Multicentre, multitime, multidimension, prospective follow-up cohort study on patients during the first wave of COVID-19 in China: a study protocol

Introduction
During the first wave of the COVID-19 outbreak in China, the surge of COVID-19 cases was rapid and drastic. Emerging evidence suggests that beyond the acute phase, patients with COVID-19 may experience a wide range of postacute or long COVID sequelae. However, the mechanism and burden of COVID-19, especially long COVID, have not yet been comprehensively clarified. To fill this knowledge gap, this large prospective follow-up study aims to investigate the short-term and long-term effects of COVID-19, explore the underlying biological mechanism and identify predictive neuroimaging and haematological biomarkers associated with these effects.

Methods and analysis
This multicentre study will recruit patients infected during the first wave of COVID-19 in China and healthy controls (HCs) with no history of COVID-19 infection from nine participating hospitals. Confirmed patients with mild or moderate COVID-19 will complete the following programmes during the acute infection phase and at 3, 12 and 24 months after infection: (a) blood test at the local laboratory, (b) multimodal brain and spine MRI scan and (c) the neuropsychological scales and questionnaires. Similarly, the uninfected HCs will complete the same programmes as the infected group mentioned above at the time of inclusion. At the first time point, 501 participants (418 patients and 83 HCs) from nine recruiting hospitals have been observed. Ultimately, all of these results will be analysed to explore the short-term and long-term effects of COVID-19.

Ethics and dissemination
Ethics approval was granted by Ethics Committee of the First Affiliated Hospital of Xi’an Jiaotong University (XJTU1AF2023LSK-013). Findings will be presented at national and international conferences, as well as published in peer-reviewed scientific journals.

Trial registration number
NCT05745805.

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Gennaio 2025

US Life Expectancy Gap Among Demographics Was Up to 20 Years in 2021

Life expectancy in the US may now vary by more than 2 decades based on demographic differences, according to a new systematic analysis. The largest gap between highest and lowest life expectancies was 12.6 years in 2000. It reached 13.9 years in 2010 and 15.8 years by 2019 before climbing to 20.4 years after the first 2 years of the COVID-19 pandemic—with the largest life expectancy difference being between Asian individuals and American Indian or Alaska Native people in the West.

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Gennaio 2025

Patient and provider factors associated with follow-up for positive depression screens in adults: a retrospective review of University of Utah primary and specialty care clinics

Objective
To identify patient and provider factors associated with lower rates of follow-up for positive depression screens in outpatient settings.

Design
Retrospective cohort study with electronic health record analysis investigating factors associated with follow-up care for patients with moderate-to-severe depressive symptoms. Patient and provider variables were associated with rates of follow-up for positive depression screens.

Setting
University of Utah and University of Utah Health-affiliated primary care and specialty clinics.

Participants
Adults who screened positive for depressive symptoms (score≥10) on the Patient Health Questionnaire (PHQ-9) at an ambulatory visit between 1 January 2021 and 31 January 2022. A total of 17 651 patients were included in the study.

Outcome measures
Follow-up for positive depression screens was defined as a new antidepressant prescription or completed mental health visit. Variables associated with follow-up included patient demographic data, anthropometric measures, geographical classification, primary language, comorbidities and socioeconomic factors as well as provider demographics, level of training and clinic type.

Results
5396 patients (30.6%) did not receive follow-up care for a positive PHQ-9 screen. Factors associated with lower rates of follow-up included male patients (gender; p=0.013), older patients (age group; p=0.016), non-White patients (ethnicity; p

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Gennaio 2025