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1.
J Affect Disord ; 324: 477-479, 2023 03 01.
Article in English | MEDLINE | ID: covidwho-2165449

ABSTRACT

Present study aimed to explore adolescent depression trajectory during the COVID-19 pandemic, and the impact of parental style on it. Five-wave data of adolescent sample in China mainland were collected, and the group-based trajectory modeling was used to examine the theory constructs. Findings showed that, during the COVID-19 pandemic, there are four distinct patterns of change in depression symptoms over time, namely, resistance (72.3 %), recovery (15.3 %), increasing (6.7 %), chronic (5.7 %). Differences about the impact of parental style and grade on depression trajectory were found. Findings contribute to the knowledge of the impact of the COVID-19 pandemic on depression trajectory among general population, and parental style and grade should be considered in adolescent psychological intervention in the pandemic.


Subject(s)
COVID-19 , Humans , Adolescent , COVID-19/epidemiology , Depression/epidemiology , Depression/psychology , Pandemics , Parents , China/epidemiology , Anxiety/psychology
2.
BMC Pulm Med ; 22(1): 339, 2022 Sep 07.
Article in English | MEDLINE | ID: covidwho-2038719

ABSTRACT

BACKGROUND: No consensus has been reached on an optimal blood lactate evaluation system although several approaches have been reported in the literature in recent years. A group-based trajectory modeling (GBTM) method could better stratify patients with acute respiratory distress syndrome (ARDS) complicated with sepsis in the intensive care unit (ICU). PATIENTS AND METHODS: 760 patients from the comprehensive ICU of Tianjin Medical University General Hospital with ARDS complicated with sepsis were eligible for analysis. Serial serum lactate levels were measured within 48 h of admission. In addition to the GBTM lactate groups, the initial lactate, peak lactate level, the area under the curve of serial lactate (lactate AUC), and lactate clearance were also considered for comparison. The short- and long-term outcomes were the 30- and 90-day mortality, respectively. RESULTS: Three lactate groups were identified based on GBTM, with group 3 exhibiting the worse short- [hazard ratio (HR) for 30-day mortality: 2.96, 95% confidence interval (CI) 1.79-4.87, P < 0.001] and long term (HR for 90-day mortality: 3.49, 95% CI 2.06-5.89, P < 0.001) outcomes followed by group 2 (HR for 30-day mortality: 2.05, 95% CI 1.48-2.84, P < 0.001 and HR for 90-day mortality: 1.99, 95% CI 1.48-2.67, P < 0.001). GBTM lactate groups exhibited significantly improved diagnostic performance of initial lactate + SOFA scores/APACHE II scores models. Based on the multivariable fractional polynomial interaction (MFPI) approach, GBTM lactate groups could better differentiate high-risk patients than the initial lactate groups in short- and long-term outcomes. CONCLUSIONS: To the best of our knowledge, this is the first report that GBTM-based serial blood lactate evaluations significantly improve the diagnostic capacity of traditional critical care evaluation systems and bring many advantages over previously documented lactate evaluation systems.


Subject(s)
Respiratory Distress Syndrome , Sepsis , APACHE , Humans , Lactic Acid , Respiratory Distress Syndrome/diagnosis , Risk Assessment , Sepsis/complications , Sepsis/diagnosis
3.
Spat Spatiotemporal Epidemiol ; 43: 100536, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2004538

ABSTRACT

COVID-19's rapid onset left many public health entities scrambling. But establishing community-academic partnerships to digest data and create advocacy steps offers an opportunity to link research to action. Here we document disparities in COVID-19 death uncovered during a collaboration between a health department and university research center. We geocoded COVID-19 deaths in Genesee County, Michigan, to model clusters during two waves in spring and fall 2020. We then aggregated these deaths to census block groups, where group-based trajectory modeling identified latent patterns of change and continuity. Linking with socioeconomic data, we identified the most affected communities. We discovered a geographic and racial gap in COVID-19 deaths during the first wave, largely eliminated during the second. Our partnership generated added and immediate value for community partners, including around prevention, testing, treatment, and vaccination. Our identification of the aforementioned racial disparity helped our community nearly eliminate disparities during the second wave.


Subject(s)
COVID-19 , Humans , Michigan/epidemiology , Seasons
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