will be considered eligible for hereditary cancer syndrome genetic testing if criteria set forth by the National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology are met. Eligible patients are 18 years or older, speak and read English, have not yet undergone hereditary cancer genetic testing and have access to a smartphone. The study aims to enrol 50 patients in each arm to allow for 80% power with two-tailed alpha of 5% to detect a 20% difference in proportion of eligible patients recommended for genetic testing. The primary outcome is the proportion of eligible individuals recommended genetic testing in the digital tool arm versus usual care arm, analysed using the χ2 or Fisher's exact test as appropriate for sample size. The secondary outcome is completion of genetic testing, as well as exploration of patient factors, particularly social determinants of health, which may affect the receipt, utilisation and experience with genetic services.

ETHICS AND DISSEMINATION

This study has been approved by the Weill Cornell Institutional Review Board (Protocol No. 21-11024123). Participants will be informed of the benefits and risks of participation prior to consent. Dissemination of data will be deidentified and conducted through academic conferences and journals. Patients identified to be eligible for genetic testing who did not receive counselling from their providers will be contacted; participants will not receive direct notification of trial results.

REGISTRATION DETAILS

This trial is registered at clinicaltrials.gov (NCT05562778) in September 2022.

PROTOCOL VERSION

This is protocol version 1, as of 22 May 2024.

COUNTRIES OF RECRUITMENT AND RECRUITMENT STATUS

USA, currently recruiting.

HEALTH CONDITIONS/PROBLEMS STUDIED

Genetic predisposition to cancers such as breast, ovarian, uterine and pancreatic. DEIDENTIFIED INDIVIDUAL CLINICAL TRIAL PARTICIPANT-LEVEL DATA IDP SHARING STATEMENT: IDP will not be shared.

TRIAL REGISTRATION NUMBER

NCT05562778.

ANA-positive versus ANA-negative Antiphospholipid Antibody-positive Patients: Results from the Antiphospholipid Syndrome Alliance for Clinical Trials and International Networking (APS ACTION) Clinical Database and Repository ("Registry")

OBJECTIVES

This study focused on the prevalence and impact of ANA in aPL-positive patients without concomitant systemic autoimmune rheumatic diseases (SARDs).

METHODS

Data from aPL-positive patients with or without Revised Sapporo APS classification criteria were retrieved from the Antiphospholipid Syndrome Alliance for Clinical Trials and International Networking (APS ACTION) Registry. Patients with concomitant SARDs were excluded.

RESULTS

A total of 430 aPL-positive patients were included in the analysis, 56% ANA-positive (ANA+) and 44% ANA-negative (ANA-). ANA positivity was significantly associated with history of haematologic manifestations (persistent autoimmune haemolytic anaemia, thrombocytopenia, leukopenia and/or lymphopenia) (16% of ANA+ vs 7% of ANA-, P = 0.006). Triple aPL-positivity was more frequent in the ANA+ subgroup (P = 0.02), along with low baseline C3 and C4 levels (P = 0.05 and P = 0.009, respectively), and higher frequency for ENA. Among aPL-positive patients with no APS classification, ANA+ patients showed a higher rate of arthritis (P = 0.006). Among female patients who have experienced at least one pregnancy, 113 were ANA+ and 96 were ANA-; ANA- patients had a higher number of pregnancies (P = 0.018), and number of live births (P = 0.014). A wider proportion of ANA+ patients were treated with HCQ (P < 0.001).

CONCLUSION

When we analysed aPL-positive patients with no other SARDs, ANA status was not associated with thrombosis or pregnancy morbidity. Interestingly, ANA+ patients showed higher rates of systemic autoimmune features, including haematologic manifestations, multiple aPL positivity, lower complement levels, ENA positivity, and joint involvement, and were more often treated with HCQ. Finally, aPL-positive subjects who were ANA- had a higher rate of pregnancies and live births.