Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19.

BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19. METHODS: For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes. FINDINGS: Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43-6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17-3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49-7·33], p=0·0033; and 2·58 [1·10-6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16-31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69-7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. INTERPRETATION: Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy. FUNDING: Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.

Addressing the Medical and Support Service Needs of People Living with HIV (PLWH) through Program Collaboration and Service Integration (PCSI).

BACKGROUND: Approximately 1.2 million Americans are living with HIV, and about 50,000 new infections occur each year. People living with HIV (PLWH) have numerous medical and psychosocial needs that impact HIV disease progression and challenge treatment outcomes. PURPOSE: Using CDC's Program Collaboration and Service Integration (PCSI) framework, we examined strategies, challenges, and lessons learned from a local health department's efforts to institute PCSI to address the diverse needs of their patients with HIV. METHODS: We captured case study data through: 1) semi-structured interviews with key program administrators, 2) analysis of program documents, and 3) site observations and review of clinic procedures. RESULTS: Findings highlight the importance of co-locating services, partnering to leverage resources, and conducting cross-training of staff. Providing co-located services reduced wait times and enhanced coordination of care. Partnering to leverage resources increased patient referrals and enhanced access to comprehensive services. Staff cross-training resulted in more coordinated care and efficient service delivery. CONCLUSION: The results show that PCSI is essential for optimal care for PLWH. Incorporating PCSI was a vital component of the health department's comprehensive approach to addressing the multiple medical and support service needs of its HIV-infected clients.

Prognostic judgments and triage decisions for patients with acute congestive heart failure.

STUDY OBJECTIVES: To determine how well triage physicians judge the probability of death or severe complications that require treatment only available in an ICU to maintain life for patients with acute congestive heart failure (CHF). DESIGN: Prospective cohort study. SETTING: An urban university hospital, a Veteran's Administration hospital, and a community hospital. PATIENTS OR PARTICIPANTS: Patients were those visiting the emergency department (ED) with acute CHF, excluding those who already required a treatment only available in an ICU to maintain life, and those with possible or definite myocardial infarction. Physician participants were those caring for the patients in the ED. MEASUREMENTS AND RESULTS: We performed chart reviews to ascertain whether each patient died or had severe complications develop by 4 days. We collected judgments of the probability of this outcome from the physicians taking care of the study patients in the ED. The prevalence of death or severe complications was 43 per 1,032 patients (4.2%). The mean +/- SD of physicians' judgments of the probability of this outcome was 32.1 +/- 28.4%. A calibration curve that stratified these judgments by decile demonstrated that physicians consistently overestimated this probability (p < 0.01). Physicians' judgments were only moderately good at discriminating which patients would have the outcome (receiver operating characteristic curve area, 0.715). Patients admitted to an ICU received the highest average predicted probability (56.4%), followed by those admitted to a telemetry unit (34.1%), to a regular hospital ward (29.8%), and those sent home (17.9%.) CONCLUSIONS: Physicians drastically overestimated the probability of a severe complication that would require critical care for patients with acute CHF who were candidates for ICU admission. Their judgments of this probability were associated with their triage decisions, as they should be according to several guidelines for ICU triage. Overestimation of the probability of severe complications may have lead to overutilization of scarce critical care resources. Current critical care triage guidelines should be revised to take this difficulty into account, and better predictive models for patients potentially requiring critical care should be developed.