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1.
J Affect Disord ; 313: 36-42, 2022 09 15.
Article in English | MEDLINE | ID: covidwho-1907233

ABSTRACT

BACKGROUND: COVID-19 is an infectious disease that has spread worldwide in 2020, causing a severe pandemic. In addition to respiratory symptoms, neuropsychiatric manifestations are commonly observed, including chronic fatigue, depression, and anxiety. The neural correlates of neuropsychiatric symptoms in COVID-19 are still largely unknown. METHODS: A total of 79 patients with COVID-19 (COV) and 17 healthy controls (HC) underwent 3 T functional magnetic resonance imaging at rest, as well as structural imaging. Regional homogeneity (ReHo) was calculated. We also measured depressive symptoms with the Patient Health Questionnaire (PHQ-9), anxiety using the General Anxiety Disorder 7-item scale, and fatigue with the Multidimension Fatigue Inventory. RESULTS: In comparison with HC, COV showed significantly higher depressive scores. Moreover, COV presented reduced ReHo in the left angular gyrus, the right superior/middle temporal gyrus and the left inferior temporal gyrus, and higher ReHo in the right hippocampus. No differences in gray matter were detected in these areas. Furthermore, we observed a negative correlation between ReHo in the left angular gyrus and PHQ-9 scores and a trend toward a positive correlation between ReHo in the right hippocampus and PHQ-9 scores. LIMITATIONS: Heterogeneity in the clinical presentation in COV, the different timing from the first positive molecular swab test to the MRI, and the cross-sectional design of the study limit the generalizability of our findings. CONCLUSIONS: Our results suggest that COVID-19 infection may contribute to depressive symptoms via a modulation of local functional connectivity in cortico-limbic circuits.


Subject(s)
COVID-19 , Depression , Brain/diagnostic imaging , Cross-Sectional Studies , Depression/diagnostic imaging , Humans , Magnetic Resonance Imaging/methods
2.
PLoS One ; 16(6): e0253433, 2021.
Article in English | MEDLINE | ID: covidwho-1278196

ABSTRACT

PURPOSE: To evaluate if reduced muscle mass, assessed with Computed Tomography (CT), is a predictor of intensive care unit (ICU) hospitalization in COVID-19 patients. METHODS: In this Institution Review Board approved study, we retrospectively evaluated COVID-19 patients treated in our tertiary center from March to November 2020 who underwent an unenhanced chest CT scan within three weeks from hospitalization.We recorded the mean Hounsfield Unit (Hu) value of the right paravertebral muscle at the level of the 12th thoracic vertebra, the hospitalization unit (ICU and COVID-19 wards), clinical symptoms, Barthel Index, and laboratory findings.Logistic regression analysis was applied to assess if muscle loss (Hu<30) is a predictor of ICU admission and outcome.Fisher's exact and Student's tests were applied to evaluate if differences between patients with and without muscle loss occurred (p<0.05). RESULTS: One-hundred-fifty patients matched the inclusion criteria (46 females; mean age±SD 61.3±15 years-old), 36 treated in ICU. Patients in ICU showed significantly lower Hu values (29±24 vs 39.4±12, p = 0.001). Muscle loss was a predictor of ICU admission (p = 0.004).Patients with muscle loss were significantly older (73.4±10 vs 56.4±14 years), had lower Barthel Index scores (54.4±33 vs 85.1±26), red blood-cell count (3.9±1 vs 4.6±1×1012L-1), and Hb levels (11.5±2 vs 13.2±2g/l) as well as higher white blood-cell count (9.4±7 vs 7.2±4×109L-1), C-reactive protein (71.5±71 vs 44±48U/L), and lactate dehydrogenase levels (335±163 vs 265.8±116U/L) (p<0.05, each). CONCLUSIONS: Muscle loss seems to be a predictor of ICU hospitalization in COVID-19 patients and radiologists reporting chest CT at admission should note this finding in their reports.


Subject(s)
COVID-19/therapy , Hospitalization/statistics & numerical data , Intensive Care Units/statistics & numerical data , Muscles/metabolism , SARS-CoV-2/isolation & purification , Aged , COVID-19/diagnosis , COVID-19/virology , Female , Humans , Male , Middle Aged , Muscles/diagnostic imaging , ROC Curve , Reproducibility of Results , Retrospective Studies , Risk Factors , SARS-CoV-2/physiology , Tomography, X-Ray Computed/methods
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